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Stepwise logistic regression. Applied logistic regression
... Within this thesis an investigation is being conducted into proportional spend within a specific area and this gives the dependent variable an absolute minimum value of 0. Due to the fact that there is no mathematical mechanism v^thin the OLS regression equation to prevent prediction of values below 0, it being simply a summation of a constant and a set of coefficients multiplied by their respective explanatory veuiables, there are limitations to the application of OLS in this instance. Logisfic regression, a nonparametric development of OLS regression, seeks to predict not the value of the dependent variable but the probability that the dependent variable is either 1 or 0, therefore removing any possibility of values below 0 (Hosmer and Lemeshow, 1989;Menard, 1995;Pampel, 2000). Although this collapsing of the dependent variable inevitably loses some of the detail of the original data In addition, for OLS regression, discriminant analysis, factor analysis or other parametric techniques, the distribution and the variance of the dependent variable should be normal and constant respectively for any value of the independent variable. ...
... Logistic regression models predict the likelihood of a dependent variable being either 1 or 0 by estimating coefficients values for selected independent variables. In order to construct a multivariate logistic regression model to explore this study's hypotheses, the series of steps suggested by Hosmer and Lemeshow (1989) Although this analysis can be used to produce a smaller set of variables for model estimation, the ease with which modem software is able to conduct elimination tests on larger numbers of variables meant that all variables were entered into the logistic regression model (next chapter). The following sections therefore detail the methodology and results obtained during the variable analysis phase of the research. ...
... In order to accommodate this, the data were transformed using the follov^ng methodologies: This process of re-coding, which represented a simplification based on examination of the data, removed all occurrences of zero cells. Hosmer et al. (1989) 128 ...
This research seeks to contribute towards the understanding of economic linkage within the rural context by exploring the relationship between rurally located small to medium-sized enterprises (SMEs) and their purchase of producer (business) services. In addition, the work considers other inter-rural and intra-rural differences, in both firm (SME) behaviour and firm characteristics. Whilst the subject of linkages has been explored by other researchers, the market town and SME focus of this thesis provides a more spatially contained framework than is often encountered within this type of research. By using four towns of similar size and structure contained within two noticeably different counties, the work is able to explore difference within the rural setting. Given its emphasis on market towns, rural areas, SMEs, the service sector and indigenous growth potential, the work contributes to current debates in both academia and in national and European government policy. The underlying hypothesis is that integration, in terms of local spending on producer services, is a function of a firm's characteristics. In order to test this hypothesis, data was collected from four rural towns, and a logistic regression model was constructed using variables that described both firms' characteristics and proportion of spend on services in their resident town. The model was then tested using data collected firom a further two towns. This thesis shows that there is a relationship between a firm's characteristics and the location of the firm's producer service spending, enhancing our understanding of firms operating within the rural context. Key characteristic variables that are shown to have a relationship with producer service spend location are: firm Standard Industrial Classification (SIC), size (in terms of total sales, total number of hours worked by all staff), total spend on producer services by firm and distance that the current location is from the firm's previous location. Given the changing role and nature of rural firms, this research provides timely information concerning the relationship between firms and service providers.
... Coefficients are expressed in log units; if a coefficient is positive, its transformed log value will be greater than one, meaning that the modeled event is more likely to occur. If a coefficient is negative, the odds of the event occurrence decrease; a coefficient of zero has a transformed log value of 1, meaning that this coefficient does not change the odds of the event one way or the other (Hosmer and Lemeshow 2000). ...
... The model fitting to the observed data was evaluated by computing the values of the Cox and Snell and Nagelkerke pseudo-R 2 in addition to the statistic − 2LL. The logistic regression component of the SPSS 26.0 software also provides the results of the model Chisquare test, which allows for assessing the global significance of the regression coefficients; the significance was also evaluated individually for each independent variable incorporated in the model by means of the Wald test (Hosmer and Lemeshow 2000). Afterwards, the regression coefficients of ...
... The AUC varies from 0.5 (diagonal line) to 1, with higher values indicating a better predictive capability of the model. As discussed in Hosmer and Lemeshow (2000) the prediction accuracy of the models based on the AUC value can be classified as follows: poor (0.5-0.6), moderate (0.6-0.7), good (0.7-0.8), very good (0.8-0.9), and excellent (0.9-1). ROC curves were drawn both for the testing and training datasets, to evaluate predictive performances of the models and to further investigate their fit to the training observations. ...
This study aimed to examine the influence of the random selection of landslide training and testing sets on the predictive performance of the shallow landslide susceptibility modelling at regional scale. The performance of frequency ratio (FR), information value (IV), logistic regression (LR), and maximum entropy (ME) methods were tested and compared for modeling shallow landslide susceptibility in Calabria region, (South Italy). A landslide database of 22,028 shallow landslides, randomly split into training (70%) and testing (30%) sets, was combined with 15 predisposing factors (lithology, soil texture, soil bulk density, soil erodibility, drainage density, land use, elevation, local relief, slope gradient, slope aspect, plan curvature, topographic wetness index, stream power index, topographic ruggedness index, and topographic position index) to calibrate and validate the models. The robustness of the models in response to changes in the landslide dataset was explored through ten training and test sets replicates. The performance of these models was evaluated using several statistical indices and the ROC curve method. The results showed that all the four methods applied achieve promising performance on the prediction of shallow landslide susceptibility at regional scale. The comparison between four methods displayed that the ME is the best performing (AUC = 0.866), followed by the LR (AUC = 0.845), FR (AUC = 0.813), and finally IV (AUC = 0.800). In addition, the findings showed that the accuracy of the four methods for modeling shallow landslide susceptibility was quite robust when the training and testing sets were changed (i.e. a very low sensitivity to varying training/testing sets).
... Regresi logistic biner merupakan suatu metode analisis data yang digunakan untuk mencari hubungan antara variabel respon (Y) yang bersifat biner atau dikotomus dengan variabel prediktor (X) yang bersifat polikotomus [6]. Output dari variabel respon (Y) terdiri dari dua kategori yang biasanya dinotasikan dengan satu (sukses) atau nol (gagal). ...
... Fungsi likelihood tersebut lebih mudah dimaksimumkan dalam bentuk ln l(β) dan dinyatakan dengan L(β) [6]. ...
... Gula darah adalah gula yang berada di dalam darah yang terbentuk dari karbohidrat dalam makanan dan disimpan sebagai glikogen di hati dan otot rangka [6]. Sedangkan kadar glukosa darah adalah tingkat gula di dalam darah, konsentrasi gula darah, atau tingkat glukosa serum, diatur dengan ketat di dalam tubuh. ...
... For logistic regression (simply as a classifier, unrelated to the popular DIF detection method by Swaminathan and Rogers (1990)), a simple way to measure invariance is by including interaction terms for the inputs to the regression, and comparing the resulting models (Hosmer Jr et al. 2013). ...
... The individual predictive equivalence method is compared to the Hosmer-Lemeshow test (Hosmer Jr et al. 2013 ...
In this paper we discuss how to evaluate the differences between fitted logistic regression models across sub-populations. Our motivating example is in studying computerized diagnosis for learning disabilities, where sub-populations based on gender may or may not require separate models. In this context, significance tests for hypotheses of no difference between populations may provide perverse incentives, as larger variances and smaller samples increase the probability of not-rejecting the null. We argue that equivalence testing for a prespecified tolerance level on population differences incentivizes accuracy in the inference. We develop a cascading set of equivalence tests, in which each test addresses a different aspect of the model: the way the phenomenon is coded in the regression coefficients, the individual predictions in the per example log odds ratio and the overall accuracy in the mean square prediction error. For each equivalence test, we propose a strategy for setting the equivalence thresholds. The large-sample approximations are validated using simulations. For diagnosis data, we show examples for equivalent and non-equivalent models.
... indicates good performance; while an AUC with 0.8-0.9 indicates excellent performance; and an AUC > 0.9 indicates outstanding model performance [56]. ...
... This was confirmed when the AT model metrics were compared to a logistic regression model developed for the same territory [90]. However, when the AT model developed in this study was compared to RF and maximal entropy (MaxEnt) models developed for the province of Tyrol in Austria [96], a slightly higher AUC value was recorded in the present AT model; but all models can be appraised as excellent [56]. ...
Forest fires are becoming a serious concern in Central European countries such as Austria (AT) and the Czech Republic (CZ). Mapping fire ignition probabilities across countries can be a useful tool for fire risk mitigation. This study was conducted to: (i) evaluate the contribution of the variables obtained from open-source datasets (i.e., MODIS, OpenStreetMap, and WorldClim) for modeling fire ignition probability at the country level; and (ii) investigate how well the Random Forest (RF) method performs from one country to another. The importance of the predictors was evaluated using the Gini impurity method, and RF was evaluated using the ROC-AUC and confusion matrix. The most important variables were the topographic wetness index in the AT model and slope in the CZ model. The AUC values in the validation sets were 0.848 (AT model) and 0.717 (CZ model). When the respective models were applied to the entire dataset, they achieved 82.5% (AT model) and 66.4% (CZ model) accuracy. Cross-comparison revealed that the CZ model may be successfully applied to the AT dataset (AUC = 0.808, Acc = 82.5%), while the AT model showed poor explanatory power when applied to the CZ dataset (AUC = 0.582, Acc = 13.6%). Our study provides insights into the effect of the accuracy and completeness of open-source data on the reliability of national-level forest fire probability assessment.
... 25 Univariate and multiple logistic regression models were performed to identify the factors associated with parents' intention to have their children vaccinated against COVID-19. 26 Variables having a univariate test with p <0.25 were selected as candidate variables for the regression model. 26 Backward multiple logistic regression was used to fit the model. ...
... 26 Variables having a univariate test with p <0.25 were selected as candidate variables for the regression model. 26 Backward multiple logistic regression was used to fit the model. The alpha level was set at 0.05 for statistical significance. ...
Introduction:
Global vaccination efforts to control the COVID-19 pandemic may be impeded by vaccine hesitancy. Attitudes and vaccine literacy are important factors that reduce vaccine hesitancy. The role of attitudes and vaccine literacy of parents on COVID-19 vaccine intention for their children under five years was unknown.
Objective:
This study aimed to assess parents' characteristics, vaccine literacy, attitudes toward the COVID-19 vaccine, and vaccine intention/hesitancy and to determine factors influencing parents' vaccine intention for their children under five years of age.
Methods:
A cross-sectional study was conducted using an online self-administered questionnaire before the authorization of the COVID-19 vaccine for very young children in Thailand. The sample consisted of 455 parents with children under five years old. The online questionnaire included parents' sociodemographic data, vaccine literacy, attitudes toward COVID-19 vaccine, and vaccine intention to get their children vaccinated.
Results:
About 98% of the parents received their COVID-19 vaccination, whereas only 45.1% reported they would have their children under five years old get vaccinated. About 54.9% were either not sure or refused their child's COVID-19 vaccination. A multiple logistic regression model identified factors that increased the odds of parents' vaccine intention: parents aged > 35 years, attitudes on safety and efficacy of COVID-19 vaccine for children, advice about the COVID-19 vaccines from healthcare personnel, and the belief that COVID-19 vaccine is helpful for their children. Attitudes that COVID-19 vaccination in children could be fatal decreased parents' vaccine intention. Need for more information about the COVID-19 vaccine for children and concern about the vaccine's side effects were the most frequent reasons for vaccine hesitancy and refusal.
Conclusion:
Parents should be provided with accurate information from healthcare personnel and media sources about the safety and effectiveness of the COVID-19 vaccine for young children under five years of age to overcome their hesitancy.
... XGBH is a fast high-performance gradient enhancement framework, a tree-based learning algorithm 21 . In this paper, by comparing four machine learning models (logistic regression 22 , linear support vector machine 23 , random forest 24 , and XGBoost 25 ), the best performing XGBoost model was chosen as the base model. XGBH introduces a histogram algorithm (Histogram) 26 based on XGBoost, and since in previous studies, XGBoost used a pre sorting method to deal with node splitting, so that the calculated split points are more accurate. ...
The risk of cardiovascular disease (CVD) is a serious health threat to human society worldwide. The use of machine learning methods to predict the risk of CVD is of great relevance to identify high-risk patients and take timely interventions. In this study, we propose the XGBH machine learning model, which is a CVD risk prediction model based on key contributing features. In this paper, the generalisation of the model was enhanced by adding retrospective data of 14,832 Chinese Shanxi CVD patients to the kaggle dataset. The XGBH risk prediction model proposed in this paper was validated to be highly accurate (AUC = 0.81) compared to the baseline risk score (AUC = 0.65), and the accuracy of the model for CVD risk prediction was improved with the inclusion of the conventional biometric BMI variable. To increase the clinical application of the model, a simpler diagnostic model was designed in this paper, which requires only three characteristics from the patient (age, value of systolic blood pressure and whether cholesterol is normal or not) to enable early intervention in the treatment of high-risk patients with a slight reduction in accuracy (AUC = 0.79). Ultimately, a CVD risk score model with few features and high accuracy will be established based on the main contributing features. Of course, further prospective studies, as well as studies with other populations, are needed to assess the actual clinical effectiveness of the XGBH risk prediction model.
... Using the OLS [Hosmer et al. (2013)], β is estimated as ...
This research deals with one of the most important nonlinear regression models widely used in the modeling of statistical applications, which is the binary Logistic Regression (LR) model, and then estimating the parameters of this model using the weighted least squares method and the accuracy of WLSE in estimating the model parameters as well as the suitability of the model used. Practical sides were performed for modeling data on patients with TB diseases for a research sample that included 299 patients and studying the most important factors affecting this disease.
... The goal here was to identify at the bivariate level the factors that were associated with both the length of the thread activity (i.e., Mann-Whitney U 1 ) and the survival of the thread (Mantel -Cox test). The second analytical step included two multivariate analyses using only independent variables that were significant at the bivariate level (Hosmer & Lemeshow, 2013). Specifically, one sequential generalized linear model (GLM) with negative binomial log function 2 (Nelder & Wedderburn, 1972), and one Cox proportional hazard regression model (Cox, 1972) were computed. ...
Purpose: This paper explores the concept of criminal expertise within the context of online pedophile community and applies rational choice theory to understand the decision-making processes of offenders. Specifically, this study aims to explore the cybersecurity concerns of dark web pedophile forum users known to be a hard-to-reach offender population.
Methods: Sequential generalized linear model and Cox proportional hazard regression model were used to examine cybersecurity themes predicting both the lifespan and survival of 290 cybersecurity-related threads extracted from three pedophile forums identified on the dark web.
Results: Results showed that risk factors for law enforcement identification-related topics were the most predictive of threads' lifespan and survival. Moreover, topics related to proactive protection strategies were more predictive than those related to reactive ones. Finally, threads with a superior skill level were more likely to survive than other types of content.
Conclusion: This study builds upon both criminal expertise and cybercrime literature, particularly on the applicability of the criminal expertise framework to dark web pedophile forum users, and provide a better understanding of the enculturation process among the pedophile community.
... Logistic regression quantifies the odds of a particular variable's influence on the outcome and has been cited as one of the better models for making predictions and classifications [37]. This method reports probabilities of outcomes and does not assume normal distributions of predictor variables or errors. ...
The present study examined demographic and academic predictors of astronomy performance among a cohort of N=1909 community college students enrolled in astronomy courses in a large suburban community college during a four-year time frame, 2015–2019. The theoretical framework was based upon a deconstructive approach for predicting community college performance, whereby students’ academic pathways through higher education institutions are examined to understand their dynamic interaction with institutional integration and progress toward academic goals. Transcript data analysis was employed to elicit student demographics and longitudinal academic coursework and performance. A logistic regression model was generated to identify significant predictors of astronomy performance, which included mathematics achievement, enrollment in remedial mathematics, and enrollment in multiple astronomy courses. The results imply a greater focus on mathematics preparation and performance may mediate astronomy outcomes for community college students. Notably, demographic variables including ethnicity, socioeconomic status, gender, and age were not significant predictors of astronomy performance in the multivariable model, suggesting the course is a potential gateway for diversifying science, technology, engineering, and mathematics access. Also, astronomy interest, as measured by enrollment in multiple astronomy courses, was related to performance. Further implications for practice are discussed.
... Based on a thorough literature review, the model includes all clinically and intuitively relevant variables, which are available in the data. This approach is chosen in order to provide the best possible control of confounding within the given data (Hosmer et al., 2013). ...
It has been frequently shown that the proximity of households to mobile money agents is a decisive factor for the adoption of mobile money. However, merely measuring the distance to agents overshadows the fact that agents are a heterogenous group, offering different services and abilities to costumers; differences, which could affect mobile money adoption. The present study therefore investigates, under the lens of the Technology Adoption Model (TAM), how agent characteristics affect mobile money adoption, using georeferenced data from a nationally representative Kenyan household survey and a census of all mobile money agents in Kenya. Results from logistic regressions show that people are statistically significantly more likely to adopt mobile money, if nearby agents offer account opening services, or if nearby agents have received formal training. The study further shows that agent training is particularly important for mobile money adoption among people without formal education. Considering that only 59 % of agents offer account opening services and only 58 % of the agents are formally trained, this article points towards a large potential for mobile money lenders and policy makers to foster financial inclusion in the future.
... For the remaining predictors (social support subdomains, 'substitute' network groups, and homelessness status), univariate tests using linear regression were conducted with each loneliness variable to determine which should be included in the multivariate model, using a generous signifcance level of α � 0.1 [34,35]. ...
People experiencing homelessness can often have small and fragmented social networks, due to the loss and absence of critical connections, leaving them particularly susceptible to loneliness. During the course of homelessness, some people experience a changing profile of networks, transitioning away from family and some friends and forming new/substitute networks, such as service providers or pets. The resulting loneliness can have profound impacts on this group, threatening their physical and mental health and their ability to exit homelessness successfully. This study aimed to understand the social network characteristics and support associated with loneliness. MOS Social Support and social network questionnaire data from 124 participants (either currently or formerly homeless) were used in three hierarchical regression models to predict romantic, social, and family loneliness (SELSA-S), respectively. Findings suggested the more supportive, important, and (often) more satisfying that participants deemed current relationships to be, the lonelier they tended to feel. This occurred even if they were no longer homeless. These findings suggest that loneliness can operate differently in the context of poverty and homelessness. Whilst experiencing homelessness, people may prioritise relationships that provide resources and safety over those that assuage loneliness. Service providers can support people exiting homelessness to (re)connect with important and valued networks to reduce loneliness.
... The indicators were then run through factor analysis in order to find out any factors with ability to correlate independent indicators observed. Principal Component Analysis (PCA) and Common Factor Analysis (CFA) were applied to determine the coefficient score factor [17][18][19]. The factor analysis was computed based on Equation (1): ...
This study aims to assess the factors influential towards decision made by consumers to purchase hydroponic products. A quantitative research employing factor analysis, 100 samples were established as per accidental random sampling. The observed 11 variables – classified in four groups – were of hydroponic product feature (packing, size, freshness, and crunchiness), hydroponic product value (competitiveness and price), customer’s background (income, education, association, and family size), and place (service). The result shows that those who chose the products were mostly female (98) – 73 of them are housewives – aged between 37 and 42 (42) with at least senior high school educational background (69).
... Finally, biologically relevant interactions (based on field observations) were evaluated based on AIC scores. Goodness of fit tests (Hosmer and Lemeshow 1989) were performed to assess model fits. ...
Microhabitat selection in patchy environments supports the co-existence of closely related species competing for resources. We examined niche partitioning in three sympatric species of pikas, Ochotona macrotis, Ochotona nubrica, and Ochotona ladacensis from Ladakh, India, that display contrasting lifestyles, social behavior and co-occur at small spatial scales. We used a classical paired quadrat approach to document biologically relevant vegetation and landscape features (niches) likely to support the presence of different species. We used a Bayesian framework to describe niche spaces , estimate niche widths and overlaps between species pairs. In addition, we used a GLM framework to identify factors that promote the presence of different species in the landscape. The rock-dwelling Ochotona macrotis was a specialist, exclusively associated with microhabitats offering a good cover of large-sized rocks and no shrubs. The social, Ochotona nubrica , was a specialist found across elevations but associated exclusively with mature stands of scrub vegetation ( Caragana sp in the South-East and Hippophae sp in the North-West) occupying a unique niche. The social Ochotona ladacensis, although an elevational specialist, was likely to be found in microhabitats of other species characterised by moderate rock cover and low-lying Caragana scrublands, in addition to being found in alpine grasslands and meadows.
... In contrast, the 5xSTS test did not show signi cant discriminative power based on the ROC analysis (AUC, 0.67). According to the general guideline for AUC analyses proposed by Hosmer and Lemeshow, [27] for acceptable and excellent discriminative power, the AUC should reach at least 0.7 and 0.8, respectively. Therefore, the BBS had the highest and the most acceptable discriminative ability, while the 5xSTS had limited discriminative ability. ...
Objectives: To compare the validity of three widely-used fall risk assessment tools—Berg Balance Scale (BBS), Time Up and Go (TUG), and Five times Sit to Stand (5xSTS)—in predicting falls in community-dwelling elderly individuals in Saudi Arabia. Moreover, the cut-off point, sensitivity, specificity, and post-test accuracy percentage for each of the three physical performance measures were determined.
Design: Prospective study.
Setting: Two physical therapy department.
Participants: We recruited 114 ambulatory community-dwelling individuals aged ≥ 65 years. The exclusion criteria included balance-disturbing neurologic or orthopedic disorders, uncontrolled hypertension, cardiovascular disease, or inability to walk and communicate independently.
Primary and secondary outcome measures: The cut-off point, sensitivity, specificity, and post-test accuracy percentage for each of the three physical performance measures were determined.
Results: The BBS was sensitive to group differences between fallers and non-fallers (P=0.0001). Results from the receiver operating characteristic curve analyses showed that the accuracies of the BBS and TUG at classifying participants with and without a fall history were high-to-moderate (area under the curve [AUC], 0.73 and 0.71, respectively). In contrast, the accuracy of the 5xSTS for the same was low (AUC, 0.67). The cut-off points for the BBS, TUG, and 5xSTS were 42, 20, and 34 seconds, respectively. The highest post-test accuracy was of the BBS at 84.39%, followed by that of the TUG at 68.05%, and 5xSTS had the lowest accuracy at 25.29%.
Conclusions: Among the three assessment tools, the BBS was the most useful, followed by the TUG. On the other hand, the 5xSTS test revealed significant inadequacies, as it failed to distinguish between fallers and non-fallers, lacked discriminative power, and had poor post-test accuracy. Identifying elderly people at risk of falling using BBS, or TUG for time efficiency, would be most helpful to prevent falls and related injuries.
... We used the likelihood ratio test to detect differences in the size of change among years, null differences were found. Since the factor year did not improve the logistic model we therefore pooled years to perform a reduced model, where only size was an independent factor (Hosmer and Lemeshow, 2000). ...
Marine organisms have evolved a suite of responses to minimize the exposure to predators. Visual crypsis is one such strategy to avoid predation. Paraxanthus barbiger (Poeppig, 1836) is a species that exhibits different color morphotypes over heterogeneous substrates as a means of protection against visual predators. Our main objectives were to quantify the occurrence of color morphotypes over a three-year period and to investigate, via an experimental approach, on the possible mechanisms involved that would provide crypsis to this species. Field surveys occurred over a three-year period at two nearby sites on the central Chilean coast. Initial observations indicated that small juvenile P. barbiger exhibited higher degrees of color polymorphism than larger (. 20 mm carapace width) conspecifics. Furthermore, survival rates of small (, 10 mm carapace width) P. barbiger exposed to predators increased on heterogeneous substrata under both natural and laboratory conditions. Laboratory experiments further demonstrated that newly settled P. barbiger actively select heterogeneous substrata. Hence, cryptic responses of this species might reduce predation-mediated mortality through color pattern disruption of individuals with respect to their environment.
... To analyse the predictive power of the significant parameters for pCR, the receiver operating characteristics (ROC) curve was performed and area under the curve (AUC) value was determined. An AUC value of > 0.7 was considered sufficient for accurate prediction [22]. P values of < 0.05 were considered statistically significant. ...
Autophagy is a cellular response to diverse stresses within tumor microenvironment (TME) such as hypoxia. It enhances cell survival and triggers resistance to therapy. This study investigated the prognostic importance of HIF-1α and miR-210 in triple negative breast cancer (TNBC). Also, we studied the relation between beclin-1 and Bcl-2 and their prognostic relevance in triple negative breast cancer. Furthermore, the involvement of hypoxia-related markers, beclin-1 and Bcl-2 in mediating resistance to neoadjuvant chemotherapy (NACT) in TNBC was evaluated. Immunohistochemistry was performed to evaluate HIF-1α, beclin-1 and Bcl-2 expression whereas, miR-210 mRNA was detected by quantitative reverse transcription PCR (q-PCR) in 60 TNBC patients. High HIF-1α expression was related to larger tumors, grade III cases, positive lymphovascular invasion, advanced stage, high Ki-67 and poor overall survival (OS). High miR-210 and negative Bcl-2 expression were related to nodal metastasis, advanced stage and poor OS. High beclin-1 was associated with grade III, nodal metastasis, advanced stage and poor OS. Also, high beclin-1 and negative Bcl-2 were significantly associated with high HIF-1α and high miR-210. High HIF- 1α, miR-210 and beclin-1 as well as negative Bcl-2 were inversely related to pathologic complete response following NACT. High beclin-1 and lack of Bcl-2 are significantly related to hypoxic TME in TNBC. High HIF-1α, miR-210, and beclin-1 expression together with lack of Bcl-2 are significantly associated with poor prognosis as well as poor response to NACT. HIF-1α and miR-210 could accurately predict response to NACT in TNBC.
... Based on geological and structural data integration, zones of high landslide susceptibility were more common within the study location's north-central, central, and southern sections. Validation of landslide predictive map reveals accuracy levels of 77.8% and is considered valid for statistical predictions (Hosmer et al. 2013). ...
Structural displacement of the earth’s crust is one of many strategies for addressing landslide issues. The current study assessed the structural and lithological control and estimated the likelihood of future landslides along the case study area of Taiping to Ipoh section of the Highway network in Malaysia. Frequency ratio analysis, fry analysis, distance correlation analysis, simple multi-attribute rating technique (SMART) multi-criteria decision analysis, and radial fractal analysis methods were employed for evaluating structural patterns for landslides hazards and estimating the number of expected landslides in the area. A visual assessment of fry points generated from landslide occurrences suggests a predominant affiliation to the NW–SE tectonic trend. The SMART multi-criteria model reveals that 23.1% of the study location is a high-risk zone. Validation of the predictive model using the receiver operating curve and area under curve (ROC/AUC) analysis suggests an accuracy level of 77.8%. Conclusively, the lithological assessment revealed that granite and allied rock lithological units are more susceptible to landslide occurrences across the study area. A spatial estimation of landslide occurrences shows the possibility of an additional 78 landslides within the Taiping to Ipoh Segment of the highway. Therefore, given the results of this research, the appropriate mitigations can be taken to ensure safety.
... Considerando fatores de dispersão para FCoVs, foi considerado histórico de convivência com outros felinos provenientes de abrigos, gatis e/ou ambientes "multigatos", com ou sem associação de episódios de estresse relacionado. Na análise univariada, a variável independente foi cruzada com variável dependente, e aquelas que apresentassem p ≤ 0,20 pelo teste do qui-quadrado ou teste exato de Fisher seriam selecionadas para análise multivariada, por meio de regressão logística múltipla 28 .O nível de signifi cância adotado na análise múltipla foi de 5%. Todos dados foram analisados com o programa SPSS 20.0 Windows. ...
OBJETIVO: O presente estudo realizou diagnóstico molecular e analisou fatores de risco associados à infecção de Leishmania spp. Hemoplasmas, Bartonella spp. e Pan-coronavírus em gatos do Nordeste do Brasil. MÉTODOS: Foram obtidas 127 amostras sanguíneas e 52 amostras de swabs retal de gatos domiciliados e errantes que foram extraídas e submetidas à PCR convencional (cPCR) com alvo na região kDNA de Leishmania spp. e do gene gltA de Bartonella spp.; e triadas por PCR em tempo real (qPCR) direcionado para o gene 16S rRNA de hemoplasmas. Amostras de RNA extraídas dos sobrenadantes de suspensões fecais foram submetidas à cPCR visando gene pan-coronavírus nsp12. RESULTADOS: A frequência de positividade foi de 12,6% (16/127) para hemoplasmas e 4,7% (6/127) para Leishmania spp., sendo identificada co-positividade para ambos os agentes em 0,79% (1/127) dos gatos avaliados. As amostras para Bartonella spp. e pan-coronavírus não foram amplificadas. Dos animais positivos para Leishmania e hemoplasma, 66,6% (4/6) e 81,2% (13/16), apresentaram maior frequência de sinais clínicos como: êmese, apatia e pirexia. CONCLUSÃO: Este estudo relata, pela primeira vez, coinfecção por Leishmania spp. e hemoplasmas em gatos da mesorregião do São Francisco, Nordeste do Brasil, expressando risco no subdiagnóstico de doenças felinas relevantes em saúde pública.
... The results are presented as crude and adjusted odds ratios (OR) with 95% confidence intervals. The discriminative ability of the model was assessed through the area under the receiver operating characteristic curve (AUC), ranging from 0.5 (no discrimination) to 1.0 (perfect discrimination) [40]. All p values are two-sided, and the significance level was 5%. ...
Background
Low back pain (LBP) is a long-term health condition with distinct clinical courses. Its characterization together with the identification of prognostic factors for a persistent LBP course may trigger the development of personalized interventions. This study aimed to investigate the courses of chronic LBP (CLBP), its cumulative impact, and the indicators for the persistence of pain.Material and methodsPatients with active CLBP from the EpiDoC, a population-based cohort study of a randomly recruited sample of 10.661 adults with prolonged follow-up, were considered. Pain, disability, and health-related quality of life (HRQoL) were assessed at three time-points over five years. According to their pain symptoms over time, participants were classified as having a persistent (pain at the baseline and at all the subsequent time-points) or a relapsing pain course (pain at the baseline and no pain at least in one of the subsequent time-points). A mixed ANOVA was used to compare mean differences within and between patients of distinct courses. Prognostic indicators for the persistent LBP course were modulated through logistic regression.ResultsAmong the 1.201 adults with active CLBP at baseline, 634 (52.8%) completed the three time-points of data collection: 400 (63.1%) had a persistent and 234 (36.9%) a relapsing course. Statistically significant interactions were found between the group and time on disability (F (2,1258) = 23.779, p
... Link function piHere, βs are the regression coefficients that are evaluated by means of an iterative maximum likelihood method. Logistic regression analysis does not consider the prior probabilities of failure as well as the restrictive assumptions regarding the normal distribution of independent variables or the equal dispersion matrices[735] ...
The effects of environmental pollution and global warming have become a reality and severe. In addition to other causes, wide adoption and huge demands for computational resources have aggravated it significantly. The production process of the computing devices involves hazardous and toxic substances which not only harm human and other living beings’ health but also contaminate the water and soil. The production and operations of these computers on a large scale also result in massive energy consumption and greenhouse gas generation. Moreover, the low use cycle of these devices produces a huge amount of not easy-to-decompose e-waste. In this outlook, instead of buying new devices, it is advisable to use the existing resources to their fullest, which will minimize the environmental penalties of production and e-waste. In this study, we advocate for mobile crowd computing (MCC) to ease off the use of centralized high-performance computers (HPCs) such as data centres and supercomputers by utilising SMDs (smart mobile devices) as computing devices. We envision establishing MCC as the most feasible computing system solution for sustainable computing. Successful real-world implementation of MCC involves several challenges. In this study, we primarily focus on resource management. We devised a methodological and structured approach for resource profiling. We present the resource selection problem as an MCDM (multi-criteria decision making) problem and compared five MCDM approaches of dissimilar families to find the appropriate methodology for dynamic resource selection in MCC. To improve the overall performance of MCC, we present two scheduling algorithms, considering different objectives such as makespan, resource utilisation, load balance, and energy efficiency. We propose a deep learning based resource availability prediction to minimise the job offloading in a local MCC. We further propose a mobility-aware resource provisioning scheme for a P2P MCC. Finally, we present a proof-of-concept of the proposed MCC model as a working prototype. For this, we consider a smart HVAC (heating, ventilation, and cooling) system in a multistorey building and use MCC as a local edge computing infrastructure. The successful implementation of the prototype proves the feasibility and potential of MCC as alternative sustainable computing.
... The Hosmer-Lemeshow recommend sample sizes greater than 400 and a minimum number of cases per predictor variable is 10. [6,7] Logistic regression used to estimate the probability (or risk) of a particular outcome, given the value(s) of the independent variable, assumes a linear relationship with the logit of the outcome (natural logarithm of odds). The logistic regression model is initially defined as the probability of a two-level result of interest. ...
... A P-value < 0.05 was considered statistically significant. Variables with P-value < 0.025 were entered into a multiple regression model to determine independent associates of intradialytic dopamine use in IDH using backward elimination to adjust for confounders [32]. The mean predialysis SPO 2 , pulse rate, systolic, and diastolic BP were higher in sessions with PDD treatment compared to IDD treatment, P=0.06, P=0.001, P<0.001 and P=0.001 respectively ( Table 2). ...
Objectives: Despite advances made in dialysis delivery, management strategies for intradialytic hypotension (IDH) has largely remained suboptimal hence the need for more interventions to improve on it. Methods: We compared in this retrospective study, predialysis dopamine (PDD) with intra-dialytic dopamine (IDD) in the treatment of severe IDH. Results: Of the 2968 sessions, 518 (17.45%) had symptomatic IDH, of this, 9.65% had PDD while 12.16% had IDD. The mean age of all participants, participants with PDD, and those with IDD were 50.73 ± 6.51 years, 64.48 ± 8.22 years and 64.64 ± 10.31 years respectively, P=0.001. The intra-dialytic pulse rate increases, with BP reductions, were more with IDD treatments than PDD. Dialysis BFR, ultrafiltration volume, duration and dose were higher with PDD than with IDD treatment, P=0.002, P=0.03, P=0.04 and P<0.001 respectively. Hospitalization, dialysis termination and intra-dialytic death were more common with IDD than with PDD treatment, P=0.08, P=0.001 and P=0.002. PDD was commoner in females, advancing age and diabetes, P=0.08, P=0.93 and Original Research Article Uduagbamen et al.; AJRN, 5(2): 18-29, 2022; Article no.AJRN.86510 19 P=0.06. Independent associates of IDD were lower predialysis systolic, and diastolic BP, shorter dialysis duration, dialysis termination and intra-dialytic death. Conclusion: The prevalence of overall IDH, of severe IDH using a nadir systolic BP less than 90 mmHg, and of severe IDH using a minimum 20 mmHg intra-dialytic fall in systolic BP were 17.45%, 1.68% and 2.12% respectively. Low dose PDD treatment of severe IDH allows for a relative optimization of the prescribed dialysis, gives higher dialysis dose and reduces the frequencies of dialysis termination and intradialytic death.
... According to Hosmer and Lemeshow, an AuROC of 0.70-0.80, 0.80-0.90, and above 0.90 was considered acceptable, excellent, and outstanding, respectively [9]. The model calibration was illustrated with a calibration plot, which refers to the agreement between model prediction and the observed outcome risk. ...
Motorcycle accidents accounted for the most common prevalence of Road traffic collision (RTC). Therefore, identifying the rider or passenger is crucial for ensuring fairness. However, patients who suffered from RTC frequently could not provide any information due to loss of consciousness, memory loss, or death. We aim to develop two separately multivariable prediction models based on the differences in the facture pattern and demographic data between the rider and passenger in collision with another vehicle and non-collision motorcycle accident. A total of 1,816 patients had fractures from motorcycle accidents. 1,583 and 233 were riders and passengers, respectively. After a multivariable logistic regression with stepwise backward elimination, six final predictors, including Age, sex, femur fracture, wrist and hand fracture, leg including ankle fracture, and pelvis and lumbar spine fracture, were required for the final models. The prediction models had an acceptable level of discrimination (auROCs of 0.79 and 0.77 for collision and non-collision accidents, respectively) and appeared well-calibrated. Overall, the prediction model is potentially useful as an assisting tool for identifying seat positions.
... The closer the AUC value to 1, the higher the model's predictive quality. Taking into account the research of Hosmer and Lemeshow (2000), AUC values ranging between 0.6 and 0.8 indicate acceptable model results, values between 0.8 and 0.9 an excellent model performance, and AUC> 0.9 stand for an outstanding model result. ...
This paper investigates the locations of past watermills in terms of their hydrological and geomorphological conditions. In our analysis, the natural landscape was treated as a resource of factors favouring or hindering the location of a specific mill and the possibility of their persistence as technological and economic conditions became increasingly unfavourable throughout history. An answer was provided to the question of which areas were environmentally preferable for the location of a plant using the energy of flowing water and in which types of landscape - enclaves of the cultural mill landscape were preserved for the longest time. The Maximum Entropy Method (MaxEnt) was used to determine the spatial probability distribution of the mill reservoir locations based on the delimitation of natural landscape types. Ten per cent of the study area shows a high occurrence probability for mill location (>0.9). The spatial distribution of MaxEnt outcomes shows that landscapes prone to mill location mainly concentrate on the edge of morainic plateaus and in the tunnel valleys. The research results allow us to understand the evolution of the cultural landscape in the lowland area, especially the role of mill settlements in colonising of forest areas and river valleys.
... The best models were selected for each full model based on a 10-fold cross-validation procedure by minimizing the AIC criterion (package 'MuMIn'; [51]). For each species, we kept only the models with AUC � 0.7 [52,53]. In addition, we analyzed the assemblage structure based on continuous occurrence probabilities instead of binarizing the outputs [46,54]. ...
Logging is the main human disturbance impacting biodiversity in forest ecosystems. However, the impact of forest harvesting on biodiversity is modulated by abiotic conditions through complex relationships that remain poorly documented. Therefore, the interplay between forest management and climate change can no longer be ignored. Our aim was to study the expected long-term variations in the assemblage of bird and beetle communities following modifications in forest management under different climate change scenarios. We developed species distribution models to predict the occurrence of 88 species of birds and beetles in eastern Canadian boreal forests over the next century. We simulated three climate scenarios (baseline, RCP4.5 and RCP8.5) under which we varied the level of harvesting. We also analyzed the regional assemblage dissimilarity by decomposing it into balanced variations in species occupancy and occupancy gradient. We predict that forest harvesting will alter the diversity by increasing assemblage dissimilarity under all the studied climate scenarios, mainly due to species turnover. Species turnover intensity was greater for ground-dwelling beetles, probably because they have lower dispersal capacity than flying beetles or birds. A good dispersal capacity allows species to travel more easily between ecosystems across the landscape when they search for suitable habitats after a disturbance. Regionally, an overall increase in the probability of occupancy is projected for bird species, whereas a decrease is predicted for beetles, a variation that could reflect differences in ecological traits between taxa. Our results further predict a decrease in the number of species that increase their occupancy after harvest under the most severe climatic scenario for both taxa. We anticipate that under severe climate change, increasing forest disturbance will be detrimental to beetles associated with old forests but also with young forests after disturbances.
... Abbreviations: AUC, area under the ROC (receiving operating characteristic) curve; CCR, correct classification rate; TSS, true skill statistic. AUC > 0.9 is considered an outstanding discrimination capacity, according to Hosmer and Lemeshow[129]. ...
The sexual species of the Dilatata complex (Paspalum dasypleurum, P. flavescens, P. plurinerve, P. vacarianum, and P. urvillei) are closely related phylogenetically and show allopatric distributions, except P. urvillei. These species show microhabitat similarities and differences in germination traits. We integrated species distribution models (SDMs) and seed germination assays to determine whether germination divergences explain their biogeographic pattern. We trained SDMs in South Amer-ica using species' presence-absence data and environmental variables. Additionally, populations sampled from highly favourable areas in the SDMs of these species were grown together, and their seeds germinated at different temperatures and dormancy-breaking conditions. Differences among species in seed dormancy and germination niche breadth were tested, and linear regressions between seed dormancy and climatic variables were explored. SDMs correctly classified both the observed presences and absences. Spatial factors and anthropogenic activities were the main factors explaining these distributions. Both SDMs and germination analyses confirmed that the niche of P. urvillei was broader than the other species which showed restricted distributions, narrower germination niches, and high correlations between seed dormancy and precipitation regimes. Both approaches provided evidence about the generalist-specialist status of each species. Divergences in seed dormancy between the specialist species could explain these allopatric distributions.
... p = 0.06). Nevertheless, the area under the ROC curve was 0.531, which, according to Hosmer et al.(9), suggests a very poor level of discrimination between the two groups. ...
Background
While stroke is one of the most dissected topics in neurology, the primary prevention of PFO-related stroke in young patients is still an unaddressed subject. We present a study concerning clinical, demographic, and laboratory factors associated with stroke and transient ischemic attack in patients with patent foramen ovale (PFO), as well as comparing PFO-patients with and without cerebrovascular ischemic events (CVEs).
Patients and methods
Consecutive patients with PFO-associated CVEs were included in the study; control group was selected from patients with a PFO and no history of stroke. All participants underwent peripheral routine blood analyses, as well as, on treating physician's recommendations, screening for thrombophilia.
Results
Ninety-five patients with CVEs and 41 controls were included. Females had a significantly lower risk of CVEs than males ( p = 0.04). PFO size was similar between patients and controls. Patients with CVEs had more often hypertension ( n = 33, 34.7%), p = 0.007. No significant differences were found between the two groups with regard to routine laboratory tests and thrombophilia status. Hypertension and gender were identified in a binomial logistic regression model as independent predictors for CVEs, but with an area under the ROC curve of 0.531, suggesting a very poor level of discrimination between the two groups.
Discussion and conclusions
There is little difference between patients with PFO with and without CVEs in terms of PFO size and routine laboratory analyses. While still a controversial topic in the specialty literature, classic first-level thrombophilic mutations are not a risk factor for stroke in patients with PFO. Hypertension and male gender were identified as factors associated with a higher risk of stroke in the setting of PFO.
... Multivariate logistic regression was conducted using the approach of Hosmer and Lemeshow. 5 This approach consists of five steps: 1) a preliminary screening of all independent variables for univariate associations, 2) selection of variables with P values less than 0.25 for construction of the full multivariate logistic regression model, 3) stepwise removal of non-significant variables from the full model while comparing the reduced model to the previous model for model fit and confounding, 4) evaluation of interaction among the remaining variables, and 5) assessment of model fit using the Hosmer-Lemeshow statistic. Model fitting was continued until all main effects or interaction terms were statistically significant by the Wald statistic at the P :S 0.10 level. ...
Data from 407 dairy risk assessments completed as part of the United States Department of Agriculture's Voluntary Bovine Johne's Disease Control Program in Washington and Oregon from November 2003 to August 2007 were evaluated to determine what management practices were associated with herd Johne's disease status, and what range of these management practices were in use in Pacific Northwest dairies. Overall, assessment scores between Johne's disease-positive and Johne's disease-negative herds did not significantly differ. A multivariate logistic regression analysis of the 32 individual management practices and two herd-level variables included in the overall risk assessment score found nine factors significantly associated with whether the assessment veterinarian reported at least one case of Johne's disease in the previous year. These nine factors were: (1) herd size, (2) addition of new animals during the previous year, (3) stocking density of the calving area, (4) degree of manure build-up in the calving area, (5) presence of Johne's disease suspects in the calving area, (6) degree of manure soiling of udders and legs of cows in the calving area, (7) exposure of bred heifers to adult cow manure, (8) pasture-sharing by bred heifers and adult cows, and (9) degree of contamination of adult cow feed with manure.
... The final model was tested for goodness-of-fit using the Hosmer-Lemeshow test. 10,12 Statistical analyses and calculations were performed in RStudio V. 1 For continuous variables, the median, interquartile range (IQR -difference between 75th and 25th percentiles), minimum and maximum were produced in place of the numbers of cases and controls (Table 1). ...
Background:
Equestrian eventing is a dangerous Olympic sport, with 16 rider and 69 horse fatalities at competition in the last 10 years. Despite this, there is limited research that aims to improve safety within the sport.
Objectives:
The purpose of this study was to identify risk factors for horse falls, which are the leading cause of rider fatality within the sport.
Study design:
Retrospective cohort study.
Methods:
Competition data between January 2005 and December 2015 were analysed. Descriptive statistics followed by univariable logistic regression to identify risk factors for inclusion in a multivariable logistic regression model were conducted. Models were constructed stepwise using a bi-directional process and assessed using the Akaike Information Criterion. A total of 749 534 cross-country starts were analysed for association with the risk of horse falls.
Results:
Sixteen risk factors were identified including: higher event levels, higher dressage penalties and higher number of days since horses' last start. For example, horse and rider combinations competing at BE100 (OR 1.64, CI 1.37-1.96, p < 0.001), Novice (OR 3.58, CI 3.03-4.24, p < 0.001), Intermediate (OR 8.00, CI 6.54-9.78, p < 0.001), Advanced (OR 12.49, CI 9.42-16.57, p < 0.001) and International (OR 4.63, CI 3.50-6.12, p < 0.001) all had a higher risk of having a horse fall in comparison to combinations competing at BE90 level. Furthermore, for every additional 10 dressage penalties awarded to a horse and rider combination, there was a higher risk of a horse fall (OR 1.20, CI 1.12-1.28, p < 0.001).
Main limitations:
The study is not geographically comprehensive (UK only) and does not include any information on training activity of horses and riders.
Conclusions:
This is the largest-scale study ever conducted on horse falls during eventing competition. Study results can be utilised by sport governing bodies to inform policy which has the potential to reduce the risk of injury and fatality to sport participants. This article is protected by copyright. All rights reserved.
... This is similar to using a case-control approach under which the invariance of the model coefficients and odds ratios has been shown by mathematical proof 41 . However, it is not possible to make inferences about absolute probabilities based on the intercept parameter 42 . In this study, it was possible to correct for this because the true and sampled fractions of the EHI and non-EHI events is known. ...
The development of exertional heat illness (EHI) is a health, welfare and performance concern for racehorses. However, there has been limited multivariable assessment of the possible risk factors for EHI in racehorses, despite such information being vital for regulators to effectively manage the condition. Consequently, this study aimed to identify the risk factors associated with the occurrence of EHI in Thoroughbred racehorses and assess the ability of the risk factor model to predict the occurrence of EHI in racehorses to assist in early identification. Runners at British racecourses recorded in the British Horseracing Authority database between 1st July 2010 and 30th April 2018 were used to model the probability that a horse would present with EHI as a function of a suite of environmental, horse level and race level factors. EHI was reported in 0.1% of runners. Race distance, wet bulb globe temperature, preceding 5-day temperature average, occurrence of a previous EHI incident, going, year and race off time were identified as risk factors for EHI. The model performed better than chance in classifying incidents with a mean area under the receiver operating characteristic curve score of 0.884 (SD = 0.02) but had a large number of false positives. The results provide vital evidence for industry on the need to provide appropriate cool down facilities, identify horses that have repeated EHI incidents for early intervention, and collect new data streams such as on course wet bulb globe temperature measurements. The results are especially relevant as the sport is operating in a changing climate and must mitigate against more extreme and longer spells of hot weather.
... This p value is recommended because the use of the traditional level (p<0.05) often fails to identify some variables that are known to be of importance (18). Ethics: The confidentiality of participants' responses and the anonymity of their identities were fully guaranteed. ...
BACKGROUND፡ Primary health care (PHC) centers help in providing a complete, universal, unbiased, and reasonable healthcare service to all. One major aim of PHC is to reduce health inequality. Most PHC centers in Nigeria cannot deliver fundamental healthcare services due to staffing, equipment distribution, quality infrastructure, and drug supply problems. The objective of this study was to assess the awareness and utilization of PHC services in a rural community in Nigeria. METHODS: The study was carried out in a pastoral area in Ekiti State, Nigeria. A multistage sampling procedure was used to recruit adults aged 18 years and over residing in 361 households. A semi-structured questionnaire was utilized for data compilation. Study data were evaluated using IBM SPSS version 28.0 and reported using descriptive and inferential statistics. Chi-square test and binary logistic regression were used to assess the associated factors and predictors of PHC utilization. RESULTS: The proportion of those who had ever utilized PHC services was 45.7%. Significant predictors of the utilization of PHC centers include knowledge of the location of a PHC center, awareness that PHC centers operate 24 hours every day, and awareness that community members are part of the PHC staff. CONCLUSIONS: Non-availability of medical personnel and ease of access to secondary and tertiary health institutions are potential threats to the use of PHC facilities.
... It was used to calculate and investigate the relationships between age at CI, audiological variables (speech perception in quiet, with fixed and adaptive noise) and language (TROG-2) outcomes. A multivariate analysis was performed to quantify the relationships between a dependent variable (It-Matrix) and a set of explanatory variables (age at CI, speech perception in quiet and with noise, language skills, TROG-2) using a stepwise hierarchical linear regression model including all the variables with p ≤ 0.05 [35]. As noted below, the contribution of each variable to the prediction of the model was assessed in stages, progressively filtering the information, and allowing the identification of a statistically significant amount of variance in the outcomes that could be related to specific predictors. ...
Background:
Long-term assessments of children with cochlear implants (CI) are important inputs to help guide families and professionals in therapeutic and counselling processes. Based on these premises, the primary aim of the present study was to assess the long-term speech and language outcomes in a sample of prelingually deaf or hard of hearing (DHH) adolescents and young adults with unilateral or bilateral implantation in childhood. The secondary aim was to investigate the correlations of age at implantation with long-term speech and language outcomes.
Materials and methods:
Retrospective observational study on 54 long-term CI users, 33 unilateral and 21 bilateral (mean age at CI surgery 38.1 ± 24.6 months; mean age at last follow-up assessment 19.1 ± 4.3 years of age and mean follow-up time 16 ± 3.7 years). Means and standards were used to describe speech perception (in quiet, in fixed noise and in adaptive noise using It-Matrix) and morphosyntactic comprehension (TROG-2) outcomes. A univariate analysis was used to evaluate outcome differences between unilateral and bilateral patients. Bivariate analysis was performed to investigate the relationships between age at CI, audiological variables, and language outcomes. Finally, multivariate analysis was performed to quantify the relationship between It-Matrix, sentence recognition in quiet and at SNR+10 and TROG-2.
Results:
The participants showed good speech recognition performance in quiet (94% for words and 89% for sentences) whilst their speech-in-noise scores decreased significantly. For the It-Matrix, only 9.2% of the participants showed scores within the normative range. This value was 60% for TROG-2 performance. For both auditory and language skills, group differences for unilateral versus bilateral CI users were not statistically significant (p > 0.05). Bivariate analysis showed that age at CI correlated significantly with overall results at TROG-2 (r = -0.6; p < 0.001) and with It-Matrix (r = 0.5; p < 0.001). TROG-2 was negatively correlated with results for It-Matrix (r = -0.5; p < 0.001). In the multivariate analysis with It-Matrix as a dependent variable, the model explained 63% of the variance, of which 60% was related to sentence recognition and 3% to morphosyntax.
Conclusions:
These data contribute to the definition of average long-term outcomes expected in subjects implanted during childhood whilst increasing our knowledge of the effects of variables such as age at CI and morphosyntactic comprehension on speech perception. Although the majority of this prelingually DHH cohort did not achieve scores within a normative range, remarkably better It-Matrix scores were observed when compared to those from postlingually deafened adult CI users.
... Because of the dichotomous outcome variable (that is, unsolved and cleared cases), we exploited logistic regression models to perform this analysis. Binary response logistic regression is based on the Bernoulli probability distribution, and it does not require independent variables to be linearly related; nor does it require homoscedasticity, which makes it a quite flexible instrument for statistical analysis (Hosmer et al., 2013). ...
... Subsequently, we fitted an additional model adjusting for all other covariates: energy intake (continuous), adherence to a Mediterranean diet (continuous), alcohol intake (three categories), BMI (continuous), physical activity (quartiles), hours of watching TV (continuous), smoking (three categories), pack-years of smoking (continuous), previous depression (yes/no), years of university (continuous), hours of siesta (over or under half an hour), added sugar in drinks (yes/no), and family history of diabetes (yes/no). We addressed the goodness of fit (calibration) of the final model with the Hosmer-Lemeshow test [40]. ...
(1) Background: Metabolic Syndrome (MetS) affects over a third of the United States population, and has similar prevalence in Europe. Dietary approaches to prevention are important. Coffee consumption has been inversely associated with mortality and chronic disease; however, its relation to the risk of MetS is unclear. We aimed to investigate the association between coffee consumption and incident MetS in the ‘Seguimiento Universidad de Navarra’ cohort. (2) Methods: From the SUN project, we included 10,253 participants initially free of MetS. Coffee consumption was assessed at baseline, and the development of MetS was assessed after 6 years of follow-up. All data were self-reported by participants. MetS was defined according to the Harmonizing Definition. We used multivariable logistic regression models to estimate odds ratios and 95% confidence intervals for incident MetS according to four categories of coffee consumption: <1 cup/month; ≥1 cup/month to <1 cup/day; ≥1 cup/day to <4 cups/day; ≥4 cups/day. (3) Results: 398 participants developed MetS. Coffee consumption of ≥1 to <4 cups/day was associated with significantly lower odds of developing MetS (multivariable adjusted OR = 0.71, 95% CI (0.50–0.99)) as compared to consumption of <1 cup/month. (4) Conclusions: In a Mediterranean cohort, moderate coffee consumption may be associated with a lower risk of MetS.
... For a marker of CRF to be considered a valid predictor of mortality, an AUROC of >0.7 was used. 38 Threshold values for markers of CRF fulfilling this criterion were subsequently calculated for pooled, male, and female patients by examination of the minimal distance between AUROC plots and the upper left corner, optimizing sensitivity and specificity. ...
Background:
To what extent sex-related differences in cardiorespiratory fitness (CRF) impact postoperative patient mortality and corresponding implications for surgical risk stratification remains to be established.
Methods:
To examine this, we recruited 640 patients (366 males vs. 274 females) who underwent cardiopulmonary exercise testing prior to elective colorectal surgery. Patients were defined high risk if peak oxygen uptake was <14.3 mL kg-1 min-1 and ventilatory equivalent for carbon dioxide at 'anaerobic threshold' >34. Between-sex CRF and mortality was assessed, and sex-specific CRF thresholds predictive of mortality calculated.
Results:
Seventeen percent of deaths were attributed to sub-threshold CRF, which was higher than established risk factors for cardiovascular disease (CVD). The group (independent of sex) exhibited a 5-fold higher mortality (high vs. low risk patients hazard ratio =4.80, 95% confidence interval 2.73 to 8.45, P <0.001). Females exhibited 39% lower CRF (P <0.001) with more classified high risk than males (36 vs. 23%, P=0.001), yet mortality was not different (P =0.544). Upon reformulation of sex-specific CRF thresholds, lower cut-offs for mortality were observed in females, and consequently, fewer (20%) were stratified with sub-threshold CRF compared to the original 36% (P<0.001).
Conclusions:
Low CRF accounted for more deaths than traditional CVD risk factors and when CRF was considered relative to sex, the disproportionate number of females stratified unfit was corrected. These findings support clinical consideration of 'sex-specific' CRF thresholds to better inform postoperative mortality and improve surgical risk stratification.
... Furthermore, the outcome of the ROC curve analysis displayed that TY G and TG/HDL were good indicators of IR. The AUC values of both parameters were greater than 0.75, which is considered as an acceptable representative of the test performance [38]. However, the TY G was a better marker for indicating IR than TG/HDL owing to the fact that it had a higher value of AUC. ...
Background
Insulin resistance (IR) means the requirement of a higher insulin concentration to produce the expected biological effect. It was proposed that triglycerides–glucose index (TY G) and triglycerides–high-density lipoprotein cholesterol ratio (TG/HDL) were dependable, applicable, and less-expensive markers of IR. However, their results varied significantly among different ethnic groups.
Aim
To assess the eligibility of TY G and TG/HDL as IR indices among overweight and/or obese Egyptians.
Patients and methods
The participants in this cross-sectional study were 328 overweight and/or obese Egyptians. Their fasting blood glucose, TG, HDL, and fasting insulin blood concentrations were estimated. Homeostasis model assessment-insulin resistance (HOMA-IR), TY G, and TG/HDL were calculated.
Results
A statistically significant positive correlation between HOMA-IR and both TY G (r = 0.688; P < 0.001) and TG/HDL (r = 0.590; P < 0.001) was identified. Four quartiles had been set up for HOMA-IR across which both indices showed trends of consistent increase. Analysis of the receiver-operating characteristic curves revealed that TY G [area under the curve = 0.858 (95% confidence interval 0.819–0.897) (P < 0.001)] is a better marker for IR than TG/HDL [area under the curve = 0.796 (95% confidence interval 0.750–0.843) (P < 0.001)] and demonstrated more than or equal to 8.22 and more than or equal to 1.82 as their respective cutoff values.
Conclusion
TY G and TG/HDL demonstrated significant association with HOMA-IR and might be applied as eligible indices of IR among overweight and/or obese Egyptians.
... Given the multicollinearity among the landscape and habitat parameters, and the apparent effect of many of these on the occurrence of the three species, we explored the independent effect of these parameters using logistic regression (Hosmer & Lemeshow 1989). The independent variables included were area, ownership (categorical variable), tree density, basal area, canopy height and canopy cover. ...
A report on the study of rainforest fragmentation on arboreal mammals (lion-tailed macaque, Nilgiri langur, and Malabar giant squirrel), rodents, and shrews in the Anamalai Hills, Western Ghats, South India.
Athlete-students who are faced with both their athletic and academic demands may identify more strongly with their academic or athletic role, depending on a number of influential factors. The aim of this study is to examine the effects of self-efficacy, gender and age of athletes-students on their academic achievement. The data were collected from a total of 980 university licensed athletes-students studying at the university's faculty of sports sciences. The results showed that high self-efficacy levels of athlete-students were an important predictor of their academic success. As the age of the athletes increases, their academic success rate increases; It was found that female athlete students were more likely to fail than male students. Another result was that as the athletes' perceptions of being confident in their abilities increased, the probability of being academically successful increased. These results revealed that age, gender and being confident about their abilities are a determinant of academic success, and athlete self-efficacy is an important factor in the academic success of students during their education period. It can be said that the results of the research are an important factor in guiding future research and educational prevention and intervention efforts for athletes.
The real estate agency industry has seen the emergence and growth of disruptive technology and innovation to the extent that real estate agents view search portals such as Zillow and Purplebricks as serious competition. In response to these threats, a major real estate agency in Singapore, OrangeTee, launched a property agent review and rating program called Property Agent Review (PAR) to provide better information on their agents for prospective clients. The PAR program provides a natural experiment to test the effect of informative reviews and ratings on agent performance in terms of commissions and transactions. This is done via a difference-in-difference approach, carefully controlling for observed agent characteristics and market conditions. This paper also analyses the informativeness of reviews.
The aim of this study is to determine to what extent adolescents' cyber victimization, peer bullying, dark triad personality traits, risk behavior and prosocial behaviors predict cyberbully and non-cyberbully adolescents. This research is a descriptive quantitative research conducted in a cross-sectional design and designed in an exploratory correlational model. A total of 952 students studying at 9 faculties and 1 vocational school at İnönü University in the 2021-2022 academic year participated in the research. Revised Cyberbullying/Victimization Inventory 2, Peer Bullying Scale, Short Dark Triad Scale Turkish Form, Risk Behaviors Scale, Prosocial Tendencies Scale and personal information form were used as data collection tools in the study. The data of the study were analyzed by percent-frequency analysis and logistic regression analysis. Before performing the logistic regression analysis, it was determined that the sample was large enough, outlier data were not included in the analysis, and the correlation coefficients between the variables were examined and it was seen that there was no multicollinearity problem. As a result of the research, it was determined that 47% of the adolescents in the sample were involved in the cyberbullying process as a bully, victim or bully/victim (both bully and victim); 53% of them were not involved in cyberbullying. It was determined that 30% of the adolescents are cyberbullies, 40% are cyber victims, 7% are only cyberbullies, 17% are only cyber victims, and 23% are bullies/victims. In the logistic regression model obtained, it was determined that there was a relationship between cyberbullying and the predictive variables in the study, that the goodness of fit of the model was sufficient and it explained 25% of the variance in cyberbullying. It was determined that the model accurately classified cyberbully and non-cyberbully adolescents at the rate of 79%, and cyber victimization, peer bullying, alcohol use, antisocial behaviors and nutrition habits made significant contributions to the prediction of cyberbully and non-cyberbully adolescents.
At the present, Indonesia operate dual banking system that are conventional banking system with its interest rate runs side by side and the Islamic banking with the profit-sharing/non-interest system of its own. Islamic banking using fiqih mu’amalat as the basic theory in the syari’ah product. In general, community’s respond toward Islamic bank is good relatively that shown by the trend of Third Parties Funding and Financing to Deposit Ratio with low level of Non Performing Loan. This paper assess the consumer’s preference toward both conventional and Islamic banking, in related with analysis of potency and development strategy of Islamic banking in Indonesia by using fiqih mu’amalat as the basic theory. The analysis of data by using qualitatively (descriptive) analysis, cross tabulation, and logistic regression model. Literature study used in this paper. In general, community’s attitude toward interest rate system still ambiguous, that are interest rate is contrary to syari’ah of Islam, meanwhile in banking transaction they still use conventional system. The reasons that motivate consumer to adopt Islamic banking related to professionalism of bank, security, and pleasure in doing transaction, strategic location, and the implementation of syari’ah system. However, community still has difficulties to comprehend the technical term of Islamic banking. Thus, socialization and education process about economic system of Islam (syari’ah economic) designate necessary requirement in encourage the development of Islamic banking in the future.
Bu araştırmanın amacı ergenlerdeki riskli davranışlar ve prososyal davranışların ergenlerin siber zorba olup olmadığını ne düzeyde öngördüğünü incelemektir. Bu araştırma kesitsel desende gerçekleştirilmiş betimsel bir nicel araştırma olup keşfedici korelasyonel modelde tasarlanmıştır. Araştırmaya 2021-2022 eğitim öğretim yılında İnönü Üniversitesi’nin 9 fakülte ve 1 meslek yüksekokulunda öğrenim gören toplam 952 öğrenci katılmıştır. Araştırmada veri toplama araçları olarak Yenilenmiş Siber Zorbalık/Mağduriyet Envanteri 2, Riskli Davranışlar Ölçeği, Olumlu Sosyal Davranış Eğilimi Ölçeği ve kişisel bilgi formu kullanılmıştır. Araştırmanın verileri lojistik regresyon analizi ile incelenmiştir. Lojistik regresyon analizi gerçekleştirilmeden önce örneklemin yeterli büyüklükte olduğu belirlenmiş, uç veriler belirlenerek analize dahil edilmemiş ve değişkenler arasındaki korelasyon katsayıları incelenerek çoklu bağlantı problemi olmadığı görülmüştür. Siber zorba olan ergenler “1” olarak, siber zorba olmayan ergenler “0” olarak kodlanmış ve lojistik regresyon analizinin standart (enter) yöntemi kullanılarak analiz gerçekleştirilmiştir. Elde edilen veriler SPSS 22 programı aracılığıyla analiz edilmiştir. Araştırma sonucunda elde edilen lojistik regresyon modelinde siber zorbalık ile araştırmada ele alınan yordayıcı değişkenler arasında ilişki olduğu belirlenmiştir. Lojistik regresyon modelinin uyum iyiliğinin yeterli düzeyde olduğu tespit edilmiştir. Modelin, siber zorbalıktaki varyansın %9.3’ünü açıkladığı saptanmıştır. Elde edilen modelin siber zorba olan ve olmayan ergenleri %70.4 oranında doğru sınıflandırdığı bulunmuştur. Modelde yer alan yordayıcı değişkenlerden riskli davranışların alt boyutlarından antisosyal davranışlar, alkol kullanımı ve beslenme alışkanlıkları değişkenlerinin siber zorba olan ve olmayan ergenlerin öngörülmesine anlamlı katkılar sağladığı belirlenmiştir. Riskli davranışların diğer alt boyutları olan sigara kullanımı, intihar eğilimi ve okul terki değişkenleri ile prososyal davranışların hiçbir alt boyutunun siber zorba olan ve olmayan ergenlerin öngörülmesine anlamlı katkılar sağlamadığı saptanmıştır.
تعد دراسة المتغيرات التابعة الثنائية من العمليات المهمة في وقتنا الحاضر لكثرة الظواهر التي توصف بهذه الطريقة ويعد انموذج الاستجابة الثنائي من اهم الوسائل لتمثيل هذا النوع من الظواهر، كما تعد عملية اختيار المتغيرات المستقلة التي تؤثر على المتغيرات التابعة الثنائية ضرورية جدا. تضمنت الدراسة استعمال اسلوبين، الاول هو الاسلوب التجريبي (محاكاة) والاسلوب الثاني هو التطبيقي على المصابين بوباء كورونا وقد تم استعمال ثلاث طرائق لاختيار افضل انموذج استجابة ثنائي وهي طريقة التقدم الامامي، و طريقة الحذف العكسي ،و طريقة مقترحة و هي طريقة التحليل العاملي مع اختبار جودة التوفيق للأنموذج النهائي الناتج عن كل طريقة باستعمال اختبارين هما اختبار الانحراف (D) واختبار هوزمر- ليمشو (H&L) و تمت المقارنة بين النماذج النهائية الناتجة عن الطرائق الثلاث باستعمال ثلاثة معايير و هي معيار نسبة الامكان الاعظم(MLR) و معيار المعلومات لـ اكاكي (ِAIC) و معيار المعلومات البيزي (BIC) و بينت النتائج ان للعوامل الناتجة عن التحليل العاملي قدرة على تقليل نسبة الامكان الاعظم افضل من اي تشكيلة مختارة من المتغيرات المستقلة باستعمال احدى طرائق الاختيار الاخرى، ومن ثم فان معايير اختيار افضل انموذج التي تعتمد على نسبة الامكان الاعظم وهما (AIC , BIC) تعطي افضلية للعوامل الناتجة عن طريقة التحليل العاملي على حساب المتغيرات المستقلة الناتجة عن طريقتي التقدم الامامي والحذف العكسي. كما بينت النتائج ايضا انه كلما كان عدد المتغيرات المستقلة التي لها تأثير معنوي على الانموذج كثيرة كلما اعطت العوامل نتائج افضل حسب المعايير المستخدمة. و أظهرت النتائج الاسلوب التطبيقي ان المتغيرين المستقلين عمر المريض والتدخين لهما اكثر تأثير على حياة المصابين بوباء كورونا.
A pesquisa teve por objetivo verificar se a presença e o percentual de mulheres no conselho de administração influenciam na participação da empresa no Índice de Sustentabilidade Empresarial (ISE). Foram utilizadas informações dos formulários de referência, da Economática, do site da Bovespa e das carteiras do ISE. Os dados analisados foram das empresas listadas na B3, no período de 2010 e 2017, e das carteiras do ISE de 2012 a 2019, por meio de um modelo econométrico e o estimador logit. Verificou-se que há associação entre a presença e o percentual de mulheres no conselho para participação das empresas no ISE e assim concluiu-se que a presença de mulheres nos conselhos de administração tem influência positiva na participação das empresas no ISE. A pesquisa contribuiu para a literatura ao propor um modelo robusto com estimação logística e uma investigação empírica sobre a participação de mulheres em conselhos empresariais. Também levantou características das conselheiras das empresas brasileiras e reforçou a contribuição positiva das mulheres no ambiente de trabalho em diversos aspectos, apesar de verificar as dificuldades de acesso delas aos cargos superiores.
This thesis provides description of the ecological niche space of the Common Wall Lizard (Podarcis muralis) in the Vojvodina region of Serbia with a detailed presentation of its distribution in the area. Additionally, a quantification of the developmental stability of the wall lizard in Vojvodina on an urbanization gradient is given. Finally, the ecological and conservational status of the species in the Vojvodina region is described. The species’ ecological niche space was analysed using the ENFA and MaxEnt modelling approaches, with ecogeographical variables derived from bioclimatic, atmospheric water regime, orographic, and land cover habitat variables. The obtained models were compared with models for peripanonian and mountainous Serbia since we believe the current distribution of the wall lizard in Vojvodina depends on ecological signals specifically present in the Vojvodina region but are absent in the two other ecogeographical regions of Serbia. Niche models for lizards in Vojvodina were significantly different from models for the peripanonian and mountainous regions of Serbia. The differences in ecological niche space were interpreted and related to the bionomy of the species. Ecological niche models revealed a wide distribution of the wall lizard across urban habitats of the Vojvodina region and a clear association with habitats of this type. Specifically, we identified a pattern of the close association of species’ presence with edge habitats of urban and industrial sites, and a general avoidance of agricultural habitats. In the other two regions, this signal was less pronounced with different habitat and orographic variables becoming more important. Overall, bionomic signals related to habitat structure were more important than scenopoetic signals related to abiotic conditions in defining the ecological space of this species in Serbia. Since urban habitats are generally believed to be stressful environments with numerous challenges to species’ overall fitness, we analyzed developmental stability of lizards across a gradient of urbanization to provide insight into the possible coping mechanisms of this species. Developmental stability was described by analyzing fluctuating asymmetry in qualitative characters of the pholidosis, as well as fluctuating asymmetry, allometry, modularity and integration of the pileus and frequency of phenodeviants in the pileus region of the lizard. Developmental stability results showed that urban and suburban lizard populations do not develop under more stressful conditions than populations from natural habitats, while they do have a more canalized developmental response. The wide distribution and a close connection to urbanized habitats with successful adaptation to new environments lead to the conclusion that the Common Wall Lizard should be considered as an indigenous species for the Vojvodina region, contrary to proposed qualifications.
Background and aims:
The World Health Organization's International Classification of Diseases (ICD-11) includes Compulsive Sexual Behavior Disorder (CSBD), a new diagnosis that is both controversial and groundbreaking, as it is the first diagnosis to codify a disorder related to excessive, compulsive, and out-of-control sexual behavior. The inclusion of this novel diagnosis demonstrates a clear need for valid assessments of this disorder that may be quickly administered in both clinical and research settings.
Design:
The present work details the development of the Compulsive Sexual Behavior Disorder Diagnostic Inventory (CSBD-DI) across seven samples, four languages, and five countries.
Setting:
In the first study, data were collected in community samples drawn from Malaysia (N = 375), the U.S. (N = 877), Hungary (N = 7,279), and Germany (N = 449). In the second study, data were collected from nationally representative samples in the U.S. (N = 1,601), Poland (N = 1,036), and Hungary (N = 473).
Findings:
Across both studies and all samples, results revealed strong psychometric qualities for the 7-item CSBD-DI, demonstrating evidence of validity via correlations with key behavioral indicators and longer measures of compulsive sexual behavior. Analyses from nationally representative samples revealed residual metric invariance across languages, scalar invariance across gender, strong evidence of validity, and utility in classifying individuals who self-identified as having problematic and excessive sexual behavior, as evidenced by ROC analyses revealing suitable cutoffs for a screening instrument.
Conclusion:
Collectively, these findings demonstrate the cross-cultural utility of the CSBD-DI as a novel measure for CSBD and provide a brief, easily administrable instrument for screening for this novel disorder.
Even though most areas, including land records, agreements between parties, legal certificates, identification cards, etc., are moving toward digital documents with digital signatures for authentication, uses only a signature written by hand. Verifying signatures is crucial because a false signature would have a significant impact on the actual owner. Therefore, it is essential to recognize genuine signatures in order to avoid such frauds. In this work, the deep learning technique is used to recognize the signature because it produces the highest accuracy and does not require excessive preprocessing. Image processing, classification, and segmentation are the most common applications for a deep learning model that is based on a convolutional neural network (CNN). The CNN algorithm learns more than KNN, SVM, and other algorithms. This work makes use of CNN to improve classification. Keywords: Signature, Convolutional Neural Networks (CNN), Support Vector Machine (SVM), K-Nearest Neighbors (KNN).
Dans le contexte agricole actuel, il est nécessaire de réduire l’utilisation des produits phytosanitaires contre les mauvaises herbes. Le désherbage localisé présente une alternative prometteuse pour limiter les coûts et l’impact environnemental. Cependant, la localisation automatique des adventices n’est pas une tâche facile car elle présente plusieurs défis scientifiques et technologiques. L’objectif de cette thèse est de proposer des méthodes de traitement d’images et d’intelligence artificielle pour la localisation des adventices en grandes cultures. Dans ce cadre, nous avons abordé deux problématiques, la détection des rangées de culture et la détection des adventices. Deux méthodes ont été proposées pour la détection des rangées de culture. La première méthode combine la transformée de Hough et l’algorithme de regroupement linéaire itératif SLIC. La deuxième, quant à elle, utilise une approche totalement nouvelle basée sur l’apprentissage profond. Ces deux méthodes ont été utilisées pour détecter les adventices inter-rang et celles qui sont en contact avec les rangées de culture. Pour tendre vers une meilleur efficacité, deux nouvelles méthodes de détection d’adventices par apprentissage machine, entièrement automatiques ont été développées. L’originalité de ces méthodes est que l’apprentissage est effectué sur des données annotées automatiquement. La première méthode est basée sur l’apprentissage profond tandis que la seconde génère des modèles à partir de descripteurs profonds et un classifieur à classe unique. Les résultats obtenus sur des données réelles montrent l’intérêt des approches proposées.
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