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Illustration of the different correlation estimates (a measure of association, represent by the height of the bars) obtained via different methods for the same data (the scatter plot).
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Correlations tests are arguably one of the most commonly used statistical procedures, and are used as a basis in many applications such as exploratory data analysis, structural modelling, data engineering etc. In this context, we present correlation, a toolbox for the R language (R Core Team, 2019) and part of the easystats collection, focused on c...
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Citations
... Boston, MA, USA). Correlation analyses and model performances were analyzed using the "easystats" ecosystem for R Lüdecke et al., 2021;Makowski et al., 2020). Plots were created using the "ggplot2" and "ggpredict" package. ...
Background:
Adverse childhood experiences (ACEs) are highly prevalent and increase the risk for long-term adverse health outcomes. Next to well-known ACE-associated risks for morbidity, recent research is increasingly invested in exploring pathways towards health, overall functioning, and partaking in society following early adversity.
Objectives:
Thus, this study aims to assess the association between latent classes of ACEs with perceived social participation and health-related Quality of Life (QoL) in a large population-based sample and to explore potential moderators of these associations.
Method:
A representative sample of the German population (N = 2531; Mage = 48.7; 51 % women) was cross-sectionally investigated for ACEs, social participation (KsT-5), and health-related QoL (EuroQol-5D-5L). Latent Class Analysis (LCA) was performed to derive groups with similar ACE patterns. Multiple regression analyses were used to investigate the association of latent classes of ACEs with social participation and health-related QoL and to explore potential moderators.
Results:
Four distinct latent classes of ACEs were identified; "no/low ACEs" (N = 1968, 77.8 %); "household-dysfunction" (N = 259, 10.2 %), "child abuse and neglect" (N = 188, 7.4 %), and "polyadversity" (N = 116, 4.6 %). Compared to participants in the no/low ACE class, those in the ACE-exposed classes showed overall lower levels of perceived social participation and health-related QoL. The polyadversity class showed lower levels of social participation compared to the two other ACE-exposed classes. Chronic stress, living with a partner, education, current job/educational involvement, and gender were found to moderate these associations in exploratory analyses.
Conclusions:
This study shows people exposed to ACEs to have a higher risk for lower perceived social participation and lower health-related QoL - an increased risk, however, is not a deterministic uninventable fortune. Reduction of chronic stress, fostering of social support, and educational and vocational paths as interventional targets are discussed to enable those with precarious starting conditions to partake in society.
... Due to the non-normal distribution of some variables, we conducted Spearman's rank-order correlations. We calculated Bayes factors using the correlation R package [65] to determine the likelihood of the alternative hypotheses (r ≠ 0) in relation to the corresponding null hypotheses (r = 0). We interpreted Bayes factors using the JASP classification scheme, so Bayes factors greater than 1 would provide support for the alternative hypothesis and Bayes factors smaller than 1 would provide support for the null hypothesis [66]. ...
Studies suggest that an attentional bias to thin bodies is common among those with high levels of body dissatisfaction, which is a risk factor for, and symptom of, various eating disorders. However, these studies have predominantly been conducted in Western countries with body stimuli involving images of White people. In a preregistered study, we recruited 150 Malaysian Chinese women and 150 White Australian women for a study using standardized images of East Asian and White Australian bodies. To measure attentional bias to thin bodies, participants completed a dot probe task which presented images of women who self-identified their ethnicity as East Asian or as White Australian. Contrary to previous findings, we found no evidence for an association between body dissatisfaction and attentional bias to thin bodies. This lack of association was not affected by participant ethnicity (Malaysian Chinese versus White Australian) or ethnic congruency between participants and body stimuli (own-ethnicity versus other-ethnicity). However, the internal consistency of the dot probe task was poor. These results suggest that either the relationship between body dissatisfaction and attentional bias to thin bodies is not robust, or the dot probe task may not be a reliable measure of attentional bias to body size.
... To determine whether habituation was related to SPHI estimates or to cognitive ability, linear correlations between habituation slopes, as collapsed across hemispheres, were examined within a Bayesian framework using the correlation R package (Makowski et al., 2020). For all models, we used the default Bayesian correlation test (Ly et al., 2016) with "medium" priors (r scale parameters of 1/3), and Bayes factors (BF 10 ) were calculated to summarize evidence for or against the hypothesis of a significant linear correlation. ...
Prior studies suggest that habituation of sensory responses is reduced in autism and that diminished habituation could be related to atypical autistic sensory experiences, for example, by causing brain responses to aversive stimuli to remain strong over time instead of being suppressed. While many prior studies exploring habituation in autism have repeatedly presented identical stimuli, other studies suggest group differences can still be observed in habituation to intermittent stimuli. The present study explored habituation of electrophysiological responses to auditory complex tones of varying intensities (50-80 dB SPL), presented passively in an interleaved manner, in a well-characterized sample of 127 autistic (MDQ = 65.41, SD = 20.54) and 79 typically developing (MDQ = 106.02, SD = 11.50) children between 2 and 5 years old. Habituation was quantified as changes in the amplitudes of single-trial responses to tones of each intensity over the course of the experiment. Habituation of the auditory N2 response was substantially reduced in autistic participants as compared to typically developing controls, although diagnostic groups did not clearly differ in habituation of the P1 response. Interestingly, the P1 habituated less to loud 80 dB sounds than softer sounds, whereas the N2 habituated less to soft 50 dB sounds than louder sounds. No associations were found between electrophysiological habituation and cognitive ability or participants' caregiver-reported sound tolerance (Sensory Profile Hyperacusis Index). The results present study results extend prior research suggesting habituation of certain sensory responses is reduced in autism; however, they also suggest that habituation differences observed using this study's paradigm might not be a primary driver of autistic participants' real-world sound intolerance.
... Spearman's rank correlation is a non-parametric measure of correlation. Therefore, while Pearson's correlation assesses linear relationship, Spearman's correlation assesses monotonic relationship whether linear or not [11]. On the other hand, while the correlation analysis helps in identifying associations or relationships between two variables, the regression technique or regression analysis is used to model this relationship so as to be able to predict what will happen in a real-world setting [12]. ...
In scope of product safety concept, all products intended to be placed on the market, supplied, made available on the market or put into service must be safe and in compliance with the relevant technical regulation. Similarly, the active electricity meters should be safe and convenient. Sometimes, although the products like as electricity meters which have the high error rates which are close to limit level of legally permissible error margins, they can be safety and in convenient legally. In such a case, the impact of these electricity meters on distribution companies and meter subscribers using energy above the average value can be more in terms of cost, negatively. Also, due to the increasing energy demand and cost, the awareness of saving planet is continuously increasing in the society. Therefore, the usage of product like as electricity meter which is produced with minimum rate of operating error becomes more meaningful, nowadays. In this context, aim of this study is to examine the impact of some variable parameters such as harmonic distortion rate and meter constant except of current shift, voltage shift, frequency shift and temperature variation on comprehensive maximum error (CME) of the electricity meters with same basic technical specifications. At the end of study, it is observed that the large variability of some working error rates of an electricity meter may be caused by reasons such as different production design according to working area, materials which have different sensitivity, quality, working range and also different measurement methods.
... In such cases, the Spearman rank correlation coefficient is used. The Spearman rank correlation coefficient, like the Pearson coefficient, indicates how much a variable tends to follow other variables [21]. The Spearman correlation coefficient of the parameters listed in Table 1 in 2 different sections of the well, which are related to 2 different stress regimes, is presented in Figure 2, using approximately 73,000 real data of the well. ...
In oil extraction projects, knowledge of reservoir geomechanics is essential for estimating the stability of wellbore walls drilled at great depths. In this regard, mechanics of porous media according to the definition of Biot's coefficient instead of Terzaghi effective stress can provide a more accurate estimate compared to other analyses. Additionally, using artificial intelligence and machine learning algorithms such as XGBoost and optimizing it with algorithms like Bayesian, along with using SHAP algorithm as an interpretable AI model, can provide us with deeper insights into available data. In this research, 1 st geomechanical data of a well in Asmari formation in southwest Iran was obtained through well logs and operational reports and then analyzed by machine learning. Also, a 1-way coupled reservoir rock-fluid model was built to investigate the volume of fractured rock around the well. The interpretation of machine learning results helps us better understand the parameters affecting instability in this well's wall. Moreover, finite element model results indicate that assuming a value equal to 1 for Biot coefficient (or Terzaghi effective stress) leads to incorrect results and overestimates the volume of fractured rock around this well up to 13 times more than actual values. Therefore, any proper analysis regarding wellbore wall stability and evaluating effective stresses requires accurate knowledge about real and existing values of this coefficient due to simultaneous behavior of stress and pore pressure.
... Therefore, we compute the Spearman rank correlation coefficient r x;y to quantify the monotonic dependency of features x and y as: where covð $Þ denotes the covariance function and s the standard deviation of the rank variables RðxÞ and RðyÞ. 20 The empirical covariance function of two variables x and y with sample size n is defined as: ...
... where R is the correlation coefficient and x and y are the mean values of the variables x and y, respectively [30]. Finally, a matrix with a sample matrix of 38 × 10 is obtained. ...
As particulate organic carbon (POC) from lakes plays an important role in lake ecosystem sustainability and carbon cycle, the estimation of its concentration using satellite remote sensing is of great interest. However, the high complexity and variability of lake water composition pose major challenges to the estimation algorithm of POC concentration in Class II water. This study aimed to formulate a machine-learning algorithm to predict POC concentration and compare their modeling performance. A Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) algorithm based on spectral and time sequences was proposed to construct an estimation model using the Sentinel 2 satellite images and water surface sample data of Chaohu Lake in China. As a comparison, the performances of the Backpropagation Neural Network (BP), Generalized Regression Neural Network (GRNN), and Convolutional Neural Network (CNN) models were evaluated for remote sensing inversion of POC concentration. The results show that the CNN–LSTM model obtained higher prediction precision than the BP, GRNN, and CNN models, with a coefficient of determination (R2) of 0.88, a root mean square error (RMSE) of 3.66, and residual prediction deviation (RPD) of 3.03, which are 6.02%, 22.13%, and 28.4% better than the CNN model, respectively. This indicates that CNN–LSTM effectively combines spatial and temporal information, quickly captures time-series features, strengthens the learning ability of multi-scale features, is conducive to improving estimation precision of remote sensing models, and offers good support for carbon source monitoring and assessment in lakes.
... For the current research, the determined descriptive statistics are explained in table 4. Table 4.1 of descriptive statistics is developed from the statements that were been asked in the questionnaire attached as an appendix to the article the statements were highlighting the importance of leadership culture to run the educational institutes. Makowski et al. (2020) identified that correlation analysis is conducted to determine the relationship among the research variables. The developed correlation between the research variables of the leadership culture and running the educational institutes is shared in table 4.2. ...
Purpose: The main purpose of the current research paper is based on (a) the identification of the leadership culture in educational institutes and, (b) the investigation of the impact of such leadership culture on successfully running educational institutes. According to the developed research aim, the identified research question was based on making the searches regarding the factors that can leadership culture in the performing educational institute practices. Methods: For developing the answers to the established research topic, the current research uses the primary quantitative survey-based research design with the use of the questionnaire surveys that were distributed among the 100 higher management members in the educational institutes. These educational institutes were identified in the southwest of England, UK. Findings: The findings of the current research mainly indicate the fact that data-driven facts about leadership practices can have a positive impact on running educational institutions. It was further analysed from the developed research results that the culture shifts in the leadership practices of the educational institutions can be brought in when the stakeholders of the educational institutions mainly decided to support the leadership practices. Conclusion: In the end, the paper concludes that the leadership culture in educational institutes must be established in a manner that supports organisational growth in the long run. There are very limited studies which are been conducted on the established topic. Therefore, the current research also recommends that future research be conducted on the mentioned topic.
... Significantly different groups were indicated by different letters (a, b, c) at P < 0.05. factors and key genes, Pearman correlation analysis was performed using the "correlation" external package (Makowski et al., 2020). Metabianalysis 5.0 software was used for OPLS-DA analysis and variable important in projection (VIP) value calculation (Pang et al., 2021). ...
Curcuma alismatifolia is a significant cut flower, but its postharvest preservation remains challenging. 6-benzyla-minopurine (6-BA) can effectively delay senescence in various horticultural plants. This study demonstrated that soaking and spraying 6-BA significantly extended the vase life of four C. alismatifolia varieties, particularly 'Siam Shadow', which had the longest vase life extension of 5.1 days by spraying and 3.7 days by soaking. Further analyses of physiological, biochemical, and transcriptomic indicators were conducted on the bracts of 'Siam Shadow' under 50 mg/L 6-BA spraying treatment and control at three senescence stages: S1 (4th day), S2 (8th day), and S3 (12th day) after vase placement. The results indicated that 6-BA spraying increased superoxide dismutase (SOD) and catalase (CAT) activities in S1 and S2 while increasing peroxidase (POD) and decreasing jasmonic acid (JA) contents in all stages. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) identified JA content as the key differential indicator of 6-BA treatment. Transcriptome analysis revealed that 6-BA treatment upregulated 102 antioxidant-related genes and downregulated 27 JA biosynthesis-related genes and 16 JA signal transduction-related genes in all stages. Among them, the gene families of POD, LOX, and JAZ, which are involved in peroxidase activity, JA biosynthesis, and JA signal transduction, respectively, may play major roles in delaying C. alismatifolia bract senescence. Moreover, correlation network analysis showed that 198 senescence-related transcription factors (WRKYs, NACs, etc.) were significantly correlated with 77 antioxidant-related genes, 22 JA biosynthesis-related genes, and 12 JA signal transduction-related genes. These findings suggest that 6-BA is a potential preservative for C. alismatifolia cut flowers and that it may primarily affect the expression of genes related to senescence-associated transcription factors, JA biosynthesis and signal trans-duction, and antioxidant enzymes, thereby reducing JA content and enhancing antioxidant enzyme activities, consequently delaying C. alismatifolia bract senescence.
... The expressions of 15 transcripts of the 11 ginsenoside biosynthesis genes were extracted from the expression dataset of the mini-core collection. Expression heatmaps of the 15 gene transcripts were constructed and visualized for the cultivars and landraces collected from different geographical regions and for different subpopulations and the admixture group using an R language package (Makowski et al., 2020). The co-expression networks of the genes were constructed using the BioLayout Express3D Version 3.3 software (Theocharidis et al., 2009). ...
... Pearson's correlation coefficients were calculated pair-wisely between cultivars and landraces of the mini-core collection to estimate their relationships using an R language package (Makowski et al., 2020). The correlation analyses between cultivars and landraces were based on the variations of 10,000 random gene transcript expressions with 10 bootstrap replications, 15 ginsenoside biosynthesis gene transcript expressions, 16 ginsenoside contents, and the representative selection of highquality genic SNPs. ...
... The correlation analyses between cultivars and landraces were based on the variations of 10,000 random gene transcript expressions with 10 bootstrap replications, 15 ginsenoside biosynthesis gene transcript expressions, 16 ginsenoside contents, and the representative selection of highquality genic SNPs. The results were visualized using an R language package (Makowski et al., 2020). The pair-wise relationships of the cultivars and landraces were compared between subpopulations or geographical regions by ANOVA, followed by least significance difference (LSD). ...
Genetic and molecular knowledge of a species is crucial to its gene discovery and enhanced breeding. Here, we report the genetic and molecular dissection of ginseng, an important herb for healthy food and medicine. A mini-core collection consisting of 344 cultivars and landraces was developed for ginseng that represents the genetic variation of ginseng existing in its origin and diversity center. We sequenced the transcriptomes of all 344 cultivars and landraces; identified over 1.5 million genic SNPs, thereby revealing the genic diversity of ginseng; and analyzed them with 26,600 high-quality genic SNPs or a selection of them. Ginseng had a wide molecular diversity and was clustered into three subpopulations. Analysis of 16 ginsenosides, the major bioactive components for healthy food and medicine, showed that ginseng had a wide variation in the contents of all 16 ginsenosides and an extensive correlation of their contents, suggesting that they are synthesized through a single or multiple correlated pathways. Furthermore, we pair-wisely examined the relationships between the cultivars and landraces, revealing their relationships in gene expression, gene variation, and ginsenoside biosynthesis. These results provide new knowledge and new genetic and genic resources for advanced research and breeding of ginseng and related species.
