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Publications (83)
Introduction
One-way repeated measures ANOVA requires sphericity. Research indicates that violation of this assumption has an important impact on Type I error. Although more advanced alternative procedures exist, most classical texts recommend the use of adjusted F -tests, which are frequently employed because they are intuitive, easy to apply, and...
This paper examined the robustness of the generalized linear mixed model (GLMM). The GLMM estimates fixed and random effects, and it is especially useful when the dependent variable is binary. It is also useful when the dependent variable involves repeated measures, since it can model correlation. The present study used Monte Carlo simulation to an...
Background:
Repeated measures designs are commonly used in health and social sciences research. Although there are other, more advanced, statistical analyses, the F-statistic of repeated measures analysis of variance (RM-ANOVA) remains the most widely used procedure for analyzing differences in means. The impact of the violation of normality has b...
We developed and evaluated the effectiveness of a new teaching strategy aimed at improving students' learning in a Research Design degree module with high mathematical content. The strategy involves presenting students with case studies based on published research and a set of questions to answer, following which they are given error analysis sheet...
Generalized linear mixed models (GLMMs) estimate fixed and random effects and are especially useful when the dependent variable is binary, ordinal, count or quantitative but not normally distributed. They are also useful when the dependent variable involves repeated measures, since GLMMs can model autocorrelation. This study aimed to determine how...
We examined the relationships between math anxiety, perfectionism and academic achievement in undergraduates enrolled in a course with high mathematical content. Participants were 251 students who completed math anxiety and perfectionism questionnaires, and whose academic achievement was measured via a multiple-choice examination. The number of hit...
Several measures of skewness and kurtosis were proposed by Hogg (1974) in order to reduce the bias of conventional estimators when the distribution is non-normal. Here we conducted a Monte Carlo simulation study to compare the performance of conventional and Hogg’s estimators, considering the most frequent continuous distributions used in health, e...
Students’ academic achievement in courses with a high mathematical content can be affected by their levels of trait, math and test anxiety. In this study, 180 university students were assessed on these types of anxiety and the relationships between them and students’ performance were evaluated. Higher levels of math anxiety were related to a low ac...
INTRODUCTION: This study analyzed the influence of two types of feedback (via rubrics and in-class) on students’ academic achievement in a higher education course with statistical content. Students’ views regarding the usefulness of these types of feedback were also examined.
METHODS: After validating the rubrics in a sample of 100 students, a sam...
This paper analyzes current practices in psychology in the use of research methods and data analysis procedures (DAP) and aims to determine whether researchers are now using more sophisticated and advanced DAP than were employed previously. We reviewed empirical research published recently in prominent journals from the USA and Europe corresponding...
Cyberbullying and social anxiety in adolescents: A systematic review. Cyberbullying has aroused the interest of researchers in the field of psychology. One of the variables related to cyberbullying that have been studied in recent years is social anxiety. However, a global and specific evaluation of results between these two big areas has not been...
We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...
We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...
We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significan...
We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science.
Given that blanket and variable alpha levels both are problematic, it is sensible to dispense
with significan...
We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...
We argue that depending on p-values to reject null hypotheses, including a recent call for changing the canonical alpha level for statistical significance from .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable criterion levels both are problematic, it is sensible to dispense...
Background:
The robustness of F-test to non-normality has been studied from the 1930s through to the present day. However, this extensive body of research has yielded contradictory results, there being evidence both for and against its robustness. This study provides a systematic examination of F-test robustness to violations of normality in terms...
Statistical analysis is crucial for research and the choice of analytical technique should take into account the specific distribution of data. Although the data obtained from health, educational, and social sciences research are often not normally distributed, there are very few studies detailing which distributions are most likely to represent da...
Inconsistencies in the research findings on F-test robustness to variance heterogeneity could be related to the lack of a standard criterion to assess robustness or to the different measures used to quantify heterogeneity. In the present paper we use Monte Carlo simulation to systematically examine the Type I error rate of F-test under heterogeneit...
This study examines students’ views regarding two types of feedback: that obtained through rubrics and that given by the class tutor (rubrics and in-class feedback, respectively). We constructed an ad hoc questionnaire to assess students’ perceived usefulness of both types of feedback. The sample comprised 135 undergraduates from the University of...
In this study, we explored the accuracy of sphericity
estimation and analyzed how the sphericity of covariance matrices
may be affected when the latter are derived from simulated
data. We analyzed the consequences that normal and
nonnormal data generated from an unstructured population
covariance matrix—with low (ε = .57) and high (ε = .75)
spheric...
Test anxiety has detrimental effects on the academic performance of many university students. Moreover, female students usually report higher levels of test anxiety than do their male peers. The present study examined gender differences in test, trait, and math anxiety among university students, as well as differences in their academic achievement....
In the health and social sciences, longitudinal data have often been analyzed without taking into account the dependence between observations of the same subject. Furthermore, consideration is rarely given to the fact that longitudinal data may come from a non-normal distribution. In addition to describing the aims and types of longitudinal designs...
Multilevel models are increasingly used to analyze hierarchically nested data, being especially appropriate in educational psychology because of the clustering of students within classrooms, classrooms within schools, schools within districts, and so on. The aim of this paper was to illustrate a step by step multilevel modeling of educational data....
This chapter analyzes current evidence between parenting styles and parenting practices for the Spanish context. As opposed to traditional results obtained in Anglo-Saxon contexts with European-American samples, evidence from emergent research from Spain (a South European country) shows that adolescents from indulgent families (characterized by war...
The aim of this study was to investigate the effectiveness of a formative assessment system in improving students’ learning. This system involved giving feedback to students regarding the errors they made in a series of assignments performed during a course. Participants were 166 students enrolled in a core course of the degree in psychology offere...
Multilevel models are becoming increasingly used to analyse hierarchically nested data, being appropriate in educational psychology because of the clustering of students within classrooms, classrooms within schools, and schools within districts, and so on. The aim of this paper is to illustrate a cross-sectional multilevel modelling of educational...
Our objective was to implement and evaluate a formative assessment system in a mandatory course of the degree in Psychology. With this system, students received feedback from the tests they performed. We found a positive correlation between feedback classes' attendance and students' grades. The correlation between math anxiety and course's performa...
Background:
This study examined the independent effect of skewness and kurtosis on the robustness of the linear mixed model (LMM), with the Kenward-Roger (KR) procedure, when group distributions are different, sample sizes are small, and sphericity cannot be assumed.
Methods:
A Monte Carlo simulation study considering a split-plot design involvi...
Simulation techniques must be able to generate the types of distributions most commonly encountered in real data, for example, non-normal distributions., Two recognized procedures for generating non-normal data are Fleishman's linear transformation method and the method proposed by Ramberg et al. that is based on generalization of the Tukey lambda...
Los diseños de caso único, conocidos también como diseños de N = 1, han mostrado ser un instrumento eficaz para evaluar el efecto de una o más intervenciones aplicadas a un solo sujeto, del que se toman medidas en distintas ocasiones de observación. Aunque, en función del diseño utilizado, no siempre se pretende mejorar la conducta de un único suje...
This study examines whether math anxiety and negative attitudes towards mathematics have an effect on university students’ academic achievement in a methodological course forming part of their degree. A total of 193 students were presented with a math anxiety test and some questions about their enjoyment, self-confidence and motivation regarding ma...
The study explores the robustness to violations of normality and sphericity of linear mixed models when they are used with the Kenward-Roger procedure (KR) in split-plot designs in which the groups have different distributions and sample sizes are small. The focus is on examining the effect of skewness and kurtosis. To this end, a Monte Carlo simul...
Parametric statistics are based on the assumption of normality. Recent findings suggest that Type I error and power can be adversely affected when data are non-normal. This paper aims to assess the distributional shape of real data by examining the values of the third and fourth central moments as a measurement of skewness and kurtosis in small sam...
This study analyzes the robustness of the linear mixed model (LMM) with the Kenward-Roger (KR) procedure to violations of normality and sphericity when used in split-plot designs with small sample sizes. Specifically, it explores the independent effect of skewness and kurtosis on KR robustness for the values of skewness and kurtosis coefficients th...
This study aimed to evaluate the robustness of the linear mixed model, with the Kenward-Roger correction for degrees of freedom, when implemented in SAS PROC MIXED, using split-plot designs with small sample sizes. A Monte Carlo simulation design involving three groups and four repeated measures was used, assuming an unstructured covariance matrix...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom, in this article we analyzed the application of the linear mixed model (LMM) to a mixed repeated measures design. The LMM was first used to select the covariance structure with three types of data distribution: normal, exponential, and log-normal. This showe...
One of the procedures used most recently with longitudinal data is linear mixed models. In the context of health research the increasing number of studies that now use these models bears witness to the growing interest in this type of analysis. This paper describes the application of linear mixed models to a longitudinal study of a sample of Spanis...
The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions about intervention effectiveness in single-case designs. Ordinary least square estimation is compared to two correction techniques dealing with general trend and a procedure that eliminates autocorrelation whenever i...
Un tema que ha suscitado mayor interés entre los investigadores del análisis de datos longitudinales ha sido el desarrollo, a través de estudios de simulación, de modelos de análisis que incorporen aquellas estructuras de covarianza que mejor se ajusten a los datos. Al analizar las estructuras de covarianza en el ámbito de datos longitudinales, nos...
A topic that has aroused great interest among researchers who analyse longitudinal data has been the development, by means of simulation studies, of analytic models that incorporate the covariance structures which best fit the data. When analysing covariance structures within the context of longitudinal data one finds that the variances are not alw...
A topic that has aroused great interest among researchers who analyse longitudinal data has been the development, by means of simulation studies, of analytic models that incorporate the covariance structures which best fit the data. When analysing covariance structures within the context of longitudinal data one finds that the variances are not alw...
A topic that has aroused great interest among researchers who analyse longitudinal data has been the development, by means of simulation studies, of analytic models that incorporate the covariance structures which best fit the data. When analysing covariance structures within the context of longitudinal data one finds that the variances are not alw...
Técnicas fundamentadas en la regresión para la decisión estadística en diseños de caso único. El estudio evalúa el rendimiento de cuatro métodos de estimación de los coefi cientes de regresión utilizados para la toma de decisiones estadísticas sobre la efectividad de las intervenciones en diseños de caso único. La estimación por mínimos cuadrados o...
Knowledge of the subject matter plays a vital role when attempting to choose the best possible linear mixed model to analyze longitudinal data. To date, in the absence of strong theory, much of the work has focused on modeling the covariance matrix by comparing non-nested models using selection criteria. In this paper, we compare the performance of...
Many areas of psychological, social, and health research are characterised by hierarchically structured data. Growth curves are usually represented by means of a two-level hierarchical structure in which observations are the first-level units nested within subjects, the second-level units. With data such as these, the best option for analysis is th...
This research examines the Type I error rates obtained when using the mixed model with the Kenward-Roger correction and compares them with the Between-Within and Satterthwaite approaches in split-plot designs. A simulated study was conducted to generate repeated measures data with small samples under normal distribution conditions. The data were ob...
Los modelos que tradicionalmente se han utilizado en el análisis de datos de medidas repetidas son de carácter lineal y siguen el enfoque basado en el análisis de la variancia. Su principal desventaja es que debe disponerse de datos balanceados lo que, en contextos aplicados, es difícil de conseguir. Por esto, se han desarrollado modelos alternativ...
Hierarchical linear models have become a very popular tool for analyzing data with a hierarchical structure. This methodology recognizes the nested structure of the data and allows obtaining unbiased estimates of the variations found in the different levels of the hierarchy. The goal of this article is to illustrate the construction of hierarchical...
The models that traditionally have been used to analyse repeated measure data are linear and follow an approach based on analysis of variance. Their main drawback is that they require balanced data, something that is difficult to achieve in applied contexts. Therefore, alternative models such as the study of growth curves have been developed, which...
The models that traditionally have been used to analyse repeated measure data are linear and follow an approach based on analysis of variance. Their main drawback is that they require balanced data, something that is difficult to achieve in applied contexts. Therefore, alternative models such as the study of growth curves have been developed, which...
Los modelos lineales jerárquicos se han convertido en una herramienta muy popular para analizar datos que presentan una estructura jerarquizada. Esta metodología reconoce la estructura anidada de los datos y permiten obtener estimaciones insesgadas de las variaciones acaecidas en los distintos niveles de la jerarquía. El objetivo de este artículo e...
This paper examines the use of the main analytical models applied to longitudinal data in the contexts of psychology and medicine. We carried out a bibliographical review of articles published during the period 1985-2005 in Psyclnfo and Medline. The quantity of longitudinal studies increased, following the pattern reported in Singer and WiIIeWs rev...
Los modelos lineales jerárquicos se han convertido en una herramienta muy popular para analizar datos que presentan una estructura jerarquizada. Esta metodología reconoce la estructura anidada de los datos y permiten obtener estimaciones insesgadas de las variaciones acaecidas en los distintos niveles de la jerarquía. El objetivo de este artículo e...
This paper examines the use of the main analytical models applied to longitudinal data in the contexts of psychology and medicine.We carried out a bibliography review of articles published during the period 1985-2005 in PsycInfo and Medline.The quantity oflongitudinal studies increased, following the pattern reported in Singer and Willett�s review...
The models that traditionally have beenused to analyse repeated measure data are linear andfollow an approach based on analysis of variance.Their main drawback is that they require balanceddata, something that is difficult to achieve in appliedcontexts. Therefore, alternative models such as thestudy of growth curves have been developed, which intur...
The objectives of this article are twofold: (a) to outline the basic concepts associated with the linear mixed model and (b) to illustrate how this model can be used to analyse systematic interindividual differences in intraindividual change, this being achieved through a longitudinal study of a cohort of children living in Cordoba (Argentina). The...
In this work, an innovative teaching model applied to methodological contents in psychology is presented. The proposed didactic model includes Information and Communication Technologies (ICT), such as CD-ROMs, web sites and Internet. These resources complement class attendance. In the classes the students are informed, guided and oriented so that t...
In the applied context, short time-series designs are suitable to evaluate a treatment effect. These designs present serious problems given autocorrelation among data and the small number of observations involved. This paper describes analytic procedures that have been applied to data from short time series, and an alternative which is a new versio...
The work of Huitema (1985) on autocorrelation in behavioral data suggests that the use of conventional statistical methods is justified. The present study restates the problem of autocorrelation by analyzing 100 baselines of small samples designs published in the Journal of Applied Behavior Analysis during 1992. The results show a negative bias in...
El análisis estadístico de los diseños de series temporales cortas está influido por la presencia de dependencia serial. De ahí la importancia de estimar correctamente la autocorrelación de primer orden en datos conductuales. El sesgo empírico es un indicador generalmente usado para evaluar el grado de precisión de un estimador. Este artículo prese...
The conventional first-order autocorrelationcoefficient r1 generates an empiricalbias when it is applied to short time series.The properties of this estimator have beenexamined with a Monte Carlo simulation studyusing the MATLAB program (version5.2). This study also analyzes the functionof the empirical bias with the polynomicregression and derives...
El análisis de series temporales (AST) constituye un procedimiento adecuado de análisis para diseños de series temporales interrumpidas (DSTI). La principal desventaja de esta técnica de análisis es que requiere un número elevado de observaciones con objeto de identificar el correspondiente modelo ARIMA (autorregresivo integrado de medias móviles)....
The time series analysis (TSA) constitutes an appropriate procedure of analysis for interrupted time series designs (ITSD). The main disadvantage of this analysis technique is that it requires a high number of observations with object of identifying the corresponding ARIMA model (autoregressive Integrated Moving Averages). However, in applied behav...
Young's C statistic (1941) makes it possible to compare the randomization of a set of sequentially organized data and constitutes an alternative of appropriate analysis in short time series designs. On the other hand, models based on the randomization of stimuli are also very important within the behavioral content applied. For this reason, a compa...
Young's C. statistic (1941) constitutes a suitable analysis alternative for quantitatively evaluating the presence of changes due to interventions in short-time series (particular of behavioral designs). In this study simulated AB design data with different change patterns are studied. The results obtained allow to conclude that the C statistic is...
El estadístico C (Young, 1941) constituye una alternativa de análisis adecuada a las series temporales interrumpidas breves o cortas, propias de diseños conductuales. Por este motivo, se lleva a cabo un estudio de simulación de Monte Carlo, con objeto de hallar la potencia estadística de la prueba C para cada una de las estrategias de uso propuesta...
The C statistic (Young, 1941) constitutes a suitable analysis alternative for interrupted brief or short-time series used in behavioral designs. For this reason, a Monte Carlo simulation study is carried out to determine the statistical power of the C statistic for each of the usage strategies proposed by Tryon (1982). The series generated allow to...
El objetivo del presente trabajo es aplicar el análisis de series temporales bivariables dentro del ámbito de la psicología social aplicada. Las variables relacionadas mediante esta técnica son desempleo y suicidio. En el período analizado (1978-1985), para todo el Estado Español se detecta una relación significativa entre tasa de paro (variable in...
Manual para que los estudiantes de psicología adquieran un conocimiento práctico de los conceptos fundamentales del diseño experimental.
Due to the increasing importance of power analysis in behavioral sciences and to the fact that the available literature on the subject has been scarce and ambiguous for decades, the objective of this study is to provide the basic conceptual framework of statistical analysis of power. For this purpose, an historical review is made of the subject, an...
Un marco teórico potente resulta clave para especificar el modelo mixto que explica mejor la variabilidad de datos longitudinales. A falta de teoría, la mayoría de las investigaciones realizadas hasta la fecha, se ha centrado en ajustar la matriz de dispersión usando criterios de selección de modelos para elegir entre estructuras de covarianza no a...
Debido a la creciente importancia del análisis de la potencia en ciencias del comportamiento y a una escasa y ambigua literatura durante décadas, el objetivo de este trabajo es presentar el marco conceptual básico del análisis estadístico de la potencia. Para ello, se lleva a cabo una revisión histórica del tema, y se discute lo más relevante acerc...
