Search Results - "Psychological methods"

Comparing Network Structures on Three Aspects: A Permutation Test by van Borkulo, Claudia D., van Bork, Riet, Boschloo, Lynn, Kossakowski, Jolanda J., Tio, Pia, Schoevers, Robert A., Borsboom, Denny, Waldorp, Lourens J.

“…Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained…”
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Effect Size Guidelines for Cross-Lagged Effects by Orth, Ulrich, Meier, Laurenz L., Bühler, Janina Larissa, Dapp, Laura C., Krauss, Samantha, Messerli, Denise, Robins, Richard W.

“…Cross-lagged models are by far the most commonly used method to test the prospective effect of one construct on another, yet there are no guidelines for…”
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A Tutorial on Regularized Partial Correlation Networks by Epskamp, Sacha, Fried, Eiko I.

“…Abstract Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework,…”
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Thanks Coefficient Alpha, We'll Take It From Here by McNeish, Daniel

“…Abstract Empirical studies in psychology commonly report Cronbach's alpha as a measure of internal consistency reliability despite the fact that many…”
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Dynamic Fit Index Cutoffs for Confirmatory Factor Analysis Models by McNeish, Daniel, Wolf, Melissa G.

“…Model fit assessment is a central component of evaluating confirmatory factor analysis models and the validity of psychological assessments. Fit indices remain…”
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Reporting Standards for Psychological Network Analyses in Cross-Sectional Data by Burger, Julian, Isvoranu, Adela-Maria, Lunansky, Gabriela, Haslbeck, Jonas M. B., Epskamp, Sacha, Hoekstra, Ria H. A., Fried, Eiko I., Borsboom, Denny, Blanken, Tessa F.

“…Statistical network models describing multivariate dependency structures in psychological data have gained increasing popularity. Such comparably novel…”
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A Primer on Two-Level Dynamic Structural Equation Models for Intensive Longitudinal Data in Mplus by McNeish, Daniel, Hamaker, Ellen L

“…Technological advances have led to an increase in intensive longitudinal data and the statistical literature on modeling such data is rapidly expanding, as are…”
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Evaluating Meta-Analytic Methods to Detect Selective Reporting in the Presence of Dependent Effect Sizes by Rodgers, Melissa A., Pustejovsky, James E.

“…Selective reporting of results based on their statistical significance threatens the validity of meta-analytic findings. A variety of techniques for detecting…”
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Statistical Power in Two-Level Models: A Tutorial Based on Monte Carlo Simulation by Arend, Matthias G, Schäfer, Thomas

“…Abstract The estimation of power in two-level models used to analyze data that are hierarchically structured is particularly complex because the outcome…”
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Which Estimation Method to Choose in Network Psychometrics? Deriving Guidelines for Applied Researchers by Isvoranu, Adela-Maria, Epskamp, Sacha

“…The Gaussian graphical model (GGM) has recently grown popular in psychological research, with a large body of estimation methods being proposed and discussed…”
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Evaluating Bifactor Models: Calculating and Interpreting Statistical Indices by Rodriguez, Anthony, Reise, Steven P, Haviland, Mark G

“…Bifactor measurement models are increasingly being applied to personality and psychopathology measures (Reise, 2012). In this work, authors generally have…”
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Two-Condition Within-Participant Statistical Mediation Analysis: A Path-Analytic Framework by Montoya, Amanda K., Hayes, Andrew F.

“…Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of 2 different…”
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Investigating the Performance of Exploratory Graph Analysis and Traditional Techniques to Identify the Number of Latent Factors: A Simulation and Tutorial by Golino, Hudson, Shi, Dingjing, Christensen, Alexander P., Garrido, Luis Eduardo, Nieto, Maria Dolores, Sadana, Ritu, Thiyagarajan, Jotheeswaran Amuthavalli, Martinez-Molina, Agustin

“…Exploratory graph analysis (EGA) is a new technique that was recently proposed within the framework of network psychometrics to estimate the number of factors…”
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A Critique of the Cross-Lagged Panel Model by Hamaker, Ellen L, Kuiper, Rebecca M, Grasman, Raoul P. P. P

“…The cross-lagged panel model (CLPM) is believed by many to overcome the problems associated with the use of cross-lagged correlations as a way to study causal…”
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Linear Mixed-Effects Models and the Analysis of Nonindependent Data: A Unified Framework to Analyze Categorical and Continuous Independent Variables that Vary Within-Subjects and/or Within-Items by Brauer, Markus, Curtin, John J.

“…Abstract In this article we address a number of important issues that arise in the analysis of nonindependent data. Such data are common in studies in which…”
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On the Unnecessary Ubiquity of Hierarchical Linear Modeling by McNeish, Daniel, Stapleton, Laura M., Silverman, Rebecca D.

“…In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular…”
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A Unified Framework of Longitudinal Models to Examine Reciprocal Relations by Usami, Satoshi, Murayama, Kou, Hamaker, Ellen L.

“…Abstract Inferring reciprocal effects or causality between variables is a central aim of behavioral and psychological research. To address reciprocal effects,…”
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Comparing the Pearson and Spearman Correlation Coefficients Across Distributions and Sample Sizes: A Tutorial Using Simulations and Empirical Data by de Winter, Joost C. F, Gosling, Samuel D, Potter, Jeff

“…The Pearson product-moment correlation coefficient (rp) and the Spearman rank correlation coefficient (rs) are widely used in psychological research. We…”
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Quantifying Explained Variance in Multilevel Models: An Integrative Framework for Defining R-Squared Measures by Rights, Jason D., Sterba, Sonya K.

“…Researchers often mention the utility and need for R-squared measures of explained variance for multilevel models (MLMs). Although this topic has been…”
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A Comparison of Full Information Maximum Likelihood and Multiple Imputation in Structural Equation Modeling With Missing Data by Lee, Taehun, Shi, Dexin

“…This article compares two missing data procedures, full information maximum likelihood (FIML) and multiple imputation (MI), to investigate their relative…”
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