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Showing 1 to 15 of 32 results Save | Export
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Marcoulides, Katerina M. – International Journal of Behavioral Development, 2021
The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is…
Descriptors: Growth Models, Computation, Mathematics, Longitudinal Studies
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Hecht, Martin; Voelkle, Manuel C. – International Journal of Behavioral Development, 2021
The analysis of cross-lagged relationships is a popular approach in prevention research to explore the dynamics between constructs over time. However, a limitation of commonly used cross-lagged models is the requirement of equally spaced measurement occasions that prevents the usage of flexible longitudinal designs and complicates cross-study…
Descriptors: Models, Longitudinal Studies, Prevention, Time
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Curran, Patrick J.; Georgeson, A. R.; Bauer, Daniel J.; Hussong, Andrea M. – International Journal of Behavioral Development, 2021
Conducting valid and reliable empirical research in the prevention sciences is an inherently difficult and challenging task. Chief among these is the need to obtain numerical scores of underlying theoretical constructs for use in subsequent analysis. This challenge is further exacerbated by the increasingly common need to consider multiple…
Descriptors: Psychometrics, Scoring, Prevention, Scores
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Ferguson, Sarah L.; Moore, E. Whitney G.; Hull, Darrell M. – International Journal of Behavioral Development, 2020
The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps: (a) data inspection, (b) iterative evaluation of models,…
Descriptors: Statistical Analysis, Computer Software, Data Analysis, Goodness of Fit
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Rioux, Charlie; Little, Todd D. – International Journal of Behavioral Development, 2021
Missing data are ubiquitous in studies examining preventive interventions. This missing data need to be handled appropriately for data analyses to yield unbiased results. After a brief discussion of missing data mechanisms, inappropriate missing data treatments and appropriate missing data treatments, we review the current state of missing data…
Descriptors: Prevention, Intervention, Data Analysis, Correlation
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Winter, Sonja D.; Depaoli, Sarah – International Journal of Behavioral Development, 2020
This article illustrates the Bayesian approximate measurement invariance (MI) approach in Mplus with longitudinal data and small sample size. Approximate MI incorporates zero-mean small variance prior distributions on the differences between parameter estimates over time. Contrary to traditional invariance testing methods, where exact invariance…
Descriptors: Bayesian Statistics, Measurement, Data Analysis, Sample Size
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Nicholson, Jody S.; Deboeck, Pascal R.; Howard, Waylon – International Journal of Behavioral Development, 2017
Inherent in applied developmental sciences is the threat to validity and generalizability due to missing data as a result of participant drop-out. The current paper provides an overview of how attrition should be reported, which tests can examine the potential of bias due to attrition (e.g., t-tests, logistic regression, Little's MCAR test,…
Descriptors: Attrition (Research Studies), Developmental Psychology, Psychological Studies, Statistical Analysis
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Deboeck, Pascal R.; Cole, David A.; Preacher, Kristopher J.; Forehand, Rex; Compas, Bruce E. – International Journal of Behavioral Development, 2021
Many interventions are characterized by repeated observations on the same individuals (e.g., baseline, mid-intervention, two to three post-intervention observations), which offer the opportunity to consider differences in how individuals vary over time. Effective interventions may not be limited to changing means, but instead may also include…
Descriptors: Intervention, Prevention, Individual Differences, Models
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Marks, Peter E. L.; Babcock, Ben; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2019
In peer nomination research, individuals who do not provide nominations (nonparticipants) are often included on rosters as potential nominees. This can present ethical questions regarding informed consent, but psychometric consequences of excluding nonparticipants from rosters are unknown. In this investigation, Study 1 simulated both random and…
Descriptors: Peer Groups, Adolescents, Grade 7, Grade 8
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Stemmler, Mark; Heine, Jörg-Henrik – International Journal of Behavioral Development, 2017
Configural frequency analysis and log-linear modeling are presented as person-centered analytic approaches for the analysis of categorical or categorized data in multi-way contingency tables. Person-centered developmental psychology, based on the holistic interactionistic perspective of the Stockholm working group around David Magnusson and Lars…
Descriptors: Classification, Data, Tables (Data), Models
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Jorgensen, Terrence D.; Rhemtulla, Mijke; Schoemann, Alexander; McPherson, Brent; Wu, Wei; Little, Todd D. – International Journal of Behavioral Development, 2014
Planned missing designs are becoming increasingly popular, but because there is no consensus on how to implement them in longitudinal research, we simulated longitudinal data to distinguish between strategies of assigning items to forms and of assigning forms to participants across measurement occasions. Using relative efficiency as the criterion,…
Descriptors: Longitudinal Studies, Research Design, Data Analysis, Monte Carlo Methods
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Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…
Descriptors: Data Analysis, Error of Measurement, Models, Longitudinal Studies
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Giallo, Rebecca; Gartland, Deirdre; Woolhouse, Hannah; Mensah, Fiona; Westrupp, Elizabeth; Nicholson, Jan; Brown, Stephanie – International Journal of Behavioral Development, 2018
The deleterious effects of maternal depression on child emotional and behavioral development are well documented, yet many children exposed to maternal depression experience positive outcomes. The aim of this study was to identify psychosocial factors associated with the emotional-behavioral resilience of four-year-old children of first-time…
Descriptors: Resilience (Psychology), Preschool Children, Mothers, Depression (Psychology)
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Pornprasertmanit, Sunthud; Little, Todd D. – International Journal of Behavioral Development, 2012
Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…
Descriptors: Data Analysis, Predictor Variables, Regression (Statistics), Evaluation
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Wu, Amery D.; Zumbo, Bruno D.; Marshall, Sheila K. – International Journal of Behavioral Development, 2014
This article describes a method based on Pratt's measures and demonstrates its use in exploratory factor analyses. The article discusses the interpretational complexities due to factor correlations and how Pratt's measures resolve these interpretational problems. Two real data examples demonstrate the calculation of what we call the…
Descriptors: Factor Analysis, Correlation, Comparative Analysis, Multiple Regression Analysis
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