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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
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
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
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
Schoemann, Alexander M.; Miller, Patrick; Pornprasertmanit, Sunthud; Wu, Wei – International Journal of Behavioral Development, 2014
Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design…
Descriptors: Monte Carlo Methods, Simulation, Sample Size, Research Design
Jocson, Rosanne M.; Alampay, Liane Pena; Lansford, Jennifer E. – International Journal of Behavioral Development, 2012
The relations of education, authoritarian child-rearing attitudes, and endorsement of corporal punishment to Filipino parents' reported use of corporal punishment were examined using two waves of data. Structured interviews using self-report questionnaires were conducted with 117 mothers and 98 fathers from 120 families when their children were 8…
Descriptors: Higher Education, Mothers, Child Rearing, Interviews
Lekhal, Ratib – International Journal of Behavioral Development, 2012
Associations between type and age of entry into Norwegian universally-accessible childcare and children's behavior problems at age 3 years were examined in this study. Data from 73,068 children in the large population-based, prospective Norwegian Mother and Child Cohort Study (MoBa) were used, and included information about childcare arrangements,…
Descriptors: Behavior Problems, Children, Foreign Countries, Norwegian
Little, Todd D.; Preacher, Kristopher J.; Selig, James P.; Card, Noel A. – International Journal of Behavioral Development, 2007
We review fundamental issues in one traditional structural equation modeling (SEM) approach to analyzing longitudinal data--cross-lagged panel designs. We then discuss a number of new developments in SEM that are applicable to analyzing panel designs. These issues include setting appropriate scales for latent variables, specifying an appropriate…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Correlation
Grimm, Kevin J. – International Journal of Behavioral Development, 2007
Recent advances in methods and computer software for longitudinal data analysis have pushed researchers to more critically examine developmental theories. In turn, researchers have also begun to push longitudinal methods by asking more complex developmental questions. One such question involves the relationships between two developmental…
Descriptors: Data Analysis, Depression (Psychology), Academic Achievement, Developmental Stages