Publication Date
In 2025 | 1 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 4 |
Since 2006 (last 20 years) | 27 |
Descriptor
Behavioral Science Research | 31 |
Computation | 31 |
Evaluation Methods | 12 |
Models | 12 |
Simulation | 10 |
Statistical Analysis | 9 |
Data Analysis | 8 |
Effect Size | 6 |
Research Methodology | 6 |
Social Science Research | 6 |
Structural Equation Models | 6 |
More ▼ |
Source
Author
Enders, Craig K. | 2 |
Kelley, Ken | 2 |
Bauer, Daniel J. | 1 |
Cai, Li | 1 |
Caplan, Jeremy B. | 1 |
Cheung, Ka-Shing | 1 |
Cheung, Mike W. -L. | 1 |
Chong, Terence Tai-Leung | 1 |
Clark, Robin | 1 |
Cross, Katy | 1 |
Duncan, Susan C. | 1 |
More ▼ |
Publication Type
Journal Articles | 27 |
Reports - Research | 18 |
Reports - Descriptive | 6 |
Reports - Evaluative | 5 |
Information Analyses | 1 |
Education Level
Higher Education | 3 |
Adult Education | 1 |
Early Childhood Education | 1 |
Elementary Education | 1 |
Grade 1 | 1 |
Grade 7 | 1 |
High Schools | 1 |
Postsecondary Education | 1 |
Primary Education | 1 |
Audience
Location
Hong Kong | 1 |
Netherlands | 1 |
Singapore | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Gerrit Bauer; Nate Breznau; Johanna Gereke; Jan H. Höffler; Nicole Janz; Rima-Maria Rahal; Joachim K. Rennstich; Hannah Soiné – Teaching of Psychology, 2025
Introduction: The replication crisis in the behavioral and social sciences spawned a credibility revolution, calling for new open science research practices that ensure greater transparency, including preregistrations, open data and code, and open access. Statement of the Problem: Replications of published research are an important element in this…
Descriptors: Teaching Methods, Replication (Evaluation), Behavioral Sciences, Social Sciences
McNeish, Daniel; Bauer, Daniel J. – Grantee Submission, 2020
Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Factor Analysis, Matrices
Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
Pustejovsky, James E. – Grantee Submission, 2018
Methods for meta-analyzing single-case designs (SCDs) are needed to inform evidence-based practice in clinical and school settings and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…
Descriptors: Meta Analysis, Case Studies, Evidence Based Practice, Behavioral Science Research
Shieh, Gwowen – Journal of Experimental Education, 2015
Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…
Descriptors: Statistical Analysis, Sample Size, Computation, Effect Size
Lai, Mark H. C.; Kwok, Oi-Man – Journal of Educational and Behavioral Statistics, 2014
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…
Descriptors: Hierarchical Linear Modeling, Differences, Effect Size, Computation
Schlesinger, Matthew; McMurray, Bob – Cognitive Development, 2012
Does modeling matter? We address this question by providing a broad survey of the computational models of cognitive development that have been proposed and studied over the last three decades. We begin by noting the advantages and limitations of computational models. We then describe four key dimensions across which models of development can be…
Descriptors: Computation, Models, Cognitive Development, Taxonomy
Kello, Christopher T. – Psychological Review, 2013
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…
Descriptors: Cognitive Science, Scaling, Neurological Organization, Cognitive Processes
Rhodes, William – Evaluation Review, 2010
Regressions that control for confounding factors are the workhorse of evaluation research. When treatment effects are heterogeneous, however, the workhorse regression leads to estimated treatment effects that lack behavioral interpretations even when the selection on observables assumption holds. Regressions that use propensity scores as weights…
Descriptors: Evaluation Research, Computation, Evaluators, Regression (Statistics)
Lee, Chun-Ting; Zhang, Guangjian; Edwards, Michael C. – Multivariate Behavioral Research, 2012
Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable.…
Descriptors: Personality Traits, Intervals, Monte Carlo Methods, Factor Analysis
Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K. – Multivariate Behavioral Research, 2012
Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…
Descriptors: Questionnaires, Data Analysis, Computation, Monte Carlo Methods
Hung, Lai-Fa – Multivariate Behavioral Research, 2011
The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…
Descriptors: Markov Processes, Computer Software, Psychology, Computation
Zhong, Xiaoling; Yuan, Ke-Hai – Multivariate Behavioral Research, 2011
In the structural equation modeling literature, the normal-distribution-based maximum likelihood (ML) method is most widely used, partly because the resulting estimator is claimed to be asymptotically unbiased and most efficient. However, this may not hold when data deviate from normal distribution. Outlying cases or nonnormally distributed data,…
Descriptors: Structural Equation Models, Simulation, Racial Identification, Computation
Marcovitch, Stuart; Zelazo, Philip David – Developmental Science, 2009
The hierarchical competing systems model (HCSM) provides a framework for understanding the emergence and early development of executive function--the cognitive processes underlying the conscious control of behavior--in the context of search for hidden objects. According to this model, behavior is determined by the joint influence of a…
Descriptors: Object Permanence, Cognitive Processes, Models, Child Development
Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients