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Eric C. Hedberg – Grantee Submission, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
E. C. Hedberg – American Journal of Evaluation, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
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Lee, Kejin; Whittaker, Tiffany Ann – AERA Online Paper Repository, 2017
The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple domain latent growth model (MDLGM). While the MDLGM is conceived as a more powerful multivariate analysis technique, the examination of its methodological…
Descriptors: Statistical Analysis, Growth Models, Structural Equation Models, Multivariate Analysis
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Radley, Keith C.; Dart, Evan H.; Wright, Sarah J. – School Psychology Quarterly, 2018
Research based on single-case designs (SCD) are frequently utilized in educational settings to evaluate the effect of an intervention on student behavior. Visual analysis is the primary method of evaluation of SCD, despite research noting concerns regarding reliability of the procedure. Recent research suggests that characteristics of the graphic…
Descriptors: Graphs, Evaluation Methods, Data, Intervention
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Rhoads, Christopher – Society for Research on Educational Effectiveness, 2016
Current practice for conducting power analyses in hierarchical trials using survey based ICC and effect size estimates may be misestimating power because ICCs are not being adjusted to account for treatment effect heterogeneity. Results presented in Table 1 show that the necessary adjustments can be quite large or quite small. Furthermore, power…
Descriptors: Statistical Analysis, Correlation, Effect Size, Surveys
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Rhoads, Christopher – Journal of Educational and Behavioral Statistics, 2017
Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Surveys, Effect Size
Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
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McNeish, Daniel M.; Stapleton, Laura M. – Educational Psychology Review, 2016
Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Sample Size, Effect Size
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Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
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Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2017
Field experiments in education frequently assign entire groups such as schools to treatment or control conditions. These experiments incorporate sometimes a longitudinal component where for example students are followed over time to assess differences in the average rate of linear change, or rate of acceleration. In this study, we provide methods…
Descriptors: Educational Experiments, Field Studies, Models, Randomized Controlled Trials
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Maslowsky, Julie; Jager, Justin; Hemken, Douglas – International Journal of Behavioral Development, 2015
Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…
Descriptors: Structural Equation Models, Computation, Goodness of Fit, Effect Size
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Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2014
Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…
Descriptors: Correlation, Statistical Analysis, Multivariate Analysis, Research Design
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Young, Anna M.; Wendel, Paul J.; Esson, Joan M.; Plank, Kathryn M. – International Journal of Science Education, 2018
Decline in student motivation is a concern for STEM education, especially for underrepresented groups in the sciences. Using the Science Motivation Questionnaire II, 41 foundational STEM courses were surveyed at the beginning and end of each semester in an academic year at a small primarily undergraduate university. Significant pre- to…
Descriptors: Higher Education, STEM Education, Student Motivation, Questionnaires
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Ham, Amanda D.; Huggins-Hoyt, Kimberly Y.; Pettus, Joelle – Research on Social Work Practice, 2016
Objectives: This study examined how evaluation and intervention research (IR) studies assessed statistical change to ascertain effectiveness. Methods: Studies from six core social work journals (2009-2013) were reviewed (N = 1,380). Fifty-two evaluation (n= 27) and intervention (n = 25) studies met the inclusion criteria. These studies were…
Descriptors: Social Work, Program Effectiveness, Intervention, Evaluation Research
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Tipton, Elizabeth; Pustejovsky, James E. – Journal of Educational and Behavioral Statistics, 2015
Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…
Descriptors: Meta Analysis, Effect Size, Computation, Robustness (Statistics)
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