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What Works Clearinghouse, 2023
The appendices accompany the full report "Using Bayesian Meta-Analysis to Explore the Components of Early Literacy Interventions. WWC 2023-008," (ED630495), which pilots a new taxonomy developed by early literacy experts and intervention developers as part of a larger effort to develop standard nomenclature for the components of literacy…
Descriptors: Bayesian Statistics, Meta Analysis, Early Intervention, Literacy
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Selig, James P.; Trott, Arianna; Lemberger, Matthew E. – Journal for Specialists in Group Work, 2017
Researchers in group counseling often encounter complex data from individual clients who are members of a group. Clients in the same group may be more similar than clients from different groups and this can lead to violations of statistical assumptions. The complexity of the data also means that predictors and outcomes can be measured at both the…
Descriptors: Group Counseling, Hierarchical Linear Modeling, Research, Client Characteristics (Human Services)
Mayhew, Matthew J.; Simonoff, Jeffrey S. – Journal of College Student Development, 2015
The purpose of this article is to describe effect coding as an alternative quantitative practice for analyzing and interpreting categorical, race-based independent variables in higher education research. Unlike indicator (dummy) codes that imply that one group will be a reference group, effect codes use average responses as a means for…
Descriptors: Coding, Educational Research, Higher Education, Statistical Analysis
Wurtz, Keith – Journal of Applied Research in the Community College, 2008
The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…
Descriptors: Regression (Statistics), Predictor Variables, Educational Background, Grades (Scholastic)
Brown, Diane Peacock – 1999
In education and the social sciences, problems of interest to researchers and users of research often involve variables that do not meet the assumptions of regression in the area of an equal interval scale relative to a zero point. Various coding schemes exist that allow the use of regression while still answering the researcher's questions of…
Descriptors: Classification, Coding, Elementary Secondary Education, Inclusive Schools
Richardson, Mary; Gabrosek, John; Reischman, Diann; Curtiss, Phyliss – Journal of Statistics Education, 2004
In this paper we describe an interactive activity that illustrates simple linear regression. Students collect data and analyze it using simple linear regression techniques taught in an introductory applied statistics course. The activity is extended to illustrate checks for regression assumptions and regression diagnostics taught in an…
Descriptors: Introductory Courses, Statistics, Class Activities, Data Collection