Journal article
Estimating Partial Standardized Mean Differences from Regression Models
The Journal of experimental education, Vol.90(4), pp.898-915
07/13/2022
DOI: 10.1080/00220973.2021.1966605
Abstract
The distribution of the standardized mean difference is well understood. However, in many situations, researchers need to estimate an effect size to represent the relationship between a continuous outcome and a dichotomous grouping variable, adjusting for the effect of a covariate (or a set of covariates). Typically, this adjustment takes place via regression models. In this article, we consider five different estimators of standardized mean differences that could arise from regression models with one or more covariates. We demonstrate that an existing correction, believed to recover the pooled standard deviation, is in fact an approximation. In addition, we compared the performance of each standardized mean difference index. The function used to generate the data for the simulation is available in the Supplemental Material. Implications for comparing results from primary studies, as well as for meta-analysis, are also considered.
Details
- Title: Subtitle
- Estimating Partial Standardized Mean Differences from Regression Models
- Creators
- Ariel M. Aloe - University of IowaChristopher G. Thompson - Texas A&MZhijiang Liu - University of IowaLifeng Lin - Florida State University
- Resource Type
- Journal article
- Publication Details
- The Journal of experimental education, Vol.90(4), pp.898-915
- Publisher
- Routledge
- DOI
- 10.1080/00220973.2021.1966605
- ISSN
- 0022-0973
- eISSN
- 1940-0683
- Grant note
- name: National Science Foundation, NSF USA
- Language
- English
- Date published
- 07/13/2022
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9984371279002771
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