Small-Sample Adjustments for Tests of Moderators and Model Fit Using Robust Variance Estimation in Meta-Regression

By Elizabeth Tipton, James Pustejovsky. 2015

294 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/082aee3056900e3f5ac10444faf326688e1e40f1

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Citations in the corpus

Influencing Climate Change Attitudes in the United States: A Systematic Review and Meta-Analysis (2020, methodology): “…make distributional assumptions about effect sizes (Hedges et al., 2010), provides valid estimates about meta-regression coefficients even in small samples (with a small sample adjustment; Hedges et al., 2010; Tipton, 2015), and includes meta-regression moderator tests (Tipton & Pustejovsky, 2015).”
Small-Sample Methods for Cluster-Robust Variance Estimation and Hypothesis Testing in Fixed Effects Models (2016, methodology): “These findings follow closely those from Tipton and Pustejovsky (2015), which indicated that the Type I error of the AHT test was close to nominal even when the working model was quite discrepant from the data-generating model.”
Achievement Motivation and Academic Dishonesty: A Meta-Analytic Investigation (2020, methodology): “For hypothesis testing, we also used smallsample adjustments for t tests (Tipton 2015).”
Loneliness and the Big Five Personality Traits: A Meta–Analysis (2020, background): “However, if the number of studies included in a meta-analysis is small or moderate, test statistics and confidence intervals (CIs) based on RVE may suffer from inflated type I error (Tipton & Pustejovsky, 2015).”
A Meta-Analysis of School-Based Group Contingency Interventions for Students With Challenging Behavior: An Update (2017, methodology): “Given the relatively small number of included samples, small-sample adjustments to RVE were used to maintain close-to-nominal error rates for hypothesis tests and confidence intervals (CIs; Tipton & Pustejovsky, 2015).”