Meta-analysis with standardized effect sizes from multilevel and latent growth models.

2017/01/09 by Alan Feingold · 13 citations
Decision Sciences · Psychology · #Psychometric Methodologies and Testing #Meta-analysis and systematic reviews #Personality Disorders and Psychopathology

paper · doi:10.1037/ccp0000162

Abstract

OBJECTIVE: Findings from multilevel and latent growth modeling analysis (GMA) need to be included in literature reviews, and this article explicates 4 rarely discussed approaches for using GMA studies in meta-analysis. METHOD: Extant and new equations are presented for calculating the effect size (d) and its variance (v) from reported statistics from GMA studies with each method, and a fixed effects meta-analysis of results from 5 randomized clinical trials was conducted to demonstrate their applications. RESULTS: Two common problematic practices--one that introduces bias in effect sizes because of attrition, measurement errors, and probable violations of assumptions for classical analysis, and the other that confounds the treatment effect with the intraclass correlation--were both found to yield smaller effect sizes from retrieved studies than were obtained with a newer model-based framework and its associated GMA d statistic. CONCLUSIONS: The optimal strategy for including a GMA study in a meta-analysis is to use GMA d and its v calculated with the standard error of the unstandardized coefficient for the treatment effect. When that standard error is unknown, the use of GMA d and its v estimated with an alternative equation that requires only GMA d and sample size is recommended. (PsycINFO Database Record

Citations

• A randomized clinical trial of acceptance and commitment therapy versus progressive relaxation training for obsessive-compulsive disorder.
• Confidence interval estimation for standardized effect sizes in multilevel and latent growth modeling.

Cited by

• Time-Varying Effect Sizes for Quadratic Growth Models in Multilevel and Latent Growth Modeling. [europepmc]
• New Approaches for Estimation of Effect Sizes and their Confidence Intervals for Treatment Effects from Randomized Controlled Trials. [europepmc]
• Effect of Parameterization on Statistical Power and Effect Size Estimation in Latent Growth Modeling. [europepmc]
• Understanding the role of positive body image during digital interventions for eating disorders: Secondary analyses of a randomized controlled trial. [europepmc]
• Project Harmony: A Meta-Analysis With Individual Patient Data on Behavioral and Pharmacologic Trials for Comorbid Posttraumatic Stress and Alcohol or Other Drug Use Disorders. [europepmc]
• A randomized controlled trial of a preventive intervention for the children of parents with depression: mid-term effects, mediators and moderators. [europepmc]
• Regression-Equivalent Effect Sizes for Latent Growth Modeling and Associated Null Hypothesis Significance Tests. [europepmc]
• Cannabis use and trauma-focused treatment for co-occurring posttraumatic stress disorder and substance use disorders: A meta-analysis of individual patient data. [europepmc]
• Examining the Effects of a Brief, Fully Self-Guided Mindfulness Ecological Momentary Intervention on Empathy and Theory-of-Mind for Generalized Anxiety Disorder: Randomized Controlled Trial. [europepmc]
• A dialectical behavior therapy skills training smartphone app for recurrent binge eating: a randomized clinical trial. [europepmc]
• The Efficacy of Experiential Dynamic Therapies: A 10-Year Systematic Review and Meta-Analysis Update. [europepmc]
• Improving body image in female Chinese social media users with eating disorder symptoms: a randomized controlled trial of two online self-guided single-session interventions. [europepmc]
• Enhancing psychological resilience in cyberbullying victims through AI-guided cognitive reappraisal. [europepmc]

Related

• Confidence interval estimation for standardized effect sizes in multilevel and latent growth modeling.
• Accuracy and precision of fixed and random effects in meta‐analyses of randomized control trials for continuous outcomes
• What can we learn from 1,000 meta-analyses across 10 different disciplines?
• A Bayesian Nonparametric Meta-Analysis Model
• Meta-analysis models relaxing the random effects normality assumption: methodological systematic review and simulation study