Understanding Meta-Analysis Through Data Simulation With Applications to Power Analysis

被引:4
作者
Gambarota, Filippo [1 ]
Altoe, Gianmarco [1 ]
机构
[1] Univ Padua, Dept Dev & Social Psychol, Padua, Italy
关键词
meta-analysis; Monte Carlo simulations; power analysis; EFFECTS META-REGRESSION; CONFIDENCE-INTERVALS; HETEROGENEITY; TESTS;
D O I
10.1177/25152459231209330
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Meta-analysis is a powerful tool to combine evidence from existing literature. Despite several introductory and advanced materials about organizing, conducting, and reporting a meta-analysis, to our knowledge, there are no introductive materials about simulating the most common meta-analysis models. Data simulation is essential for developing and validating new statistical models and procedures. Furthermore, data simulation is a powerful educational tool for understanding a statistical method. In this tutorial, we show how to simulate equal-effects, random-effects, and metaregression models and illustrate how to estimate statistical power. Simulations for multilevel and multivariate models are available in the Supplemental Material available online. All materials associated with this article can be accessed on OSF (https://osf.io/54djn/).
引用
收藏
页数:18
相关论文
共 46 条
[1]   Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study [J].
Antonio Lopez-Lopez, Jose ;
Marin-Martinez, Fulgencio ;
Sanchez-Meca, Julio ;
Van den Noortgate, Wim ;
Viechtbauer, Wolfgang .
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, 2014, 67 (01) :30-48
[2]  
Aust F., 2022, Papaja: Prepare American Psychological Association Journal Articles with R Markdown
[3]   A tutorial on Bayesian model-averaged meta-analysis in JASP [J].
Berkhout, Sophie W. ;
Haaf, Julia M. ;
Gronau, Quentin F. ;
Heck, Daniel W. ;
Wagenmakers, Eric-Jan .
BEHAVIOR RESEARCH METHODS, 2024, 56 (03) :1260-1282
[4]   Heterogeneity estimation in meta-analysis of standardized mean differences when the distribution of random effects departs from normal: A Monte Carlo simulation study [J].
Blazquez-Rincon, Desiree ;
Sanchez-Meca, Julio ;
Botella, Juan ;
Suero, Manuel .
BMC MEDICAL RESEARCH METHODOLOGY, 2023, 23 (01)
[5]  
Borenstein M., 2009, Introduction to Meta-Analysis, DOI DOI 10.1002/9780470743386
[6]  
Cohen J., 1988, STAT POWER ANAL BEHA
[7]   Understanding Mixed-Effects Models Through Data Simulation [J].
DeBruine, Lisa M. ;
Barr, Dale J. .
ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE, 2021, 4 (01)
[8]  
Gelman A., 2020, Regression and other stories, DOI DOI 10.1017/9781139161879
[9]  
Gentle JE, 2009, STAT COMPUT SER, P417, DOI 10.1007/978-0-387-98144-4_11
[10]   A Primer on Bayesian Model-Averaged Meta-Analysis [J].
Gronau, Quentin F. ;
Heck, Daniel W. ;
Berkhout, Sophie W. ;
Haaf, Julia M. ;
Wagenmakers, Eric-Jan .
ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE, 2021, 4 (03)