Meta-Analysis Resources

Tools for Those Who Summarize the Evidence Base

Resources and networking for those who conduct or interpret meta-analyses related to any phenomenon that is gauged in multiple studies.

Kevria
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huiyong fan replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"Hi, please find the following for three examples using meta analysis of factor loading matrices. [1]Chiungjung Huang, & Jyun-Hong Chen. Meta-Analysis of the Factor Structures of the Beck Depression Inventory–II. Assessment, 2015, 22(4)…"
Feb 7
Mike Cheung replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"Hi Kevria, If you have the raw data, EFA/CFA/IRT is the obvious choice. You only need meta-analysis when you have lots of summary statistics. If you want to validate the "items," you need item-level correlations. If you only have the…"
Feb 7
huiyong fan replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"please see the journal named as measurement, which once published meta analysis of EFA."
Feb 7
Kevria added a discussion to the group Calculating Effect Sizes and Their Variances or Standard Errors
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calculating Cohen's d for pre-post changes among paired groups?

Dear all,I am using the programme "Comprehensive Meta-Analysis" (CMA) to meta-analyze the effectiveness of a particular intervention. I want to meta-analyze whether there are effective changes in some hypothesized outcomes after joining the intervention. I would like to seek your advice on which effect size measure(s) to use appropriately.I wanted to use Cohen’s d as the effect size measure using r.  However, my whole batch of those included studies got two types — one type with both…See More
Feb 6
Kevria replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"thanks huiyong for your advice and shared reference, will go through it in detail!Would you mind sharing a bit more about meta-analyzing factor loading matrices from EFA? Would you have any sample papers?"
Feb 6
huiyong fan replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"if you only get the factor loadong matrices."
Feb 5
huiyong fan replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"meta analysis of factor loading matrices looks not so rigorous, but appears in literature sometimes."
Feb 5
huiyong fan replied to Kevria's discussion testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT in the group Meta-analytic structural equation modeling
"RE: 1. item-level intercorrelation is must in meta-sem. but, if it has some subscales, you can treat subscales as items, i. e. the meta analysis canbe set on the subscale level. and your research question should be reset correspondingly. here is an…"
Feb 5
Kevria added a discussion to the group Meta-analytic structural equation modeling
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testing factor structure: meta-SEM vs CFA followed by EFA vs Rasch vs IRT

Dear Mike and all,I want to examine the factor structure of two scales respectively (scale A: 14 items; scale B: 26 items). We are trying several methods: CFA followed by EFA; Rasch analysis and IRT respectively. IRT seems to be a more and more popular methodology for the purpose. But I have also come across some studies using meta-SEM to examine the factor structure. It basically refers to: getting the pooled inter-item correlation matrix from the respective inter-item correlation matrix from…See More
Feb 5
Kevria joined Blair T. Johnson's group
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Calculating Effect Sizes and Their Variances or Standard Errors

Tips and techniques to help meta-analysts calculate effect sizes and the variances that are needed for the purpose of analysis.See More
Feb 5

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