Meta-regression examines the impact of moderator variables on study effect size using regression-based techniques. Meta-regression is more effective at this task than are standard meta-analytic techniques (Wikipedia).

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Mixed-model meta-regression

I have a collection of continuous data from the literature, including the mean, the standard deviation and the number of observations for both experimental and control groups, as well some ...
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How big is the risk for regression in a single arm meta-analysis?

I'm performing a single arm meta-analysis of continous data deriving from efficacy evaluation of control gorups surgical procedure. How big is the risk for regression to the mean? And How it could ...
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Data imputation for meta analysis using mice package in R

I have a data-set with 32 effect size estimates- only 11 of which report a value for the continuous moderator of interest (the samples anxiety level). A complete case analysis (restricted to the 11 ...
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Oddly large R squared values in meta regression (metafor)

I am using the metafor package in R. I have fit a random effects model with a continuous predictor as follows SIZE=rma(yi=Ds,sei=SE,data=VPPOOLed,mods=~SIZE) ...
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Difference between Meta-Analysis, Meta-Regression and Moderator-Analysis

What is the difference between the classic meta-analysis (that aggregates effect sizes from a sample of studies to a summary effect size), meta-regression analysis and moderator analysis? As I ...
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Independence of effects in meta-analysis and meta-regression

In meta-analysis, I know that an important assumption is independence. Clearly, if we want to estimate a pooled effect size, its best if each effect comes from an independent sample of observers. ...
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Metafor package: Interpreting rma model with two (or more) moderators.

New user of both stackexchange and R here. My questions are about mainly about interpretation, and my dataset is quite large, so I have not included my dataframe. I have two queries (in bold). Using ...
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How to perform a meta regression with a random effect model?Which model should I use?How to start? (beginner)

I have to perform a meta-regression, using mixed or random effects model, but I don't have any software (except Matlab) and I'm new on this topic (having a relativelly poor statistics background). ...
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What to do with coefficients of log-transformed predictors in meta regression of effect sizes?

I am preparing data for a meta-analysis regression of effect sizes, in which I will study the determinants of effect size for a specific variable across several studies. I have some studies in my ...
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Is the approach to moderator analysis advocated by Hunter, Schmidt and Jackson (1982) valid?

There are several approaches, for example, moderated regression analysis and Hunter, Schmidt and Jackson. The HSJ (1982) approach invokes true variance computation based on subsets say male- vs ...
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How to remove non-significant interaction(s) from meta-regression (rma) model

According to the rule of marginality, I should remove all non-significant interactions from model to achive simplicity (MInimal Adequate Model). I am familiar with removing such interactions from ...
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Meta-analysis of prevalence at the country level

I'm working on a meta-analysis of prevalence data. The aim is to get estimates of prevalence at the country level. The main issue is that the disease is highly correlated with age, and the sample ages ...
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Stepwise meta-regression with R (metafor)

I am using the "metafor" package to do a multivariate meta-regression in "R". I have 6 predictors and I am able to run the full model (all the predictors simultaneously in the model) just fine. ...
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Multivariate meta analysis and metaregression with multi arm randomized controlled studies

Please, i need to do a network meta-analysis and metaregression or a multivariate meta analysis and metaregression. I have multi arm randomized controlled studies. I tried the metafor package Dummy ...
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How to best handle subscores in a meta-analysis?

I am conducting a meta-analysis of effect sizes d in R using the metafor package. d represents differences in memory scores between patients and healthy. However some studies report only subscores of ...
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How to perform meta-analysis comparing different proportional mortality ratios of subgroups?

I am working on a meta-analysis of observational studies (basically 39 retrospective papers on different surgical interventions for one condition). I've obtained different weighted proportions ...
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Can I incude an effect size as an independent variable in a meta-regression?

My question is whether I can use an effect size $X$ as a dependent variable and another effect size $Y$ as the independent variable in a meta-regression. For example, I conducted a meta-analysis for ...
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Principled ways of constraining $E[Y]=0$ when one of your regressors $\rightarrow$ 0

Consider the following ridiculous example. There is a real, non-ridiculous research question here, I promise -- I'm just a little bit uncomfortable posting what I'm working on on the internet in ...
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How to do meta-analysis and create forest plots using Beta correlation coefficients

Does anyone knows how to do meta-analysis and create forest plots using beta-correlation coefficients?
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Using mvmeta to perform a network meta-analysis

A few months ago, I posted these two questions about practical considerations in collecting data for a network meta-analysis and the available R packages that can analyze such data. For those ...
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Multiple imputation for outcome variables

I've got a dataset on agricultural trials. My response variable is a response ratio: log(treatment/control). I'm interested in what mediates the difference, so I'm running RE meta-regressions ...
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R software implementation of combining mixed treatment comparisons and meta-regression

I am currently conducting a meta-analysis in which I need to use a mixed treatment comparison method. As I understand it, this method works in the following way: Say you have a group of studies that ...
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169 views

Metaregression with Age as a Covariate

Imagine that you have access to a collection of studies in which an age range, a sample size and an "effect" (say, cigarettes per day) is reported. What is the best way to construct a meta-regression ...
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Meta-regression with dependent variables of different distributions

The textbook examples of metaregression I demonstrate how to combine coefficients when the dependent variable has the one distribution (for instance, exclusively binomial or exclusively continuous). ...
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How to do meta-regression in SPSS?

I am trying to manage a meta-regression in SPSS17 using the effect size as the dependent variable. I want to explore if my independent variables affects the effect size. Some small practical ...