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It depends on the structure of the random effects (i.e., the ?working model? in the RVE framework). If one used a model with independent random effects for each ES estimate, then yes, increased heterogeneity would mean that the study...

I would hazard a guess that the +/- 0.07, which is described as "SD", might actually be the standard error of the effect size estimate. So in the example, ES = 1.38 and sampling variance = 0.07^2 = 0.049...

Greetings, I noticed a bug in the getVarCov function from nlme. I am posting here because it is not currently possible to register and file a report through https://bugs.r-project.org/. (If this is not the appropriate venue...

Hi Stefanou, clubSandwich provides standard errors, hypothesis tests, and confidence intervals for regression coefficient estimates (for meta-regressions and an array of other types of linear, generalized linear, and linear mixed effects models). It does *not* adjust variance component estimates...

Hi Danka, It's possible that we missed your first registration because of the issue with the Google Form that you noted. Here's the correct link to register: https://docs.google.com/forms/d/e/1FAIpQLScGX-GOm1nn93sj67_LF7MnngcFrOoOOcRS2cNsbgcw9-ujbg...

Dear meta-analysis folks, I am using metafor to fit a multi-level meta-regression model. I want to generate an 80% prediction interval for the effect size in a new study with a given set of characteristics. Here's...

Hi Wolfgang, I see in the metafor documentation for selmodel ( https://wviechtb.github.io/metafor/reference/selmodel.html#half-normal-negative-exponential-logistic-and-power-selection-models) that the half-normal, negative exponential, logistic, and power curve selection models can...

> > > When you note, 'if you trust the specification of your random effects > structure' can you elaborate on this? I imagine in the extreme, no random > effects structure will ever truly be perfect, so I guess it comes down to > some...

Hi Arthur, Yes, these sorts of models are now supported in metafor::rma.uni(). For details, see https://wviechtb.github.io/metafor/reference/rma.uni.html#location-scale-models For a sub-group analysis with a categorical moderator called `mod...

Hello, I am writing some additional functionality for lme objects, and I have a question about how lme() handles corAR1() structures. I noticed that sometimes, if I specify a model with corAR1(), the fitted model has a corStruct of class...

> 1. Would you like to explain a bit "the SD of the BLUPs is not the > same thing as the SD of the population distribution". Conceptually, I > thought they are the same - both representing the marginal distribution > after accounting for...

Reza, Both packages use the same method to calculate standard errors and covariances for meta-analytic average effect size estimates and meta-regression coefficients. However, the packages implement different estimation methods for between-study heterogeneity and they use different weighting...

But I am not using global variables at all in the package code (in /R)---only for unit testing. Is this distinction relevant? Or do I need to avoid global assignment even in the unit tests? On Thu, Jan 27...

Dear R users: I'm happy to announce the first CRAN release of the clubSandwich package: https://cran.r-project.org/web/packages/clubSandwich clubSandwich provides several variants of the cluster-robust variance estimator for ordinary and weighted least squares...

I find the functions safely() and possibly() from the purrr package for this sort of error handling stuff. For instance, create safe_reitsma <- safely(mada::reitsma) Then run X_mada <- safe_reitsma(data=subset(X,SUBMA_num==iii), correction.control...

That makes sense. RVE won't work and is not appropriate if you only have a single study falling into a given category. For it to work, there need to be multiple independent studies that contribute effects to a given...

Hi Catia, The issue is with drawing inferences. When the degrees of freedom are low (less than 4, say), the point estimates and the sampling variance estimates should still be unbiased (or close to unbiased, for the sampling variances). However...

The approximations there are predicated on k (the number of studies) being large enough that the estimated heterogeneity (tau-hat) converges to the true heterogeneity parameter. On Thu, Jun 29, 2023 at 11:29?PM Yefeng Yang <yefeng.yang1 at...

Dear R users: I'm happy to announce the first CRAN release of the clubSandwich package: https://cran.r-project.org/web/packages/clubSandwich clubSandwich provides several variants of the cluster-robust variance estimator for ordinary and weighted least squares...

Correct. The slope on sqrt(vi) indicates an association between SE and effect size. The intercept is a "PET"-style estimate of the average effect size in a population of infinitely large studies (i.e. SE = 0). James On Mon...