Hi Mike and all,I'm a new learner of meta-analysis and just try to use metaSEM.My dataset comprises 90 sets of 19*19 correlation matrix and every one contains some missing values. I'm trying to estimate a TSSEM model but encounter a problem in the first stage.After loading all the 90 matrices, I use "is.pd" to check if they are positive definite, and the results are all "TRUE". When I use "tssem1(my.R, n, method="FEM"), it returns an error message saying that "Error in eigen(if (doDykstra) R else Y, symmetric = TRUE) : infinite or missing values in 'x'". Then I try to apply a random effect model by "tssem1(my.R, n, method="REM", RE.type="Diag", acov="weighted")", but no result has come out.Is it due to the missing value, or any other issues that I have mistakenly ignored? how should I do to resolve the problem? Sincerely appreciate if you could help, thanks!Best regards,Eleanor See More

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Hi everybody,I want to calculate the standard error of d, VR, and Proportion ratios. And I'm looking for the standard error formula of them? (if it's possible all of them by using the Jackknife)(there are two independent groups)1. d = standard mean differences2. VR (variance ratio)VR = variance of group A / variance of group B3. Proportion ratios: For example the ratio of the top 10% subjectsThe ratio of the top 10% subjects = their frequency in group A / their frequency in group BPlease let me know if there are some mistakes in my question.thank you in advance,MajidSee More

Issues related to meta-analysis that performs psychometric corrections to effect sizes (a.k.a. validity generalization).

Hi there,I'm working on a meta-analysis where i combine different designs: independent groups (treatment and control group) on the one hand and only dependent pre post without control group on the other. For both study types I computed hedges' g according to Borenstein et al. (2009).As prescribed for studies that use pre post scores I used the correlation between pre- and post-scores to compute the standard deviation within groups and the variance of d. To compute the weight for each study I used the inverse of that study’s variance.And here is my problem/question:If the pre- / postscore-correlation is relativ high (e.g. .06) the weight of this study shoots up extremly. One study showed a pre post correlation of .08 and its weight is more than 20th times the most precise study with independent groups has. I tried to use an averaged pre post correlation but also then as result some of these studies have a much higher weight than the independent ones. I read a few papers that adressed this problem but i didnt find a solution. I also read the chapter in Borenstein et al. about the factors that affect precision. But I'm not sure how to deal with that.Thanks for any replyMichaelSee More

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