[R-meta] Multivariate multi-level meta-analysis: adjusting control variables when modeling publication bias?
Hi Wolfgang, Thank you! Sorry, I am new to Stack Exchange and did not realize that you had already provided a response. I deeply appreciate your insights. I do have a follow up question, if that's okay. I am also carrying two other multilevel analyses - one uses the t-statistic as a dependent outcome, and another uses the partial correlation coefficient (the computation of which is derived from the t-statistic) as the dependent variable. You mention that the authors divide everything because they are working with test statistics, which makes me wonder whether the analyses I just mentioned require the same adjustment? However, you go on to say that random-effects models and models with a multilevel structure do not require this adjustment. Do you mind clarifying? Thank you again for your time! The mailing list archives are an incredible resource!! I will also post this response on stack exchange, so that it is available to others. Best, Daniel
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> on behalf of Viechtbauer, Wolfgang (NP) via R-sig-meta-analysis <r-sig-meta-analysis at r-project.org>
Sent: Tuesday, December 5, 2023 2:46 PM
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-project.org>
Cc: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl>
Subject: Re: [R-meta] Multivariate multi-level meta-analysis: adjusting control variables when modeling publication bias?
Sent: Tuesday, December 5, 2023 2:46 PM
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-project.org>
Cc: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl>
Subject: Re: [R-meta] Multivariate multi-level meta-analysis: adjusting control variables when modeling publication bias?
[You don't often get email from r-sig-meta-analysis at r-project.org. Learn why this is important at https://aka.ms/LearnAboutSenderIdentification ] Hi Daniel, Didn't you ask the same question here? https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstats.stackexchange.com%2Fq%2F633046%2F1934&data=05%7C01%7Cdaniel.foster%40utoronto.ca%7C2e5052078db84090f23c08dbf5cb060f%7C78aac2262f034b4d9037b46d56c55210%7C0%7C0%7C638374024577218808%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=IcOgv30X42Ns1dIFMUHBay1I%2BudhJw8Ofc5yh%2FmmtYM%3D&reserved=0<https://stats.stackexchange.com/q/633046/1934> Please see my answer there. Best, Wolfgang > -----Original Message----- > From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> On Behalf > Of Daniel Foster via R-sig-meta-analysis > Sent: Tuesday, December 5, 2023 20:09 > To: r-sig-meta-analysis at r-project.org > Cc: Daniel Foster <daniel.foster567 at gmail.com> > Subject: [R-meta] Multivariate multi-level meta-analysis: adjusting control > variables when modeling publication bias? > > Hello Wolfgang and all, > > I am carrying out multivariate multilevel meta-analysis using the > rma.mv function in the metafor package, and I have come across an > issue that has been giving me a lot of trouble. At this point I am at > a stand still and any insight would be greatly appreciated!! > > When testing for publication bias using the PET approach, Doucouliagos > & Stanley (2009), suggest using the following model in a weighted > least squares formula: > > ES= B1(1/SE) + SIGMA ak(Zj/SEi )+ e > > Where SE is the standard error of the effect estimate, Z is a vector > of meta-independent variables reflecting differences across studies > for the jth study in literature, ak is the meta-regression coefficient > which reflects the effect of particular study characteristics. > > My confusion lies in the fact that they are suggesting that the > control variables (Z) included need to be divided by the standard > error of the effect estimate. My questions are this: > > Should I be dividing my control variables by the standard error of > the effect estimate when using the rma.mv function? I have found some > multivariate multilevel meta-analyses that follow this method > (Klomp, 2009), but then others that don't (at least explicitly; > Akgunduz, 2018) > > If I do need to do this, it is not clear to me how a binary control > variable can be incorporated in my mra.mv model (i.e., 1, 0). To my > mind, it seems strange to divide a dichotomous variable by a > continuous variable. What steps do I need to execute to include these > variables in my mra.mv model? > > Thank you so much in advance for your insights! > > Daniel > > Akgunduz, Y. E., & Plantenga, J. (2018). doi: 10.1111/joes.12192 > Doucouliagos, H., & Stanley, T. D. (2009). doi: 10.1111/j.1467-8543.2009.00723.x > Klomp, J., & De Haan, J. (2010). doi: 10.1111/j.1467-6419.2009.00597.x _______________________________________________ R-sig-meta-analysis mailing list @ R-sig-meta-analysis at r-project.org To manage your subscription to this mailing list, go to: https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-sig-meta-analysis&data=05%7C01%7Cdaniel.foster%40utoronto.ca%7C2e5052078db84090f23c08dbf5cb060f%7C78aac2262f034b4d9037b46d56c55210%7C0%7C0%7C638374024577218808%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2FQ%2BCa44M16CwWVmRCbTF1AOfTUpiHxH6%2FlklRYdkfbc%3D&reserved=0<https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis>