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</o:shapelayout></xml><![endif]--></head><body lang=DE link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>Hi all,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>I am currently working on a meta-analysis on strategic orientations (IV) and firm performance (DV), using correlational data, and struggle with how I should best handle dependencies among effect sizes.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>Short elaboration of the issue:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>The strategic orientation I am interested in consists of three subdimensions and some studies report correlational data between the subdimensions and e.g. profitability, whereas other studies report only a correlation between the whole construct and profitability. Moreover, some studies use more than one profitability measure. I am interested in the overall aggregate effect between the “whole” strategic orientation and “whole” profitability.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>This leaves me with the following cases:<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>1. Whole orientation and single profitability measure (trivial)<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>2. Whole orientation and multiple profitability measures<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>3. Multiple dimensions and single profitability measure<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>4. Multiple dimensions and multiple profitability measures <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>Following the mailing list and the metaphor website, I could handle the 2nd case through nesting the multiple effects in studies and using the impute_covariance_matrix function of the clubSandwhich package. However, I am not exactly sure on how to appropriately handle case 3 and 4 and especially, how to combine 2 to 4 in order to run the analysis on the aggregate level (whole orientation – whole profitability).<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'>Due to working with correlations, the respective studies report the correlations between the variables e.g. between the dimensions, between the profitability measures and the correlations between the dimensions and profitability measures.<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Best<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Jens<o:p></o:p></span></p></div></body></html>