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10.1037/ccp0000162 http://scihub22266oqcxt.onion/10.1037/ccp0000162 C5319897!5319897!28068118     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Consult+Clin+Psychol 2017 ; 85 (3): 262-6 Nephropedia Template TP {{tp|p=28068118|t=2017. Meta-Analysis with Standardized Effect Sizes from Multilevel and Latent Growth Models |pdf=|usr=}}{{28068118}} gab.com Text Meta-Analysis with Standardized Effect Sizes from Multilevel and Latent Growth Models JO: J Consult Clin Psychol http://www.kidney.de/pget.php?&tw=1&pmid=28068118 #FOAvip Objective: Findings from multilevel and latent growth modeling analysis (GMA) need to be included in literature reviews, and this article explicates four rarely discussed approaches for using GMA studies in meta-analysis. Method: Extant and new equations are presented for calculating the effect size (d) and its variance (v) from reported statistics from GMA studies with each method, and a fixed effects meta-analysis of results from five randomized clinical trials was conducted to demonstrate their applications. Results: Two common practices that were known to introduce bias in effect sizes because of attrition, confounding of treatment effects with the intraclass correlation, measurement errors, and probable violations of assumptions limited to classical analysis were found to yield smaller effects sizes from retrieved studies than were obtained with a newer model-based framework and its associated GMA d statistic. Conclusions: The optimal strategy for including a GMA study in a meta-analysis is to use GMA d and its v calculated with the standard error of the unstandardized coefficient for the treatment effect. When that standard error is unknown, the use of GMA d and its v estimated with an alternative equation that requires only GMA d and sample size is recommended. Twit Text FOAVip Meta-Analysis with Standardized Effect Sizes from Multilevel and Latent Growth Models ????J Consult Clin Psychol http://www.kidney.de/pget.php?&tw=1&pmid=28068118 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28068118 #FOAvip English Wikipedia <ref>{{Cite pmid|28068118}}</ref> Meta-Analysis with Standardized Effect Sizes from Multilevel and Latent Growth Models #MMPMID28068118 Feingold A J Consult Clin Psychol 2017[Mar]; 85 (3): 262-6 PMID28068118show ga Objective: Findings from multilevel and latent growth modeling analysis (GMA) need to be included in literature reviews, and this article explicates four rarely discussed approaches for using GMA studies in meta-analysis. Method: Extant and new equations are presented for calculating the effect size (d) and its variance (v) from reported statistics from GMA studies with each method, and a fixed effects meta-analysis of results from five randomized clinical trials was conducted to demonstrate their applications. Results: Two common practices that were known to introduce bias in effect sizes because of attrition, confounding of treatment effects with the intraclass correlation, measurement errors, and probable violations of assumptions limited to classical analysis were found to yield smaller effects sizes from retrieved studies than were obtained with a newer model-based framework and its associated GMA d statistic. Conclusions: The optimal strategy for including a GMA study in a meta-analysis is to use GMA d and its v calculated with the standard error of the unstandardized coefficient for the treatment effect. When that standard error is unknown, the use of GMA d and its v estimated with an alternative equation that requires only GMA d and sample size is recommended. äMeta-Analysis with Standardized Effect Sizes from Multilevel and Laten(epmc).pdf DeepDyve Pubget Overpricing