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analyses:raudenbush2009 [2021/11/08 16:05] – Wolfgang Viechtbaueranalyses:raudenbush2009 [2022/08/03 11:21] – Wolfgang Viechtbauer
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 dat dat
 </code> </code>
-(I copy the dataset into ''dat'', which is a bit shorter and therefore easier to type further below). The contents of the dataset are: +(I copy the dataset into ''dat'', which is a bit shorter and therefore easier to type further below). The contents of the dataset are:
 <code output> <code output>
    study               author year weeks setting tester    yi     vi    study               author year weeks setting tester    yi     vi
Line 77: Line 77:
 H^2 (total variability / sampling variability):  1.72 H^2 (total variability / sampling variability):  1.72
  
-Test for Heterogeneity: +Test for Heterogeneity:
 Q(df = 18) = 35.830, p-val = 0.007 Q(df = 18) = 35.830, p-val = 0.007
  
 Model Results: Model Results:
  
-estimate       se     zval     pval    ci.lb    ci.ub           +estimate       se     zval     pval    ci.lb    ci.ub 
-   0.084    0.052    1.621    0.105   -0.018    0.185          +   0.084    0.052    1.621    0.105   -0.018    0.185
  
 --- ---
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 H^2 (total variability / sampling variability):  1.99 H^2 (total variability / sampling variability):  1.99
  
-Test for Heterogeneity: +Test for Heterogeneity:
 Q(df = 18) = 35.830, p-val = 0.007 Q(df = 18) = 35.830, p-val = 0.007
  
 Model Results: Model Results:
  
-estimate       se     zval     pval    ci.lb    ci.ub           +estimate       se     zval     pval    ci.lb    ci.ub 
-   0.089    0.056    1.601    0.109   -0.020    0.199          +   0.089    0.056    1.601    0.109   -0.020    0.199
  
 --- ---
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 R^2 (amount of heterogeneity accounted for):            100.00% R^2 (amount of heterogeneity accounted for):            100.00%
  
-Test for Residual Heterogeneity: +Test for Residual Heterogeneity:
 QE(df = 17) = 16.571, p-val = 0.484 QE(df = 17) = 16.571, p-val = 0.484
  
-Test of Moderators (coefficient(s) 2): +Test of Moderators (coefficient(s) 2):
 QM(df = 1) = 19.258, p-val < .001 QM(df = 1) = 19.258, p-val < .001
  
 Model Results: Model Results:
  
-         estimate     se    zval   pval   ci.lb   ci.ub     +         estimate     se    zval   pval   ci.lb   ci.ub
 intrcpt     0.407  0.087   4.678  <.001   0.237   0.578  *** intrcpt     0.407  0.087   4.678  <.001   0.237   0.578  ***
 weeks.c    -0.157  0.036  -4.388  <.001  -0.227  -0.087  *** weeks.c    -0.157  0.036  -4.388  <.001  -0.227  -0.087  ***
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 res.hw$HE   <- robust(res.std$HE,   cluster=dat$study, adjust=FALSE) res.hw$HE   <- robust(res.std$HE,   cluster=dat$study, adjust=FALSE)
  
-round(t(sapply(res.hw, function(x) c(tau2=x$tau2, mu=x$b, se=x$se, t=x$tval, ci.lb=x$ci.lb, ci.ub=x$ci.ub))), 3)   +round(t(sapply(res.hw, function(x) c(tau2=x$tau2, mu=x$b, se=x$se, t=x$tval, ci.lb=x$ci.lb, ci.ub=x$ci.ub))), 3)
 </code> </code>
 <code output> <code output>
Line 312: Line 312:
 ==== References ==== ==== References ====
  
-Hedges, L. V. (1983). A random effects model for effect sizes. //Psychological Bulletin, 93//(2), 388--395. +Hedges, L. V. (1983). A random effects model for effect sizes. //Psychological Bulletin, 93//(2), 388--395.
  
 Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. //Statistics in Medicine, 21//(11), 1539--1558. Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. //Statistics in Medicine, 21//(11), 1539--1558.
analyses/raudenbush2009.txt · Last modified: 2022/08/03 17:09 by Wolfgang Viechtbauer