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tips:comp_two_independent_estimates

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tips:comp_two_independent_estimates [2021/11/08 15:49] – Wolfgang Viechtbauertips:comp_two_independent_estimates [2022/08/03 11:31] – Wolfgang Viechtbauer
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 Fixed-Effects with Moderators Model (k = 2) Fixed-Effects with Moderators Model (k = 2)
  
-Test for Residual Heterogeneity: +Test for Residual Heterogeneity:
 QE(df = 0) = 0.000, p-val = 1.000 QE(df = 0) = 0.000, p-val = 1.000
  
-Test of Moderators (coefficient(s) 2): +Test of Moderators (coefficient(s) 2):
 QM(df = 1) = 1.946, p-val = 0.163 QM(df = 1) = 1.946, p-val = 0.163
  
 Model Results: Model Results:
  
-            estimate     se    zval   pval   ci.lb   ci.ub   +            estimate     se    zval   pval   ci.lb   ci.ub
 intrcpt       -0.481  0.217  -2.218  0.027  -0.907  -0.056  * intrcpt       -0.481  0.217  -2.218  0.027  -0.907  -0.056  *
-metarandom    -0.490  0.351  -1.395  0.163  -1.178   0.198   +metarandom    -0.490  0.351  -1.395  0.163  -1.178   0.198
  
 --- ---
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 </code> </code>
 <code output> <code output>
-  zval +  zval
 -1.395 -1.395
 </code> </code>
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 R^2 (amount of heterogeneity accounted for):            0.00% R^2 (amount of heterogeneity accounted for):            0.00%
  
-Test for Residual Heterogeneity: +Test for Residual Heterogeneity:
 QE(df = 11) = 138.511, p-val < .001 QE(df = 11) = 138.511, p-val < .001
  
-Test of Moderators (coefficient(s) 2): +Test of Moderators (coefficient(s) 2):
 QM(df = 1) = 1.833, p-val = 0.176 QM(df = 1) = 1.833, p-val = 0.176
  
 Model Results: Model Results:
  
-             estimate     se    zval   pval   ci.lb  ci.ub   +             estimate     se    zval   pval   ci.lb  ci.ub
 intrcpt        -0.467  0.257  -1.816  0.069  -0.972  0.037  . intrcpt        -0.467  0.257  -1.816  0.069  -0.972  0.037  .
-allocrandom    -0.490  0.362  -1.354  0.176  -1.199  0.219   +allocrandom    -0.490  0.362  -1.354  0.176  -1.199  0.219
  
 --- ---
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 Multivariate Meta-Analysis Model (k = 13; method: REML) Multivariate Meta-Analysis Model (k = 13; method: REML)
  
-Variance Components: +Variance Components:
  
 outer factor: trial (nlvls = 13) outer factor: trial (nlvls = 13)
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 tau^2.2    0.393  0.627      7     no  random tau^2.2    0.393  0.627      7     no  random
  
-Test for Residual Heterogeneity: +Test for Residual Heterogeneity:
 QE(df = 11) = 138.511, p-val < .001 QE(df = 11) = 138.511, p-val < .001
  
-Test of Moderators (coefficient(s) 2): +Test of Moderators (coefficient(s) 2):
 QM(df = 1) = 1.946, p-val = 0.163 QM(df = 1) = 1.946, p-val = 0.163
  
 Model Results: Model Results:
  
-             estimate     se    zval   pval   ci.lb   ci.ub   +             estimate     se    zval   pval   ci.lb   ci.ub
 intrcpt        -0.481  0.217  -2.218  0.027  -0.907  -0.056  * intrcpt        -0.481  0.217  -2.218  0.027  -0.907  -0.056  *
-allocrandom    -0.490  0.351  -1.395  0.163  -1.178   0.198   +allocrandom    -0.490  0.351  -1.395  0.163  -1.178   0.198
  
 --- ---
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 </code> </code>
 <code output> <code output>
-        df     AIC     BIC    AICc   logLik    LRT   pval       QE  +        df     AIC     BIC    AICc   logLik    LRT   pval       QE 
-Full     4 29.2959 30.8875 35.9626 -10.6480               138.5113 +Full     4 29.2959 30.8875 35.9626 -10.6480               138.5113
 Reduced  3 27.5948 28.7885 31.0234 -10.7974 0.2989 0.5845 138.5113 Reduced  3 27.5948 28.7885 31.0234 -10.7974 0.2989 0.5845 138.5113
 </code> </code>
  
 So in this example, we would not reject the null hypothesis $H_0: \tau^2_1 = \tau^2_2$ ($p = .58$). So in this example, we would not reject the null hypothesis $H_0: \tau^2_1 = \tau^2_2$ ($p = .58$).
tips/comp_two_independent_estimates.txt · Last modified: 2024/04/18 11:36 by Wolfgang Viechtbauer