The metafor Package

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tips:clogit_paired_binary_data

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tips:clogit_paired_binary_data [2018/01/31 20:14]
Wolfgang Viechtbauer
tips:clogit_paired_binary_data [2019/07/03 08:12] (current)
Wolfgang Viechtbauer
Line 124: Line 124:
 <code rsplus> <code rsplus>
 library(metafor) library(metafor)
-rma.glmm(measure="​OR",​ ai=ai, bi=bi, ci=ci, di=di, model="​CM.EL",​ method="​FE"​, control=list(hessianCtrl=list(r=8)))+rma.glmm(measure="​OR",​ ai=ai, bi=bi, ci=ci, di=di, model="​CM.EL",​ method="​FE"​)
 </​code>​ </​code>​
 <code output> <code output>
Line 130: Line 130:
 Model Type: Conditional Model with Exact Likelihood Model Type: Conditional Model with Exact Likelihood
  
-Tests for Heterogeneity:​  +Tests for Heterogeneity:​ 
-Wld(df = 25) =  ​0.0000, p-val = 1.0000+Wld(df = 25) =      NA, p-val = NA
 LRT(df = 25) = 32.0966, p-val = 0.1552 LRT(df = 25) = 32.0966, p-val = 0.1552
  
Line 137: Line 137:
  
 estimate ​     se    zval    pval    ci.lb   ​ci.ub ​ estimate ​     se    zval    pval    ci.lb   ​ci.ub ​
-  0.8109 ​ 0.4248  1.9088  ​0.0563 ​ -0.0218  1.6436  .+  0.8109 ​ 0.4249  1.9085  ​0.0563 ​ -0.0219  1.6437  ​. ​
  
 --- ---
 Signif. codes: ​ 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Signif. codes: ​ 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
 </​code>​ </​code>​
-To get the same SE (at least to 4 decimal places), I adjusted a setting for the computation of the Hessian.+Results again match what we obtained above.
tips/clogit_paired_binary_data.txt · Last modified: 2019/07/03 08:12 by Wolfgang Viechtbauer