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A Meta-Analysis Package for R

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tips:multiple_factors_interactions

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tips:multiple_factors_interactions [2018/12/08 13:22]
127.0.0.1 external edit
tips:multiple_factors_interactions [2020/06/26 06:49]
Wolfgang Viechtbauer
Line 172: Line 172:
 </code> </code>
 <code output> <code output>
-     pred     se   ci.lb  ci.ub   cr.lb  cr.ub+     pred     se   ci.lb  ci.ub   pi.lb  pi.ub
 1  0.4020 0.1300  0.1472 0.6567  0.0839 0.7200 1  0.4020 0.1300  0.1472 0.6567  0.0839 0.7200
 2  0.1127 0.0804 -0.0448 0.2702 -0.1345 0.3599 2  0.1127 0.0804 -0.0448 0.2702 -0.1345 0.3599
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 </code> </code>
 <code output> <code output>
-     pred     se   ci.lb  ci.ub   cr.lb  cr.ub+     pred     se   ci.lb  ci.ub   pi.lb  pi.ub
 1  0.3509 0.1297  0.0966 0.6051  0.0332 0.6685 1  0.3509 0.1297  0.0966 0.6051  0.0332 0.6685
 2  0.0616 0.0735 -0.0824 0.2056 -0.1772 0.3004 2  0.0616 0.0735 -0.0824 0.2056 -0.1772 0.3004
 3 -0.0913 0.0857 -0.2592 0.0767 -0.3452 0.1627 3 -0.0913 0.0857 -0.2592 0.0767 -0.3452 0.1627
 </code> </code>
-Note that, by default, the intercept is automatically included in the calculation of these predicted values (so only a vector of length 3 or a matrix with 3 columns should be specified via the ''newmods'' argument). The values under ''ci.lb'' and ''ci.ub'' are the bounds of the 95% confidence intervals, while the values under ''cr.lb'' and ''cr.ub'' are the bounds of the 95% credibility/prediction intervals (see ''help(predict.rma)'' for more details).+Note that, by default, the intercept is automatically included in the calculation of these predicted values (so only a vector of length 3 or a matrix with 3 columns should be specified via the ''newmods'' argument). The values under ''ci.lb'' and ''ci.ub'' are the bounds of the 95% confidence intervals, while the values under ''pi.lb'' and ''pi.ub'' are the bounds of the 95% prediction intervals (see ''help(predict.rma)'' for more details).
  
 We can use an alternative model specification, where we leave out the model intercept: We can use an alternative model specification, where we leave out the model intercept:
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 </code> </code>
 <code output> <code output>
-     pred     se   ci.lb  ci.ub   cr.lb  cr.ub+     pred     se   ci.lb  ci.ub   pi.lb  pi.ub
 1 -0.1074 0.1134 -0.3296 0.1148 -0.4751 0.2602 1 -0.1074 0.1134 -0.3296 0.1148 -0.4751 0.2602
 </code> </code>
tips/multiple_factors_interactions.txt ยท Last modified: 2021/11/10 20:20 by Wolfgang Viechtbauer