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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 [2021/10/22 14:44]
Wolfgang Viechtbauer
Line 10: Line 10:
 dat <- dat.raudenbush1985 dat <- dat.raudenbush1985
 </code> </code>
-I copy the dataset into 'dat', which is a bit shorter and therefore easier to type further below.+I copy the dataset into ''dat'', which is a bit shorter and therefore easier to type further below.
  
 For illustration purposes, we will categorize the ''weeks'' variable (i.e., the number of weeks of contact prior to the expectancy induction) into three levels (0 weeks = "none", 1-9 weeks = "some", and 10+ weeks = "high"): For illustration purposes, we will categorize the ''weeks'' variable (i.e., the number of weeks of contact prior to the expectancy induction) into three levels (0 weeks = "none", 1-9 weeks = "some", and 10+ weeks = "high"):
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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  0.4020 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
Line 182: Line 182:
 </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