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--- news:news [2021/04/25 19:32] – Wolfgang Viechtbauer
+++ news:news [2021/04/25 19:32] – Wolfgang Viechtbauer
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 ~~NOTOC~~
-==== April 25th, 2021: Better Degrees of Freedom Calculation ====
+==== April 21st, 2021: Better Degrees of Freedom Calculation ====
 In random/mixed-effects models as can be fitted with the [[https://wviechtb.github.io/metafor/reference/rma.html|rma()]] function, tests and confidence intervals for the model coefficients are by default constructed based on a standard normal distribution.((In a random-effects model, there is just one coefficient, namely $\hat{\mu}$, the estimated average true outcome.)) In general, it is better to use the Knapp-Hartung method for this purpose, which does two things: (1) the standard errors of the model coefficients are estimated in a slightly different way and (2) a t-distribution is used with $k-p$ degrees of freedom (where $k$ is the total number of estimates and $p$ the number of coefficients in the model). When conducting a simultaneous (or 'omnibus') test of multiple coefficients, then an F-distribution with $m$ and $k-p$ degrees of freedom is used (for the 'numerator' and 'denominator' degrees of freedom, respectively), with $m$ denoting the number of coefficients tested. To use this method, set argument ''test="knha"''.