[R-sig-ME] Effect sizes for mixed-effects models

Schäfer, L. (Lena) |@@ch@|er @end|ng |rom @tudent@ru@n|
Fri Oct 11 17:45:18 CEST 2019

Hi Phillip, 

Thank you for your response; this was very helpful. The studies analyzed using mixed-effects models have a minimum of 24 participants. Setting the degrees of freedom equal to infinity (i.e., Cohen’s d = Hedge’s g) seems to be justifiable in that case. 


> Am 11.10.2019 um 02:05 schrieb Phillip Alday <phillip.alday using mpi.nl>:
> On 10/10/2019 23:41, Schäfer, L. (Lena) wrote:
>> We are uncertain how to best estimate the dfs in our mixed-models. We considered using Kenward-Roger approximated dfs but this does not seem feasible since we only have access to parts of the raw data-sets used to derive dw and V{dw}.
> You have 30-60 observations per participant, but how many participants?
> If it's the typical 20+ in psychology, I would use the easiest
> approximation of all for denominator degrees of freedom: treat them as
> infinite, i.e. treat the t values as z values. The Kenward-Roger
> approximation really doesn't really change your results for non trivial
> datasets and the implementation in R (in pbkrtest, which lmerTest and
> car::Anova() use internally) computes a matrix inverse for an n x n
> matrix, where n is the total number of observations. This is
> computationally painful for non trivial n with minimal benefit.
> Best (from next door at the MPI),
> Phillip

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