[R-sig-ME] Logit model in R

Phillip Alday ph||||p@@|d@y @end|ng |rom mp|@n|
Tue Oct 22 04:04:26 CEST 2019

Also, since you emphasize that you're in cognitive science, it might
make sense to take a look at the following papers, which would bring
this closer to the topic of mixed models:

Jaeger, T. F. (2008). Categorical Data Analysis: Away from ANOVAs
(Transformation or Not) and Towards Logit Mixed Models. Journal of
Memory and Language , 59 (4), 434–446. doi:10.1016/j.jml.2007.11.007

Davidson, D. J., & Martin, A. E. (2013). Modeling accuracy as a function
of response time with the generalized linear mixed effects model. Acta
Psychologica , 144 , 83–96.



On 22/10/2019 03:17, landon hurley wrote:
> Chiara,
>> I would like to ask which code i have to write in R to calculate the
>> percentage of categorial responses "Yes" or "Not" delivered for each of my
>> 15 perceptual stimuli.
> Typically the mean of a sequence of binary yes/no questions would be
> sufficient to answer this question. Take the m x n data set matrix D
> with n> 15 and apply the code
> colMeans(D[,1:15])
> to compute the mean of each column vector. The sequence 1:15 denotes the
> list sequence from the number 1 to the number 15, increasing by 1 at
> each step. If the 15 stimuli are not in sequential order, then they must
> be identified by the index sequence c(a,b,...,o) for which each letter
> is replaced by the respective column number of matrix D. Alternatively,
> the indices can be column names instead of numbers, for which each
> number must be enclosed in a separate " " quote string.
> colMeans(D[,c(a,b,...,o)])
> As a side note, you may wish to consider that since this is a mailing
> list for mixed models, it would be perhaps advisable to perhaps consider
> Stack Exchange or some other mailing list or other forum strictly
> devoted to performing basic operations in R. Also, since your email
> message has nothing to do with the implementation of a logit model in R,
> perhaps a better choice of email subject header would benefit in
> directing individuals to addressing your question.
> If you are interested in ultimately performing a regression upon a
> categorical unordered outcome measure, then I would recommend
> investigating the glm function in R, with the family operation set to
> 'binomial'.
> best,
>> Many thanks,
>> Chiara
>> 	[[alternative HTML version deleted]]
>> _______________________________________________
>> R-sig-mixed-models using r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

More information about the R-sig-mixed-models mailing list