[R-sig-ME] Logit model in R
Chiara Fini
ch|@r@||n| @end|ng |rom gm@||@com
Tue Oct 22 09:02:39 CEST 2019
Thanks a lot for the helpful hints,
Chiara
Il giorno mar 22 ott 2019 alle ore 04:05 Phillip Alday <phillip.alday using mpi.nl>
ha scritto:
> 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.
>
> Best,
>
> Phillip
>
> 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
> >>
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> >>
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>
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