[R-sig-ME] help with the logistic formula using nlme/nlmer

[Phillip Alday]

See for example the gamm4 package (which hooks into and extends the lme4
formula syntax). Instead of I(...), you would have s(...)

Best,

Phillip Alday

On Mon, 2015-06-08 at 15:37 +0200, Thierry Onkelinx wrote:
> Dear Hans,
> 
> I'd rather use a gamm with a penalized regression spline for
> total.hours.worked with a small basis for the smoother (k = 3 of k = 4).
> 
> Best regards,
> 
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> 
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
> 
> 2015-06-08 15:07 GMT+02:00 Hans Ekbrand <hans.ekbrand at gmail.com>:
> 
> > Dear list,
> >
> > I model the effect of child labour on the childs probability of being
> > in school. The data comes from 22 countries. Countries have different
> > means on the outcome variable, ie. the probability is in school is to
> > a large part determined on in which country the child resides. The
> > sample includes only children aged 7-14 years.
> >
> > Child labour is a numerical covariate measured in hours, being in
> > school is binary variable, age is a numerical covariate, measured in
> > years.
> >
> > Data is available here: http://hansekbrand.se/code/cl.df.RData
> >
> > > str(cl.df)
> > 'data.frame':   345321 obs. of  8 variables:
> >  $ country           : Factor w/ 23 levels "Armenia","Burkina Faso",..: 1
> > 1 1 1 1 1 1 1 1 1 ...
> >  $ areaID            : Factor w/ 14584 levels "Armenia.1","Armenia.10",..:
> > 3 3 3 3 3 3 2 2 2 2 ...
> >  $ school            : Factor w/ 2 levels "No","Yes": 2 2 2 2 2 2 2 2 2 2
> > ...
> >  $ age               : num  9 10 8 11 14 10 12 10 14 12 ...
> >  $ total.hours.worked: num  1 1 1 0 1 0 0 0 0 0 ...
> >  $ Chorehours        : num  1 1 1 0 1 0 0 0 0 0 ...
> >  $ Chwkhours         : num  0 0 0 0 0 0 0 0 0 0 ...
> >  $ Chothwkhours      : num  0 0 0 0 0 0 0 0 0 0 ...
> >
> > The distribution of child labour, which is indicated by the variable
> > total.hours.worked, has a positive skew.
> >
> > > quantile(cl.df$total.hours.worked, probs = seq(from = 0, to = 1, by =
> > 0.1))
> >   0%  10%  20%  30%  40%  50%  60%  70%  80%  90% 100%
> >    0    0    0    0    3    5    7   10   14   28  133
> >
> > I have manually defined classes for this variable,
> >
> > library(car)
> > cl.df$hours.class <- recode(cl.df$total.hours.worked, recodes = ("lo:7=1;
> >  7:14=2; 14:21=3; 21:28=4; 28:35=5; 35:42=6; 42:49=7; 49:56=8; 56:63=9;
> >  63:hi='more than ten'"), as.factor.result=TRUE)
> >
> > and used them like this:
> >
> > fm1 <- glmer(school ~ age + hours.class + (1|country) + (1|areaID), data =
> > cl.df, family = binomial)
> >
> > this works, but I would prefer to fit a non-linear regression with a
> > polynomal form instead. I think a simple exponential function would
> > work.
> >
> > E.g.
> >
> > fm1 <- glmer(school ~ age + I(total.hours.worked^2) + (1|country) +
> > (1|areaID), data = cl.df, family = binomial)
> >
> > However, I *think* nlmer() could be used to find the optimal number
> > instead of "2" here. But I don't know how to do that. I have searched
> > the archive, but found rather few posts concerning nlmer(), so any
> > help is much appreciated.
> >
> > If you can solve the problem with nlme() or anything else for that
> > matter, that's perfectly fine, I'm used to lme4, but I'm happy to
> > learn new stuff.
> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> 
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