[R-sig-ME] Linear mixed model - heterogeneity

[Etn bot]

Many thanks Ben, I will try this approach



On 2 November 2015 at 22:11, Ben Bolker <bbolker at gmail.com> wrote:

>   If you have 5 reps per patient, unless those reps vary in some
> interesting way or they have structure you need to know about (e.g.
> you're trying to estimate slope of improvement over time, or
> patient/rep instances having differing values of covariates you need
> to adjust for), it would definitely help to just aggregate (i.e., take
> the mean over reps: see Murtauch "Simplicity and complexity in
> ecological data analysis") ...
>
> On Mon, Nov 2, 2015 at 5:58 AM, Etn bot <etnbot1 at gmail.com> wrote:
> > @Ben many thanks or your response - with reference to the source of the
> > zeros - the clinical data: patients force is recorded using a machine,
> this
> > force reading is recorded 5 times for each patient at each time point (4
> > different visiting times). Sometimes the machine has a reading of zero
> (for
> > all 5 reps) and other times it has a zero reading for e.g. 1st rep, 3rd
> rep.
> > If there is a full zero reading (for all 5 reps at each of the four time
> > points), this is due to the patient having no force (true reading and
> this
> > does not happen very often in the data). If there is zero reading (for
> some
> > of the 5 reps) then this could be due to the patient not having ability
> to
> > consistently push hard enough for that reading and the machine recorded
> > zero.
> >
> > On 30 October 2015 at 01:10, Ben Bolker <bbolker at gmail.com> wrote:
> >>
> >> lme4 will run Gamma mixed models, but these don't accomodate zeros.  I
> >> don't think Weibull will either.  You're also right that
> >> transformation won't generally solve these problems. There are very
> >> few positive distributions, not considering censored variants of
> >> real-valued distributions, that will naively allow zeros.   You could
> >> run a two-stage model (Bernoulli model for zero vs non-zero, then a
> >> positive-distribution model for the conditional effects on the
> >> non-zero values only).
> >>
> >> The cplm package allows tweedie mixed models, which might work for
> >> you. AD Model Builder and Template Model Builder will allow you to fit
> >> fixed models from any distribution you can specify (with a generic
> >> Laplace approximation engine built in), but the learning curve is
> >> pretty steep ...
> >>
> >> It's important in this case to consider the source of your zeros.  Are
> >> they below minimal detection limits (in which case something like a
> >> Tobit is appropriate)?  Do they represent a separate process (in which
> >> case two-stage models are sensible)? Or ... ?
> >>
> >> On Fri, Oct 23, 2015 at 10:15 AM, Etn bot <etnbot1 at gmail.com> wrote:
> >> > I have a run a linear mixed effects model in R to model clinical data,
> >> > however this model is heteroscedastic (as there excess zeros in the
> >> > response variable)....
> >> >
> >> > I have tried transforming the data (log transform) and (sqrt), however
> >> > neither transformation resolve the issue (see residual versus fitted
> >> > value
> >> > plot). I have not used cox proportional hazards model as the data is
> not
> >> > time-to-event data, the data measures force and there are a large
> number
> >> > of
> >> > observations have a reading of zero. I cannot exclude these readings
> as
> >> > they are valid.
> >> >
> >> > I have found a R package that runs Tobit regression (AER), however
> this
> >> > will not accommodate the random effects in the model. I cannot find
> any
> >> > R
> >> > packages that run Weibull mixed effects models (or gamma mixed effects
> >> > models)...
> >> >
> >> > Does anyone know if there is a package to run these type of models?
> (or
> >> > can
> >> > they suggest any alternative approach).
> >> >
> >> > Many thanks
> >> >
> >> >
> >> > Etn
> >> >
> >> >         [[alternative HTML version deleted]]
> >> >
> >> > _______________________________________________
> >> > R-sig-mixed-models at r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> >
>

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