Linear mixed model - heterogeneity (Etn bot)

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Message: 1
Date: Fri, 23 Oct 2015 15:15:45 +0100
From: Etn bot <etnbot1 at gmail.com>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Linear mixed model - heterogeneity
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	<CAF79uvkRGaWXkzjPz9grTRhdQSVcqUmLrB+5QWUNS76JJLwmYg at mail.gmail.com>
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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