[R-sig-ME] zero-truncated mixed effects logistic regression?

[David Duffy]

On Tue, 17 Jan 2012, Martin Schmettow wrote:

> The problem I have is similar to the capture-recapture approach for
> estimating abundance. In my case the captured animals are design flaws of
> software.
>
> A given number of testers independently tries to find these flaws, which
> makes it a binomial problem. However, flaws that were never discovered
> during the study are not known to the experimenter.

> Furthermore this is a crossed mixed-effects 
> situation as
> discovery trials are repeated over testers and flaws.
>
> (1)    Does effectiveness of testers increases with years of experience?
> (2)    Are certain classes of flaws easier to find than others?
>
> A general finding of previous research is that testers as well as flaws are
> heterogeneous. Some flaws are less visible than others and testers differ in
> overall effectiveness. Hence, random effects are needed to account for
> overdispersion, right?

I may be corrected, but I think your setup is "actually" a Rasch type 
model with each flaw being an item.  Some flaws are just too difficult to 
see, ie the item is "too hard".  I presume, given your research questions, 
you are not actually interested in estimating the number of undetected 
flaws from each class, so a missing data type setup is not really needed.

http://www.jstatsoft.org/v20/a02/paper

is one paper from our esteemed leader ;)

-- 
| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
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