--- tom albrecht <[email protected]> wrote:
> The observations in my data are comparable to job applications. There
> are several different jobs and one group of applications for each
> job. From these competing applications one is picked for the job.
>
> Now I want to determine, which characteristics of an application have
> a significant influence on the probability that the application is
> getting picked - across all jobs.
>
> So I considered a logit or probit model with robust standard errors
> clustering on job level as well as including random-effects or
> fixed-effects for the jobs.
>
> My problem is: how do I correct for the differences of the
> characteristics between jobs?
>
> Let's say one characteristic is that people ask for a desired income
> in their application. So I have jobs where applicants ask for an
> income of 1000$ on average and groups where they ask for $ 1 million.
> Could I just calculate the income asked for relative to the group
> average or should apply a z-transformation? Are there standard
> procedures for this case or more advanced models?
If I understant correctly you have several person choose between
several jobs, and you want to control for characteristics of the person
and of the job. This sounds to me like a problem for -clogit-.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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