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Re: st: multinomial multilevel analysis in Stata
From
Rosie Chen <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: multinomial multilevel analysis in Stata
Date
Fri, 14 Oct 2011 11:18:59 -0700 (PDT)
Thank you, Maarten. If I keep the outcome variable as a continuous variable, what would be a better way? 1. to treat it as it is, 2. log of the outcome, since its' distribution is skewed. But what to do with it since there are lot of cases have zero value for the outcome? 3. standardize the outcome.
Any thoughts would be appreciated.
Rosie
----- Original Message -----
From: Maarten Buis <[email protected]>
To: [email protected]
Cc:
Sent: Friday, October 14, 2011 11:42 AM
Subject: Re: st: multinomial multilevel analysis in Stata
On Fri, Oct 14, 2011 at 5:22 PM, Rosie Chen <[email protected]> wrote:
> (1) For example, suppose the outcome variable measures the percentage of budget purchasing luxurious items within a person's monthly salary, and it is on a continuous scale. I can recode it into a three-category variable, 1 indicating no purchase at all, 2 indicating larger than zero but smaller than 20%, and 3 indicating 20% or more. Should I treat it as an ordinal outcome or multinomial outcome?
You should not recode it at all but model the continuous variable as
is. With recoding you just loose information and loosing information
is bad.
> (3) Do I need to include weighting variable for each level of data, if there are 3 levels in the model? It seems to me to be common to use level 1 weights, but I haven't seen a lot of studies using weights for all levels.
I believe you can do so with -gllamm-.
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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