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Re: st: Predictions and psuedo Rsq in zoib


From   Prerna S <maruiprerna@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Predictions and psuedo Rsq in zoib
Date   Sun, 25 Sep 2011 19:13:04 -0400

Thanks for reference, Cam.

Prerna

On 24 September 2011 22:00, Cameron McIntosh <cnm100@hotmail.com> wrote:
> Prerna,
>
> Perhaps you might consider some of the likelihood-based pseudo-explained variance measures instead. See for example:
> DeMaris, A. (2002). Explained Variance in Logistic Regression: A Monte Carlo Study of Proposed Measures. Sociological Methods & Research, 31(1), 27-74.http://gabarrot.psychologie-sociale.org/documents/DM2002.pdf
> Cam
>
>> From: maruiprerna@gmail.com
>> Date: Sat, 24 Sep 2011 07:38:35 -0400
>> Subject: st: Predictions and psuedo Rsq in zoib
>> To: statalist@hsphsun2.harvard.edu
>>
>> Hello Statalisters,
>>
>> I have estimated the following equation:
>>
>> zoib y1 x1 x2, zeroinflate (x1 x2) cluster (z) nolog
>> zoib y2 x1 x2 zeroinflate (x1 x2) cluster (z) nolog
>>
>> where yi = income from various sources and z = geographical location
>> (city dummies).
>>
>> I would like to calculate the pseudo-R squares.
>>
>> Thus I specified the following:
>>
>> predict y1_pred
>>
>> Stata responded with:
>>
>> (option pr assumed)
>>
>> I think I am okay with this because I just want to get a sense of the
>> global measure of explained variance as Ferrari and Cribari-Neto (
>> 2004) suggest for beta regression. I'm assuming that a similar method
>> on zoib is not so bad.
>>
>> However, on running a correlation, I get a correlation of -0.5. Why
>> would the correlation be negative!?! I used the command below.
>>
>> correlate y1 y1_pred
>>
>> On the other hand,
>>
>> correlate y2 y2_pred
>>
>> gives me a positive correlation.
>>
>> Am I misinterpreting the result or is this an incorrect way to
>> ascertain Rsquares for an inflated beta regression?
>>
>> I am using Stata 11.2. I installed zoib from ssc.
>>
>> Ferrai, S., & Cribari-Neto, F. (2004). Beta Regression for Modelling
>> Rates and Proportions. Jl. of Applied Statistics. Vol. 31, No. 7,
>> 799-815.
>>
>> Thanks.
>>
>> Prerna
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