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RE: st: beta regression


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: beta regression
Date   Tue, 25 Oct 2011 23:47:02 -0400

Yes, you can compute odds ratios if you are using the logit link.
Zhao, L., Chen, Y., & Schaffner, D.W. (2001). Comparison of Logistic Regression and Linear Regression in Modeling Percentage Data. Applied and Environmental Microbiology, 67(5), 2129–2135. http://foodsci.rutgers.edu/schaffner/pdf%20files/Zhao%20AEM%202001.pdf
Kieschnick, R., & McCullough, B.D. (2003). Regression analysis of variates observed on (0,1): percentages, proportions and fractions. Statistical Modelling, 3, 193-213. http://www.pages.drexel.edu/~bdm25/statmodelling.pdf
Rocha, A.V., & Simas, A.B. (2010). Influence diagnostics in a general class of beta regression models. TEST, 20(1), 95-119.
Paolino, P. (2001). Maximum likelihood estimation of models with beta-distributed dependent variables. Political Analysis, 9(4), 325-346.http://polmeth.wustl.edu/analysis/vol/9/WV008-Paolino.pdf
Smithson, M., & Verkuilen, J. (2006). A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables. Psychological Methods, 11(1), 54-71.  http://web.gc.cuny.edu/content/edpsychology/documents/Smithson%20and%20Verkuilen%202006.pdfSee SAS code at:http://psychology3.anu.edu.au/people/smithson/details/betareg/SAS_beta_regression.sas
Ferrari, S.L.P., & Cribari-Neto, F. (2004). Beta regression for modelling rates and proportions. Journal of Applied Statistics, 31(7), 799-815.
Cam


> Date: Tue, 25 Oct 2011 23:33:14 -0400
> Subject: st: beta regression
> From: lsj555@gmail.com
> To: statalist@hsphsun2.harvard.edu
> 
> Hi, I have a question about interpreting beta regression for
> proportion/ratio outcomes. Do we need to exponentiate the estimated
> coefficients, and interpret the exp(B) as changes in odds ratio (of
> having what value?) or as changes in the outcome measured as
> proportion/ratio?
> 
> For the estimated value in the margins in the post-estimation
> function, do we interpret the ouptut as the predicted proportion or
> probability? Thank you.
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