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Quasi-Least Squares Regression


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Authors:
Justine Shults and Joseph M. Hilbe
Publisher: Chapman & Hall/CRC
Copyright: 2014
ISBN-13: 978-1-4200-9993-5
Pages: 203  
Authors:
Justine Shults and Joseph M. Hilbe
Publisher: Chapman & Hall/CRC
Copyright: 2014
ISBN-13:
Pages: 203; eBook
Price: $0.00
Authors:
Justine Shults and Joseph M. Hilbe
Publisher: Chapman & Hall/CRC
Copyright: 2014
ISBN-13:
Pages: 203; Kindle
Price: $

Comment from the Stata technical group

Quasi-Least Squares Regression, by Justine Shults and Joseph M. Hilbe, is a great resource for graduate students and researchers interested in estimating population-averaged effects from longitudinal and clustered data.

The book provides an introduction to quasi-least-squares (QLS) estimators and provides many examples using the author-written Stata commands. QLS estimators extend GEE estimators to incorporate a wider set of correlation structures. The QLS estimators also allow researchers to determine the correlation structure that best fits their data.

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