Fixed Effects Regression Methods for Longitudinal Data Using SAS

Author:   Paul D. Allison (University of Pennsylvania, Philadelphia)
Publisher:   SAS Publishing
ISBN:  

9781590475683


Pages:   160
Publication Date:   05 March 2005
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Fixed Effects Regression Methods for Longitudinal Data Using SAS


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Overview

Fixed Effects Regression Methods for Longitudinal Data Using SAS, written by Paul Allison, is an invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques. First introduced by economists, fixed effects methods are gaining widespread use throughout the social sciences. Designed to eliminate major biases from regression models with multiple observations (usually longitudinal) for each subject (usually a person), fixed effects methods essentially offer control for all stable characteristics of the subjects, even characteristics that are difficult or impossible to measure. This straightforward and thorough text shows you how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. The theoretical background of each model is explained, and the models are then illustrated with detailed examples using real data. The book contains thorough discussions of the following uses of SAS procedures: PROC GLM for estimating fixed effects linear models for quantitative outcomes, PROC LOGISTIC for estimating fixed effects logistic regression models, PROC PHREG for estimating fixed effects Cox regression models for repeated event data, PROC GENMOD for estimating fixed effects Poisson regression models for count data, and PROC CALIS for estimating fixed effects structural equation models. To gain the most benefit from this book, readers should be familiar with multiple linear regression, have practical experience using multiple regression on real data, and be comfortable interpreting the output from a regression analysis. An understanding of logistic regression and Poisson regression is a plus. Some experience with SAS is helpful, but not required.

Full Product Details

Author:   Paul D. Allison (University of Pennsylvania, Philadelphia)
Publisher:   SAS Publishing
Imprint:   SAS Publishing
Dimensions:   Width: 21.00cm , Height: 0.80cm , Length: 28.00cm
Weight:   0.376kg
ISBN:  

9781590475683


ISBN 10:   1590475682
Pages:   160
Publication Date:   05 March 2005
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

Allison has done a remarkable job in distilling a vast literature on the analysis of panel data, including continuous and categorical outcomes. For those familiar with these models, Allison provides an invaluable guide to using SAS to estimate these models. For those just beginning to use panel models, Allison provides a sophisticated yet accessible guide to understanding the key issues in the analysis of panel data. Even though the focus is on fixed effects models, the book provides detailed information on random coefficient models as well.


Author Information

Paul D. Allison is Professor of Sociology at the University of Pennsylvania, and President of Statistical Horizons LLC. He is the author of

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