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Multilevel and longitudinal modeling...

Rabe-Hesketh, S.

Multilevel and longitudinal modeling using Stata /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Multilevel and longitudinal modeling using Stata // Sophia Rabe-Hesketh, Anders Skrondal.
Author:	Rabe-Hesketh, S.
other author:	Skrondal, Anders.
Published:	College Station, Tex. :Stata Press Publication, : Ã2012.,
[NT 15000922]:	3rd ed.
Description:	2 v. (xxx, xxiii, 974 p.) :ill. ; : 24 cm.;
基督教聖經之智慧書導讀 :	"Multilevel and Longitudinal Modeling Using Stata, Third Edition, discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients nested in hospitals, or employees nested in firms. Longitudinal data are also clustered with, for instance, repeated measurements on patients or several panel waves per survey respondent. Multilevel and longitudinal modeling can exploit the richness of such data and can disentangle processes operating at different levels." "Assuming some knowledge of linear regression, this bestseller explains models and their assumptions, applies methods to real data using Stat, and shows how to interpret the results. Across volume, the 16 chapters and 144 exercises are based on the 110 datasets that span a wide range of disciplines, making the book suitable for courses in the medical, social, and behavioral sciences, and in applied statistics." "Th[e] first volume is dedicated to models for continuous responses and is a prerequisite for the second volume on models for other response types. It contains two new chapters on longitudinal data, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12." "Following volume I on models for continuous responses, th[e] second volume covers models for all other important response types: binary, ordinal, and nominal (discrete choice) responses; counts; and discrete-time and continuous-time survival (durations). It contains three new chapters, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12"--Covers.
Subject:	Multilevel models (Statistics) -
ISBN:	9781597181082 (vols. I and II:pbk.) :

Multilevel and longitudinal modeling using Stata /
Rabe-Hesketh, S.

Multilevel and longitudinal modeling using Stata /Sophia Rabe-Hesketh, Anders Skrondal. - 3rd ed. - College Station, Tex. :Stata Press Publication,Ã2012. - 2 v. (xxx, xxiii, 974 p.) :ill. ;24 cm.

Includes bibliographical references (p. [941]-953) and indexes.

v. 1. Continuous responses: -- 1. Review of linear regression -- 2. Variance-components models -- 3. Random-intercept models with covariates -- 4. Random-coefficient models -- 5. Subject-specific effects and dynamic models -- 6. Marginal models -- 7. Growth-curve models -- 8. Higher-level models with nested random effects -- 9. Crossed random effects -- Appendix. A : Useful Stata commands.

"Multilevel and Longitudinal Modeling Using Stata, Third Edition, discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients nested in hospitals, or employees nested in firms. Longitudinal data are also clustered with, for instance, repeated measurements on patients or several panel waves per survey respondent. Multilevel and longitudinal modeling can exploit the richness of such data and can disentangle processes operating at different levels." "Assuming some knowledge of linear regression, this bestseller explains models and their assumptions, applies methods to real data using Stat, and shows how to interpret the results. Across volume, the 16 chapters and 144 exercises are based on the 110 datasets that span a wide range of disciplines, making the book suitable for courses in the medical, social, and behavioral sciences, and in applied statistics." "Th[e] first volume is dedicated to models for continuous responses and is a prerequisite for the second volume on models for other response types. It contains two new chapters on longitudinal data, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12." "Following volume I on models for continuous responses, th[e] second volume covers models for all other important response types: binary, ordinal, and nominal (discrete choice) responses; counts; and discrete-time and continuous-time survival (durations). It contains three new chapters, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12"--Covers.

ISBN: 9781597181082 (vols. I and II:pbk.) :NT4640

LCCN: 2012392863Subjects--Uniform Titles:

Stata.
Subjects--Topical Terms:

254493
Multilevel models (Statistics)

LC Class. No.: QA278.6 / .R33 2012

Dewey Class. No.: 519.5/4

Multilevel and longitudinal modeling using Stata /
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504 $a Includes bibliographical references (p. [941]-953) and indexes.
505 0 # $a v. 1. Continuous responses: -- 1. Review of linear regression -- 2. Variance-components models -- 3. Random-intercept models with covariates -- 4. Random-coefficient models -- 5. Subject-specific effects and dynamic models -- 6. Marginal models -- 7. Growth-curve models -- 8. Higher-level models with nested random effects -- 9. Crossed random effects -- Appendix. A : Useful Stata commands.
505 0 # $a v. 2. Categorical responses, counts, and survival: -- 10. Dichotomous or binary responses -- 11. Ordinal responses -- 12. Nominal responses and discrete choice -- 13. Counts -- 14. Discrete-time survival -- 15. Continuous-time survival -- 16. Models with nested and crossed random effects -- Appendices. A : Syntax for gllamm, eq, and gllapred : the bare essentials ; B : Syntax for gllamm ; C : Syntax for gllapred ; D : Syntax for gllasim.
520 # $a "Multilevel and Longitudinal Modeling Using Stata, Third Edition, discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients nested in hospitals, or employees nested in firms. Longitudinal data are also clustered with, for instance, repeated measurements on patients or several panel waves per survey respondent. Multilevel and longitudinal modeling can exploit the richness of such data and can disentangle processes operating at different levels." "Assuming some knowledge of linear regression, this bestseller explains models and their assumptions, applies methods to real data using Stat, and shows how to interpret the results. Across volume, the 16 chapters and 144 exercises are based on the 110 datasets that span a wide range of disciplines, making the book suitable for courses in the medical, social, and behavioral sciences, and in applied statistics." "Th[e] first volume is dedicated to models for continuous responses and is a prerequisite for the second volume on models for other response types. It contains two new chapters on longitudinal data, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12." "Following volume I on models for continuous responses, th[e] second volume covers models for all other important response types: binary, ordinal, and nominal (discrete choice) responses; counts; and discrete-time and continuous-time survival (durations). It contains three new chapters, several new exercises and datasets, and has been thoroughly revised and updated for Stata 12"--Covers.
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