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Handbook for applied modeling :non-g...

Lalonde, Trent.

Handbook for applied modeling :non-gaussian and correlated data /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Handbook for applied modeling :Jamie D. Riggs, Trent L. Lalonde.
Reminder of title:	non-gaussian and correlated data /
Author:	Riggs, Jamie.
other author:	Lalonde, Trent.
Published:	Cambridge, United Kingdom ;Cambridge University Press,c2017.
Description:	xv, 216 p. :ill. ;26 cm
Subject:	Gaussian processes.
ISBN:	9781316601051 (pbk.) :

Handbook for applied modeling :non-gaussian and correlated data /
Riggs, Jamie.

Handbook for applied modeling :non-gaussian and correlated data /Jamie D. Riggs, Trent L. Lalonde. - Cambridge, United Kingdom ;Cambridge University Press,c2017. - xv, 216 p. :ill. ;26 cm

Includes bibliographical references (p. 211-212) and index.

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for their own data analysis needs. --

ISBN: 9781316601051 (pbk.) :NT$ 1036

LCCN: 2017004641Subjects--Topical Terms:

211434
Gaussian processes.

LC Class. No.: QA276 / .R569 2017

Dewey Class. No.: 519.5/3

Handbook for applied modeling :non-gaussian and correlated data /
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245 1 0 $a Handbook for applied modeling : $b non-gaussian and correlated data / $c Jamie D. Riggs, Trent L. Lalonde.
260 $a Cambridge, United Kingdom ; $a New York, NY : $b Cambridge University Press, $c c2017.
300 $a xv, 216 p. : $b ill. ; $c 26 cm
504 $a Includes bibliographical references (p. 211-212) and index.
520 $a Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating more advanced modeling techniques. This Handbook presents clearly explained modeling options for such situations, along with extensive example data analyses. The book explains core models such as logistic regression, count regression, longitudinal regression, survival analysis, and structural equation modelling without relying on mathematical derivations. All data analyses are performed on real and publicly available data sets, which are revisited multiple times to show differing results using various modeling options. Common pitfalls, data issues, and interpretation of model results are also addressed. Programs in both R and SAS are made available for all results presented in the text so that readers can emulate and adapt analyses for their own data analysis needs. -- $c Provided by publisher.
650 0 $a Gaussian processes. $3 211434
650 0 $a Mathematical models. $3 182479
650 0 $a Mathematical statistics. $3 181877
650 0 $a Stochastic processes. $3 181874
700 1 $a Lalonde, Trent. $3 796781