Event History Analysis
Four Volume Set
Edited by:
- Lawrence Wu - University of Wisconsin - Madison, USA
November 2011 | 1 656 pages | SAGE Publications Ltd
Event history analysis is an umbrella term for a set of procedures for time series analysis. Event history models focus on the hazard function, which has to do with the probabilities that an event will occur after any given duration. Duration to the hazard of death was the classic example in medical research, but the hazard may have a positive meaning also, such as duration until the event of adoption of an innovation in diffusion research
Over the last two decades, event-history analysis has emerged as a mature analytical tool in the social sciences. This four-volume edited collection consists of a) classic papers that have been key in determining or explicating various subareas of event history analysis, and b) high quality applications that demonstrate the utility of event history analysis, drawn from a wide range of substantive areas.
VOLUME 1
Overviews
Lawrence Wu
Nonparametric Estimation: Theory
E.L. Kaplan and Paul Meier
Wayne Nelson
Odd Aalen
Jan Hoem
Lawrence Wu
Nonparametric Estimation: Applications
Samuel Preston and John McDonald
Mary Jo Bane and David Ellwood
Larry Bumpass and Hsien-Hen Lu
Lawrence Wu
The Cox Model: Theory
D. R. Cox
Richard Gill
The Cox Model: Applications
Thomas DiPrete
Robert Michael and Nancy Brandon Tuma
Parametric Models: Theory
Benjamin Gompertz
Ansley Coale and Donald McNeil
Gudmund Hernes
Andreas Diekmann and Peter Mitter
VOLUME 2
Parametric Models: Applications
Neil Bennett, David Bloom and Patricia Craig
Andreas Diekman and Henriette Engelhardt
Lauren Edelman
Diane Felmlee and Donna Eder
John Freeman, Glenn Carroll and Michael Hannan
Michael Hannan, Nancy Brandon Tuma and Lyle Groeneveld
Steven Martin
Nancy Brandon Tuma
Christopher Uggen
Time-Varying Covariates: Applications
William Axinn and Scott Yabiku
Julie Brines and Kara Joyner
Daniel Myers
Martin Nystrand, Lawrence Wu, Adam Gamoran, Susie Zeiser and Daniel Long
Lawrence Wu and Brian Martinson
Lawrence Wu
VOLUME 3
Discrete-Time Models: Theory
Paul Allison
Robert Mare
Discrete-Time Models: Applications
William Axinn and Arland Thornton
Megan Sweeney
Jui-Chung Allen Li and Lawrence Wu
Robert Hauser and Megan Andrew
Unobserved Heterogeneity: Theory
James Vaupel and Anatoli Yashin
James Heckman and Burton Singer
Gary Chamberlain
Lee Lillard
J.W. Vaupel
Unobserved Heterogeneity: Applications
Michael Brien, Lee Lillard and Linda Waite
James Heckman and George Borjas
James Heckman, V. Joseph Hotz and James Walker
VOLUME 4
Competing Risks: Theory
A Tsiatis
James Heckman and Bo Honoré
Competing Risks: Applications
Kazuo Yamaguchi and Denise Kandel
Alberto Palloni, Douglas Massey, Miguel Ceballos, Kristin Espinosa and Michael Spittel
Nonproportionalmodels
Lawrence Wu and Nancy Brandon Tuma
Yu Xie
Gang Li and Hani Doss
Elwood Carlson, Jan Hoem and Jitka Rychtarikova
Left Truncation and Left Censoring
Alfred Hamerle
Geert Ridder
Models for Clustered, Sequential, and Diffusion Processes
Guang Guo and German Rodriguez
Mark Hill
Narayan Sastry
David Strang and Nancy Brandon Tuma
Lawrence Wu and Steven Martin