Regression With Social Data

An accessible introduction to the use of regression analysis in
the social sciences

Regression with Social Data: Modeling Continuous and Limited
Response Variables represents the most complete and fully
integrated coverage of regression modeling currently available for
graduate-level behavioral science students and practitioners.
Covering techniques that span the full spectrum of levels of
measurement for both continuous and limited response variables, and
using examples taken from such disciplines as sociology,
psychology, political science, and public health, the author
succeeds in demystifying an academically rigorous subject and
making it accessible to a wider audience.

Content includes coverage of:

* Logit, probit, scobit, truncated, and censored regressions

* Multiple regression with ANOVA and ANCOVA models

* Binary and multinomial response models

* Poisson, negative binomial, and other regression models for
event-count data

* Survival analysis using multistate, multiepisode, and
interval-censored survival models

Concepts are reinforced throughout with numerous chapter
problems, exercises, and real data sets. Step-by-step solutions
plus an appendix of mathematical tutorials make even complex
problems accessible to readers with only moderate math skills. The
book's logical flow, wide applicability, and uniquely
comprehensive coverage make it both an ideal text for a variety of
graduate course settings and a useful reference for practicing
researchers in the field.