Linear probability, logit, and probit models /
After showing why ordinary regression analysis is not appropriate for investigating dichotomous or otherwise 'limited' dependent variables, this volume examines three techniques which are well suited for such data. It reviews the linear probability model and discusses alternative specifica...
| Основен автор: | Aldrich, John H., 1947- |
|---|---|
| Други автори: | Nelson, Forrest D. |
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
Beverly Hills :
Sage Publications,
℗♭1984.
|
| Серия: |
Quantitative applications in the social sciences ;
no. 07-045. |
| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=24734 |
| Подобни документи: |
Print version::
Linear probability, logit, and probit models. |
Съдържание:
- The linear probability model
- Specification of nonlinear probability models
- Estimation of probit and logit models for dichotomous dependent variables
- Minimum chi-square estimation and polytomous models
- Minimum chi-square estimation and polytomous models
- Summary and extensions.