## Regression Models for Categorical and Limited Dependent VariablesA unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible. |

### What people are saying - Write a review

User Review - Flag as inappropriate

p.24

### Contents

Introduction | 1 |

The Linear Regression Model | 11 |

The Linear Probability Probit and Logit | 34 |

Hypothesis Testing and Goodness of Fit | 85 |

Ordered Logit and Ordered Probit Analysis | 114 |

Multinomial Logit and Related Models | 148 |

mial Logit Model With Three Outcomes | 174 |

The Tobit Model | 187 |

Regression Models for Counts | 217 |

Conclusions | 251 |

A Answers to Exercises | 264 |

274 | |

Author Index | 283 |

About the Author | 297 |

### Common terms and phrases

analysis assume assumption binary logit binomial regression model censored observations change in xk Chapter CLDVs computed conditional mean conditional variance consider constraints count models dependent discrete change dummy variables equal errors example exp(xp expected count expected value factor change Figure fully standardized given independent variables intercept interpreted Labor Force Participation latent variable likelihood function linear regression linear regression model log likelihood log-linear models logit and probit LR test marginal effect methods ML estimator MNLM multinomial logit model NBRM negative binomial regression nonlinear normal distribution odds ratio ordered logit ordered logit model ordered probit ordinal overdispersion Panel parallel regression parameters partial derivative Poisson distribution Poisson regression Poisson regression model Pr(y predicted probability prestige scientist slope standard deviation standardized coefficient statistic Table tobit truncated regression model uncensored unit change unstandardized variables constant versus Wald test zero counts ZINB