What techniques can social scientists use when an outcome variable for a sample is not representative of the population for whom they would like to generalize the results? This book provides an introduction to regression ...

Buy Now From Amazon

Product Review

What techniques can social scientists use when an outcome variable for a sample is not representative of the population for whom they would like to generalize the results? This book provides an introduction to regression models for such data including censored, sample-selected and truncated data.



Similar Products

Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models (Quantitative Applications in the Social Sciences)Logistic Regression: A Primer (Quantitative Applications in the Social Sciences)Regression with Dummy Variables (Quantitative Applications in the Social Sciences)Mostly Harmless Econometrics: An Empiricist's CompanionFixed Effects Regression Models (Quantitative Applications in the Social Sciences)Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences)Multilevel Modeling (Quantitative Applications in the Social Sciences)Interaction Effects in Logistic Regression (Quantitative Applications in the Social Sciences)Regression Models for Categorical Dependent Variables Using Stata, Third EditionUnderstanding Regression Assumptions (Quantitative Applications in the Social Sciences)