Interpreting and Visualizing Regression Models Using Stata

Event History Analysis With Stata Provides An Introduction To Event History Modeling Techniques Using Stata (version 9), A Widely Used Statistical Program That Provides Tools For Data Analysis. The Book Emphasizes The Usefulness Of Event History Models For Causal Analysis In The Social Sciences And The Application Of Continuous-time Models. The Authors Illustrate The Entire Research Path Required In The Application Of Event-history Analysis, From The Initial Problems Of Recording Event-oriented Data, To Data Organization, To Applications Using The Software, To The Interpretation Of Results.the Book Also Demonstrates, Through Example, How To Implement Hypotheses Tests And How To Choose The Right Model. The Strengths And Limitations Of Various Techniques Are Emphasized In Each Example, Along With An Introduction To The Model, Details On How To Input Data, And The Related Stata Commands. Each Application Is Accompanied By A Brief Explanation Of The Underlying Statistical Concept. Readers Are Offered The Unique Opportunity To Easily Run And Modify All Of The Book's Application Examples On A Computer, By Visiting The Author's Web Site And Includes Survival Rates Of Patients In Medical Studies; Unemployment Periods In Economic Studies; And The Time It Takes A Criminal To Break The Law After His Release In A Criminological Study.this New Book Supplements Event History Analysis, By Blossfeld Et Al, And Techniques Of Event History Modeling, By Blossfeld And Rohwer, Extending On Their Coverage Of Practical Applications And Statistical Theory. Intended For Researchers In A Variety Of Fields Such As Statistics, Economics, Psychology, Sociology, And Political Science, Event History Analysis With Stata Also Serves As A Text, In Combination With The Authors' Other Two Books, For Courses On Event History Analysis.-- Continuous Predictors: Linear -- Continuous Predictors: Polynomials -- Continuous Predictors: Piecewise Models -- Continuous By Continuous Interactions -- Continuous By Continuous By Continuous Interactions -- Categorical Predictors -- Categorical By Categorical Interactions -- Categorical By Categorical By Categorical Interactions -- Linear By Categorical Interactions -- Polynomial By Categorical Interactions -- Piecewise By Categorical Interactions -- Continuous By Continuous By Categorical Interactions -- Continuous By Categorical By Categorical Interactions -- Multilevel Models -- Time As A Continuous Predictor -- Time As A Categorical Predictor -- Nonlinear Models -- Complex Survey Data. Michael N. Mitchell. A Stata Press Publication. Includes Bibliographical References (p. [545]-547) And Indexes.