000			01216nam a2200193 4500
003			OSt
005			20180403143435.0
008			171227b xxu||||| |||| 00| 0 eng d
020			_a9780520289291
040			_c
082			_a519.536 _bHOF
100			_aHoffmann, John P. _923885
245			_aRegression Models for Categorical, Count and Related Variables: An Applied Approach
260			_bUniversity of California Press _c2016 _aOakland
300			_a411p
500			_a1. Review of linear regression models 2. Categorical data and generalized linear models 3. Logistic and profit regression models 4. Ordered logistic and probit regression models 5. Multinomial logistic and probit regression models 6. Poisson and negative binomial regression models 7. Event history models 8. Regression models for longitudinal data 9. Multilevel regression models 10. Principal components and factor analysis 11. Appendix A : SAS, SPSS and R code for examples in chapters 12. Appendix B : using simulations to examine assumptions of OLS regression 13. Appendix C : working with missing data
600			_aRegression Analysis - Mathematical Models _924216
942			_2ddc _cLB _k519.536 _mHOF
999			_c106534 _d106534