Regression with a Binary Dependent Variable - Chapter 9

I Ordered Responses, e.g., completed educational credentials. Ordered logit or probit. I Discrete Choice Data, e.g., mode of travel. Characteristics of choice, chooser, and interaction. Multinomial logit or probit, I Can sometimes convert to several binary problems. I Censored and Truncated Regression Models. Tobit or sample selection models.

  Model, Logit, Ordered, Ordered logit

Title stata.com mlogit — Multinomial (polytomous) logistic ...

If the outcomes are ordered, see[R] ologit. Description of the model For an introduction to multinomial logit models, seeGreene(2012, 763–766),Hosmer, Lemeshow,

  Model, Logit, Ordered, Logit model

CHAPTER 3 EXAMPLES: REGRESSION AND PATH ANALYSIS

models are used. Logistic regression for ordered categorical dependent variables uses the proportional odds specification. For unordered categorical dependent variables, multinomial logistic regression models are used. For count dependent variables, Poisson regression models are used, with or without inflation at the zero point.

  Analysis, Model, Chapter, Example, Regression, Path, Ordered, Chapter 3 examples, Regression and path analysis

[FMM] Finite Mixture Models - Stata

Title fmm intro — Introduction to finite mixture models DescriptionRemarks and examplesAcknowledgment ReferencesAlso see Description Finite mixture models (FMMs) are used to classify observations, to adjust for clustering, and tomodel unobserved heterogeneity.

  Model

The Effects of Class Size on Student Performance and ...

The Effects of Class Size on Student Performance and Retention at Binghamton University Abstract New York, like many other states, has had a call to increase faculty productivity.