Version info: Code for this page was tested in Stata 12. As the name implies, multivariate regression is a technique that estimates a single regression model with more than one…
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Version info: Code for this page was tested in Stata 12. Negative binomial regression is for modeling count variables, usually for over-dispersed count outcome variables. Please note: The purpose of…
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Version info: Code for this page was tested in Stata 12. Examples of ordered logistic regression Example 1:  A marketing research firm wants to investigate what factors influence the size…
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Unless you specify otherwise, Stata estimation commands assume that your observations were sampled from the population using Simple Random Sampling. If this is true, you can use standard Stata commands…
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Many Stata estimation commands support alternative ways of estimating standard errors. Three common methods are 1) robust standard errors (not to be confused with robust regression), 2) bootstrap standard errors,…
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Version info: Code for this page was tested in Stata 12. Poisson regression is used to model count variables. Please note: The purpose of this page is to show how…
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Introduction Power analysis is the name given to the process for determining the sample size for a research study. The technical definition of power is that it is the probability…
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Version info: Code for this page was tested in Stata 12. Probit regression, also called a probit model, is used to model dichotomous or binary outcome variables. In the probit…
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Introduction Power analysis is the name given to the process for determining the sample size for a research study. The technical definition of power is that it is the probability…
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Version info: Code for this page was tested in Stata 12. Robust regression is an alternative to least squares regression when  data is contaminated with outliers or influential observations and…
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