Transcription of glm — Generalized linear models - Stata
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glm — Generalized linear models - Stata
Title glm Generalized linear models Description Quick start Menu Syntax Options Remarks and examples Stored results Methods and formulas Acknowledgments References Also see Description glm fits Generalized linear models . It can fit models by using either IRLS (maximum quasilikelihood). or Newton Raphson (maximum likelihood) optimization, which is the default. See [U] 27 Overview of Stata estimation commands for a description of all of Stata 's estimation commands, several of which fit models that can also be fit using glm. Quick start model of y as a function of x when y is a proportion glm y x, family(binomial). Logit model of y events occurring in 15 trials as a function of x glm y x, family(binomial 15) link(logit). Probit model of y events as a function of x using grouped data with group sizes n glm y x, family(binomial n) link(probit). model of discrete y with user-defined family myfamily and link mylink glm y x, family(myfamily) link(mylink).
or logistic regression. If g() is the natural log function and yis distributed as Poisson, we have ln E(y) = x , y˘Poisson or Poisson regression, also known as the log-linear model. Other combinations are possible. Although glm can be used to perform linear regression (and, in fact, does so by default), this
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