📄 y_e_bin.hlp
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{smcl}
{p 0 4}
{help contents:Top}
> {help y_stat:Statistics}
> {help y_est:Estimation}
> {help y_est0:Regression models}
{bind:> {bf:Binary outcome data}}
{p_end}
{hline}
{title:Help and category listings}
{p 4 8 4}
{bf:{help y_e_probit:Probit}}{break}
probit, bivariate probit, heteroskedastic probit, ...
{p 4 8 4}
{bf:{help y_e_logit:Logit and logistic regression}}{break}
logit, logistic, skewed logit, ROC, ...
{p 4 8 4}
{bf:{help cloglog:Complementary log-log estimation}}{break}
maximum-likelihood complementary log-log regression model
{p 4 8 4}
{bf:{help clogit:Conditional logistic regression}}{break}
handles both case-control and fixed-effects logistic regression
{p 4 8 4}
{bf:{help binreg:Generalized linear models for the binomial family}}{break}
estimates odds ratio, risk ratios, health ratios, and risk differences
{p 4 8 4}
{bf:{help glm:Generalized linear model}}{break}
including binomial family and logit, probit, cloglog, ... links
{p 4 8 4}
{bf:{help cusum:Cusum plots and tests for binary variables}}{break}
cumulative sum plot and test statistics
INCLUDE help ypostnote
{hline}
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