available regression methods

`fit_lm`: linear regression model lm.

`fit_logistic`: logistic regression model glm.

`fit_poisson`: poisson regression model glm.

`fit_cox`: proportional hazards regression model coxph.

`fit_lme`: linear mixed-effects model lme.

`fit_glmer`: logistic linear mixed-effects model glmer.

`fit_lmer`: linear mixed-effects model lmer.

Usage

fit_lm(data = NULL, formula = NULL, keep = NULL)

fit_logistic(data = NULL, formula = NULL, keep = NULL)

fit_poisson(data = NULL, formula = NULL, keep = NULL)

fit_cox(data = NULL, formula = NULL, keep = NULL)

fit_lme(data = NULL, formula = NULL, keep = NULL, ...)

fit_glmer(data = NULL, formula = NULL, keep = NULL, ...)

fit_lmer(data = NULL, formula = NULL, keep = NULL, ...)

Arguments

data

A data.table with all variables to be fitted.

formula

A "formula" object to be fitted.

keep

Variables to keep regression results.

...

Further arguments passed to regression model.

Value

term estimate std.error statistic p.value n.

See also

regression