Description Usage Arguments Details
Conducts regression analysis to model outcome variable using OLS
Conducts logistic regression analysis to model binary outcome variable using a generalized (binomial with logit link) linear model
Conducts logistic regression analysis to model approximations of binary outcome variables (doesn't have to be 2 levels) using a generalized (quasi-binomial with logit link) linear model
Conducts poisson regression to model count outcome variables using a generalized (poisson with logit link) linear model.
Conducts poisson regression analysis to model approximations of count outcome variables (doesn't have to be integers) using a generalized (quasi-poisson with logit link) linear model
Conducts negative binomial regression (generalized linear models for overdispersed count data)
1 2 3 4 5 6 7 8 9 10 11 | ols_regression(data, model, robust = FALSE, ...)
logistic_regression(data, model, robust = FALSE, ...)
quasilogistic_regression(data, model, robust = FALSE, ...)
poisson_regression(data, model, robust = FALSE, ...)
quasipoisson_regression(data, model, robust = FALSE, ...)
negbinom_regression(data, model, robust = FALSE, ...)
|
data |
Data frame containing variables in model |
model |
Model formula to be estimated. |
robust |
Logical indicating whether to estimate a robust model. This is available for all models but negative binomial. |
... |
Other arguments passed to modeling function. |
Available types of regression models.
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