`glm_model.Rd`

Fit a generalized linear regression using `glm()`

. This function is still in early development stage.

```
glm_model(
data,
response_variable,
predictor_variable,
two_way_interaction_factor = NULL,
three_way_interaction_factor = NULL,
family,
quite = FALSE
)
```

- data
data frame

- response_variable
response variable. Support

`dplyr::select()`

syntax.- predictor_variable
predictor variable. Support

`dplyr::select()`

syntax.- two_way_interaction_factor
two-way interaction factors. You need to pass 2+ factor. Support

`dplyr::select()`

syntax.- three_way_interaction_factor
three-way interaction factor. You need to pass exactly 3 factors. Specifying three-way interaction factors automatically included all two-way interactions, so please do not specify the two_way_interaction_factor argument. Support

`dplyr::select()`

syntax.- family
a GLM family. It will passed to the family argument in glmer. See

`?glmer`

for possible options.- quite
suppress printing output

an object class of `glm`

representing the linear regression fit

```
fit <- glm_model(
response_variable = incidence,
predictor_variable = period,
family = "poisson", # or you can enter as poisson(link = 'log'),
data = lme4::cbpp
)
#> Warning: The following columns are coerced into numeric: herd, period
#> Fitting Model with glm:
#> Formula = incidence ~ period
```