Function to run generalized linear model (glm) across multiple grouping variables.

grouped_glm(
  data,
  grouping.vars,
  ...,
  output = "tidy",
  tidy.args = list(conf.int = TRUE, conf.level = 0.95),
  augment.args = list()
)

Arguments

data

Dataframe (or tibble) from which variables are to be taken.

grouping.vars

Grouping variables.

...

Additional arguments to broom::tidy, broom::glance, or broom::augment S3 method.

output

A character describing what output is expected. Two possible options: "tidy" (default), which will return the results, or "glance", which will return model summaries.

tidy.args

A list of arguments to be used in the relevant S3 method.

augment.args

A list of arguments to be used in the relevant S3 method.

Value

A tibble dataframe with tidy results from linear model.

See also

Examples

groupedstats::grouped_glm( data = mtcars, formula = am ~ wt, grouping.vars = cyl, family = stats::binomial(link = "logit") )
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: algorithm did not converge
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: collapsing to unique 'x' values
#> Warning: collapsing to unique 'x' values
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> # A tibble: 6 x 9 #> cyl term estimate std.error statistic p.value conf.low conf.high #> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 4 (Intercept) 13.8 7.79 1.77 0.0773 3.30 38.4 #> 2 4 wt -5.12 2.98 -1.71 0.0865 -14.5 -1.04 #> 3 6 (Intercept) 417. 871566. 0.000478 1.00 -113315. NA #> 4 6 wt -137. 284315. -0.000481 1.00 NA 25376. #> 5 8 (Intercept) 28.3 21.4 1.32 0.187 0.00542 99.8 #> 6 8 wt -8.46 6.17 -1.37 0.171 -29.1 -0.563 #> significance #> <chr> #> 1 ns #> 2 ns #> 3 ns #> 4 ns #> 5 ns #> 6 ns