# Default arguments for calculating and displaying effects in `crosstable()`

Source: `R/effect.R`

`crosstable_effect_args.Rd`

This helper function provides default parameters for defining how the effect sizes should be computed. It belongs to the `effect_args`

argument of the `crosstable()`

function. See effect_summary, effect_tabular, and effect_survival for more insight.

## Usage

```
crosstable_effect_args(
effect_summarize = diff_mean_auto,
effect_tabular = effect_odds_ratio,
effect_survival = effect_survival_coxph,
effect_display = display_effect,
conf_level = 0.95,
digits = 2
)
```

## Arguments

- effect_summarize
a function of three arguments (continuous variable, grouping variable and conf_level), used to compare continuous variable. Returns a list of five components:

`effect`

(the effect value(s)),`ci`

(the matrix of confidence interval(s)),`effect.name`

(the interpretation(s) of the effect value(s)),`effect.type`

(the description of the measure used) and`conf_level`

(the confidence interval level). Users can use`diff_mean_auto()`

,`diff_mean_student()`

,`diff_mean_boot()`

, or`diff_median()`

, or their custom own function.- effect_tabular
a function of three arguments (two categorical variables and conf_level) used to measure the associations between two factors. Returns a list of five components:

`effect`

(the effect value(s)),`ci`

(the matrix of confidence interval(s)),`effect.name`

(the interpretation(s) of the effect value(s)),`effect.type`

(the description of the measure used) and`conf_level`

(the confidence interval level).Users can use`effect_odds_ratio()`

,`effect_relative_risk()`

, or`effect_risk_difference()`

, or their custom own function.- effect_survival
a function of two argument (a formula and conf_level), used to measure the association between a censored and a factor. Returns the same components as created by

`effect_summarize`

.Users can use`effect_survival_coxph()`

or their custom own function.- effect_display
a function to format the effect. See

`display_effect()`

.- conf_level
the desired confidence interval level

- digits
the decimal places