Effect measure for association between two categorical variables — effect_tabular • crosstable

User can either use or extend these functions to configure effect calculation.

effect_odds_ratio(x, by, conf_level = 0.95)

effect_relative_risk(x, by, conf_level = 0.95)

effect_risk_difference(x, by, conf_level = 0.95)

Arguments

x: categorical vector (character, factor, ...)
by: categorical vector (of exactly 2 unique levels)
conf_level: confidence interval level

Value

A list with five components: effect, ci, effect.name, effect.type, and conf_level

Functions

effect_odds_ratio(): (Default) calculate the odds ratio
effect_relative_risk(): calculate the relative risk
effect_risk_difference(): calculate the risk difference

See also

crosstable_effect_args()

Author

Dan Chaltiel, David Hajage