log_odds: Calculate the log odds ratio with wald confidence intervals

In Ischi94/palint: This package currently contains all helper functions I privately use in my projects

Description

log_odds computes the log odds ratio between two binary outcomes.

Usage

log_odds(n00, n01, n10, n11, alpha = 0.05, print.result = "df")

Arguments

n00	(numeric) A scalar for the number of observations exposed with the condition.
n01	(numeric) A scalar for the number of observations exposed without the condition.
n10	(numeric) A scalar for the number of observations not exposed with the condition.
n11	(numeric) A scalar for the number of observations not exposed without the condition.
alpha	(numeric) A value defining the probability for the wald confidence interval. Default is an alpha of 0.05, corresponding to a 0.95 % confidence interval.
print.result	(character) Either "vector" for output given in a vector or "df" for output given within a tibble (default).

Examples

# If we have a hypothetical group of smokers (exposed) and non-smokers (not exposed),
# then we can look for the rate of lung cancer (condition).
# 20 smokers have lung cancer (n00),
# 80 smokers do not have lung cancer (n01),
# one non-smoker has lung cancer (n10),
# and 99 non-smokers do not have lung cancer (n11).
log_odds(20, 80, 1, 99)

Ischi94/palint documentation built on Feb. 7, 2021, 4:37 a.m.