ci_prop_diff_wald: Wald Confidence Interval for Difference in Proportions

Description

Calculates the Wald interval by following the usual textbook definition for a difference in proportions confidence interval using the normal approximation.

Usage

ci_prop_diff_wald(x, by, conf.level = 0.95, correct = FALSE, data = NULL)

Value

An object containing the following components:

n: Number of responses in each by group
N: Total number in each by group
estimate: The point estimate of the difference in proportions (p_1 - p_2)
conf.low: Lower bound of the confidence interval
conf.high: Upper bound of the confidence interval
conf.level: The confidence level used
method: Type of method used

Arguments

x: (binary/numeric/logical)
vector of a binary values, i.e. a logical vector, or numeric with values c(0, 1)
by: (string)
A character or factor vector with exactly two unique levels identifying the two groups to compare. Can also be a column name if a data frame provided in the data argument.
conf.level: (scalar numeric)
a scalar in (0,1) indicating the confidence level. Default is 0.95
correct: (logical)
apply continuity correction.
data: (data.frame)
Optional data frame containing the variables specified in x and by.

Details

$$(\hat{p}_1 - \hat{p}_2) \pm z_{\alpha/2} \sqrt{\frac{\hat{p}_1(1 - \hat{p}_1)}{n_1}+\frac{\hat{p}_2(1 - \hat{p}_2)}{n_2}}$$

Examples

Run this code

responses <- expand(c(9, 3), c(10, 10))
arm <- rep(c("treat", "control"), times = c(10, 10))

# Calculate 95% confidence interval for difference in proportions
ci_prop_diff_wald(x = responses, by = arm)

Run the code above in your browser using DataLab