calc_conf_int: Calculate Confidence Intervals for a Parameter

In beezdiscounting: Behavioral Economic Easy Discounting

Calculate Confidence Intervals for a Parameter

Description

This function computes the lower and upper bounds of the confidence interval for a parameter estimate, given its standard error, a specified significance level, and the degrees of freedom from the model.

Usage

calc_conf_int(estimate, std_error, model, alpha = 0.05)

Arguments

estimate	A numeric value representing the parameter estimate.
std_error	A numeric value representing the standard error of the parameter estimate.
model	A fitted model object that provides the residual degrees of freedom via df.residual().
alpha	A numeric value representing the significance level. Default is 0.05 (95% confidence interval).

Value

A numeric vector of length two:

• First element: Lower bound of the confidence interval.

• Second element: Upper bound of the confidence interval.

Examples

# Example using a linear model
data <- data.frame(x = 1:10, y = c(2.3, 2.1, 3.7, 4.5, 5.1, 6.8, 7.3, 7.9, 9.2, 10.1))
lm_model <- lm(y ~ x, data = data)
calc_conf_int(estimate = 0.5, std_error = 0.1, model = lm_model, alpha = 0.05)

beezdiscounting documentation built on April 4, 2025, 4:44 a.m.