MCID (version 0.1.0)

pmcid: Point and interval estimation for the MCID at the population level

Description

pmcid returns the point estimate for the MCID at the population level

Usage

pmcid(x, y, n, delta, maxit = 100, tol = 0.01, alpha = 0.05)

Arguments

x

a continuous variable denoting the outcome change of interest

y

a binary variable indicating the patient-reported outcome derived from the anchor question

n

the sample size

delta

the selected tuning parameter \(\delta\), can be returned by cv.pmcid

maxit

the maximum number of iterations. Defaults to 100

tol

the convergence tolerance. Defaults to 0.01

alpha

nominal level of the confidence interval. Defaults to 0.05

Value

a list including the point estimate of the population MCID and its standard error, and the confidence interval based on the asymptotic normality

Examples

# NOT RUN {
n <- 500
deltaseq <- seq(0.1, 1, 0.1)
a <- 0.2
b <- -0.1
p <- 0.5
### True MCID is 0.5 ###

set.seed(115)
y <- 2 * rbinom(n, 1, p) - 1
y_1 <- which(y == 1)
y_0 <- which(y == -1)
x <- c()
x[y_1] <- rnorm(length(y_1), a, 0.1)
x[y_0] <- rnorm(length(y_0), b, 0.1)

sel <- cv.pmcid(x = x, y = y, delseq = deltaseq, k = 5,
         maxit = 100, tol = 1e-02)
delsel <- sel$'Selected delta'

result <- pmcid(x = x, y = y, n = n, delta = delsel,
            maxit = 100, tol = 1e-02, alpha = 0.05)
result$'Point estimate'
result$'Standard error'
result$'Confidence interval'


# }