# imcid: Point and interval estimation for the MCID at the individual... In MCID: Estimating the Minimal Clinically Important Difference

## Description

We formulate the individualized MCID as a linear function of the patients' clinical profiles. `imcid` returns the point estimate for the linear coefficients of the MCID at the individual level

## Usage

 `1` ```imcid(x, y, z, n, lambda, 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 `z` a vector or matrix denoting the patient's clinical profiles `n` the sample size `lambda` the selected tuning parameter λ, can be returned by `cv.imcid` `delta` the selected tuning parameter δ, can be returned by `cv.imcid` `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 estimates for the linear coefficients of the individualized MCID and their standard errors, and the corresponding confidence intervals based on the asymptotic normality

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```n <- 500 lambdaseq <- 10 ^ seq(-3, 3, 0.1) deltaseq <- seq(0.1, 0.3, 0.1) a <- 0.1 b <- 0.55 c <- -0.1 d <- 0.45 ### True linear coefficients of the individualized MCID: ### ### beta0=0, beta1=0.5 ### set.seed(115) p <- 0.5 y <- 2 * rbinom(n, 1, p) - 1 z <- rnorm(n, 1, 0.1) y_1 <- which(y == 1) y_0 <- which(y == -1) x <- c() x[y_1] <- a + z[y_1] * b + rnorm(length(y_1), 0, 0.1) x[y_0] <- c + z[y_0] * d + rnorm(length(y_0), 0, 0.1) sel <- cv.imcid(x = x, y = y, z = z, lamseq = lambdaseq, delseq = deltaseq, k = 5, maxit = 100, tol = 1e-02) lamsel <- sel\$'Selected lambda' delsel <- sel\$'Selected delta' result <- imcid(x = x, y = y, z = z, n = n, lambda = lamsel, delta = delsel, maxit = 100, tol = 1e-02, alpha = 0.05) result\$'Point estimates' result\$'Standard errors' result\$'Confidence intervals' ```

MCID documentation built on Sept. 10, 2021, 5:07 p.m.