preference: Fit Preference Data Collected from a Two-stage Clinical Trial

In preference: 2-Stage Preference Trial Design and Analysis

Description

The variables in the formula should reference columns in the data parameter and should have the following characteristics.

• outcome: Numeric values giving the outcome of interest.

• treatment: Character, categorical, or integer values denoting the treatment received by an individual.

• random: Logical value indicating whether the sample was from the random arm (TRUE) or choice (FALSE).

• strata: An optional integer value denoting which strata individuals belong to.

Usage

preference(form, data, alpha = 0.05)

Arguments

form	a formula of the form outcome ~ treatment:arm {| strata}.
data	a data.frame containing variables specified in the formula. It should be noted that the arm values must be either "choice" or "random".
alpha	(optional numeric) Level of significance (default 0.05)

Examples

# Unstratified

outcome <- c(10, 8, 6, 10, 5, 8, 7, 6, 10, 12, 11, 6, 8, 10, 5, 7, 9, 
             12, 6, 8, 9, 10, 7, 8, 11)
arm <- c(rep("choice", 13), rep("random", 12))
treatment <- c(rep(1, 5), rep(2, 8), rep(1, 6), rep(2, 6))
d <- data.frame(outcome=outcome, treatment=treatment, arm=arm)
preference(outcome ~ treatment:arm, d)

# Stratified
random <- c(rep(FALSE, 13), rep(TRUE, 12))
treatment <- c(rep(1, 5), rep(2, 8), rep(1, 6), rep(2, 6))
strata <- c(1,1,2,2,2,1,1,1,1,2,2,2,2,1,1,1,2,2,2,1,1,1,2,2,2)
d <- data.frame(outcome=outcome, treatment=treatment, arm=arm, 
                strata=strata)
preference(outcome ~ treatment:arm|strata, d, alpha=0.1)

preference documentation built on Sept. 13, 2020, 5:08 p.m.