## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
library(hypr)

## ----eval = FALSE-------------------------------------------------------------
#  vignette("hypr-intro", package = "hypr")

## -----------------------------------------------------------------------------
set.seed(123)
M <- c(mu1 = 10, mu2 = 20, mu3 = 10, mu4 = 40) # condition means
N <- 5
SD <- 10
simdat <- do.call(rbind, lapply(names(M), function(x) {
  data.frame(X = x, DV = as.numeric(MASS::mvrnorm(N, unname(M[x]), SD^2, empirical = TRUE)))
}))
simdat$X <- factor(simdat$X)
simdat$id <- 1:nrow(simdat)
simdat

## -----------------------------------------------------------------------------
trtC <- hypr(mu1~0, mu2~mu1, mu3~mu1, mu4~mu1)

## -----------------------------------------------------------------------------
trtC

## -----------------------------------------------------------------------------
contrasts(simdat$X) <- contr.hypothesis(trtC)
contrasts(simdat$X)

## -----------------------------------------------------------------------------
round(coef(summary(lm(DV ~ X, data=simdat))), 3)

## -----------------------------------------------------------------------------
sumC <- hypr(mu1 ~ (mu1+mu2+mu3+mu4)/4, mu2 ~ (mu1+mu2+mu3+mu4)/4, mu3 ~ (mu1+mu2+mu3+mu4)/4)
sumC

## -----------------------------------------------------------------------------
contrasts(simdat$X) <- contr.hypothesis(sumC)
contrasts(simdat$X)

## -----------------------------------------------------------------------------
contrasts(simdat$X) <- contr.hypothesis(
  mu1 ~ (mu1+mu2+mu3+mu4)/4, 
  mu2 ~ (mu1+mu2+mu3+mu4)/4, 
  mu3 ~ (mu1+mu2+mu3+mu4)/4
)
contrasts(simdat$X)

## -----------------------------------------------------------------------------
round(coef(summary(lm(DV ~ X, data=simdat))),3)