## ----echo = FALSE, message = FALSE, results = 'hide', warning = FALSE---------
cat("this is hidden; general initializations.\n")
## ----warning=FALSE, message=FALSE---------------------------------------------
options("ANOPA.feedback" = 'none')
library(ANOPA)
library(testthat)
nsim <- 1000 # increase for more reliable simulations.
theN <- 20 # number of simulated participants
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- s ~ grp # the formula
# BSDesign <- list(grp = c("ctrl","plcbo")) #one factor, two groups
# thePs <- c(0.3, 0.3) # the true proportions, equal
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(41)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign )
# w <- anopa(frm, smp[,2:3] )
# res <- c(res, if(summarize(w)[1,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design B, testing B: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.early, s.middle, s.late) ~ .
# WSDesign <- list(moment = c("early","middle","late"))
# thePs <- c(0.3, 0.3, 0.3)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(42)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, NULL, WSDesign )
# w <- anopa(frm, smp[,2:4] , WSFactors = "M(3)" )
# res <- c(res, if(summarize(w)[1,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design W, testing W: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- s ~ grp * eta
# WSDesign <- list()
# BSDesign <- list(eta = c("repue","ajun"), grp = c("early","middle","late"))
# thePs <- c(0.3, 0.3, 0.5, 0.5, 0.7, 0.7)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(41)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign )
# w <- anopa(frm, smp )
# res <- c(res, if(summarize(w)[2,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design BxB, testing B: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.repue.early, s.ajun.early,
# s.repue.middle, s.ajun.middle,
# s.repue.late, s.ajun.late) ~ .
# BSDesign <- list()
# WSDesign <- list(eta = c("repue","ajun"), moment = c("early","middle","late"))
# thePs <- c(0.3, 0.3, 0.5, 0.5, 0.7, 0.7)
# # thePs <- c(0.3, 0.7, 0.3, 0.7, 0.3, 0.7) # or no effect on factor 1
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(41)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, NULL, WSDesign )
# w <- anopa(frm, smp, WSFactors = c("e(2)", "m(3)") )
# res <- c(res, if(summarize(w)[2,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design WxW, testing W: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.early, s.middle, s.late) ~ grp
# BSDesign <- list(grp = c("ctrl","plcbo"))
# WSDesign <- list(moment = c("early","middle","late"))
# thePs <- c(0.3, 0.3, 0.5, 0.5, 0.7, 0.7)
# # thePs <- c(0.3, 0.7, 0.3, 0.7, 0.3, 0.7) # or no effect on factor 1
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(41)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign, WSDesign )
# w <- anopa(frm, smp[,2:5] , WSFactors = "M(3)")
# res <- c(res, if(summarize(w)[2,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design WxB, testing B: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- s ~ grp * eta * a
# BSDesign <- list(eta = c("repue","ajun"),
# grp = c("early","middle","late"), a = c("1","2","3","4"))
# thePs <- rep(0.3, 24)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(41)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign )
# w <- anopa(frm, smp )
# res <- c(res, if(summarize(w)[2,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design BxBxB, testing B: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.repue.early.1, s.ajun.early.1, s.repue.middle.1,
# s.ajun.middle.1, s.repue.late.1, s.ajun.late.1, s.repue.early.2,
# s.ajun.early.2, s.repue.middle.2, s.ajun.middle.2, s.repue.late.2,
# s.ajun.late.2, s.repue.early.3, s.ajun.early.3, s.repue.middle.3,
# s.ajun.middle.3, s.repue.late.3, s.ajun.late.3, s.repue.early.4,
# s.ajun.early.4, s.repue.middle.4, s.ajun.middle.4, s.repue.late.4,
# s.ajun.late.4 ) ~ .
# WSDesign <- list(eta = c("repue","ajun"), grp = c("early","middle","late"), a = c("1","2","3","4"))
# thePs <- rep(0.3, 24)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(43)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, NULL, WSDesign )
# w <- anopa(frm, smp, WSFactors = c("e(2)","g(3)", "a(4)") )
# res <- c(res, if(summarize(w)[2,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design WxWxW, testing W: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.repue.early, s.ajun.early, s.repue.middle,
# s.ajun.middle, s.repue.late, s.ajun.late ) ~ a
# BSDesign <- list( a = c("1","2","3","4") )
# WSDesign <- list(eta = c("repue","ajun"), grp = c("early","middle","late") )
# thePs <- rep(0.3, 24)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(43)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign, WSDesign )
# w <- anopa(frm, smp, WSFactors = c("e(2)","g(3)") )
# res <- c(res, if(summarize(w)[1,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design BxWxW, testing W: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## ----message=FALSE, warning=FALSE, echo=TRUE, eval=FALSE----------------------
# frm <- cbind(s.repue.early, s.ajun.early, s.repue.middle,
# s.ajun.middle, s.repue.late, s.ajun.late ) ~ a
# BSDesign <- list( a = c("1","2","3","4") )
# WSDesign <- list(eta = c("repue","ajun"), grp = c("early","middle","late") )
# thePs <- rep(0.3, 24)
#
# # test type-I error rate when no effect as is the case for factor 2
# set.seed(42)
# res <- c()
# for (i in 1:nsim) {
# smp <- GRP( thePs, theN, BSDesign, WSDesign )
# w <- anopa(frm, smp, WSFactors = c("e(2)","g(3)") )
# res <- c(res, if(summarize(w)[3,4]<.05) 1 else 0)
# }
# typeI <- mean(res)
# cat( "Design BxWxW, testing B: ", typeI, "\n")
#
# # tolerance is large as the number of simulations is small
# expect_equal( typeI, .05, tolerance = 0.035)
## -----------------------------------------------------------------------------
options("ANOPA.feedback" = 'all')