## ----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')