## ----echo = FALSE, warning=FALSE, message = FALSE, results = 'hide'----------- cat("this will be hidden; use for general initializations.\n") library(superb) library(ggplot2) ## ----------------------------------------------------------------------------- dta <- GRD() head(dta) ## ----------------------------------------------------------------------------- dta <- GRD( RenameDV = "score" ) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = 'Group(3)') ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = c('Surgery(2)', 'Therapy(3)') ) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = c('Surgery(yes, no)', 'Therapy(CBT,Control,Exercise)') ) unique(dta$Surgery) unique(dta$Therapy) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = c('Surgery(yes,no)', 'Therapy(CBT, Control,Exercise)'), WSFactors = 'Contrast(C1,C2,C3)', ) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = "Therapy(3)", SubjectsPerGroup = c(2, 5, 1) ) dta ## ----dpi=72, fig.height=3, fig.width=4---------------------------------------- dta <- GRD( RenameDV = "IQ", Population=list(mean=100,stddev=15) ) hist(dta$IQ) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors = "Group(2)", Population = list( mean = 100, # this set GM to 100 stddev = 15, # this set STDDEV to 15 scores = "rnorm(1, mean = GM, sd = STDDEV )" ) ) ## ----dpi=72, fig.height=3, fig.width=4---------------------------------------- dta <- GRD( BSFactors = "Group(2)", Population = list( mean = 100, # this set GM to 100 stddev = 15, # this set STDDEV to 15 scores = "rnorm(1, mean = GM, sd = Group * STDDEV )" ) ) superb( DV ~ Group, dta, plotStyle = "pointjitterviolin" ) ## ----dpi=72, fig.height=3, fig.width=4---------------------------------------- dta <- GRD(SubjectsPerGroup = 5000, RenameDV = "RT", Population=list( scores = "rweibull(1, shape=2, scale=40)+250" ) ) hist(dta$RT,breaks=seq(250,425,by=5)) ## ----message=FALSE, dpi=72, fig.height=3, fig.width=4------------------------- dta <- GRD( BSFactors = 'Therapy(CBT, Control, Exercise)', WSFactors = 'Contrast(3)', SubjectsPerGroup = 1000, Effects = list('Contrast' = slope(2)) ) superb( crange(DV.1, DV.3) ~ Therapy, dta, WSFactors = "Contrast(3)", plotStyle = "line" ) ## ----message=FALSE, dpi=72, fig.height=3, fig.width=4------------------------- dta <- GRD( BSFactors = 'Therapy(CBT,Control,Exercise)', WSFactors = 'Contrast(3) ', SubjectsPerGroup = 1000, Effects = list( "code1"=Rexpression("if (Therapy =='CBT'){-1} else {0}"), "code2"=Rexpression("if (Contrast ==3) {+1} else {0}") ) ) superb( crange(DV.1, DV.3) ~ Therapy, dta, WSFactors = "Contrast(3)", plotStyle = "line" ) ## ----dpi=72, fig.width=4, fig.height=4---------------------------------------- dta <- GRD( WSFactors = 'Difficulty(1, 2)', SubjectsPerGroup = 1000, Population=list(mean = 0,stddev = 20, rho = 0.5) ) plot(dta$DV.1, dta$DV.2) ## ----dpi=72, fig.width=4, fig.height=4---------------------------------------- dta <- GRD( WSFactors = 'Difficulty(1, 2)', SubjectsPerGroup = 1000, Population=list(mean = c(10,2),stddev= c(1,0.2),rho =-0.85) ) plot(dta$DV.1, dta$DV.2) ## ----dpi=72, fig.height=3, fig.width=4---------------------------------------- dta <- GRD(SubjectsPerGroup = 5000, Population= list( mean=100, stddev = 15 ), Contaminant=list( mean=200, stddev = 15, proportion = 0.10 ) ) hist(dta$DV,breaks=seq(-25,300,by=2.5)) ## ----dpi=72, fig.height=3, fig.width=4---------------------------------------- dta <- GRD(SubjectsPerGroup = 10000, Population=list( mean=100, stddev = 15 ), Contaminant=list( proportion = 0.10, scores="rweibull(1,shape=1.5, scale=30)+1.5*GM") ) hist(dta$DV,breaks=seq(0,365,by=2.5)) ## ----------------------------------------------------------------------------- dta <- GRD( BSFactors="grp(2)", WSFactors = "Moment (2)", SubjectsPerGroup = 1000, Effects = list("grp" = slope(100) ), Population=list(mean=0,stddev=20,rho= -0.85), Contaminant=list(scores = "NA", proportion=0.2) )