Nothing
## ----setup, include=FALSE, cache=FALSE----------------------------------------
require(knitr)
opts_chunk$set(
dev="pdf",
fig.path="figures/",
fig.height=3,
fig.width=4,
out.width=".47\\textwidth",
fig.keep="high",
fig.show="hold",
fig.align="center",
prompt=TRUE, # show the prompts; but perhaps we should not do this
comment=NA # turn off commenting of ouput (but perhaps we should not do this either
)
## ----pvalues, echo=FALSE, message=FALSE---------------------------------------
print.pval = function(pval) {
threshold = 0.0001
return(ifelse(pval < threshold, paste("p<", sprintf("%.4f", threshold), sep=""),
ifelse(pval > 0.1, paste("p=",round(pval, 2), sep=""),
paste("p=", round(pval, 3), sep=""))))
}
## ----setup2,echo=FALSE,message=FALSE------------------------------------------
require(Sleuth3)
require(mosaic)
trellis.par.set(theme=col.mosaic()) # get a better color scheme for lattice
set.seed(123)
# this allows for code formatting inline. Use \Sexpr{'function(x,y)'}, for exmaple.
knit_hooks$set(inline = function(x) {
if (is.numeric(x)) return(knitr:::format_sci(x, 'latex'))
x = as.character(x)
h = knitr:::hilight_source(x, 'latex', list(prompt=FALSE, size='normalsize'))
h = gsub("([_#$%&])", "\\\\\\1", h)
h = gsub('(["\'])', '\\1{}', h)
gsub('^\\\\begin\\{alltt\\}\\s*|\\\\end\\{alltt\\}\\s*$', '', h)
})
showOriginal=FALSE
showNew=TRUE
## ----install_mosaic,eval=FALSE------------------------------------------------
# install.packages('mosaic') # note the quotation marks
## ----load_mosaic,eval=FALSE---------------------------------------------------
# require(mosaic)
## ----install_Sleuth3,eval=FALSE-----------------------------------------------
# install.packages('Sleuth3') # note the quotation marks
## ----load_Sleuth3,eval=FALSE--------------------------------------------------
# require(Sleuth3)
## ----eval=TRUE----------------------------------------------------------------
trellis.par.set(theme=col.mosaic()) # get a better color scheme for lattice
options(digits=4, show.signif.stars=FALSE)
## -----------------------------------------------------------------------------
# logit transformation
case1301$logitcover = with(case1301, log(Cover/(100-Cover)))
## -----------------------------------------------------------------------------
summary(case1301)
favstats(logitcover~Treat, data=case1301)
## ----fig.height=8, fig.width=8------------------------------------------------
with(case1301, interaction.plot(Block, Treat, Cover))
## ----fig.height=8, fig.width=8------------------------------------------------
plot(aov(Cover ~ Block*Treat, data=case1301), which=1)
## ----fig.height=8, fig.width=8------------------------------------------------
with(case1301, interaction.plot(Block, Treat, logitcover))
## -----------------------------------------------------------------------------
anova(lm(logitcover ~ Block*Treat, data=case1301))
## -----------------------------------------------------------------------------
anova(lm(logitcover ~ Block+Treat, data=case1301))
## ----fig.height=8, fig.width=8------------------------------------------------
plot(aov(logitcover ~ Block+Treat, data=case1301), which=1)
## ----fig.height=8, fig.width=8, message=FALSE---------------------------------
case1301$resid = predict(aov(logitcover ~ Block+Treat, data=case1301))
histogram(~ resid, type='density', density=TRUE, data=case1301)
## ----fig.height=8, fig.width=8------------------------------------------------
plot(aov(logitcover ~ Block+Treat, data=case1301), which=3)
## ----fig.height=8, fig.width=8------------------------------------------------
plot(aov(logitcover ~ Block+Treat, data=case1301), which=4)
## -----------------------------------------------------------------------------
case1301[c(13, 22, 87),]
## -----------------------------------------------------------------------------
model.tables(aov(lm(logitcover ~ Block*Treat, data=case1301)), type="effects")
## -----------------------------------------------------------------------------
model.tables(aov(lm(logitcover ~ Block*Treat, data=case1301)), type="means")
## -----------------------------------------------------------------------------
require(gmodels)
lm1 = lm(logitcover ~ Treat+Block, data=case1301); coef(lm1)
large = rbind('Large fish' = c(0, 0, -1/2, 1/2, -1/2, 1/2))
small = rbind('Small fish' = c(-1/2, -1/2, 1/2, 0, 1/2, 0))
limpets = rbind('Limpets' = c(-1/3, 1/3, 1/3, 1/3, -1/3, -1/3))
limpetsSmall = rbind('Limpets X Small' = c(1, -1, 1/2, 1/2, -1/2, -1/2))
limpetsLarge = rbind('Limpets X Large' = c(0, 0, -1, 1, 1, -1))
fit.contrast(lm1, "Treat", large, conf.int=.95)
fit.contrast(lm1, "Treat", small, conf.int=.95)
fit.contrast(lm1, "Treat", limpets, conf.int=.95)
fit.contrast(lm1, "Treat", limpetsSmall, conf.int=.95)
fit.contrast(lm1, "Treat", limpetsLarge, conf.int=.95)
## -----------------------------------------------------------------------------
summary(case1302)
case1302$newTreat = relevel(case1302$Treat, ref="Control")
## ----fig.height=8, fig.width=8------------------------------------------------
with(case1302, interaction.plot(Company, newTreat, Score))
## -----------------------------------------------------------------------------
lm1 = lm(Score ~ Company*newTreat, data=case1302); summary(lm1)
lm2 = lm(Score ~ Company+newTreat, data=case1302); summary(lm2) # Display 13.18 page 406
anova(lm1)
anova(lm2)
anova(lm2, lm1)
## ----fig.height=8, fig.width=8------------------------------------------------
plot(lm2, which=1)
## -----------------------------------------------------------------------------
obs = summary(lm(Score ~ Company+newTreat, data=case1302))$coefficients["newTreatPygmalion", "t value"]
nulldist = do(10000) * summary(lm(Score ~ shuffle(Company)+shuffle(newTreat), data=case1302))$coefficients["shuffle(newTreat)Pygmalion", "t value"]
histogram(~ result, groups=result >= obs, v=obs, data=nulldist) # akin to Display 13.20 page 408
tally(~ result >= obs, format="proportion", data=nulldist)
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