Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
digits = 3,
collapse = TRUE,
comment = "#>"
)
options(digits = 3)
library(knitr)
library(contrast)
library(nlme)
library(ggplot2)
library(geepack)
library(dplyr)
library(tidyr)
options(useFancyQuotes = FALSE, width = 80)
## -----------------------------------------------------------------------------
library(contrast)
library(dplyr)
two_factor_crossed %>%
group_by(diet, group) %>%
count()
## ----example1Plot, fig = TRUE, echo = FALSE, width = 6, height = 4.25---------
library(ggplot2)
theme_set(theme_bw() + theme(legend.position = "top"))
ggplot(two_factor_crossed) +
aes(x = diet, y = expression, col = group, shape = group) +
geom_point() +
geom_smooth(aes(group = group), method = lm, se = FALSE)
## ----example1LinearMod--------------------------------------------------------
lm_fit_1 <- lm(expression ~ (group + diet)^2, data = two_factor_crossed)
summary(lm_fit_1)
## ----example1Contrast---------------------------------------------------------
high_fat <- contrast(lm_fit_1,
list(diet = "low fat", group = "vehicle"),
list(diet = "low fat", group = "treatment"))
print(high_fat, X = TRUE)
## ----example1ContrastStat, include = FALSE------------------------------------
basic_test_stat <- high_fat$testStat
## ----eachTest-----------------------------------------------------------------
trt_effect <-
contrast(
lm_fit_1,
list(diet = levels(two_factor_crossed$diet), group = "vehicle"),
list(diet = levels(two_factor_crossed$diet), group = "treatment")
)
print(trt_effect, X = TRUE)
## ----meanEffect---------------------------------------------------------------
mean_effect <-
contrast(
lm_fit_1,
list(diet = levels(two_factor_crossed$diet), group = "vehicle"),
list(diet = levels(two_factor_crossed$diet), group = "treatment"),
type = "average"
)
print(mean_effect, X = TRUE)
## ----example1Sand-------------------------------------------------------------
high_fat_sand <-
contrast(
lm_fit_1,
list(diet = "low fat", group = "vehicle"),
list(diet = "low fat", group = "treatment"),
covType = "HC3"
)
print(high_fat_sand)
## ----example1GenLinearMod-----------------------------------------------------
glm_fit_1 <- glm(2^expression ~ (group + diet)^2,
data = two_factor_crossed,
family = gaussian(link = "log"))
summary(glm_fit_1)
high_fat <-
contrast(glm_fit_1,
list(diet = "low fat", group = "vehicle"),
list(diet = "low fat", group = "treatment")
)
print(high_fat, X = TRUE)
## ----example2Data-------------------------------------------------------------
library(tidyr)
two_factor_incompl %>%
group_by(subject, config, day) %>%
count() %>%
ungroup() %>%
pivot_wider(
id_cols = c(config, day),
names_from = c(subject),
values_from = c(n)
)
## ----design2factor------------------------------------------------------------
two_factor_incompl %>%
group_by(group) %>%
count()
## ----design2gls---------------------------------------------------------------
gls_fit <- gls(expression ~ group,
data = two_factor_incompl,
corCompSymm(form = ~ 1 | subject))
summary(gls_fit)
## ----design2glsCont-----------------------------------------------------------
print(
contrast(
gls_fit,
list(group = "4:C"),
list(group = "4:D")
),
X = TRUE)
## ----example2Plot, fig = TRUE, echo = FALSE, width = 6, height = 4.25---------
ggplot(two_factor_incompl) +
aes(x = day, y = expression, col = config, shape = config) +
geom_point() +
stat_summary(fun.y=mean, aes(group = config), geom = "line")
## ----design2lme---------------------------------------------------------------
lme_fit <- lme(expression ~ group, data = two_factor_incompl, random = ~1|subject)
summary(lme_fit)
print(
contrast(
lme_fit,
list(group = "4:C"),
list(group = "4:D")
),
X = TRUE)
## ----design2gee---------------------------------------------------------------
gee_fit <- geese(2^expression ~ group,
data = two_factor_incompl,
id = subject,
family = gaussian(link = "log"),
corstr = "exchangeable")
summary(gee_fit)
print(
contrast(
gee_fit,
list(group = "4:C"),
list(group = "4:D")
),
X = TRUE)
## ----ex1FC--------------------------------------------------------------------
trt_effect <-
contrast(lm_fit_1,
list(diet = levels(two_factor_crossed$diet), group = "vehicle"),
list(diet = levels(two_factor_crossed$diet), group = "treatment"),
fcfunc = function(u) 2^u
)
print(trt_effect, X = TRUE)
trt_effect$foldChange
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