Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
message = FALSE,
warning = FALSE,
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
finalfit(dependent, explanatory) %>%
knitr::kable(row.names=FALSE) # This line only needed for formatting.
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory)
# Note this example uses fig.height=3, fig.width=9
## -----------------------------------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
random_effect = "hospital"
colon_s %>%
finalfit(dependent, explanatory, random_effect = random_effect)%>%
knitr::kable(row.names=FALSE) # This line only needed for formatting.
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
random_effect = "hospital"
colon_s %>%
or_plot(dependent, explanatory, random_effect = random_effect)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=2, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
# Run summary_factorlist for variables you wish to include
## Include total_col = TRUE and fit_id = TRUE
factorlist = colon_s %>%
summary_factorlist(dependent, "age.factor", total_col = TRUE, fit_id = TRUE)
# Run full model including factorlist
colon_s %>%
or_plot(dependent, explanatory, factorlist = factorlist)
# Note this example uses fig.height=2, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
random_effect = "hospital"
fit = colon_s %>%
glmmixed(dependent, explanatory, random_effect)
# Equivalent to:
fit = colon_s %>%
lme4::glmer(mort_5yr ~ age.factor + sex.factor + obstruct.factor + perfor.factor + (1 | hospital),
family="binomial", data = .)
# Which is incidentally equivalent to:
fit = colon_s %>%
lme4::glmer(ff_formula(dependent, explanatory, random_effect),
family="binomial", data = .)
# Plot
system.time(colon_s %>%
or_plot(dependent, explanatory, random_effect = random_effect, glmfit = fit)
)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, confint_type = "default")
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, remove_ref = TRUE)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, breaks = c(0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.8, 2.4))
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, column_space = c(-0.5, -0.1, 0.5))
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, dependent_label = "Mortality")
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, prefix = "Figure 1 - ")
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, suffix = "")
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, table_text_size = 3)
# Note this example uses fig.height=4, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory, title_text_size = 12)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
library(ggplot2)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory,
plot_opts = list(xlim(0.1, 3),
xlab("OR (95% CI, log)"),
theme(axis.title = element_text(size=10))
)
)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=10-----------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
or_plot(dependent, explanatory,
digits = c(3,3,3), confint_sep = " to ", column_space = c(-0.5, -0.1, 0.5))
# Note this example uses fig.height=3, fig.width=10
## -----------------------------------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "Surv(time, status)"
colon_s %>%
finalfit(dependent, explanatory) %>%
knitr::kable(row.names=FALSE) # This line only needed for formatting.
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "Surv(time, status)"
colon_s %>%
hr_plot(dependent, explanatory)
# Note this example uses fig.height=3, fig.width=9
## -----------------------------------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "nodes"
colon_s %>%
finalfit(dependent, explanatory) %>%
knitr::kable(row.names=FALSE) # This line only needed for formatting.
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "nodes"
colon_s %>%
coefficient_plot(dependent, explanatory)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=3, fig.width=9------------------------------------------------
library(finalfit)
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "nodes"
colon_s %>%
ff_plot(dependent, explanatory)
# Note this example uses fig.height=3, fig.width=9
## ----fig.height=4.5, fig.width=6----------------------------------------------
library(finalfit)
explanatory = "perfor.factor"
dependent = "Surv(time, status)"
colon_s %>%
surv_plot(dependent, explanatory)
## ----fig.height=4.5, fig.width=6----------------------------------------------
library(finalfit)
explanatory = "perfor.factor"
dependent = "Surv(time, status)"
colon_s %>%
surv_plot(dependent, explanatory, xlab="Time (days)", pval=TRUE, legend="none")
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