Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE, comment = "#>", out.width = "100%",
dpi = 150, fig.path = "mmrm-"
)
## ----review-setup, message=FALSE, warning=FALSE, include=FALSE----------------
library(MASS)
library(clusterGeneration)
library(dplyr)
library(purrr)
library(microbenchmark)
library(stringr)
library(mmrm)
library(lme4)
library(nlme)
library(glmmTMB)
library(sasr)
library(knitr)
library(emmeans)
library(ggplot2)
set.seed(5123)
## ----warning=FALSE, message=FALSE, echo=FALSE---------------------------------
# format table in markdown
cached_mmrm_results$conv_time_fev %>%
arrange(median) %>%
transmute(
Implementation = expression,
Median = median,
`First Quartile` = lower,
`Third Quartile` = upper
) %>%
knitr::kable(
caption = "Comparison of convergence times: milliseconds", digits = 2
)
## ----warning=FALSE, message=FALSE, echo=FALSE---------------------------------
# format table in markdown
cached_mmrm_results$conv_time_bcva %>%
arrange(median) %>%
transmute(
Implementation = expression,
Median = median,
`First Quartile` = lower,
`Third Quartile` = upper
) %>%
knitr::kable(
caption = "Comparison of convergence times: seconds", digits = 2
)
## ----review-treatment-fev, echo = FALSE, warning = FALSE, message = FALSE-----
# plot estimates
ggplot(
cached_mmrm_results$rel_diff_ests_tbl_fev,
aes(x = parameter, y = rel_diff, color = estimator, shape = converged)
) +
geom_point(position = position_dodge(width = 0.5)) +
geom_hline(yintercept = 0, linetype = 2, alpha = 0.5) +
scale_color_discrete(name = "Procedure") +
scale_shape_discrete(name = "Convergence") +
ylab("Relative Difference") +
xlab("Marginal Treatment Effect") +
ggtitle("Average Treatment Effect Estimates Relative to SAS Estimates") +
theme_classic()
## ----review-treatment-bcva, echo = FALSE, warning = FALSE, message = FALSE----
# plot estimates
ggplot(
cached_mmrm_results$rel_diff_ests_tbl_bcva,
aes(x = parameter, y = rel_diff, color = estimator, shape = converged)
) +
geom_point(position = position_dodge(width = 0.5)) +
geom_hline(yintercept = 0, linetype = 2, alpha = 0.5) +
scale_color_discrete(name = "Procedure") +
scale_shape_discrete(name = "Convergence") +
ylab("Relative Difference") +
xlab("Marginal Treatment Effect") +
ggtitle("Average Treatment Effect Estimates Relative to SAS Estimates") +
theme_classic()
# excluding glmmTMB
cached_mmrm_results$rel_diff_ests_tbl_bcva %>%
dplyr::filter(estimator != "glmmTMB") %>%
ggplot(
aes(x = parameter, y = rel_diff, color = estimator, shape = converged)
) +
geom_point(position = position_dodge(width = 0.5)) +
geom_hline(yintercept = 0, linetype = 2, alpha = 0.5) +
scale_color_discrete(name = "Procedure") +
scale_shape_discrete(name = "Convergence") +
ylab("Relative Difference") +
xlab("Marginal Treatment Effect") +
ggtitle(
"Average Treatment Effect Estimates Relative to SAS Estimates
(Excluding glmmTMB)"
) +
theme_classic()
## ----review-missingness-table, warning=FALSE, message=FALSE, echo=FALSE-------
## construct the table
cached_mmrm_results$df_missingness %>%
kable(caption = "Number of patients per visit")
## ----review-convergence-rate-missingness, warning=FALSE, message=FALSE, echo=FALSE----
## plot the convergence rates
cached_mmrm_results$conv_rate %>%
mutate(
missingness = factor(
missingness,
levels = c("none", "mild", "moderate", "high")
)
) %>%
ggplot(aes(x = method, y = convergence_rate)) +
geom_point() +
facet_grid(rows = vars(missingness)) +
xlab("Method") +
ylab("Convergence Rate (10 Replicates)") +
ggtitle("Convergence Rates by Missingness Levels") +
scale_y_continuous(labels = scales::percent_format(accuracy = 1)) +
theme_bw()
## ----review-session-info, echo=FALSE------------------------------------------
sessionInfo()
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