adsl <- tern_ex_adsl
adlb <- tern_ex_adlb %>% dplyr::filter(ANL01FL == "Y", PARAMCD == "ALT", AVISIT != "SCREENING")
adlb$AVISIT <- droplevels(adlb$AVISIT)
adlb <- dplyr::mutate(adlb, AVISIT = forcats::fct_reorder(AVISIT, AVISITN, min))
# Mean with CI
g_lineplot(adlb, adsl, subtitle = "Laboratory Test:")
# Mean with CI, no stratification with group_var
g_lineplot(adlb, variables = control_lineplot_vars(group_var = NA))
# Mean, upper whisker of CI, no group_var(strata) counts N
g_lineplot(
adlb,
whiskers = "mean_ci_upr",
title = "Plot of Mean and Upper 95% Confidence Limit by Visit"
)
# Median with CI
g_lineplot(
adlb,
adsl,
mid = "median",
interval = "median_ci",
whiskers = c("median_ci_lwr", "median_ci_upr"),
title = "Plot of Median and 95% Confidence Limits by Visit"
)
# Mean, +/- SD
g_lineplot(adlb, adsl,
interval = "mean_sdi",
whiskers = c("mean_sdi_lwr", "mean_sdi_upr"),
title = "Plot of Median +/- SD by Visit"
)
# Mean with CI plot with stats table
g_lineplot(adlb, adsl, table = c("n", "mean", "mean_ci"))
# Mean with CI, table and customized confidence level
g_lineplot(
adlb,
adsl,
table = c("n", "mean", "mean_ci"),
control = control_analyze_vars(conf_level = 0.80),
title = "Plot of Mean and 80% Confidence Limits by Visit"
)
# Mean with CI, table with customized formats/labels
g_lineplot(
adlb,
adsl,
table = c("n", "mean", "mean_ci"),
table_format = list(
mean = function(x, ...) {
ifelse(x < 20, round_fmt(x, digits = 3), round_fmt(x, digits = 2))
},
mean_ci = "(xx.xxx, xx.xxx)"
),
table_labels = list(
mean = "mean",
mean_ci = "95% CI"
)
)
# Mean with CI, table, filtered data
adlb_f <- dplyr::filter(adlb, ARMCD != "ARM A" | AVISIT == "BASELINE")
g_lineplot(adlb_f, table = c("n", "mean"))
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