Binary outcomes

Example

The example uses the breastcancer data set from the risks package and compares the risk of death (a binary variable in this case) by categories of cancer stage.

library(rifttable)
library(dplyr)
data(breastcancer, package = "risks")

tibble::tribble(
  ~label,                      ~type,
  "**Absolute estimates**",    "",
  "Observations",              "total",
  "Outcomes",                  "outcomes",
  "Outcomes/Total",            "outcomes/total",
  "Cases/Controls",            "cases/controls",
  "Risk",                      "risk",
  "Risk (95% CI)",             "risk (ci)",
  "Outcomes (Risk)",           "outcomes (risk)",
  "Outcomes/Total (Risk)",     "outcomes/total (risk)",
  "",                          "",
  "**Comparative estimates**", "",
  "Risk ratio (95% CI)",       "rr",
  "Risk difference (95% CI)",  "rd",
  "Odds ratio (95% CI)",       "or"
) |>
  mutate(
    exposure = "stage",
    outcome = "death"
  ) |>
  rifttable(
    data = breastcancer,
    overall = TRUE
  ) |>
  rt_gt() # Formatted output
Summary Overall Stage I Stage II Stage III
Absolute estimates
Observations 192 67 96 29
Outcomes 54 7 26 21
Outcomes/Total 54/192 7/67 26/96 21/29
Cases/Controls 54/138 7/60 26/70 21/8
Risk 0.28 0.10 0.27 0.72
Risk (95% CI) 0.28 (0.22, 0.35) 0.10 (0.05, 0.20) 0.27 (0.19, 0.37) 0.72 (0.54, 0.85)
Outcomes (Risk) 54 (0.28) 7 (0.10) 26 (0.27) 21 (0.72)
Outcomes/Total (Risk) 54/192 (0.28) 7/67 (0.10) 26/96 (0.27) 21/29 (0.72)
Comparative estimates
Risk ratio (95% CI) 1 (reference) 2.59 (1.20, 5.6) 6.9 (3.3, 14)
Risk difference (95% CI) 0 (reference) 0.17 (0.05, 0.28) 0.62 (0.44, 0.80)
Odds ratio (95% CI) 1 (reference) 3.2 (1.35, 8.4) 22 (7.7, 75)

Absolute estimates per exposure category

type Description Options (arguments =)
"cases/controls" Cases and non-cases (events and non-events); useful for case-control studies.
"outcomes" Outcome count.
"outcomes (risk)" A combination: Outcomes followed by risk in parentheses.
"outcomes/total (risk)" A combination: Outcomes slash total followed by risk in parentheses.
"risk" Risk (or prevalence), calculated as a proportion, i.e., outcomes divided by number of observations. Change between display as proportion or percent using the parameter risk_percent of rifttable().
"risk (ci)" Risk with confidence interval (default: 95%): Wilson score interval for binomial proportions, see rifttable::scoreci().

Comparative estimates with confidence intervals

type Description Options (arguments =)
"irr" Incidence rate ratio for count outcomes from Poisson regression model, with confidence interval (default: 95%).
"or" Odds ratio from logistic regression, with confidence interval (default: 95%).
"rd" Risk difference (or prevalence difference) from risks::riskdiff(), with confidence interval (default: 95%). list(approach = "margstd_boot", bootrepeats = 2000) to request model fitting via marginal standardization with 2000 bootstraps.
"rr" Risk ratio (or prevalence ratio) from risks::riskratio(), with confidence interval (default: 95%). See "rd".