Estimate covariate associations with survival at the cutoff time

Estimates odds ratios with confidence intervals for associations between covariates and survival at the cutoff time within a selected treatment group.

Usage

ORCI(data, formula, a, conf_level = 0.95)

Arguments

data

Data prepared by DataStandard().

formula

A logistic regression formula with the survival variable on the left-hand side and the covariates of interest on the right-hand side.

a

The treatment group to analyze at the cutoff time, either 0 or 1.

conf_level

The confidence level, expressed as a single number between 0 and 1. Defaults to 0.95.

Value

An odds_ratios object containing odds-ratio estimates and confidence intervals, the fitted model, model-checking information, and a forest plot. Reported estimates are rounded to three decimal places.

Details

ORCI() fits the supplied logistic regression model using observations from treatment group a at the cutoff time. It reports an odds ratio and Wald confidence interval for every non-intercept coefficient that can be estimated. Covariates are not selected according to statistical significance.

Examples

# \donttest{
data("BiSample", package = "PDRobust")
map <- Mapping(
  id = "id", time = "time", treatment = "A",
  survival = "S", outcome = "Y",
  baseline_time = 0, cutoff_time = 2,
  covariates = c("X1", "X2", "X4"),
  interest_vars = c("X1", "X2"), y_type = "B"
)
pd_dat <- DataStandard(BiSample, map)
result <- ORCI(
  pd_dat, S ~ X1 + X2 + X4, a = 0
)
result$forestplotdat
#>    covname estcoef lowerbd upperbd
#> X1      X1   1.788   1.021   3.132
#> X2      X2   1.834   0.988   3.404
#> X4      X4   2.028   0.677   6.076
# }