stratWO.data.frame: Stratified win odds with adjustment

In hce: Design and Analysis of Hierarchical Composite Endpoints

Stratified win odds with adjustment

Description

Stratified win odds with adjustment

Usage

## S3 method for class 'data.frame'
stratWO(
  x,
  AVAL,
  TRTP,
  STRATA,
  ref,
  COVAR = NULL,
  alpha = 0.05,
  WOnull = 1,
  ...
)

Arguments

x	a data frame containing subject-level data.
AVAL	variable in the data with ordinal analysis values.
TRTP	the treatment variable in the data.
STRATA	a character variable for stratification.
ref	the reference treatment group.
COVAR	a numeric covariate.
alpha	the reference treatment group.
WOnull	the null hypothesis. The default is 1.
...	additional parameters.

Value

a data frame containing the following columns:

• WO stratified (or adjusted/stratified) win odds.

• LCL lower confidence limit for adjusted (or adjusted/stratified) WO.

• UCL upper confidence limit for adjusted (or adjusted/stratified) WO.

• SE standard error of the adjusted (or adjusted/stratified) win odds.

• WOnull win odds of the null hypothesis (specified in the WOnull argument).

• alpha two-sided significance level for calculating the confidence interval (specified in the alpha argument).

• Pvalue p-value associated with testing the null hypothesis.

• WP adjusted (or adjusted/stratified) win probability.

• LCL_WP lower confidence limit for adjusted (or adjusted/stratified) WP.

• UCL_WP upper confidence limit for adjusted (or adjusted/stratified) WP.

• SE_WP standard error for the adjusted (or adjusted/stratified) win probability.

• SD_WP standard deviation of the adjusted (or adjusted/stratified) win probability.

• N total number of patients in the analysis.

• Type "STRATIFIED" or "STRATIFIED/ADJUSTED" depending on whether COVAR is specified.

References

Gasparyan SB et al. (2021) "Adjusted win ratio with stratification: calculation methods and interpretation." Statistical Methods in Medical Research 30.2: 580-611. doi:10.1177/0962280220942558.

See Also

stratWO().

Examples

# Stratified win odds
res <- stratWO(x = KHCE, AVAL = "AVAL", TRTP = "TRTP", 
               STRATA = "STRATAN", ref = "P")
res
## Compare with the non-stratified win odds
res0 <- calcWO(AVAL ~ TRTP, data = KHCE,  ref = "P")
res0
## Compare with the win odds in each stratum separately
l <- lapply(split(KHCE, KHCE$STRATAN), calcWO, AVAL = "AVAL", TRTP = "TRTP", ref = "P")
l <- do.call(rbind, l)
l <- l[, c("WO", "LCL", "UCL", "N")]
l$STRATA <- as.numeric(row.names(l))
plot(y = l$WO, x = l$STRATA, ylim = c(0.5, 2.5), log = "y", xlim = c(0, 6),
      ylab = "Win Odds", xlab = "", xaxt = "n")
axis(1, at = 1:6, labels = c(paste0("STR = ", l$STRATA), "Stratified", "Non-stratified"))
arrows(l$STRATA, l$LCL, l$STRATA, 
       l$UCL, angle = 90, code = 3, length = 0.05, col = "darkgreen")
points(5, res$WO)
arrows(5, res$LCL, 5, res$UCL, angle = 90, code = 3, 
       length = 0.05, col = "darkblue")
abline(h = c(1, res$WO), col = "red", lty = 4)
points(6, res0$WO)
arrows(6, res0$LCL, 6, res0$UCL, angle = 90, code = 3, 
       length = 0.05, col = "darkred")
# Stratified and adjusted win odds
res <- stratWO(x = KHCE, AVAL = "AVAL", COVAR = "EGFRBL", 
              TRTP = "TRTP", STRATA = "STRATAN", ref = "P")
res

hce documentation built on June 8, 2025, 11:43 a.m.