Merge pull request #303 from jdblischak/survival-formula

Do not preface Surv() or strata() with survival:: in formulas
Merck · Jan 9, 2025 · ea88914 · ea88914
2 parents 258a911 + 2d13005
commit ea88914
Show file tree

Hide file tree

Showing 5 changed files with 11 additions and 8 deletions.
diff --git a/NAMESPACE b/NAMESPACE
@@ -54,5 +54,6 @@ importFrom(mvtnorm,GenzBretz)
 importFrom(mvtnorm,pmvnorm)
 importFrom(survival,Surv)
 importFrom(survival,is.Surv)
+importFrom(survival,strata)
 importFrom(survival,survfit)
 useDynLib(simtrial, .registration = TRUE)
diff --git a/R/rmst.R b/R/rmst.R
@@ -126,6 +126,7 @@ rmst <- function(
 #' - `rmst_diff`: the calculation results of RMST differences.
 #'
 #' @importFrom data.table setDF rbindlist
+#' @importFrom survival Surv
 #' @keywords internal
 #'
 #' @examples
@@ -280,7 +281,7 @@ rmst_single_arm <- function(
   stopifnot(0 <= alpha & alpha <= 1)
 
   # Fit a single Kaplan-Meier curve
-  fit <- survival::survfit(survival::Surv(time_var, event_var) ~ 1)
+  fit <- survival::survfit(Surv(time_var, event_var) ~ 1)
 
   # Extract survival probability, number of event, number at risk,
   # and number of censored along with observed time from the fitted model

diff --git a/R/sim_fixed_n.R b/R/sim_fixed_n.R
@@ -70,6 +70,7 @@
 #' @importFrom doFuture "%dofuture%"
 #' @importFrom future nbrOfWorkers plan
 #' @importFrom methods is
+#' @importFrom survival strata Surv
 #'
 #' @export
 #'
@@ -405,12 +406,12 @@ doAnalysis <- function(d, rho_gamma, n_stratum) {
 
   event <- sum(d$event)
   if (n_stratum > 1) {
-    ln_hr <- survival::coxph(survival::Surv(tte, event) ~ (treatment == "experimental") + survival::strata(stratum), data = d)$coefficients
+    ln_hr <- survival::coxph(Surv(tte, event) ~ (treatment == "experimental") + strata(stratum), data = d)$coefficients
     ln_hr <- as.numeric(ln_hr)
     ans$event <- rep(event, nrow(rho_gamma))
     ans$ln_hr <- rep(ln_hr, nrow(rho_gamma))
   } else {
-    ln_hr <- survival::coxph(survival::Surv(tte, event) ~ (treatment == "experimental"), data = d)$coefficients
+    ln_hr <- survival::coxph(Surv(tte, event) ~ (treatment == "experimental"), data = d)$coefficients
     ln_hr <- as.numeric(ln_hr)
     ans$event <- event
     ans$ln_hr <- ln_hr

diff --git a/tests/testthat/test-independent_test_fh_weight.R b/tests/testthat/test-independent_test_fh_weight.R
@@ -11,7 +11,7 @@ test_that("the z values match with the correspondings in fh_weight", {
   max <- TRUE
   alpha <- 0.025
   data.anal <- data.frame(cbind(y$tte, y$event, y$treatment))
-  fit <- survMisc::ten(survival::Surv(y$tte, y$event) ~ y$treatment, data = y)
+  fit <- survMisc::ten(Surv(y$tte, y$event) ~ y$treatment, data = y)
 
   # Testing
   survMisc::comp(fit, p = sapply(wt, function(x) x[1]), q = sapply(wt, function(x) x[2])) |>
@@ -42,7 +42,7 @@ test_that("fh_weight calculated correct correlation value when input a sequence
   max <- TRUE
   alpha <- 0.025
   data.anal <- data.frame(cbind(y$tte, y$event, y$treatment))
-  fit <- survMisc::ten(survival::Surv(y$tte, y$event) ~ y$treatment, data = y)
+  fit <- survMisc::ten(Surv(y$tte, y$event) ~ y$treatment, data = y)
 
   # Testing
   survMisc::comp(fit, p = sapply(wt, function(x) x[1]), q = sapply(wt, function(x) x[2])) |>
@@ -70,7 +70,7 @@ test_that("fh_weight calculated correct correlation value when input a sequence
   d1 <- data.frame(do.call(rbind, wt2))
   wt3 <- unique(wt2)
   d2 <- data.frame(do.call(rbind, wt3))
-  fit2 <- survMisc::ten(survival::Surv(y$tte, y$event) ~ y$treatment, data = y)
+  fit2 <- survMisc::ten(Surv(y$tte, y$event) ~ y$treatment, data = y)
 
   # Testing (for calculating the covariances)
   survMisc::comp(fit2, p = sapply(wt3, function(x) x[1]), q = sapply(wt3, function(x) x[2])) |>

diff --git a/tests/testthat/test-independent_test_pvalue_maxcombo.R b/tests/testthat/test-independent_test_pvalue_maxcombo.R
@@ -12,7 +12,7 @@ test_that("the p-values correspond to pvalue_maxcombo", {
   HT.est <- FALSE
   max <- TRUE
   alpha <- 0.025
-  fit <- survMisc::ten(survival::Surv(y$tte, y$event) ~ y$treatment, data = y)
+  fit <- survMisc::ten(Surv(y$tte, y$event) ~ y$treatment, data = y)
 
   # Testing
   survMisc::comp(fit, p = sapply(wt, function(x) x[1]), q = sapply(wt, function(x) x[2])) |>
@@ -35,7 +35,7 @@ test_that("the p-values correspond to pvalue_maxcombo", {
   d1 <- data.frame(do.call(rbind, wt2))
   wt3 <- unique(wt2)
   d2 <- data.frame(do.call(rbind, wt3))
-  fit2 <- survMisc::ten(survival::Surv(y$tte, y$event) ~ y$treatment, data = y)
+  fit2 <- survMisc::ten(Surv(y$tte, y$event) ~ y$treatment, data = y)
 
   # Testing (for calculating the covariances)
   survMisc::comp(fit2, p = sapply(wt3, function(x) x[1]), q = sapply(wt3, function(x) x[2])) |>