1.0.3

jinseob2kim · Jun 24, 2021 · 9418241 · 9418241
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Showing 5 changed files with 13 additions and 11 deletions.
diff --git a/CRAN-RELEASE b/CRAN-RELEASE
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: jstable
 Title: Create Tables from Different Types of Regression
-Version: 1.0.2
-Date: 2021-03-13
+Version: 1.0.3
+Date: 2021-06-24
 Authors@R: c(person("Jinseob", "Kim", email = "[email protected]", role = c("aut", "cre"),  comment = c(ORCID = "0000-0002-9403-605X")),
              person("Zarathu", role = c("cph", "fnd"))
              )
@@ -11,7 +11,7 @@ License: Apache License 2.0
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.1.1
-Imports: geepack, lme4, stats, data.table, labelled, tableone, coxme, survival (>= 3.0.0), survey, methods, dplyr, purrr, magrittr, tibble, car
+Imports: geepack, lme4, stats, data.table, labelled, tableone, coxme, survival (>= 3.0.0), survey, methods, dplyr, purrr, magrittr, tibble
 URL: https://github.com/jinseob2kim/jstable
 BugReports: https://github.com/jinseob2kim/jstable/issues
 Suggests: 

diff --git a/NAMESPACE b/NAMESPACE
@@ -33,7 +33,6 @@ export(svyCreateTableOne2)
 export(svyCreateTableOneJS)
 export(svycox.display)
 export(svyregress.display)
-importFrom(car,Anova)
 importFrom(coxme,coxme)
 importFrom(coxme,fixef)
 importFrom(data.table,":=")

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,9 @@
+# jstable 1.0.3
+
+* Remove dependency with `car` packages
+
+
+
 # jstable 1.0.2
 
 * Bugfix `CreateTableOneJS`, `svyCreateTableOneJS`: when with labeldata, variables other than numeric or factor types are excluded.  

diff --git a/R/forestcox.R b/R/forestcox.R
@@ -40,7 +40,6 @@
 #' @importFrom survival coxph
 #' @importFrom survey svycoxph
 #' @importFrom stats confint coefficients
-#' @importFrom car Anova
 #' @importFrom utils tail
 
 TableSubgroupCox <- function(formula, var_subgroup = NULL, var_cov = NULL, data, time_eventrate = 3 * 365, decimal.hr = 2, decimal.percent = 1, decimal.pvalue = 3){
@@ -127,8 +126,8 @@ TableSubgroupCox <- function(formula, var_subgroup = NULL, var_cov = NULL, data,
         model.int <- survival::coxph(as.formula(gsub(xlabel, paste(xlabel, "*", var_subgroup, sep=""), deparse(formula))), data = data.int, weights = get(names(data$allprob)), robust =T)
         model.int$call$formula <- as.formula(gsub(xlabel, paste(xlabel, "*", var_subgroup, sep=""), deparse(formula)))
         model.int$call$data <- as.name("data.int")
-        pv_anova <- car::Anova(model.int, test.statistics = "Wald")
-        pv_int <- pv_anova[nrow(pv_anova), 3]
+        pv_anova <- anova(model.int)
+        pv_int <- pv_anova[nrow(pv_anova), 4]
       }
       res.kap <- purrr::map(label_val, ~survey::svykm(formula.km, design = subset(data, get(var_subgroup) == . )))
       mkz <- function(reskap){
@@ -151,8 +150,8 @@ TableSubgroupCox <- function(formula, var_subgroup = NULL, var_cov = NULL, data,
       if (length(label_val) > 2){
         model.int$call$formula <- as.formula(gsub(xlabel, paste(xlabel, "*", var_subgroup, sep=""), deparse(formula)))
         model.int$call$data <- as.name("data")
-        pv_anova <- car::Anova(model.int, test.statistics = "Wald")
-        pv_int <- round(pv_anova[nrow(pv_anova), 3], decimal.pvalue)
+        pv_anova <- anova(model.int)
+        pv_int <- round(pv_anova[nrow(pv_anova), 4], decimal.pvalue)
       }
       res.kap.times <- data %>% filter(!is.na(get(var_subgroup))) %>% group_split(get(var_subgroup)) %>% purrr::map(~survival::survfit(formula.km, data = .)) %>% purrr::map(~summary(., times = time_eventrate, extend = T))
       prop <- res.kap.times %>% purrr::map(~round(100 * (1 - .[["surv"]]), decimal.percent)) %>% dplyr::bind_cols() %>% t