R Under development (unstable) (2023-12-15 r85690 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(survstan) Loading required package: survival > > test_check("survstan") Attaching package: 'dplyr' The following object is masked from 'package:testthat': matches The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Martingale residuals plots available only for models with at least one covariate! Martingale residuals plots available only for models with at least one covariate! Martingale residuals plots available only for models with at least one covariate! Martingale residuals plots available only for models with at least one covariate! `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' `geom_smooth()` using method = 'loess' and formula = 'y ~ x' weibull(aft) 1: Surv(futime, fustat) ~ 1 weibull(aft) 2: Surv(futime, fustat) ~ age weibull(aft) 3: Surv(futime, fustat) ~ age + rx --- loglik LR df Pr(>Chi) weibull(aft) 1: -12.606 -152.311 2 1.0000 weibull(aft) 2: -90.001 2.479 1 0.1154 weibull(aft) 3: -88.762 - - - weibull(aft) 1: Surv(futime, fustat) ~ 1 weibull(aft) 2: Surv(futime, fustat) ~ age weibull(ph) 3: Surv(futime, fustat) ~ age + rx --- loglik LR df Pr(>Chi) weibull(aft) 1: -12.606 -152.311 2 1.0000 weibull(aft) 2: -90.001 2.479 1 0.1154 weibull(ph) 3: -88.762 - - - [ FAIL 0 | WARN 7 | SKIP 0 | PASS 0 ] [ FAIL 0 | WARN 7 | SKIP 0 | PASS 0 ] > > proc.time() user system elapsed 11.09 0.50 11.59