Nothing
###############################################################################
context("testing returning residual for survival")
test_that("testing returning residual for survival", {
data_for_survival <- survival::lung
surv_estimated <- use_parametric_survival("status", data_for_survival, "sex",
info_distribution = "weibull",
covariates = c("ph.ecog"), "time"
)
plot_return_residual_survival("status", "sex",
covariates = c("ph.ecog"), surv_estimated$fit)
data_for_survival <- data_for_survival[!is.na(data_for_survival$meal.cal), ]
surv_estimated <- use_parametric_survival("status", data_for_survival, "sex",
info_distribution = "weibull",
covariates = c("ph.ecog"), "time",
cluster_var = "meal.cal"
)
plot_return_residual_survival("status", "sex",
covariates = c("ph.ecog"),
surv_estimated$fit)
#Error - parameter to be estimated can not be NA
expect_error(plot_return_residual_survival(NA, "sex",
covariates = c("ph.ecog"), surv_estimated$fit))
#Error - independent variable can not be NULL
expect_error(plot_return_residual_survival("status", NULL,
covariates = c("ph.ecog"), surv_estimated$fit))
#Error - fit should be of survreg object
expect_error(plot_return_residual_survival("status", "sex",
covariates = c("ph.ecog"), "fit"))
})
###############################################################################
context("testing plotting prediction parameteric survival")
test_that("testing plotting prediction parameteric survival", {
data_for_survival <- survival::lung
surv_estimated <- use_parametric_survival("status", data_for_survival, "sex",
info_distribution = "weibull",
covariates = c("ph.ecog"), "time")
newdata <- data_for_survival
newdata[newdata$sex == 2, ]$sex <- "male"
newdata[newdata$sex == 1, ]$sex <- "female"
surv_estimated <- use_parametric_survival("status", newdata, "sex",
info_distribution = "weibull",
covariates = NA, "time")
plot_prediction_parametric_survival("status", "sex", covariates = NA,
newdata, surv_estimated$fit,
"time")
surv_estimated <- use_parametric_survival("status", data_for_survival, "sex",
info_distribution = "weibull",
covariates = NA, "time")
plot_prediction_parametric_survival("status", "sex", covariates = NA,
data_for_survival, surv_estimated$fit,
"time")
surv_estimated <- use_parametric_survival("status", data_for_survival, "sex",
info_distribution = "weibull",
covariates = c("ph.ecog"),
"time")
plot_prediction_parametric_survival("status", "sex",
covariates = c("ph.ecog"), data_for_survival,
surv_estimated$fit,
"time")
#Error - parameter to be estimated can not be NA
expect_error(plot_prediction_parametric_survival(NA, "sex",
covariates = c("ph.ecog"), data_for_survival, surv_estimated$fit,
"time"))
#Error - independent variable can not be NULL
expect_error(plot_prediction_parametric_survival("status", NULL,
covariates = c("ph.ecog"), data_for_survival,
surv_estimated$fit, "time"))
#Error - dataset should not be NULL
expect_error(plot_prediction_parametric_survival("status", "sex",
covariates = c("ph.ecog"), NULL, surv_estimated$fit, "time"))
#Error - fit object should be of survreg type
expect_error(plot_prediction_parametric_survival("status", "sex",
covariates = c("ph.ecog"), data_for_survival, "fit", "time"))
#Error - time variable can not be NULL
expect_error(plot_prediction_parametric_survival("status", "sex",
covariates = c("ph.ecog"), data_for_survival, surv_estimated$fit, NULL))
})
###############################################################################
context("testing creating a new dataset based on given one")
test_that("testing creating a new dataset based on given one", {
dataset <- survival::lung
temp <- sample(c("no", "yes"), nrow(dataset), replace = T)
dataset[["check"]] <- temp
new <- create_new_dataset("status", c("check"), dataset, c(TRUE))
expect_equal(unique(new$check), "no")
new <- create_new_dataset("status", c("age"), dataset, c(FALSE))
expect_equal(unique(new$age), 62.4437, tol = 1e-3)
#Error -var null or Na
expect_error(create_new_dataset(NULL, c("age"), dataset, c(FALSE)))
expect_error(create_new_dataset(NA, c("age"), dataset, c(FALSE)))
# Error- dataset null
expect_error(create_new_dataset("status", c("age"), NULL, c(FALSE)))
# Error- column not in dataset
expect_error(create_new_dataset("status", c("age1"), dataset, c(FALSE)))
expect_error(create_new_dataset("status1", c("age"), dataset, c(FALSE)))
df <- data.frame(status = c(1, 2),
age = c(62.44737, 62.44737))
expect_equal(create_new_dataset("status", c("age"), dataset,
c(FALSE)), df, tol = 1e-3)
})
###############################################################################
context("testing plotting survival function")
test_that("testingplotting survival function", {
data_for_survival <- survival::lung
data_for_survival <- na.omit(data_for_survival)
plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = "time")
plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = "sex", covariates = NA,
timevar_survival = "time")
#Error - parameter to be estimated can not be NA or NULL
expect_error(plot_return_survival_curve(param_to_be_estimated = NULL,
dataset = data_for_survival,
indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = "time"))
expect_error(plot_return_survival_curve(param_to_be_estimated = NA,
dataset = data_for_survival,
indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = "time"))
#Error -data set can not be NULL
expect_error(plot_return_survival_curve(param_to_be_estimated = "status",
dataset = NULL, indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = "time"))
#Error -independent variable can not be NULL or NA
expect_error(plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = NULL,
covariates = c("ph.ecog"),
timevar_survival = "time"))
expect_error(plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = NA, covariates = c("ph.ecog"),
timevar_survival = "time"))
#Error -time variable can not be NULL or NA
expect_error(plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = NULL))
expect_error(plot_return_survival_curve(param_to_be_estimated = "status",
dataset = data_for_survival,
indep_var = "sex",
covariates = c("ph.ecog"),
timevar_survival = NA))
})
###############################################################################
context("testing plotting residual for cox ph models")
test_that("testing plotting residual for cox ph models", {
data_for_survival <- survival::lung
data_for_survival <- na.omit(data_for_survival)
surv_estimated <- use_coxph_survival("status", data_for_survival, "sex",
covariates = c("ph.ecog"), "time")
plot_return_residual_cox("status", "sex", covariates = NA,
surv_estimated$fit, data_for_survival)
plot_return_residual_cox("status", "sex", covariates = c("ph.ecog"),
surv_estimated$fit, data_for_survival)
#Error - param to be estimated can not be null or NA
expect_error(plot_return_residual_cox(NULL, "sex",
covariates = c("ph.ecog"),
surv_estimated$fit,
data_for_survival))
expect_error(plot_return_residual_cox(NA, "sex",
covariates = c("ph.ecog"),
surv_estimated$fit,
data_for_survival))
#Error - independent variable can not be null or na
expect_error(plot_return_residual_cox("status", NULL,
covariates = c("ph.ecog"),
surv_estimated$fit,
data_for_survival))
expect_error(plot_return_residual_cox("status", NA,
covariates = c("ph.ecog"),
surv_estimated$fit,
data_for_survival))
# Error - fit object is not of type coxph
expect_error(plot_return_residual_cox("status", "sex",
covariates = c("ph.ecog"),
"fit", data_for_survival))
})
###############################################################################
context("testing plotting residual for cox ph models")
test_that("testing plotting residual for cox ph models", {
data_for_survival <- survival::lung
data_for_survival <- na.omit(data_for_survival)
surv_estimated <- use_coxph_survival("status", data_for_survival, "sex",
covariates = c("ph.ecog"), "time")
predict_coxph(surv_estimated$fit, data_for_survival, "status", "sex",
covariates = c("ph.ecog"), "time")
#Error - fit object is not of coxph type
expect_error(predict_coxph("fit", data_for_survival, "status", "sex",
covariates = c("ph.ecog"), "time"))
#Error - dataset should not be NULL
expect_error(predict_coxph(surv_estimated$fit, NULL, "status", "sex",
covariates = c("ph.ecog"), "time"))
#Error - param to be estimated should not be NULL or NA
expect_error(predict_coxph(surv_estimated$fit, data_for_survival, NULL, "sex",
covariates = c("ph.ecog"), "time"))
expect_error(predict_coxph(surv_estimated$fit, data_for_survival, NA, "sex",
covariates = c("ph.ecog"), "time"))
#Error - independent varaible should not be NULL or NA
expect_error(predict_coxph(surv_estimated$fit, data_for_survival,
"status", NULL,
covariates = c("ph.ecog"), "time"))
expect_error(predict_coxph(surv_estimated$fit, data_for_survival,
"status", NA,
covariates = c("ph.ecog"), "time"))
#Error -time variable should not be NULL or NA
expect_error(predict_coxph(surv_estimated$fit, data_for_survival, "status",
"sex", covariates = c("ph.ecog"), NULL))
expect_error(predict_coxph(surv_estimated$fit, data_for_survival, "status",
"sex", covariates = c("ph.ecog"), NA))
})
###############################################################################
context("testing plotting residual for cox ph models")
test_that("testing plotting residual for cox ph models", {
data_for_survival <- survival::lung
data_for_survival <- na.omit(data_for_survival)
surv_estimated <- use_coxph_survival("status", data_for_survival, "sex",
covariates = c("ph.ecog"), "time")
plot_survival_cox_covariates(surv_estimated$fit, data_for_survival, "status",
covariates = c("ph.ecog"), "sex")
new_data <- data_for_survival
new_data[new_data$sex == 1, ]$sex <- "F"
new_data[new_data$sex == 2, ]$sex <- "M"
surv_estimated <- use_coxph_survival("status", new_data, "sex",
covariates = c("ph.ecog"), "time")
plot_survival_cox_covariates(surv_estimated$fit, new_data, "status",
covariates = c("ph.ecog"), "age")
surv_estimated <- use_coxph_survival("status", data_for_survival, "sex",
covariates = NA, "time")
plot_survival_cox_covariates(surv_estimated$fit, data_for_survival, "status",
covariates = NA, "sex")
#Error - fit object is not of coxph type
expect_error(plot_survival_cox_covariates("fit", data_for_survival,
"status",
covariates = c("ph.ecog"), "sex"))
#Error - dataset should not be NULL
expect_error(plot_survival_cox_covariates(surv_estimated$fit,
NULL, "status",
covariates = c("ph.ecog"), "sex"))
#Error - param to be estimated should not be NULL or NA
expect_error(plot_survival_cox_covariates(surv_estimated$fit,
data_for_survival, NULL,
covariates = c("ph.ecog"), "sex"))
expect_error(predict_coxph(surv_estimated$fit, data_for_survival, NA,
covariates = c("ph.ecog"), "sex", NA))
#Error - independent varaible should not be NULL or NA
expect_error(plot_survival_cox_covariates(surv_estimated$fit,
data_for_survival, "status",
covariates = c("ph.ecog"), NULL))
expect_error(plot_survival_cox_covariates(surv_estimated$fit,
data_for_survival, "status",
covariates = c("ph.ecog"), NA))
})
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