vital_status {msSPChelpR} | R Documentation |
Determine vital status at end of follow-up depending on pat_status - tidyverse version
Description
Determine vital status at end of follow-up depending on pat_status - tidyverse version
Usage
vital_status(
wide_df,
status_var = "p_status",
life_var_new = "p_alive",
check = TRUE,
as_labelled_factor = FALSE
)
Arguments
wide_df |
dataframe in wide format |
status_var |
Name of the patient status variable that was previously created. Default is p_status. |
life_var_new |
Name of the newly calculated variable for patient vital status. Default is p_alive. |
check |
Check newly calculated variable life_var_new by printing frequency table. Default is TRUE. |
as_labelled_factor |
If true, output life_var_new as labelled factor variable. Default is FALSE. |
Value
wide_df
Examples
#load sample data
data("us_second_cancer")
#prep step - make wide data as this is the required format
usdata_wide <- us_second_cancer %>%
msSPChelpR::reshape_wide_tidyr(case_id_var = "fake_id",
time_id_var = "SEQ_NUM", timevar_max = 10)
#prep step - calculate p_spc variable
usdata_wide <- usdata_wide %>%
dplyr::mutate(p_spc = dplyr::case_when(is.na(t_site_icd.2) ~ "No SPC",
!is.na(t_site_icd.2) ~ "SPC developed",
TRUE ~ NA_character_)) %>%
dplyr::mutate(count_spc = dplyr::case_when(is.na(t_site_icd.2) ~ 1,
TRUE ~ 0))
#prep step - create patient status variable
usdata_wide <- usdata_wide %>%
msSPChelpR::pat_status(., fu_end = "2017-12-31", dattype = "seer",
status_var = "p_status", life_var = "p_alive.1",
birthdat_var = "datebirth.1", lifedat_var = "datedeath.1")
#now we can run the function
msSPChelpR::vital_status(usdata_wide,
status_var = "p_status",
life_var_new = "p_alive_new",
check = TRUE,
as_labelled_factor = FALSE)
[Package msSPChelpR version 0.9.1 Index]