View source: R/vital_status_tt.R
vital_status_tt | R Documentation |
Calculate vital status at end of follow-up depending on pat_status - tidytable version
vital_status_tt( wide_df, status_var = "p_status", life_var_new = "p_alive", check = TRUE, as_labelled_factor = FALSE )
wide_df |
dataframe or data.table 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. |
wide_df
#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_tt(usdata_wide, status_var = "p_status", life_var_new = "p_alive_new", check = TRUE, as_labelled_factor = FALSE)
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