library(dplyr, warn.conflicts = FALSE)
library(survival)

test_that("residuals_phregr: null model for right-censored data", {
  pbc <- pbc %>% mutate(event = 1*(status == 2))
  
  for (type in c("martingale", "deviance")) {
    fit1 <- phregr(pbc, time="time", event="event", covariates="")
    rr1 <- residuals_phregr(fit1, type=type)
    
    fit2 <- coxph(Surv(time, event) ~ 1, data=pbc)
    rr2 <- resid(fit2, type=type)
    
    names(rr2) <- NULL
    expect_equal(rr1, rr2)
  }
})


test_that("residuals_phregr: right-censored data with covariates", {
  pbc <- pbc %>% mutate(event = 1*(status == 2))
  
  for (type in c("martingale", "deviance", "score", "schoenfeld", 
                 "dfbeta", "dfbetas", "scaledsch")) {
    fit1 <- phregr(pbc, time="time", event="event", 
                   covariates=c("age", "edema", "log(bili)", 
                                "log(protime)", "log(albumin)"))
    
    rr1 <- residuals_phregr(fit1, type=type)
    
    fit2 <- coxph(Surv(time, event) ~ age + edema + log(bili) + 
                    log(protime) + log(albumin), data=pbc)
    
    rr2 <- resid(fit2, type=type)
    
    if (type=="martingale" || type=="deviance") {
      names(rr2) <- NULL
    } else {
      rownames(rr2) <- NULL
      if (type=="schoenfeld") {
        attr(rr1, "time") <- NULL
      } else if (type=="dfbeta" || type=="dfbetas") {
        colnames(rr1) <- NULL
      }
    }

    expect_equal(rr1, rr2)
  }
})


test_that("residuals_phregr: null model for counting process data", {
  pbcseq <- pbcseq %>% 
    group_by(id) %>%
    arrange(id, day) %>%
    mutate(tstart = day, 
           tstop = ifelse(row_number() != n(), lead(day), futime),
           event = ifelse(row_number() != n(), 0, 1*(status == 2)))
  
  for (type in c("martingale", "deviance")) {
    fit1 <- phregr(pbcseq, time="tstart", time2="tstop", event="event",
                   covariates="", id="id", robust=TRUE)
    
    rr1 <- residuals_phregr(fit1, type=type)
    
    fit2 <- coxph(Surv(tstart, tstop, event) ~ 1, data=pbcseq,
                  cluster=id, robust=TRUE)
    
    rr2 <- resid(fit2, type=type)
    
    names(rr2) <- NULL
    expect_equal(rr1, rr2)
  }
})


test_that("residuals_phregr: counting process data with covariates", {
  pbcseq <- pbcseq %>% 
    group_by(id) %>%
    arrange(id, day) %>%
    mutate(tstart = day, 
           tstop = ifelse(row_number() != n(), lead(day), futime),
           event = ifelse(row_number() != n(), 0, 1*(status == 2)))
  
  for (type in c("martingale", "deviance", "score", "schoenfeld", 
                 "dfbeta", "dfbetas", "scaledsch")) {
    fit1 <- phregr(pbcseq, time="tstart", time2="tstop", event="event",
                   covariates=c("age", "edema", "log(bili)", 
                                "log(protime)", "log(albumin)"),
                   id="id", robust=TRUE)
    
    rr1 <- residuals_phregr(fit1, type=type)
    
    fit2 <- coxph(Surv(tstart, tstop, event) ~ age + edema + log(bili) + 
                    log(protime) + log(albumin), data=pbcseq,
                  cluster=id, robust=TRUE)
    
    rr2 <- resid(fit2, type=type)
    
    if (type=="martingale" || type=="deviance") {
      names(rr2) <- NULL
    } else {
      rownames(rr2) <- NULL
      if (type=="schoenfeld") {
        attr(rr1, "time") <- NULL
      } else if (type=="dfbeta" || type=="dfbetas") {
        colnames(rr1) <- NULL
      }
    }
    
    expect_equal(rr1, rr2)
  }
})