Test Proportional Hazards Assumption — test

Assesses the proportional hazards assumption for survival data using a Cox proportional hazards model and related tests.

Usage

test_ph(data, time, event, group, plot_theme = theme_easysurv())

Arguments

data: A data frame containing the survival data.
time: The name of the column in data containing the time-to-event information.
event: The name of the column in data indicating whether the event of interest occurred.
group: The name of the column in data defining the grouping variable.
plot_theme: The theme to be used for the plots.

Value

A list containing plots and test results related to the assessment of the proportional hazards assumption.

cloglog_plot: A plot of the log cumulative hazard function. If the lines are roughly parallel, this suggests that the proportional hazards assumption holds."
coxph_model: The coefficients from the Cox proportional hazards model. The exp(coef) column shows the hazard ratio.
survdiff: The results of the log-rank test for differences in survival curves between groups. A p-value less than 0.05 suggests that survival differences between groups are statistically significant.
coxph_test: The results of the proportional hazards assumption test. A p-value less than 0.05 suggests that the proportional hazards assumption may be violated.
schoenfeld_plot: A plot of the Schoenfeld residuals. A flat smoothed line close to zero supports the proportional hazards assumption. A non-flat smoothed line with a trend suggests the proportional hazards assumption is violated.

Examples

ph_results <- test_ph(
  data = easysurv::easy_bc,
  time = "recyrs",
  event = "censrec",
  group = "group"
)

ph_results
#> 
#> ── Testing Survival Curve Differences ──────────────────────────────────────────
#> ℹ `survival::survdiff()` found a p-value of 0.
#> ✔ suggests survival differences between groups are statistically significant.
#> 
#> ── Testing Proportional Hazards Assumption ─────────────────────────────────────
#> 
#> ── Cox Proportional Hazards Model ──
#> 
#> `survival::coxph()` output:
#> 
#>                  coef exp(coef)  se(coef)        z     Pr(>|z|)
#> groupMedium 0.8401002  2.316599 0.1713926 4.901613 9.505295e-07
#> groupPoor   1.6180720  5.043358 0.1645443 9.833656 8.063728e-23
#> 
#> The exp(coef) column shows the hazard ratios were 2.317 and 5.043.
#> 
#> ℹ `survival::cox.zph()` found a p-value of 0.017.
#> ! suggests the PH assumption may not be valid.
#> 
#> ── Plots ──
#> 
#> ℹ Schoenfeld residuals and log cumulative hazard plots have been printed.
#> ℹ PH tests may not always agree, so consider the results of all tests and plots in totality.
#> ────────────────────────────────────────────────────────────────────────────────
#> → For more information, run `View()` on saved `test_ph()` output.