maicplus (version 0.1.2)

ph_diagplot: Diagnosis plot of proportional hazard assumption for anchored and unanchored

Description

Diagnosis plot of proportional hazard assumption for anchored and unanchored

Usage

ph_diagplot(
  weights_object,
  tte_ipd,
  tte_pseudo_ipd,
  trt_ipd,
  trt_agd,
  trt_common = NULL,
  trt_var_ipd = "ARM",
  trt_var_agd = "ARM",
  endpoint_name = "Time to Event Endpoint",
  time_scale,
  zph_transform = "log",
  zph_log_hazard = TRUE
)

Value

a 3 by 2 plot, include log-cumulative hazard plot, time dependent hazard function and unscaled Schoenfeld residual plot, before and after matching

Arguments

weights_object

an object returned by estimate_weight

tte_ipd

a data frame of individual patient data (IPD) of internal trial, contain at least "USUBJID", "EVENT", "TIME" columns and a column indicating treatment assignment

tte_pseudo_ipd

a data frame of pseudo IPD by digitized KM curves of external trial (for time-to-event endpoint), contain at least "EVENT", "TIME"

trt_ipd

a string, name of the interested investigation arm in internal trial tte_ipd (real IPD)

trt_agd

a string, name of the interested investigation arm in external trial tte_pseudo_ipd (pseudo IPD)

trt_common

a string, name of the common comparator in internal and external trial, by default is NULL, indicating unanchored case

trt_var_ipd

a string, column name in tte_ipd that contains the treatment assignment

trt_var_agd

a string, column name in tte_pseudo_ipd that contains the treatment assignment

endpoint_name

a string, name of time to event endpoint, to be show in the last line of title

time_scale

a string, time unit of median survival time, taking a value of 'years', 'months', 'weeks' or 'days'

zph_transform

a string, pass to survival::cox.zph, default is "log"

zph_log_hazard

a logical, if TRUE (default), y axis of the time dependent hazard function is log-hazard, otherwise, hazard.

Examples

# unanchored example using ph_diagplot
data(weighted_sat)
data(adtte_sat)
data(pseudo_ipd_sat)

ph_diagplot(
  weights_object = weighted_sat,
  tte_ipd = adtte_sat,
  tte_pseudo_ipd = pseudo_ipd_sat,
  trt_var_ipd = "ARM",
  trt_var_agd = "ARM",
  trt_ipd = "A",
  trt_agd = "B",
  trt_common = NULL,
  endpoint_name = "Overall Survival",
  time_scale = "week",
  zph_transform = "log",
  zph_log_hazard = TRUE
)
# anchored example using ph_diagplot
data(weighted_twt)
data(adtte_twt)
data(pseudo_ipd_twt)

ph_diagplot(
  weights_object = weighted_twt,
  tte_ipd = adtte_twt,
  tte_pseudo_ipd = pseudo_ipd_twt,
  trt_var_ipd = "ARM",
  trt_var_agd = "ARM",
  trt_ipd = "A",
  trt_agd = "B",
  trt_common = "C",
  endpoint_name = "Overall Survival",
  time_scale = "week",
  zph_transform = "log",
  zph_log_hazard = TRUE
)