progression_cdf_fun: Fast implementation of cumulative density function, survival...

In SimNPH: Simulate Non-Proportional Hazards

Fast implementation of cumulative density function, survival function, ... for scenarios with progression

Description

Fast implementation of cumulative density function, survival function, ... for scenarios with progression

Usage

progression_cdf_fun(hazard_before, prog_rate, hazard_after)

progression_surv_fun(hazard_before, prog_rate, hazard_after)

progression_pdf_fun(hazard_before, prog_rate, hazard_after)

progression_haz_fun(hazard_before, prog_rate, hazard_after)

progression_quant_fun(hazard_before, prog_rate, hazard_after)

Arguments

hazard_before	hazard for death before progression
prog_rate	hazard rate for progression
hazard_after	hazard for death after progression

Details

Calculations are done by viewing the disease process as a three state (non-progressed disease, progressed disease, death) continuous time markov chain. Calculations can then easily be done using the matrix exponential function and Q-matrices.

Value

A function with one parameter, a vector of times/probabilities where the function should be evaluated.

Functions

• progression_cdf_fun(): cumulative density function for progression scenario

• progression_surv_fun(): survival function for progression scenario

• progression_pdf_fun(): probability density function for progression scenario

• progression_haz_fun(): hazard function for progression scenario

• progression_quant_fun(): quantile function for progression scenario

Examples

cdf <- progression_cdf_fun(
  hazard_before = m2r(48),
  prog_rate = m2r(18),
  hazard_after = m2r(6)
)
t <- 0:1000
plot(t, cdf(t), type="l")
surv <- progression_surv_fun(
  hazard_before = m2r(48),
  prog_rate = m2r(18),
  hazard_after = m2r(6)
)
t <- 0:1000
plot(t, surv(t), type="l")
pdf <- progression_pdf_fun(
  hazard_before = m2r(48),
  prog_rate = m2r(18),
  hazard_after = m2r(6)
)
t <- 0:1000
plot(t, pdf(t), type="l")
haz <- progression_haz_fun(
  hazard_before = m2r(48),
  prog_rate = m2r(18),
  hazard_after = m2r(6)
)
t <- 0:1000
plot(t, haz(t), type="l")
quant <- progression_quant_fun(
  hazard_before = m2r(48),
  prog_rate = m2r(18),
  hazard_after = m2r(6)
)
p <- seq(0,0.99, by=.01)
plot(p, quant(p), type="l")

SimNPH documentation built on April 12, 2025, 9:13 a.m.