simPH: coxsimPoly – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

coxsimPoly

Simulate quantities of interest for a range of values for a polynomial nonlinear effect from Cox Proportional Hazards models

Description

coxsimPoly simulates quantities of interest for polynomial covariate effects estimated from Cox Proportional Hazards models. These can be plotted with simGG.

Usage

coxsimPoly(
  obj,
  b = NULL,
  qi = "Relative Hazard",
  pow = 2,
  Xj = NULL,
  Xl = NULL,
  nsim = 1000,
  ci = 0.95,
  spin = FALSE,
  extremesDrop = TRUE
)

Arguments

`obj`	a `coxph` class fitted model object with a polynomial coefficient. These can be plotted with `simGG`.
`b`	character string name of the coefficient you would like to simulate. To find the quantity of interest using only the polynomial and not the polynomial + the linear terms enter the polynomial created using `I`, e.g. `I(natreg^2)` as a string.
`qi`	quantity of interest to simulate. Values can be `"Relative Hazard"`, `"First Difference"`, `"Hazard Ratio"`, and `"Hazard Rate"`. The default is `qi = "Relative Hazard"`. If `qi = "Hazard Rate"` and the `coxph` model has strata, then hazard rates for each strata will also be calculated.
`pow`	numeric polynomial used in `coxph`.
`Xj`	numeric vector of fitted values for `b` to simulate for.
`Xl`	numeric vector of values to compare `Xj` to. If `NULL`, then it is automatically set to 0.
`nsim`	the number of simulations to run per value of `Xj`. Default is `nsim = 1000`.
`ci`	the proportion of simulations to keep. The default is `ci = 0.95`, i.e. keep the middle 95 percent. If `spin = TRUE` then `ci` is the confidence level of the shortest probability interval. Any value from 0 through 1 may be used.
`spin`	logical, whether or not to keep only the shortest probability interval rather than the middle simulations. Currently not supported for hazard rates.
`extremesDrop`	logical whether or not to drop simulated quantity of interest values that are `Inf`, `NA`, `NaN` and > 1000000 for `spin = FALSE` or > 800 for `spin = TRUE`. These values are difficult to plot `simGG` and may prevent `spin` from finding the central interval.

Details

Simulates quantities of interest for polynomial covariate effects. For example if a nonlinear effect is modeled with a second order polynomial–i.e. β[1]x[i] + β[2]x[i]^2–we can draw n simulations from the multivariate normal distribution for both β[1] and β[2]. Then we simply calculate quantities of interest for a range of values and plot the results as before. For example, we find the first difference for a second order polynomial with:

FD(h[i](t)) = exp(β[1]x[j-1] + β[2]x[j-l]^2) - 1) * 100

where x[j-l] = x[j] - x[l].

Note, you must use I to create the polynomials.

Value

a simpoly, coxsim object

References

Gandrud, Christopher. 2015. simPH: An R Package for Illustrating Estimates from Cox Proportional Hazard Models Including for Interactive and Nonlinear Effects. Journal of Statistical Software. 65(3)1-20.

Keele, Luke. 2010. ”Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models.” Political Analysis 18(2): 189-205.

Carpenter, Daniel P. 2002. ”Groups, the Media, Agency Waiting Costs, and FDA Drug Approval.” American Journal of Political Science 46(3): 490-505.

King, Gary, Michael Tomz, and Jason Wittenberg. 2000. ”Making the Most of Statistical Analyses: Improving Interpretation and Presentation.” American Journal of Political Science 44(2): 347-61.

Liu, Ying, Andrew Gelman, and Tian Zheng. 2013. ”Simulation-Efficient Shortest Probability Intervals.” Arvix. https://arxiv.org/pdf/1302.2142v1.pdf.

Examples

# Load Carpenter (2002) data
data("CarpenterFdaData")

# Load survival package
library(survival)

# Run basic model
M1 <- coxph(Surv(acttime, censor) ~ prevgenx + lethal + deathrt1 +
            acutediz + hosp01  + hhosleng + mandiz01 + femdiz01 +
            peddiz01 + orphdum + natreg + I(natreg^2) +
            I(natreg^3) + vandavg3 + wpnoavg3 +
            condavg3 + orderent + stafcder, data = CarpenterFdaData)

# Simulate simpoly First Difference
Sim1 <- coxsimPoly(M1, b = "natreg", qi = "First Difference",
                pow = 3, Xj = seq(1, 150, by = 5), nsim = 100)

## Not run: 
# Simulate simpoly Hazard Ratio with spin probibility interval
Sim2 <- coxsimPoly(M1, b = "natreg", qi = "Hazard Ratio",
              pow = 3, Xj = seq(1, 150, by = 5), spin = TRUE)

## End(Not run)

simPH

Simulate and Plot Estimates from Cox Proportional Hazards Models

v1.3.13

GPL-3

Authors

Christopher Gandrud [aut, cre]

Initial release

2021-01-09