lnmixsurv (version 3.1.6)

predict.survival_ln_mixture: Predict from a Lognormal Mixture Model

Description

Predict from a Lognormal Mixture Model

Usage

# S3 method for survival_ln_mixture
predict(
  object,
  new_data,
  type,
  eval_time,
  interval = "none",
  level = 0.95,
  ...
)

Value

A tibble of predictions. The number of rows in the tibble is guaranteed to be the same as the number of rows in new_data.

Arguments

object

A survival_ln_mixture object.

new_data

A data frame or matrix of new predictors.

type

A single character. The type of predictions to generate. Valid options are:

• "time" for the survival time. not implmeented

• "survival" for the survival probability.

• "hazard" for the hazard.

eval_time

For type = "hazard" or type = "survival", the times for the distribution.

interval

should interval estimates be added? Options are "none" and "credible".

level

the tail area of the intervals. Default value is 0.95.

...

Not used, but required for extensibility.

Examples

# Categorical variables must be converted to factor before the fit.

require(survival)
# Wrong way of doing
set.seed(1)
mod <- survival_ln_mixture(Surv(time, status == 2) ~ factor(sex), lung, intercept = TRUE)

if (FALSE) {
# this piece of code will throw error
predict(mod, data.frame(sex = 1), type = "survival", eval_time = 100)
}

# Correct way
lung$sex <- factor(lung$sex) # converting to factor before
set.seed(1)
mod2 <- survival_ln_mixture(Surv(time, status == 2) ~ sex, lung, intercept = TRUE)
# Note: the categorical predictors must be a character.
predict(mod2, data.frame(sex = "1"), type = "survival", eval_time = 100)