coxidm {survidm}

Fit proportional hazards regression model in each transition of the Illness-Death Model.

Description

Fits a Cox proportional hazards regression model for each transition.

Usage

coxidm(formula, data, semiMarkov = FALSE)

Arguments

formula

A formula object, which must have a survIDM object as the response on the left of the ~ operator and, if desired, a term on the right. The term may be a qualitative or quantitative variable. Without covariates, the right hand side should be ~ 1.

data

A data.frame including at least four columns named time1, event1, Stime and event, which correspond to disease free survival time, disease free survival indicator, time to death or censoring, and death indicator, respectively.

semiMarkov

By default, FALSE.

Value

A data frame or a list containing the following components:

coef

Estimated coeficients.

exp(coef)

Exponent of the estimated coefficients.

lower 0.95

Lower limit of the confidence interval.

upper 0.95

Upper limit of the confidence interval.

pvalue

obtained pvalue testing that the coefficient is equals to zero.

Other data frames or lists:

anova

Analysis of Deviance for the Cox Regression models.

zph

Test the Proportional Hazards Assumption of the Cox Regression models.

term

Predicted values of splines and partial residual for the terms of the model.

Author(s)

Luis Meira-Machado, Marta Sestelo and Gustavo Soutinho.

Examples

  cmm1 <- coxidm(survIDM(time1, event1, Stime, event) ~ age, data = colonIDM)
  summary(cmm1, conf.level = 0.95)

  cmm2 <- coxidm(survIDM(time1, event1, Stime, event) ~ rx + sex + age + nodes,
                 data = colonIDM)
  summary(cmm2)

  cmm3 <- coxidm(survIDM(time1, event1, Stime, event) ~ rx + sex + age + nodes,
                 data = colonIDM, semiMarkov = TRUE)
  summary(cmm3)