summary.cmm: Summarizing fits of 'cmm' class

In survidm: Inference and Prediction in an Illness-Death Model

Description

Produces a summary of a fitted coxidm model (proportional hazards regression model in each transition of the Illness-Death Model.

Usage

  ## S3 method for class 'cmm'
summary(object, type=NULL, conf.level = 0.95, ...)

Arguments

object	A fitted cmm object as produced by coxidm().
type	Type of summary of the Cox model. Default value is "NULL" that produces a summary of a fitted coxidm model. Possible choices are "anova" and "ph". The "anova" option provides the Analysis of Deviance of the regression model. The "ph" option computes the tests of the proportional hazards assumption of the Cox Regression models.
conf.level	Level for computation of the confidence intervals. If set to FALSE no confidence intervals are printed.
...	Other options.

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 with the Analysis of Deviance or the tests of the Proportional Hazards Assumption of the Cox Regression models.

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)

  summary(cmm2,type = 'anova')

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

  cmm4 <- coxidm(survIDM(time1, event1, Stime, event) ~ rx + sex + age +
                pspline(nodes) + surg + adhere, data = colonIDM)

  summary(cmm4, type = 'ph')
  

survidm documentation built on June 25, 2021, 1:07 a.m.