bootstrap.summary: Based on the output obtained from ipw.bootstrap.ph2 function,...

In xiaoli-mcw/PIcompete: Prevalence-Incidence mixture model for competing risks time-to-event outcomes

Description

Based on the output obtained from ipw.bootstrap.ph2 function, empirical distribution based-variance/-confidence intervals for the estimated regression coefficients, prevalences, cumulative sub-distribution hazards and cumulative incidences for events 1 and 2 are calculated.

Usage

bootstrap.summary(o.input, b.input, p.mat, i.mat1, i.mat2, time.points,
  alpha = 0.05, ...)

Arguments

o.input	the model fit output obtained from ipw.pi.competing function
b.input	the bootstrap output obtained from ipw.bootstrap.ph2 function
p.mat	design matrix for predicting prevalence by using the inverse of logit function; both of vector and matrix types are allowed; the first component or column should include 1 for the intercept.
i.mat1	design matrix for predicting cumulative sub-distribution hazards and cumulative incidences for event 1
i.mat2	design matrix for predicting cumulative sub-distribution hazards and cumulative incidences for event 2
time.points	time points at which cumulative sub-distribution hazards and cumulative incidences for events 1 and 2 are predicted
alpha	The nominal coverage probability is (1-alpha)*100%. Default to 0.05

Value

The output is a list of class ipw.bootstrap.ph2, which contains the following elements.

• reg.covariance empirical distribution based-covariance for the regression coefficients included in o.input

• reg.coef.ci empirical distribution based-confidence intervals for the regression coefficients included in o.input

• prev.ci empirical distribution based-confidence intervals for the predicted prevalence

• subdist.hazard1.ci confidence intervals for the predicted cumulative sub-distribution hazard function for event 1

• subdist.hazard2.ci confidence intervals for the predicted cumulative sub-distribution hazard function for event 2

• cum.inc1.ci confidence intervals for the predicted cumulative incidences for event 1

• cum.inc2.ci confidence intervals for the predicted cumulative incidences for event 2

• trans.r the transformation parameters used in the bootstrap summary

• p.mat the input information, the design matrix for prevalence

• i.mat1 the input information, the design matrix for cumulative sub-distribution hazard and cumulative incidence for event 1

• i.mat2 the input information, the design matrix for cumulative sub-distribution hazard and cumulative incidence for event 1

Author(s)

Noorie Hyun, [e-mail], Xiao Li [e-mail]

References

• Hyun N, Katki HA, Graubard BI. Sample-Weighted Semiparametric Estimation of Cause-Specific Cumulative Risk and Incidence Using Left or Interval-Censored Data from Electronic Health Records. Statistics in Medicine 2020; under the 2nd review.

xiaoli-mcw/PIcompete documentation built on May 20, 2020, 7:44 p.m.