MIpredict: Predict incidence rate estimates after multiple imputation.

In vando026/ahri: R functions for estimating HIV incidence with AHRI data

Predict incidence rate estimates after multiple imputation.

Description

Used with mitools to get incidence rate estimates per 100 person-years after multiple imputation.

Usage

MIpredict(object, newdata)

Arguments

object	Results from the object generated by MIcombine.
newdata	Dataframe of variables for prediction.

Value

data.frame

Examples

rtdat <- getRTData(dat=getHIV())
Args <- setArgs(nSim=2, Years=c(2008:2018))
mdat <- MIdata(rtdat, Args)
mdat <- mitools::imputationList(mdat)
F1 <- "sero_event ~ -1 + as.factor(Year) + Age +
  as.factor(Year):Age + offset(log(tscale))" 
mods <- with(mdat, glm(as.formula(F1), family=poisson))
betas <- mitools::MIextract(mods,fun=coef)
var <- mitools::MIextract(mods, fun=vcov)
res <-  mitools::MIcombine(betas, var) 
MIpredict(object=mods, newdata=getAgeYear(setHIV(Args)))

vando026/ahri documentation built on Aug. 10, 2024, 3:20 p.m.