# Indexed HQM hazard estimator for one bootstrap sample Compute the bootstrap estimate of the indexed HQM hazard estimate for a single (bootstrap) sample. The function is meant to be used internally for the calculation of confidence intervals ```r Boot.hqm(in.par, data, data.id, ls, X1, XX1, event_time_name = 'years', time_name = 'year', event_name = 'status2', b, t) ``` ## Arguments - `in.par`: Numeric vector, the values of the indexing parameters. - `data`: Bootstrap data.frame. - `data.id`: Id-level data.frame (result of to_id). - `ls`: user supplied grid length on the time_name argument. - `X1`: List of vectors for indexing: each vector corresponds to a biomarker and contains one summary measurement per individual. - `XX1`: List of vectors for indexing: each vector corresponds to a single biomarker and contains its longitudinal measurements across all individuals/time points. - `event_time_name`: Name of event time column. - `time_name`: Name of observation time column. - `event_name`: Name of event indicator column. - `b`: Bandwidth parameter. - `t`: Conditioning level. ## Returns Numeric vector with estimated hazard on the grid. ## Examples ```r #Single instance of the bootstrap version of the bootstrap version #of the indexed HQM estimator b.alb = 0.9 b.bil = 4 t.alb = 1 # refers to zero mean variables - slightly high t.bil = 1.9 # refers to zero mean variable - high par.alb <- 0.0702 #0.149 par.bil <- 0.0856 #0.10 b = 0.42 # The result, on the indexed marker 'indmar' of #\code{b_selection(pbc2, 'indmar', 'years', 'year', 'status2', I=26, seq(0.2,0.4,by=0.01))} t = t.alb * par.alb + t.bil *par.bil marker_name1 <- 'albumin' marker_name2 <- 'serBilir' event_time_name <- 'years' time_name <- 'year' event_name <- 'status2' id<-'id' ls<-50 data.use<-pbc2 data.use.id<-to_id(data.use) data.use.id<-data.use.id[complete.cases(data.use.id), ] # mean adjust the data: X1t=data.use[,marker_name1] -mean(data.use[, marker_name1]) XX1t=data.use.id[,marker_name1] -mean(data.use.id[, marker_name1]) X2t=data.use[,marker_name2] -mean(data.use[, marker_name2]) XX2t=data.use.id[,marker_name2] -mean(data.use.id[, marker_name2]) X1=list(X1t, X2t) XX1=list(XX1t, XX2t) boot.haz<-Boot.hqm (c(par.alb,par.bil), data.use, data.use.id, ls=ls, X1, XX1, event_time_name = 'years', time_name = 'year', event_name = 'status2', b, t) ```

Boot.hqm function