## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(marlod) ## ----------------------------------------------------------------------------- y <- c(0,0,0,3.06,4.41,7.23,8.29,9.52,19.94,20.25) ## Limit of detection (LOD) = 3 lod <- 3 Fillin(y, lod, "BetaMean") Fillin(y, lod, "BetaGM") ## ----------------------------------------------------------------------------- data(simdata15) head(simdata15) ## ----------------------------------------------------------------------------- id=as.matrix(as.vector(t(simdata15$id))) y=as.matrix(as.vector(t(simdata15$y))) x1=as.matrix(as.vector(t(simdata15$x1))) x2=as.matrix(as.vector(t(simdata15$x2))) x=cbind(x1,x2) ## LOD = 2 is equivalent to detection proportion = 56.3% (censoring proportion = 43.7%). lod=2 ## Intercept is not included in the "x" and "typed". ## Modified.GEE(id, y, x, lod, substitue, corstr, typetd, maxiter) Modified.GEE(id, y, x, lod, "QQplot", "AR-1", c(1,1), 1000) ## ----------------------------------------------------------------------------- ## Gets initial estimates for the QIF approach through independence structure initial=glm(y ~ x1 + x2, data=simdata15, family=gaussian) beta_initial=as.matrix(initial$coefficients) ## Intercept is not included in the "x" and "typed". ## Modified.QIF(id, y, x, lod, substitue, corstr, beta, typetd, maxiter) Modified.QIF(id, y, x, lod, "QQplot", "exchangeable", beta_initial, c(1,1), 1000) ## ----------------------------------------------------------------------------- ## Gets initial estimates for the GMM approach through independence structure initial=glm(y ~ x1 + x2, data=simdata15, family=gaussian) beta_initial=as.matrix(initial$coefficients) ## Intercept is not included in the "x" and "typed". ## Modified.GMM(id, y, x, lod, substitue, beta, maxiter) Modified.GMM(id, y, x, lod, "QQplot", beta_initial, 1000) ## ----------------------------------------------------------------------------- data(simdata58) head(simdata58) ## ----------------------------------------------------------------------------- id=as.matrix(as.vector(t(simdata58$id))) y=as.matrix(as.vector(t(simdata58$y))) x1=as.matrix(as.vector(t(simdata58$x1))) ## LOD = 0.05 is equivalent to detection proportion = 50.7% (censoring proportion = 49.3%). lod=0.05 ## Intercept is not included in the "x". ## Selected.GEE(id, y, x, lod, substitue, corstr, maxiter) Selected.GEE(id, y, x1, lod, "MIWithID", "AR-1", 1000) ## ----------------------------------------------------------------------------- id=as.matrix(as.vector(t(simdata58$id))) y=as.matrix(as.vector(t(simdata58$y))) x1=as.matrix(as.vector(t(simdata58$x1))) Modified.GEE(id, y, x1, lod, "MIWithID", "AR-1", c(3), 1000) ## ----------------------------------------------------------------------------- ## Gets initial estimates for the QIF approach through independence structure initial=glm(y ~ x1, data=simdata58, family=gaussian) beta_initial=as.matrix(initial$coefficients) ## Intercept is not included in the "x" and "typed". ## Selected.QIF(id, y, x, lod, substitue, corstr, beta, maxiter) Selected.QIF(id, y, x1, lod, "MIWithID", "AR-1", beta_initial, 1000) ## ----------------------------------------------------------------------------- y=as.matrix(as.vector(t(simdata15$y))) x1=as.matrix(as.vector(t(simdata15$x1))) x2=as.matrix(as.vector(t(simdata15$x2))) x=cbind(matrix(1,length(x1),1),x1,x2) ## LOD = 2 is equivalent to detection proportion = 56.3% (censoring proportion = 43.7%). lod=2 ## Median or 50th quantile is given. tau=0.5 ## Intercept is included in the "x" but not in the "typed". ## Quantile.FWZ(y, x, lod, substitue, tau, corstr, typetd, data) Quantile.FWZ(y, x, lod, "LOD2", tau, "exchangeable", c(1,1), simdata15) ## ----------------------------------------------------------------------------- y=as.matrix(as.vector(t(simdata58$y))) x1=as.matrix(as.vector(t(simdata58$x1))) x=cbind(matrix(1,length(x1),1),x1) ## LOD = 0.05 is equivalent to detection proportion = 50.7% (censoring proportion = 49.3%). lod=0.05 ## 95th quantile is given. tau=0.95 ## Intercept is included in the "x". ## Quantile.select.FWZ(y, x, lod, substitue, tau, data) Quantile.select.FWZ(y, x, lod, "LOD2", tau, simdata58) ## ----------------------------------------------------------------------------- y=as.matrix(as.vector(t(simdata58$y))) x1=as.matrix(as.vector(t(simdata58$x1))) x=cbind(matrix(1,length(x1),1),x1) ## LOD = 0.05 is equivalent to detection proportion = 50.7% (censoring proportion = 49.3%). lod=0.05 ## 95th quantile is given. tau=0.95 ## Intercept is included in the "x" but not in the "typed". ## Quantile.FWZ(y, x, lod, substitue, tau, corstr, typetd, data) Quantile.FWZ(y, x, lod, "LOD2", tau, "AR-1", c(2), simdata58)