## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 4 ) ## ----setup-------------------------------------------------------------------- library(clusteredMSM) # 1=Healthy, 2=Ill, 3=Dead. Allowed: 1->2, 1->3, 2->3. tmat <- trans_mat( list(c(2, 3), 3, integer(0)), names = c("Healthy", "Ill", "Dead") ) tmat ## ----data--------------------------------------------------------------------- mydata <- data.frame( pid = c(1, 1, 2, 3, 4, 4), site = c(1, 1, 1, 2, 2, 2), treatment = c("A", "A", "A", "B", "B", "B"), t0 = c(0.0, 1.5, 0.0, 0.0, 0.0, 1.0), t1 = c(1.5, 3.0, 2.0, 1.0, 1.0, 2.5), s0 = c(1, 2, 1, 1, 1, 2), s1 = c(2, 3, 1, 3, 2, 3) ) mydata ## ----estimate, eval = FALSE--------------------------------------------------- # fit <- patp( # msm(t0, t1, s0, s1) ~ 1, # data = mydata, # tmat = tmat, # id = "pid", # cluster = "site", # h = 1, j = 2, s = 0, # B = 1000, cband = TRUE, # seed = 1 # ) # fit ## ----test, eval = FALSE------------------------------------------------------- # tt <- patp( # msm(t0, t1, s0, s1) ~ treatment, # data = mydata, # tmat = tmat, # id = "pid", # cluster = "site", # h = 1, j = 2, s = 0, # B = 1000, # seed = 1 # ) # tt ## ----recovery, eval = FALSE--------------------------------------------------- # tmat_rec <- trans_mat( # list(c(2, 3), c(1, 3), integer(0)), # names = c("Healthy", "Ill", "Dead") # ) # # # Subject who went Healthy -> Ill -> Healthy -> censored: # recovery_data <- data.frame( # pid = c(1, 1, 1), # t0 = c(0.0, 1.0, 2.0), # t1 = c(1.0, 2.0, 3.5), # s0 = c(1, 2, 1), # s1 = c(2, 1, 1) # last row: censored healthy # ) # # patp(msm(t0, t1, s0, s1) ~ 1, # data = recovery_data, tmat = tmat_rec, # id = "pid", # h = 1, j = 2, s = 0, # B = 500, seed = 1) ## ----lmaj, eval = FALSE------------------------------------------------------- # patp(msm(t0, t1, s0, s1) ~ 1, # data = mydata, tmat = tmat, # id = "pid", cluster = "site", # h = 1, j = 2, s = 1.0, # LMAJ = TRUE, B = 1000, seed = 1) ## ----weighted, eval = FALSE--------------------------------------------------- # patp(msm(t0, t1, s0, s1) ~ 1, # data = mydata, tmat = tmat, # id = "pid", cluster = "site", # h = 1, j = 2, s = 0, # weighted = TRUE, B = 1000, seed = 1)