Nothing
## ---- echo = FALSE, message = FALSE-------------------------------------------
#knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(Matrix)
library(nlme)
library(survival)
library(joineRML)
if (requireNamespace('joineR', quietly = TRUE)) {
library('joineR')
} else {
message("'joineR' not available")
}
## ----vignette, eval=FALSE-----------------------------------------------------
# vignette("technical", package = "joineRML")
## ----heart.valve_help, eval=FALSE---------------------------------------------
# help("heart.valve", package = "joineRML")
## ----heart.valve_data---------------------------------------------------------
library("joineRML")
data("heart.valve")
head(heart.valve)
## ----heart.valve_dimnames-----------------------------------------------------
dim(heart.valve)
names(heart.valve)
## ----hvd_data-----------------------------------------------------------------
hvd <- heart.valve[!is.na(heart.valve$grad) & !is.na(heart.valve$lvmi), ]
## ----hvd_model_fit, cache=TRUE------------------------------------------------
set.seed(12345)
fit <- mjoint(
formLongFixed = list("grad" = log.grad ~ time + sex + hs,
"lvmi" = log.lvmi ~ time + sex),
formLongRandom = list("grad" = ~ 1 | num,
"lvmi" = ~ time | num),
formSurv = Surv(fuyrs, status) ~ age,
data = list(hvd, hvd),
inits = list("gamma" = c(0.11, 1.51, 0.80)),
timeVar = "time")
## ----hvd_model_summary--------------------------------------------------------
summary(fit)
## ----hvd_model_generics-------------------------------------------------------
coef(fit)
fixef(fit, process = "Longitudinal")
fixef(fit, process = "Event")
head(ranef(fit))
## ----hvd_model_conv, fig.height=8, fig.width=7.25-----------------------------
plot(fit, params = "gamma")
plot(fit, params = "beta")
## ----hvd_model_boot, eval=FALSE-----------------------------------------------
# fit.se <- bootSE(fit, nboot = 100)
## ----hvd_model_boot_print, eval=FALSE-----------------------------------------
# fit.se
## ----hvd_model_boot_summary, eval=FALSE---------------------------------------
# summary(fit, bootSE = fit.se)
## ----joineR_require, echo=FALSE, message=FALSE--------------------------------
joineR_available <- require(joineR)
## ----joineR, cache=TRUE, eval=joineR_available--------------------------------
library(joineR, quietly = TRUE)
hvd.surv <- UniqueVariables(hvd, var.col = c("fuyrs", "status"), id.col = "num")
hvd.cov <- UniqueVariables(hvd, "age", id.col = "num")
hvd.long <- hvd[, c("num", "time", "log.lvmi")]
hvd.jd <- jointdata(longitudinal = hvd.long,
baseline = hvd.cov,
survival = hvd.surv,
id.col = "num",
time.col = "time")
fit.joiner <- joint(data = hvd.jd,
long.formula = log.lvmi ~ time + age,
surv.formula = Surv(fuyrs, status) ~ age,
model = "intslope")
summary(fit.joiner)
## ----joineRML, cache=TRUE-----------------------------------------------------
set.seed(123)
fit.joinerml <- mjoint(formLongFixed = log.lvmi ~ time + age,
formLongRandom = ~ time | num,
formSurv = Surv(fuyrs, status) ~ age,
data = hvd,
timeVar = "time")
summary(fit.joinerml)
## ----re_comp_plot, fig.width=7.25, fig.height=4, eval=joineR_available--------
id <- as.numeric(row.names(fit.joiner$coefficients$random))
id.ord <- order(id) # joineR rearranges patient ordering during EM fit
par(mfrow = c(1, 2))
plot(fit.joiner$coefficients$random[id.ord, 1], ranef(fit.joinerml)[, 1],
main = "Predicted random intercepts",
xlab = "joineR", ylab = "joineRML")
grid()
abline(a = 0, b = 1, col = 2, lty = "dashed")
plot(fit.joiner$coefficients$random[id.ord, 2], ranef(fit.joinerml)[, 2],
main = "Predicted random slopes",
xlab = "joineR", ylab = "joineRML")
grid()
abline(a = 0, b = 1, col = 2, lty = "dashed")
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