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library(mvtnorm) | |
### correlation for the bivariate normal distribution | |
rho <- 0.4 | |
### number of points for x and y at which to evaluate the density of the bivariate normal distribution | |
n <- 501 | |
sigma <- matrix(c(1,rho,rho,1), nrow=2) |
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\documentclass{beamer} | |
\usetheme{Singapore} | |
\usepackage{tipa} | |
%% Make the r-code small | |
\ifdefined\knitrout | |
\renewenvironment{knitrout}{\begin{footnotesize}}{\end{footnotesize}} | |
\else | |
\fi |
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## | |
## Example code for time-to-event analysis in R | |
## [email protected] | |
## Dec 28, 2012 | |
## | |
## joineR package: analyzing longitudinal data where the response | |
## from each person is a time-sequence of repeated measurements | |
## and we are interested in a possibly censored time-to-event outcome | |
## | |
## example: repeated ad viewings leading to a sale |
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# | |
# Functions to make ggplot KM survivor curves made with survfit() in library(survival) | |
# | |
# code written by Ramon Saccilotto | |
# and included in his ggplot2 tutorial | |
# 2010-12-08 | |
# define custom function to create a survival data.frame | |
createSurvivalFrame <- function(f.survfit){ | |
# initialise frame variable |