1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/spaghetti.R
\name{spaghetti}
\alias{spaghetti}
\title{Spaghetti plot}
\usage{
spaghetti(
formula,
data = NULL,
id = "id",
group = NULL,
type = "o",
lty = 1,
pch = NA,
col = 1:10,
alpha = 0.3,
lwd = 1,
level = 0.95,
trend.formula = formula,
tau = NULL,
trend.lty = 1,
trend.join = TRUE,
trend.delta = 0.2,
trend = !is.null(tau),
trend.col = col,
trend.alpha = 0.2,
trend.lwd = 3,
trend.jitter = 0,
legend = NULL,
by = NULL,
xlab = "Time",
ylab = "",
add = FALSE,
...
)
}
\arguments{
\item{formula}{Formula (response ~ time)}
\item{data}{data.frame}
\item{id}{Id variable}
\item{group}{group variable}
\item{type}{Type (line 'l', stair 's', ...)}
\item{lty}{Line type}
\item{pch}{Colour}
\item{col}{Colour}
\item{alpha}{transparency (0-1)}
\item{lwd}{Line width}
\item{level}{Confidence level}
\item{trend.formula}{Formula for trendline}
\item{tau}{Quantile to estimate (trend)}
\item{trend.lty}{Trend line type}
\item{trend.join}{Trend polygon}
\item{trend.delta}{Length of limit bars}
\item{trend}{Add trend line}
\item{trend.col}{Colour of trend line}
\item{trend.alpha}{Transparency}
\item{trend.lwd}{Trend line width}
\item{trend.jitter}{Jitter amount}
\item{legend}{Legend}
\item{by}{make separate plot for each level in 'by' (formula, name of column, or vector)}
\item{xlab}{Label of X-axis}
\item{ylab}{Label of Y-axis}
\item{add}{Add to existing device}
\item{...}{Additional arguments to lower level arguments}
}
\description{
Spaghetti plot for longitudinal data
}
\examples{
if (interactive() & requireNamespace("mets")) {
K <- 5
y <- "y"\%++\%seq(K)
m <- lvm()
regression(m,y=y,x=~u) <- 1
regression(m,y=y,x=~s) <- seq(K)-1
regression(m,y=y,x=~x) <- "b"
N <- 50
d <- sim(m,N); d$z <- rbinom(N,1,0.5)
dd <- mets::fast.reshape(d); dd$num <- dd$num+3
spaghetti(y~num,dd,id="id",lty=1,col=Col(1,.4),
trend.formula=~factor(num),trend=TRUE,trend.col="darkblue")
dd$num <- dd$num+rnorm(nrow(dd),sd=0.5) ## Unbalance
spaghetti(y~num,dd,id="id",lty=1,col=Col(1,.4),
trend=TRUE,trend.col="darkblue")
spaghetti(y~num,dd,id="id",lty=1,col=Col(1,.4),
trend.formula=~num+I(num^2),trend=TRUE,trend.col="darkblue")
}
}
\author{
Klaus K. Holst
}
|