spaghetti | R Documentation |
Spaghetti plot for longitudinal data
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, ... )
formula |
Formula (response ~ time) |
data |
data.frame |
id |
Id variable |
group |
group variable |
type |
Type (line 'l', stair 's', ...) |
lty |
Line type |
pch |
Colour |
col |
Colour |
alpha |
transparency (0-1) |
lwd |
Line width |
level |
Confidence level |
trend.formula |
Formula for trendline |
tau |
Quantile to estimate (trend) |
trend.lty |
Trend line type |
trend.join |
Trend polygon |
trend.delta |
Length of limit bars |
trend |
Add trend line |
trend.col |
Colour of trend line |
trend.alpha |
Transparency |
trend.lwd |
Trend line width |
trend.jitter |
Jitter amount |
legend |
Legend |
by |
make separate plot for each level in 'by' (formula, name of column, or vector) |
xlab |
Label of X-axis |
ylab |
Label of Y-axis |
add |
Add to existing device |
... |
Additional arguments to lower level arguments |
Klaus K. Holst
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") }
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