spaghetti function

Spaghetti plot

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,
  ...
)

Arguments

• 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

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(s)

Klaus K. Holst