mlxR (version 4.2.0)

catplotmlx: Plot Categorical Longitudinal Data

Description

Plot the empirical distribution of categorical longitudinal data.

Usage

catplotmlx(
  r,
  col = NULL,
  breaks = NULL,
  plot = TRUE,
  color = "#194280",
  group = NULL,
  facet = TRUE,
  labels = NULL
)

Arguments

r

a data frame with a column id, a column time, a column with values and possibly Hk[ja column group.

col

a vector of 3 column numbers: (id, time/x, y. Default = c(1, 2,3).

breaks

one of:

• a vector giving the breakpoints,

• a single number giving the number of segments.

plot

if TRUE the empirical distribution is displayed, if FALSE the values are returned

color

a color to be used for the plots (default="#194280")

group

variable to be used for defining groups (by default, group is used when it exists)

facet

makes subplots for different groups if TRUE

labels

vector of strings

Value

a ggplot object if plot=TRUE ; otherwise, a list with fields:

• color a vector of colors used for the plot

• y a data frame with the values of the empirical distribution computed at each time point

Details

See http://simulx.webpopix.org/mlxr/catplotmlx/ for more details.

Examples

# NOT RUN {
  catModel <- inlineModel("
  [LONGITUDINAL]
  input =  {a,b}
  EQUATION:
  lp1=a-b*t
  lp2=a-b*t/2
  DEFINITION:
  y = {type=categorical, categories={1,2,3}, 
  logit(P(y<=1))=lp1, logit(P(y<=2))=lp2}
  ")
  
  y.out  <- list(name='y', time=seq(0, 100, by=4))

  Ng  <- 1000
  g1 <- list(size=Ng, parameter=c(a=6,b=0.2))
  res <- simulx(model=catModel, output=y.out, group=g1)
  catplotmlx(res$y)
  catplotmlx(res$y, breaks=seq(-2,102,by=8), color="purple") 
  catplotmlx(res$y, breaks=5, color="#490917") 
  
  g2 <- list(size=Ng, parameter=c(a=10,b=0.2))
  res <- simulx(model=catModel, output=y.out, group=list(g1,g2))
  catplotmlx(res$y) 
  catplotmlx(res$y, group="none")
  
  g3 <- list(size=Ng, parameter=c(a=6,b=0.4))
  g4 <- list(size=Ng, parameter=c(a=10,b=0.4))
  res <- simulx(model=catModel, output=y.out, group=list(g1,g2,g3,g4))
  catplotmlx(res$y)
   
  cov <- data.frame(id=levels(res$y$id), a=rep(c(6,10,6,10),each=Ng), 
                    b=rep(c(0.2,0.2,0.4,0.4),each=Ng))
  catplotmlx(res$y, group=cov) 
# }