Hmisc (version 4.4-0)

combplotp: Combination Plot

Description

Generates a plotly attribute plot given a series of possibly overlapping binary variables

Usage

combplotp(
  formula,
  data = NULL,
  subset,
  na.action = na.retain,
  vnames = c("labels", "names"),
  includenone = FALSE,
  showno = FALSE,
  maxcomb = NULL,
  minfreq = NULL,
  N = NULL,
  pos = function(x) 1 * (toupper(x) %in% c("true", "yes", "y", "positive", "+",
    "present", "1")),
  obsname = "subjects",
  ptsize = 35,
  width = NULL,
  height = NULL,
  ...
)

Arguments

formula

a formula containing all the variables to be cross-tabulated, on the formula's right hand side. There is no left hand side variable. If formula is omitted, then all variables from data are analyzed.

data

input data frame. If none is specified the data are assumed to come from the parent frame.

subset

an optional subsetting expression applied to data

na.action

see lm etc.

vnames

set to "names" to use variable names to label axes instead of variable labels. When using the default labels, any variable not having a label will have its name used instead.

includenone

set to TRUE to include the combination where all conditions are absent

showno

set to TRUE to show a light dot for conditions that are not part of the currently tabulated combination

maxcomb

maximum number of combinations to display

minfreq

if specified, any combination having a frequency less than this will be omitted from the display

N

set to an integer to override the global denominator, instead of using the number of rows in the data

pos

a function of vector returning a logical vector with TRUE values indicating positive

obsname

character string noun describing observations, default is "subjects"

ptsize

point size, defaults to 35

width

width of plotly plot

height

height of plotly plot

optional arguments to pass to table

Value

plotly object

Details

Similar to the UpSetR package, draws a special dot chart sometimes called an attribute plot that depicts all possible combination of the binary variables. By default a positive value, indicating that a certain condition pertains for a subject, is any of logical TRUE, numberic 1, "yes", "y", "positive", "+" or "present" value, and all others are considered negative. The user can override this determination by specifying her own pos function. Case is ignored in the variable values.

The plot uses solid dots arranged in a vertical line to indicate which combination of conditions is being considered. Frequencies of all possible combinations are shown above the dot chart. Marginal frequencies of positive values for the input variables are shown to the left of the dot chart. More information for all three of these component symbols is provided in hover text.

Variables are sorted in descending order of marginal frqeuencies and likewise for combinations of variables.

Examples

Run this code
# NOT RUN {
g <- function() sample(0:1, n, prob=c(1 - p, p), replace=TRUE)
set.seed(2); n <- 100; p <- 0.5
x1 <- g(); label(x1) <- 'A long label for x1 that describes it'
x2 <- g()
x3 <- g(); label(x3) <- 'This is<br>a label for x3'
x4 <- g()
combplotp(~ x1 + x2 + x3 + x4, showno=TRUE, includenone=TRUE)

n <- 1500; p <- 0.05
pain       <- g()
anxiety    <- g()
depression <- g()
soreness   <- g()
numbness   <- g()
tiredness  <- g()
sleepiness <- g()
combplotp(~ pain + anxiety + depression + soreness + numbness +
          tiredness + sleepiness, showno=TRUE)
# }

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