summarizeNA: Summarize missing data patterns
In LMMstar: Repeated Measurement Models for Discrete Times

summarizeNA

R Documentation

Summarize missing data patterns

Description

Summarize missing data patterns.

Usage

summarizeNA(
  data,
  repetition = NULL,
  sep = "",
  newnames = c("variable", "frequency", "missing.pattern", "n.missing"),
  keep.data = TRUE
)

Arguments

`data`	[data.frame] dataset containing the observations.
`repetition`	[formula] Specify the structure of the data when in the long format: the time/repetition variable and the grouping variable, e.g. ~ time\|id. When specified the missing data pattern is specific to each variable not present in the formula.
`sep`	[character] character used to separate the missing data indicator (0/1) when naming the missing data patterns.
`newnames`	[character vector of length 4] additional column containing the variable name (only when argument `repetition` is used), the frequency of the missing data pattern in the dataset, the name of the missing data pattern in the dataset, and the number of missing data per pattern.
`keep.data`	[logical] should the indicator of missing data per variable in the original dataset per pattern be output.

Value

a data frame

Examples

data(gastricbypassW, package = "LMMstar")
summarizeNA(gastricbypassW) 
summarizeNA(gastricbypassW, keep.data = FALSE)

data(gastricbypassL, package = "LMMstar")
summarizeNA(gastricbypassL, repetition = ~time|id)

data(calciumL, package = "LMMstar")
mp <- summarizeNA(calciumL, repetition = ~visit|girl)
plot(mp, variable = "bmd")
summarizeNA(calciumL[,c("visit","girl","bmd")], repetition = ~visit|girl)

data(vasscoresW, package = "LMMstar")
summarizeNA(vasscoresW)

LMMstar documentation built on Nov. 9, 2023, 1:06 a.m.