Lists missing data patterns in the specified dataset

This function summarises the missing data patterns in the specified dataset. Each row in the output corresponds to a missing data pattern (1=observed, 0=missing). The number and percentage of observations is also displayed for each missing data pattern. The first column indicates the number of missing data patterns. The second column refers to the analysis model outcome ('y'), with all other variables ('covs') displayed in subsequent columns. Alternatively, 'y' can be used to display the primary variable of interest, e.g. 'y' could refer to the exposure, with all other variables listed in 'covs'.

Usage

descMissData(y, covs, data, plot = FALSE)

Arguments

y: The analysis model outcome, specified as a string
covs: The analysis model covariate(s), specified as a string (space delimited)
data: A data frame containing the specified analysis model outcome and covariate(s)
plot: If TRUE, displays a plot using md.pattern to visualise the missing data patterns; use plot = FALSE (the default) to disable the plot

Value

A summary of the missing data patterns

Examples

descMissData(y="bmi7", covs="matage mated", data=bmi)
#>   pattern bmi7 matage mated   n pct
#> 1       1    1      1     1 592  59
#> 2       2    0      1     1 408  41
descMissData(y="bmi7", covs="matage mated pregsize bwt", data=bmi, plot=TRUE)

#>   pattern bmi7 matage mated pregsize bwt   n pct
#> 1       1    1      1     1        1   1 592  59
#> 2       2    0      1     1        1   1 408  41