na.pattern: Missing Data Pattern

Description

This function computes a summary of missing data patterns, i.e., number ( cases with a specific missing data pattern.

Usage

na.pattern(..., data = NULL, order = FALSE, digits = 2, as.na = NULL, write = NULL,
           append = TRUE, check = TRUE, output = TRUE)

Value

Returns an object of class misty.object, which is a list with following entries:

call: function call
type: type of analysis
data: data frame used for the current analysis
args: specification of function arguments
result: result tables
pattern: group variable of missing data pattern

Arguments

...: a matrix or data frame with incomplete data, where missing values are coded as NA. a matrix or data frame with incomplete data, where missing values are coded as NA. Alternatively, an expression indicating the variable names in data e.g., na.pattern(x1, x2, x3, data = dat).Note that the operators ., +, -, ~, :, ::, and ! can also be used to select variables, see 'Details' in the df.subset function.
data: a data frame when specifying one or more variables in the argument .... Note that the argument is NULL when specifying a matrix or data frame for the argument ....
order: logical: if TRUE, variables are ordered from left to right in increasing order of missing values.
digits: an integer value indicating the number of decimal places to be used for displaying percentages.
as.na: a numeric vector indicating user-defined missing values, i.e. these values are converted to NA before conducting the analysis.
write: a character string naming a file for writing the output into either a text file with file extension ".txt" (e.g., "Output.txt") or Excel file with file extention ".xlsx" (e.g., "Output.xlsx"). If the file name does not contain any file extension, an Excel file will be written.
append: logical: if TRUE (default), output will be appended to an existing text file with extension .txt specified in write, if FALSE existing text file will be overwritten.
check: logical: if TRUE (default), argument specification is checked.
output: logical: if TRUE (default), output is shown.

Author

Takuya Yanagida takuya.yanagida@univie.ac.at

References

Enders, C. K. (2010). Applied missing data analysis. Guilford Press.

Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549-576. https://doi.org/10.1146/annurev.psych.58.110405.085530