na.pattern: Missing Data Pattern

In misty: Miscellaneous Functions 'T. Yanagida'

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)

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.

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

Author(s)

Takuya Yanagida [e-mail]

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

van Buuren, S. (2018). Flexible imputation of missing data (2nd ed.). Chapman & Hall.

See Also

write.result, as.na, na.as, na.auxiliary, na.coverage, na.descript, na.indicator, na.prop, na.test

Examples

## Not run: 
# Example 1a: Compute a summary of missing data patterns
dat.pattern <- na.pattern(airquality)

# Example 1b: Alternative specification using the 'data' argument
dat.pattern <- na.pattern(., data = airquality)

# Example 2: Vector of missing data pattern for each case
dat.pattern$pattern

# Data frame without cases with missing data pattern 2 and 4
airquality[!dat.pattern$pattern 

# Example 3a: Write Results into an text file
result <- na.pattern(airquality, write = "NA_Pattern.txt")

# Example 3b: Write Results into an Excel file
result <- na.pattern(airquality, write = "NA_Pattern.xlsx")

result <- na.pattern(dat, output = FALSE)
write.result(result, "NA_Pattern.xlsx")

## End(Not run)

misty documentation built on June 29, 2024, 9:07 a.m.