misty (version 0.5.0)

na.descript: Descriptive Statistics for Missing Data

Description

This function computes descriptive statistics for missing data, e.g. number ( of incomplete cases, number ( the number (

Usage

na.descript(x, table = FALSE, digits = 2, as.na = NULL, write = NULL,
            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

matrix or data frame specified in x

args

specification of function arguments

result

list with results

Arguments

x

a matrix or data frame.

table

logical: if TRUE, a frequency table with number of observed values ("nObs"), percent of observed values ("pObs"), number of missing values ("nNA"), and percent of missing values ("pNA") is printed for each variable on the console.

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 for writing the results into a Excel file naming a file with or without file extension '.xlsx', e.g., "Results.xlsx" or "Results".

check

logical: if TRUE, argument specification is checked.

output

logical: if TRUE, output is shown on the console.

Author

Takuya Yanagida

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.indicator, na.pattern, na.prop, na.test

Examples

dat <- data.frame(x1 = c(1, NA, 2, 5, 3, NA, 5, 2),
                  x2 = c(4, 2, 5, 1, 5, 3, 4, 5),
                  x3 = c(NA, 3, 2, 4, 5, 6, NA, 2),
                  x4 = c(5, 6, 3, NA, NA, 4, 6, NA))

# Descriptive statistics for missing data
na.descript(dat)

# Descriptive statistics for missing data, print results with 3 digits
na.descript(dat, digits = 3)

# Descriptive statistics for missing data, convert value 2 to NA
na.descript(dat, as.na = 2)

# Descriptive statistics for missing data with frequency table
na.descript(dat, table = TRUE)

if (FALSE) {
# Write Results into a Excel file
na.descript(dat, table = TRUE, write = "NA_Descriptives.xlsx")

result <- na.descript(dat, table = TRUE, output = FALSE)
write.result(result, "NA_Descriptives.xlsx")
}