misty (version 0.4.5)

na.descript: Descriptive Statistics for Missing Data

Description

This function computes descriptive statistics for missing data, e.g. number ( of missing values, and summary statistics for the number (

Usage

na.descript(x, table = FALSE, digits = 2, as.na = NULL, check = TRUE, output = TRUE)

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.

check

logical: if TRUE, argument specification is checked.

output

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

Value

Returns an object of class misty.object, which is a list with following entries: function call (call), type of analysis type, matrix or data frame specified in x (data), specification of function arguments (args), and list with results (result).

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

# NOT RUN {
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)

# }
# NOT RUN {
# Write Results into a Excel file
result <- na.descript(dat, table = TRUE, output = FALSE)
write.result(result, "NA_Descriptives.xlsx") 
# }