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Read SAS Data with Tagged Missing Values

Source: R/read_sas.R
read_sas.Rd

Reads a SAS .sas7bdat file and integrates with mariposa's tagged NA system. Handles two scenarios:

  1. Native special missing values (.A through .Z, ._): Automatically detected and annotated.

  2. Numeric missing codes (e.g., -9, -42): When tag.na is provided, these regular values are converted to tagged NAs, giving the same result as read_spss() with tag.na = TRUE.

Usage

read_sas(
  path,
  catalog_file = NULL,
  encoding = NULL,
  catalog_encoding = NULL,
  tag.na = NULL,
  verbose = FALSE
)

Arguments

path

Path to a SAS .sas7bdat data file.

catalog_file

Path to a SAS catalog file (.sas7bcat) for value labels. If NULL, no catalog is used.

encoding

Character encoding for the data file. If NULL, haven's default encoding detection is used.

catalog_encoding

Character encoding for the catalog file. If NULL, the same encoding as the data file is used.

tag.na

Numeric vector of values to treat as missing (e.g., c(-9, -8, -42)). These values will be converted to tagged NAs across all numeric variables. Use this when SAS files contain missing codes stored as regular values. Default: NULL (only detect native SAS special missing values).

verbose

If TRUE, prints a message summarizing how many variables contain tagged missing values.

Value

A tibble with the SAS data. Variables with missing value codes have:

  • Tagged NAs for each missing type

  • An "na_tag_map" attribute mapping tag characters to original codes

  • is.na() returns TRUE for these values (standard R behavior)

Details

Native Special Missing Values

SAS supports 28 distinct missing value types: . (system missing), .A through .Z, and ._ (underscore). The haven package preserves these as tagged NAs automatically. read_sas() adds the na_tag_map attribute so that mariposa's tagged NA functions work seamlessly.

Numeric Missing Codes (tag.na)

Some SAS files store missing value codes as regular numeric values (e.g., -9 = "No answer"). The tag.na parameter converts these to tagged NAs, enabling proper handling in frequency(), codebook(), and other functions.

When tag.na is used, untag_na() can recover the original numeric codes.

See also

read_xpt(), na_frequencies(), strip_tags(), untag_na(), read_spss(), read_stata(), haven::read_sas()

Other data-import: na_frequencies(), read_por(), read_spss(), read_stata(), read_xlsx(), read_xpt(), strip_tags(), untag_na()

Examples

if (FALSE) { # \dontrun{
# Read SAS file with native special missing values
data <- read_sas("survey.sas7bdat")

# Read with catalog for value labels
data <- read_sas("survey.sas7bdat", catalog_file = "formats.sas7bcat")

# Read SAS file with numeric missing codes
data <- read_sas("survey.sas7bdat", tag.na = c(-9, -8, -42))

# Check what types of missing values exist
na_frequencies(data$income)

# Recover original codes or convert to regular NAs
untag_na(data$income)   # Recovers -9, -8, etc.
strip_tags(data$income) # Converts all to NA
} # }