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Recode common missing-value sentinels to NA

Source: R/api-estimation.R
recode_missing_codes.Rd

Convenience helper that replaces the standard non-NA missing-code sentinels used in SPSS / SAS / FACETS exports (99, 999, -1, "N", "NA", "n/a", ".", "") with NA across the columns you select. This is the R counterpart of the preprocessing UI in the companion Streamlit app and is useful before calling fit_mfrm() on data exported with those conventions.

Usage

recode_missing_codes(
  data,
  columns = NULL,
  codes = c("99", "999", "-1", "N", "NA", "n/a", ".", ""),
  numeric_codes = TRUE,
  verbose = FALSE
)

Arguments

data

A data frame.

columns

Character vector of column names to recode. Defaults to NULL, in which case all columns are scanned.

codes

Character vector of code values to convert to NA. Defaults to the FACETS / SPSS / SAS conventions; override when your instrument uses different sentinels.

numeric_codes

Logical; if TRUE (default), numeric columns are also compared against the numeric conversion of codes.

verbose

Logical; if TRUE, emits a message() summary of per-column replacement counts.

Value

The input data with the specified missing sentinels replaced by NA. A mfrm_missing_recoding attribute records the per-column replacement counts for traceability logs.

See also

describe_mfrm_data(), fit_mfrm().

Examples

dat <- data.frame(
  Person = paste0("P", 1:5),
  Rater = c("R1", "R1", "R2", "R2", "R2"),
  Score = c(1, 99, 2, -1, 3)
)
cleaned <- recode_missing_codes(dat, columns = "Score")
cleaned$Score
#> [1]  1 NA  2 NA  3
attr(cleaned, "mfrm_missing_recoding")
#>   Column Replaced
#> 1  Score        2