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28 Ways to Be Missing in SAS	A SAS numeric missing is not a lone wolf - there are 28 of them, and Data Controller has handled all of them since v4. How they work, and what the validation rules do with them.	2026-09-22 09:00:00	Allan Bowe	https://www.linkedin.com/in/allanbowe/	Special Missings Data Quality	./cover.jpeg

28 Ways to Be Missing in SAS

A numeric missing value in SAS is not a lone wolf. The ordinary missing (.) is one of 28 distinct missing values available for a numeric variable - the other 27 are written with a single character, the letters A to Z or an underscore (._).

They exist because "missing" is usually not the whole story. A survey question that was never reached, a reading that was illegible, a value the respondent refused to give - in a well run process those are different facts, and a lone . throws the difference away. Special missings record why the value is missing.

They are numbers, not text

• Arithmetic on them yields missing - .A + 1 is .
• proc means, proc summary and friends exclude them, exactly as they exclude .
• They sort below every non-missing number, in the order ._, then ., then .A to .Z
• The NMISS() and CMISS() functions count them as missing
• Converting one to text drops the period - cats(.A) is the string A

A display gotcha worth knowing: a regular missing prints as ., unless options MISSING= changes that character - set it to blank and a regular missing renders as an empty cell. The option affects only the regular missing; ._ and .A-.Z always print as their own letter. So a blank cell in a SAS listing is still unambiguously a regular missing, and a lone letter is still a special one. Data Controller itself is unaffected either way - it sends a regular missing to the browser as null and a special missing as its letter.

In a SAS dataset they are written with a leading period (.A, .B ... ._). In Data Controller you type just the letter or the underscore - no period - and the letter is not case sensitive. Two letters, or a letter mixed with a number, are refused rather than guessed.

There is one cell where the letter cannot be typed at all. A numeric column that carries a date, datetime or time format is edited through a date picker rather than the numeric editor, and a picker accepts only a date.

Carrying them between the browser and SAS

The Data Controller frontend and the SAS backend exchange data as JSON, and JSON has no way to express a letter as a numeric value - A is a string. The conversion is handled in the open source SASjs Adapter:

• The adapter infers each column's SAS type from the values it is given. All numeric values means numeric; all strings means character; and a column holding a single character (a-z, _ or .) alongside numeric values is numeric, with the lone characters written to SAS as special missings.
• null becomes . or an empty string, according to the type derived for that column.
• Two cases cannot be inferred from the values alone: a numeric column containing only special missings looks like a single character column, and a character column containing only nulls looks numeric. For those, the adapter accepts an explicit format for the column - and Data Controller sends one automatically, because it already knows each column's SAS format from the metadata returned by the backend.
• A value that is neither a number nor a single valid character is refused rather than guessed (for example aaaa, or ! in a numeric column), and a literal . is refused in favour of null for a regular missing.

There is nothing to configure. Special missings are available by default, for numeric cells - a date, datetime or time formatted column aside, since those edit through a date picker.

Once in SAS they are ordinary values, so they are what the approval DIFF screen compares, and the DIFF's formatted / unformatted switch shows either the formatted representation or the raw value - useful for confirming exactly which missing was set.

What the Data Controller validation rules do with them

These are Data Controller's own rules, configured per column in the MPE_VALIDATIONS table and applied in the browser as you edit and submit.

• NOTNULL - works the same as SAS: cannot use special missings. A special missing is NULL to a NOT NULL (or primary key) constraint, so the rule rejects it, and so does a physical constraint on the target table
• HARDREGEX - checked against the pattern like any other value; unlike blanks and the plain ., special missings are not exempt, so a numeric column that carries them needs a pattern which allows for a single letter
• SOFTREGEX - the same check, but a failure is only a warning rather than a block, and it is ignored entirely if the column also has a HARDREGEX rule
• SOFTSELECT / HARDSELECT - both support special missings; a soft dropdown never blocks a value, and a hard one lists them alongside the ordinary values
• ROUND - harmless. It only rounds values that are numbers, so a special missing is left exactly as it was typed

Special missings are not supported in a column that carries a range rule or a formula:

• MINVAL / MAXVAL - a special missing sorts below every number, so MINVAL rejects it and MAXVAL accepts it while rejecting the column's real numbers. The rule's own value has to be a number too: put a special missing in MINVAL and every cell in the column fails, put one in MAXVAL and every real number fails
• HARDFORMULA / SOFTFORMULA - a formula that reads a special-missing cell does not compute; the grid's spreadsheet engine returns #VALUE! for that row, where the plain . contributes 0

CASE (UPCASE / LOWCASE) is a character rule and does not come into it: SAS hands the browser a special missing as an uppercase letter, so there is no case to enforce, and a CASE rule on a numeric column would reject the column's numbers rather than the missing.

One thing worth knowing about the regex rules: although the pattern is written in SAS PRX syntax, the check itself runs in the browser - SAS only parses the pattern (PRXPARSE) when the rule is saved - so the two engines can disagree on exotic patterns, and SAS pads a numeric-to-character conversion, so a pattern re-used in SAS needs strip() for an anchored match.

In short, a special missing counts as a value for the pattern and dropdown rules, and as a missing value for everything that asks for a number.

video: [Managing Special Missing Values with Data Controller for SAS](https://www.youtube-nocookie.com/embed/ggrcNr23Jzw)

The recording shows the full cycle: typing special missings into numeric cells, the rejections, submitting the changes, approving them, and reviewing the DIFF - including a change from one special missing to another, and the formatted / unformatted switch on date and datetime columns.