datacontroller.io/content/feed/sas-special-missings/index.md

title, description, date, author, authorLink, tags, previewImg

title	description	date	author	authorLink	tags	previewImg
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 the letter or the underscore, with or without that period - .a and a are the same missing - 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 - aaaa, or ! in a numeric column
• A lone . is accepted as another way of typing the 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 - rejects one. A special missing is a missing value, so it fails the rule, and a physical NOT NULL constraint on the target table rejects it as well. A primary key column is treated as NOT NULL whether or not a rule is configured for it
• 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 them. The dropdown lists a special missing as a bare letter alongside the ordinary values, and a hard rule then accepts it like any other listed value - it still rejects a value that is not in the list
• ROUND - harmless. It only rounds values that are numbers, so a special missing is left exactly as it was typed

The range rules compare in the order SAS itself uses, which is what makes them interesting here. SAS puts every missing below every non-missing value, and orders the missing values among themselves: ._ is the lowest, then the regular missing, then .A through .Z. So a range can be written in special missings and mean exactly what SAS would mean by it:

• MINVAL .A with MAXVAL .C accepts .B and rejects .D, and a blank - the regular missing - fails that floor because it sorts below .A
• a number sits above every missing, so it passes a floor of .A and fails a ceiling of .C
• against a numeric bound the ordering does the obvious thing: a missing sorts below every number, so it fails a MINVAL of 1 and passes a MAXVAL of 100. Use NOTNULL if the column has to be populated
• a rule value that is neither a number nor a special missing - a typo such as .. or AB - satisfies nothing, so the column fails until the rule is corrected

A formula is the one case where a special missing genuinely does not work:

• 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 value with its own place in the order for the range rules: it sits below every number, so a numeric minimum rejects it and a numeric maximum accepts it, while a range written in special missings is decided among the missing values themselves.

See it in action

The recording below runs the whole cycle on one table: entering special missings, the rules that reject them, submitting the changes, approving them, and reviewing the DIFF - including a change from one special missing to another, and the formatted / unformatted switch on a date column.

It also shows the range rules doing what the section above describes. A special missing is refused by a numeric MINVAL and accepted by a numeric MAXVAL, and on a column carrying MINVAL .A with MAXVAL .C, .B is taken while .D is refused.