CDISC dataset migration

SDTM Programming in R for SAS Teams

Explore practical SAS-to-R patterns for SDTM data preparation, then validate controlled terminology, date handling, metadata, and domain conformance against your study standards.

Try the SAS to R converter

Example

Map treatment, controlled terminology, and start dates for an SDTM CM domain

SAS

proc format;
  value $route_ct
    'PO', 'ORAL' = 'ORAL'
    'IV', 'INTRAVENOUS' = 'INTRAVENOUS'
    other = ' ';
run;

data cm;
  set raw.cm;
  length cmtrt $200 cmroute $40 cmstdtc $19;
  cmtrt = cmtrt_raw;
  cmroute = put(upcase(cmroute_raw), $route_ct.);
  if not missing(cmstdt_raw) then
    cmstdtc = put(input(cmstdt_raw, yymmdd10.), e8601da.);
run;

library(sdtm.oak)

cm <- assign_no_ct(
  tgt_var = 'CMTRT',
  raw_dat = raw_cm,
  raw_var = 'CMTRT_RAW',
  id_vars = oak_id_vars()
) |>
  assign_ct(
    tgt_var = 'CMROUTE',
    raw_dat = raw_cm,
    raw_var = 'CMROUTE_RAW',
    ct_spec = study_ct,
    ct_clst = 'C66729',
    id_vars = oak_id_vars()
  ) |>
  assign_datetime(
    tgt_var = 'CMSTDTC',
    raw_dat = raw_cm,
    raw_var = 'CMSTDT_RAW',
    raw_fmt = 'y-m-d',
    raw_unk = c('UN', 'UNK'),
    id_vars = oak_id_vars()
  )

What to validate after conversion

Handle partial and ISO-format dates deliberately.
Keep controlled terminology mappings explicit and reviewable.
Validate required variables, metadata, and domain-level rules.

Always validate source keys, controlled terminology, date precision, metadata, and domain rules against the SAS output and your study standards.

Frequently asked questions

How should SAS formats be represented in R for SDTM?

Use explicit parsing and formatting rules, plus documented controlled-terminology mappings. Do not assume a SAS display format carries all of the required semantic meaning.

What should be checked after converting an SDTM derivation?

Review required variables, variable attributes, controlled terminology, date precision, key uniqueness, sorting rules, and traceability to the defined source data.

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