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Generate CDISC Findings data
set for a specified domain %findings (data = source dataset,
studyid = study identifier,
rdomain = related domain,
usubjid
= unique subject id,
testvars
= test variable(s),
varname
= variable names,
output =
output dataset,
basecode = SAS/Base Code);
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Where |
Is Type... |
And represents... |
| data | C (200) | A two
level dataset name specification in the form of
libname.dataname. |
| studyid | C (200) | Study identifier. This can be specified as a name or a
numeric number. |
| rdomain | C (200 | Related domain abbreviation to the current dataset
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| usubjid | C (200) | Unique
Subject Identifier of the SDS domain record(s). |
| varname | C (200) | Additional variables separated by spaces. |
| testvars | C (200 optional) | Test variable for the findings. This could be more than
one variable separated by spaces. For example:
testvars = var1 var2 The default value assigned to
the new test name is the value of the specified test variables.
Optionally, the test name can get the value of the variable label if
the value is "YES". This is specified with a slash followed by
the value indicating a YES. An example would be:
testvars = var1/YES var2/YES Where the "YES" is the value
found in these variables. |
| output | C (200 Optional) |
Output dataset
name. This can be either a two level or one level name.
If it is one level, it will be defaulted to be produced in the same
location as specified in the data parameter. If no value is
specified, it will generate a data set name of the related domain in
the default location. |
| basecode | C (200 optional) | Saved location of SAS Base code that is used to create the
relational records dataset. | Details
CDISC
defines a class of data specified as Findings. This set of domain
data type captures the observations resulting from planned evaluations to
address specific questions such as observations made during a physical
examination, laboratory tests, ECG testing, and sets of individual
questions listed on questionnaires. Among the domains that are
considered findings include:
| Code | Domain |
| AU | Autopsy |
| BM | Bone Mineral Density (BMD) Data |
| BR | Biopsy |
| CP | Compliance |
| DC | Disease Characteristics |
| DR | Disease Response |
| DV | Protocol Deviations |
| DY | Diary Data |
| EE | EEG |
| EG | ECG |
| HU | Healthcare Resource Utilization |
| IE | Inclusion / Exclusion |
| IM | Imaging |
| LB | Laboratory Data |
| MB | Microbiology |
| NE | Neurological Exam |
| OM | Organ Measurements |
| PC | PK Concentration |
| PE | Physical Exam |
| PP | PK Parameters |
| QS | Questionnaires |
| SC | Subject Characteristics |
| SK | Skin Test |
| SL | Sleep (Polysomnography) Data |
| ST | Stress (Exercise) Test Data |
| VS | Vital Signs | The input data can have more
than one test variable. The %findings tool will transpose to repeat
the data so that it will be a "skinny" data by the specified test
variables. If the values specified by the parameters: studyid,
usubjid, varname, testvar are missing, it will not be inserted into
the final output data. The basecode parameter will generate
SAS/BASE code that will perform the same task of transposing input data
into the findings dataset. In addition, it will generate optional
code that can be used to perform the reverse transposition from findings
back into the original data structure. This is useful if you have
legacy code that you wish to use with the findings data. This
reverse transposition code can be regenerate the data that can then be
used with the original legacy code. Example %findings (data = inlib.physexam,
studyid = Protocol 1234,
rdomain = PE,
usubjid
= usubjid,
testvars
= petest exam1 exam2,
varname = peseq petestcd pemodify pecat peloc pebodsys
peorres pestresc pestat pereasnd pespid
visit visitnum visitdy pedtc pedy,
output = pe,
basecode = c:\temp\findings.sas);
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