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SASInstitute A00-282 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Regulatory Submissions | 5% | - ICH and FDA guidelines - Compliance for clinical data reporting |
| Topic 2: Manage Clinical Trials Data | 5% | - Use SQL and dictionary tables - Access and explore clinical datasets - Clean, merge, and subset data |
| Topic 3: Clinical Trials Process | 5% | - Clinical trial lifecycle and protocol - Derive programming requirements from protocol and CRF |
| Topic 4: Transform or Summarize Clinical Trials Data | 15% | - Derive variables and study days - Aggregation and transposition - Data step manipulation |
| Topic 5: Macro Programming for Clinical Trials | 15% | - Create and call macros - Macro variables and parameters - Debugging macros |
| Topic 6: Report Clinical Trials Results | 10% | - Produce tables, listings, and figures - PROC REPORT and PROC PRINT |
| Topic 7: Validate Clinical Trial Data Reporting | 20% | - Validation principles - Programming validation techniques - Use PROC COMPARE and log review |
| Topic 8: Clinical Trials Data Structures | 10% | - CDISC standards: SDTM, ADaM - Clinical domain structures - Define.xml and dataset specifications |
| Topic 9: Apply Statistical Procedures for Clinical Trials | 15% | - Basic statistical analysis for clinical data - PROC MEANS, FREQ, TABULATE |
SASInstitute Clinical Trials Programming Using SAS 9.4 Sample Questions:
Which clause allows macro variable creation on a select statement in PROC SQL?
- A. %MACRO
- B. INTO
- C. SYMPUT
- D. AS
Correct Answer: A 🗳️
This question will ask you to provide a line of missing code. The following SAS program is submitted:
Which statement is required to produce this output?
- A. TABLES site*group;
- B. TABLES site*group /nocol;
- C. TABLES site*group /norow;
- D. TABLES site*group /nocol norow;
Correct Answer: B 🗳️
In a study, inclusion criteria required patients be between 18 and 65. Patients will be analyzed in 2 age groups: group one is subjects who are under 36 years of age and group two is subjects who are 36 years of age or older.
Which statements properly assign age group, and writes an error message to the log for any patient with an out of range age value?
- A. select;
when (18 <= age < 36) agegrp = 1;
when (36 <= age < 66) agegrp = 2;
otherwise put "ERROR: AGE OUT OF PROTOCOL SPECIFIED RANGE FOR " subject= age=; end; - B. select;
when (age >= 66) put "ERROR: AGE OUT OF PROTOCOL SPECIFIED RANGE FOR " subject= age=; when (36 <= age < 66) agegrp = 2; when (18 <= age < 66) agegrp = 1; end; - C. select;
when (age >= 18) agegrp = 1;
when (age >= 36) agegrp = 2;
when (age >= 66) put "ERROR: AGE OUT OF PROTOCOL SPECIFIED RANGE FOR " subject= age=; end; - D. select;
when (age >= 66) put "ERROR: AGE OUT OF PROTOCOL SPECIFIED RANGE FOR " subject= age=; when (age >= 36) agegrp = 2; when (age >= 18) agegrp = 1; otherwise; end;
Correct Answer: A 🗳️
The following SAS program is submitted:
You want to store all calculated means and standard deviations in one SAS data set.
Which statement must be added to the program?
- A. output mean std;
- B. output out=WORK.RESULTS mean=m1 m2 std=s1 s2;
- C. ods output mean=m1 m2 std=s1 s2;
- D. ods output out=WORK.RESULTS mean=m1 m2 std=s1 s2;
Correct Answer: B 🗳️
The first six (6) records from the LABS data set are shown below:
The following SAS program is written to reshape this data set and place it in a new data set named LBTR.
proc transpose data=labs out=lbtr(rename = (col1 = value));
by subjid sampldat;
var Calcium Glucose Hemoglobin;
run;
Which of the following DATA steps produces a data set that is equivalent to the LBTR data set created by the PROC TRANSPOSE step above?
- A. data lbtr2(drop = i calcium glucose hemoglobin);
set labs;
array orig[3] calcium glucose hemoglobin;
array testcds[3] $ 10 _temporary_ ("CALCIUM" "GLUCOSE" "HEMOGLOBIN");
do i = 1 to 3;
value = orig[i];
_name_ = testcds[i];
output;
end;
run; - B. data lbtr2(drop = i calcium glucose hemoglobin);
set labs;
array orig[3] calcium glucose hemoglobin;
array testcds[3] $ 10 ("CALCIUM" "GLUCOSE" "HEMOGLOBIN");
do i = 1 to 3;
value = orig[i];
_name_ = testcds[i];
output;
end;
run; - C. data lbtr2(drop = i calcium glucose hemoglobin);
set labs;
array orig[3] calcium glucose hemoglobin;
array testcds[3] $ 10 ("CALCIUM" "GLUCOSE" "HEMOGLOBIN");
do i = 1 to 3;
value = orig[i];
_name_ = testcds[i];
end;
output;
run; - D. data lbtr2(drop = i calcium glucose hemoglobin);
set labs;
array orig[3] calcium glucose hemoglobin;
array testcds[3] $ 10 _temporary_ ("CALCIUM" "GLUCOSE" "HEMOGLOBIN");
do i = 1 to 3;
value = orig[i];
_name_ = testcds[i];
end;
output;
run;
Correct Answer: A 🗳️
Olivia 
Jack 
Geraldine 
Tony 
Candice 
Debby 
Fitch 
Cherry 
Marcus 
