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A00-282 PDF Practice Q&A's
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- Total Questions: 144
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SASInstitute A00-282 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Apply Statistical Procedures for Clinical Trials | 15% | - PROC MEANS, FREQ, TABULATE - Basic statistical analysis for clinical data |
| Topic 2: Clinical Trials Data Structures | 10% | - Define.xml and dataset specifications - Clinical domain structures - CDISC standards: SDTM, ADaM |
| Topic 3: Report Clinical Trials Results | 10% | - Produce tables, listings, and figures - PROC REPORT and PROC PRINT |
| Topic 4: Macro Programming for Clinical Trials | 15% | - Debugging macros - Create and call macros - Macro variables and parameters |
| Topic 5: Transform or Summarize Clinical Trials Data | 15% | - Aggregation and transposition - Data step manipulation - Derive variables and study days |
| Topic 6: Clinical Trials Process | 5% | - Derive programming requirements from protocol and CRF - Clinical trial lifecycle and protocol |
| Topic 7: Manage Clinical Trials Data | 5% | - Access and explore clinical datasets - Use SQL and dictionary tables - Clean, merge, and subset data |
| Topic 8: Validate Clinical Trial Data Reporting | 20% | - Programming validation techniques - Use PROC COMPARE and log review - Validation principles |
| Topic 9: Regulatory Submissions | 5% | - ICH and FDA guidelines - Compliance for clinical data reporting |
SASInstitute Clinical Trials Programming Using SAS 9.4 Sample Questions:
1. Identify the data structure with the following characteristics:
- Contains one or more records per subject, per analysis parameter, and per analysis timepoint.
- May be derived from findings, events, interventions and special-purpose SDTM domains, or other ADaM datasets.
- A record can represent an observed, derived, or imputed value required for analysis.
A) General Data Structure (GDS)
B) Event Level Analysis Data Set (ADAE)
C) Basic Data Structure (BDS)
D) Subject Level Analysis Data Set (ADSL)
2. From the Statistical Analysis Plan, patients age is calculated as an integer relative to date randomized divided by 365.25.
Given the following annotated CRF:

Which programming code defines the patient's age?
A) age= int(yrdif(birthdt,randdt, "act/365.25" ));
B) age = int((today()-birthdt)/365.25);
C) age = int((randdt-birthdt)/365.25);
D) age = int((birthdt-randdt)/365.25);
3. Review the following procedure code:
proc ttest data=DATA1;
class GROUPVAR1;
var VAR1;
run;
Which variable is most appropriate to be analyzed as variable VAR1?
A) Age, with possible values of any integer between and including 18 and 65
B) Number of infections, with possible values of 0, 1, or 2
C) Systolic blood pressure, with possible values of "<120", "120 - 139", "140 - 159", "160 - 179", and
"180+"
D) Treatment, with possible values of "Placebo" or "Active"
4. Review the following procedure format:
PROC TTEST date=date;
class group-variable;
var variable;
run;
What is the required type of data for the variable in this procedure?
A) Categorical
B) Character
C) Treatment
D) Continuous
5. Given the data set below, which SAS program correctly counts the of number of unique subjects for each combination of system organ class and treatment?
A) proc sort data=a out=b;
by trta aesoc subjidn;
run;
proc freq data=b noprint;
by trta;
table aesoc/out=freq;
run;
B) proc sort data=a out=b nodupkey;
by trta aesoc;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;
C) proc sort data=a out=b;
by trta aesoc;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;
D) proc sort data=a out=b nodupkey;
by trta aesoc subjidn;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: D |
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