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SASInstitute Clinical Trials Programming Using SAS 9.4 Sample Questions:

1. 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) Treatment, with possible values of "Placebo" or "Active"
B) Number of infections, with possible values of 0, 1, or 2
C) Age, with possible values of any integer between and including 18 and 65
D) Systolic blood pressure, with possible values of "<120", "120 - 139", "140 - 159", "160 - 179", and
"180+"

2. Given the data set WORK.BP with the following variable list:

Which output will be created by the program?

A) Option A
B) Option D
C) Option B
D) Option C

3. 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];
end;
output;
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];
end;
output;
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];
output;
end;
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];
output;
end;
run;

4. What is the key to ensuring traceability across CDISC data sets and modes?

A) Creating a map for each variable to all of its related predecessors.
B) Establishing a clear path between an element and all of its immediate predecessors.
C) Including STDM variables used to derive ADaM variables in the ADaM data set.
D) Establishing a clear path between an element and all of its immediate successors.

5. Which two variables are required in BDS ADaM data sets?
(Choose two.)

A) ASEQ
B) AVAL
C) PARAM
D) STUDYID

Solutions: