최신SASInstitute Clinical Trials Programming Using SAS 9.4 - A00-282무료샘플문제

A. SDTMIG.pdf

B. define.xml

C. specs.xml

D. acrf.pdf

A. proc sort data=cm out=data_bb (keep=usubjid cmstdtc cmtrt);
by usubjid CMSTDTC;
where cmtrt in('BLOCKER');
run;

B. data data_bb;
set cm (where=(find(cmtrt,'BLOCKER','i')>0));
by usubjid CMSTDTC;
run;

C. proc sort data=CM (keep=usubjid cmstdtc cmtrt) out=data_bb;
by usubjid CMSTDTC;
where cmtrt contains 'BLOCKER';
run;

D. data data_bb;
set cm (keep=usubjid cmstdtc cmtrt);
by usubjid CMSTDTC;
where cmtrt in('BLOCKER');
run;

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 subjidn;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;

C. proc sort data=a out=b nodupkey;
by trta aesoc;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;

D. proc sort data=a out=b;
by trta aesoc;
run;
proc freq data=b noprint;
by trta;
table aesoc / out=freq;
run;

A. if LBORRES = . then output;

B. if LBORRES in (. ._) then output;

C. if missing(LBORRES) then output;

D. if LBORRES <= .A then output;

A. The internal values of Frequency are different in the base and comparison data sets.

B. The formatted values of Frequency are different in the base and comparison data sets.

C. The variable types of Frequency are different in the base and comparison data sets.

D. The variable labels of Frequency are different in the base and comparison data sets.

A. 7

B. 6

C. 8

D. 1

A. if age <=18 then do AGECAT=1; else if 18<AGE<=40 then do AGECAT=2; else do AGECAT=3;

B. if age <18 then AGECAT=1; if 18<=AGE<=40 then AGECAT=2; else AGECAT=3;

C. if age <=18 then AGECAT=1; else if 18<AGE<=40 then AGECAT=2; else AGECAT=3;

D. if age <18 then AGECAT=1; else if 18<=AGE<=40 then AGECAT=2; else AGECAT=3;

A. Copy statistical code directly from the SAP.

B. Copy statistical code directly from the production program.

C. Ensure the production program has been run prior to compare.

D. Delete subjects from the production side that are causing differences with the validation data set.

A. Operational Data Model (ODM)

B. Study Data Tabulation Model (SDTM)

C. Trial Design Model (TDM)

D. Clinical Data Acquisition Standards Harmonization (CDASH)

A. ods output mean=m1 m2 std=s1 s2;

B. output mean std;

C. ods output out=WORK.RESULTS mean=m1 m2 std=s1 s2;

D. output out=WORK.RESULTS mean=m1 m2 std=s1 s2;