The SAS clinical trials exam, A00-282, checks whether you can carry a study's data from the protocol all the way to validated tables. It has 60 to 70 questions, you get 1 hour 50 minutes, and you need 68% to pass. The biggest single section is not statistics or macros. It is validation, at 20%.
Most guides list the nine exam sections one after another, as if they were separate subjects. They are not. In a real study they are steps on one path: you read the plan, map the data, derive what the analysis needs, run the statistics, build the tables, and then prove the tables are right. This entry walks that path and shows where each section sits on it, with the weight SAS gives it. It ends with a six-week plan, the mistakes that cost the most marks, and five short answers. Every exam figure here was read on SAS's own pages on 2 November 2026.
What is the SAS clinical trials exam, in short?
A00-282 is the exam ID for the SAS Certified Professional: Clinical Trials Programming Using SAS 9.4 credential, which the SAS site also shows as Clinical Trials Programming Professional. SAS and Pearson VUE run it. The fee is $180, charged in US dollars in every country.
The format, as the SAS clinical trials programming credential page gives it:
- 60 to 70 multiple choice and short-answer questions
- 1 hour 50 minutes (110 minutes)
- Passing score of 68%
- Nine sections, from 5% to 20% each
The AnalyticsExam channel has a three-minute overview of what to study, which is a good place to start before you open the official guide.
Who can sit A00-282?
This is a professional-level exam, and SAS sets three conditions on its credential page. You need to hold the Base Programming Specialist or the Advanced Programming Professional credential first. You need the recommended training or equivalent experience. And you need at least six months of experience as a clinical trials programmer using SAS software.
The first condition matters most for planning. If you do not hold one of those two credentials yet, that exam comes first, and your A00-282 date moves back with it. The six months of real clinical programming matter too: several objectives in the guide are written as work tasks, such as working out why two validation programs disagree, and those come easier to people who have already seen a messy lab data set or a table that did not match.
Why read the nine sections as one data path?
Because that is how the work happens, and the objectives follow the work. When you group the sections by the stage of a study they belong to, the exam turns into four blocks you can study in order:
- Plan and structure (20%): clinical trials process 5%, clinical trials data structures 10%, regulatory submissions 5%.
- Build (35%): manage clinical trials data 5%, transform or summarize clinical trials data 15%, macro programming 15%.
- Analyse and report (25%): apply statistical procedures 15%, report clinical trials results 10%.
- Check (20%): validate clinical trial data reporting 20%.
The grouping is ours. The percentages are SAS's. Read this way, two things stand out. The build stage is the largest block, at 35%. And checking the output is worth as much as the whole first stage, which surprises most candidates.
What does the plan and structure stage ask?
It asks whether you can read a study's documents and know where every piece of data should end up. The A00-282 exam content guide lists the tasks in detail, and this stage is where it starts.
For the clinical trials process (5%), you describe the phases of clinical research, the key roles and the key organizations, and you derive programming requirements from a statistical analysis plan (SAP) and an annotated case report form. In practice that means reading an SAP table shell and saying which variables you need and where they come from.
For data structures (10%), the guide names CDISC principles and terms, the structure and purpose of the SDTM and ADaM models, and tracing data from raw data to any of the mapped domains. Think of SDTM as the collected data put into standard domains, and ADaM as the analysis-ready layer built from it. The exam expects you to follow one value through both.
For regulatory submissions (5%), you apply the SAS V5 requirements to exported data sets and describe what define.xml contains and why it exists. The V5 transport format has tight limits, such as 8-character variable names and 40-character labels, so a long name that works in your session can break a submission file.
What does the build stage ask?
This is the biggest block, and it is plain SAS programming applied to trial data. Managing data (5%) means using DICTIONARY tables with PROC SQL to look at your libraries, and using DATA step checks to find outliers, odd values, and the difference between a missing value and a real zero.
Transforming or summarizing data (15%) is where most of the daily work sits. The guide lists:
- Deriving variables by categorization and windowing, for example putting each visit into an analysis window by study day
- Checking that dates follow ISO 8601 and storing them that way with functions
- Reshaping data with PROC TRANSPOSE and with arrays in the DATA step
- Calculating change from baseline
- Counting events
- Using FIRST. and LAST. variables
Macro programming (15%) covers macro variables and parameters, user-defined and automatic macro variables, defining and calling macros to automate repeated work, and the debugging options MPRINT, SYMBOLGEN and MLOGIC. Know what each one writes to the log: MPRINT shows the code a macro generates, SYMBOLGEN shows how each macro variable resolves, and MLOGIC traces the macro's own logic, such as %IF conditions.
What does the analyse and report stage ask?
It asks you to pick the right procedure, read its output, and turn it into tables, listings and graphs. For statistical procedures (15%), the guide names FREQ, UNIVARIATE, MEANS and SUMMARY for descriptive statistics. It adds two tasks people skip: deciding whether a procedure can produce an analysis given categorical or quantitative data, and finding syntax or semantic errors in sample code from FREQ, TTEST, GLM and REG. You also create output data sets with ODS OUTPUT and with OUTPUT statements, and program for both safety and efficacy data.
Reporting (10%) is mostly PROC REPORT and ODS. The guide goes statement by statement: COLUMN, DEFINE, BREAK and RBREAK, COMPUTE blocks, LINE, CALL DEFINE and the OUT= option. On the ODS side it lists ODS TRACE, ODS SELECT and EXCLUDE, opening and closing destinations such as RTF, PDF and WORD, and ODS GRAPHICS. Graphs come from PROC SGPLOT and SGPANEL, including box plots, histograms, series, high-low and waterfall plots, grouped data, reference lines, axes and legends.
Why is validation the biggest single section?
Because in clinical work a table that is wrong is worse than no table, and the industry checks every output with independent programming. SAS gives validation 20% of the exam, more than any other section.
The guide lists six tasks here. You explain the principles of programming validation in the clinical trial industry. You use the log to validate reporting. You use PROC COMPARE and the MSGLEVEL option. You work out why two independent validation programs gave different results. You identify what PROC COMPARE does not check. And you find and fix data, syntax and logic errors.
The fifth task is the one to learn by heart. PROC COMPARE compares data, so it does not check titles or footnotes, and depending on how they were added in a procedure like PROC REPORT, it may not check formats or labels either. Two programs can match perfectly in PROC COMPARE while the printed tables still differ.
What does one value look like on that path?
Here is a worked example of our own, written to show how the sections connect. It is not an exam item.
Say the SAP asks for the change from baseline in a lab test at week 12. You start from the annotated CRF and the raw lab file (process). The value lands in the SDTM lab domain with an ISO 8601 date, then in an ADaM data set where each record carries the analysis value and the baseline (data structures, transform). The visit was recorded on study day 87, so your windowing rule decides whether it counts as week 12. Baseline is the last value before the first dose, which is a FIRST./LAST. job once the data is sorted. Change from baseline is the analysis value minus the baseline value.
You then run PROC MEANS by treatment group, send the result to a data set with ODS OUTPUT or an OUTPUT statement, and lay out the table with PROC REPORT (statistics, reporting). A second programmer builds the same numbers on their own, and PROC COMPARE shows a difference in two subjects (validation). The cause turns out to be a missing lab value that one program treated as zero (manage data). One value has touched six of the nine sections.
How should you pace 110 minutes?
Our own arithmetic, not a SAS rule: 110 minutes over 70 questions is about 1.6 minutes each, and over 60 questions about 1.8 minutes. That is enough for short code reading, but not for long tracing on every item.
At 68%, 41 correct answers out of 60, or 48 out of 70, would meet the mark if every question counts the same. SAS does not say they do, so use these only as planning numbers. A sensible rhythm is to answer what you know at once, flag any long code or tracing item, and come back to the flags with the time you saved.
What does a six-week study plan look like?
Six weeks works for someone who already meets the prerequisites and programs in SAS at work. Go stage by stage, in the same order as the data path:
- Week 1, plan and structure: read the content guide end to end, then map one SAP table shell to its SDTM and ADaM sources. Learn the V5 limits and what define.xml holds.
- Week 2, managing and transforming: DICTIONARY tables, missing vs zero checks, ISO 8601 dates, windowing, PROC TRANSPOSE and arrays on the same data set.
- Week 3, baseline and macros: change from baseline and event counts with FIRST./LAST., then wrap one repeated task in a macro and debug it with MPRINT, SYMBOLGEN and MLOGIC.
- Week 4, statistics: FREQ, MEANS, SUMMARY and UNIVARIATE output to data sets; read TTEST, GLM and REG code and spot what is wrong with it.
- Week 5, reporting: one demographics table and one adverse event table in PROC REPORT with COMPUTE and CALL DEFINE, sent to RTF and PDF; one SGPLOT graph with a reference line.
- Week 6, validation and timing: double-program one table and reconcile it with PROC COMPARE, then take a timed practice run and rework every section where you hesitated.
Which mistakes cost the most marks?
From the way the guide is written, five patterns stand out:
- Treating validation as an afterthought. At 20% it deserves a full week, not the last evening.
- Trusting a clean PROC COMPARE. It does not check titles and footnotes, and it may miss formats and labels.
- Mixing up missing and zero. In a lab or dosing data set the two mean very different things, and the guide calls this out on its own.
- Reading macro logs too fast. Know which option writes which line before you need it.
- Skipping the SAP. The first section is only 5%, but requirements from the SAP drive the questions in every later stage.
Which practice resources help?
Start with the official ones. The free SAS certification practice exams include one for the Clinical Trials Programming Professional credential. Access lasts 180 days from activation, and you can re-attempt it as many times as you like.
Use it twice: once at the end of week 3 to find gaps, and once in week 6 under time. Between the two, keep a list of every topic where you guessed, and rebuild each one in SAS before the second run.
For a quick review between sessions, the A00-282 study guide slides on Kahoot walk through the nine sections one by one.
Slides help with recall, but they do not train your pace. Timing only improves when you sit a full set of questions against the clock and then review every miss.
When you want more timed runs, the A00-282 practice exam on AnalyticsExam follows the same question count, time limit and passing mark, so you can check that your pace holds across a full sitting.
Whatever you use, keep the official content guide as the master list. If a practice source drills a topic the guide does not name, treat it as background, not as exam scope.
If you are planning more than one SAS credential, the earlier entry on this blog that sets out the A00-470 Visual Analytics objectives and their weights uses the same section-by-section approach for SAS Viya.
Frequently asked questions
1. How many questions are on the SAS clinical trials exam?
The A00-282 exam has 60 to 70 multiple choice and short-answer questions. You get 1 hour 50 minutes, and the passing score is 68%.
2. Which A00-282 section carries the most weight?
Validate clinical trial data reporting, at 20%. Transform or summarize data, statistical procedures and macro programming follow at 15% each.
3. What do I need before I can take A00-282?
SAS asks for the Base Programming Specialist or the Advanced Programming Professional credential, the recommended training or equivalent experience, and at least six months of experience as a clinical trials programmer using SAS software.
4. Does the exam cover CDISC SDTM and ADaM?
Yes. The clinical trials data structures section, worth 10%, covers key CDISC principles and terms, the structure and purpose of SDTM and ADaM, and tracing data from raw data to the mapped domains.
5. How much does the A00-282 exam cost?
The exam fee is $180, charged in US dollars in every country. SAS offers academic discounts for students and educators.