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SASInstitute A00-281 : Clinical Trials Programming Using SAS 9 Accelerated Version Exam

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Test Number : A00-281
Test Name : Clinical Trials Programming Using SAS 9 Accelerated Version
Vendor Name : SASInstitute
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A00-281 test Format | A00-281 Course Contents | A00-281 Course Outline | A00-281 test Syllabus | A00-281 test Objectives


Exam ID : A00-281
Exam Title : Clinical Trials Programming Using SAS 9 - Accelerated Version
Questions : 70 to 75
Pass Marks : 70%
Duration : 2 hours
Exam Type : Multiple Choice

Clinical Trials Process
Describe the clinical research process (phases, key roles, key organizations).
Interpret a Statistical Analysis Plan.
Derive programming requirements from an SAP and an annotated Case Report Form.
Describe regulatory requirements (principles of 21 CFR Part 11, International Conference on Harmonization, Good Clinical Practices).
Clinical Trials Data Structures
Identify the classes of clinical trials data (demographic, lab, baseline, concomitant medication, etc.).
Identify key CDISC principals and terms.
Describe the structure and purpose of the CDISC SDTM data model.
Describe the structure and purpose of the CDISC ADaM data model.
Describe the contents and purpose of define.xml.
Import and Export Clinical Trials Data
Apply regulatory requirements to exported SAS data sets (SAS V5 requirements).
Manage Clinical Trials Data
Access DICTIONARY Tables using the SQL procedure.
Examine and explore clinical trials input data (find outliers, missing vs. zero values, etc).
Transform Clinical Trials Data
Apply categorization and windowing techniques to clinical trials data.
Transpose SAS data sets.
Apply 'observation carry forward' techniques to clinical trials data (LOCF, BOCF, WOCF).
Calculate 'change from baseline' results.
Obtain counts of events in clinical trials.
Apply Statistical Procedures for Clinical Trials
Use SAS procedures to obtain descriptive statistics for clinical trials data (FREQ, UNIVARIATE, MEANS, SUMMARY).
Use PROC FREQ to obtain p-values for categorical data (2x2 and NxP test for association).
Use PROC TTEST to obtain p-values for continuous data (one-sample, paired and two-sample t-tests).
Create output data sets from statistical procedures.
Macro Programming for Clinical Trials
Create and use user-defined and automatic macro variables.
Automate programs by defining and calling macros.
Use system options to debug macros and display values of macro variables in the SAS log (MPRINT, SYMBOLGEN, MLOGIC, MACROGEN).
Report Clinical Trials Results
Use PROC REPORT to produce tables and listings for clinical trials reports.
Use ODS and global statements to produce and augment clinical trials reports.
Validate Clinical Trial Data Reporting
Explain the principles of programming validation in the clinical trial industry.
Utilize the log file to validate clinical trial data reporting.
Use programming techniques to validate clinical trial data reporting (PROC COMPARE, MSGLEVEL).
Identify and Resolve data, syntax and logic errors.



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SASInstitute Practice Questions

SAS global forum - democratize your information, says CEO Jim Goodnight, it should meet the correct americans | A00-281 Real test Questions and test dumps

A consistent theme emerging from seller online conferences this season is the democratization of records and what that presents to users in terms of their exploitation of the a lot wider availability of that useful resource. however there is a sub-plot to that process, and that is the democratization of the provider neighborhood as a by-product.

This become the case at the fresh SAS Institute conference, where the field of partnerships between companies and complementary provider providers subtly shifted from a ‘high-quality to have’ further capability to ‘must have’ most effective true strategy to get to the next step. within the case of SAS, this become got here within the kind of a major bettering of two present partnerships, with Microsoft and KPMG.

in a single manner, the enhanced democratization of statistics and its exploitation means the de-skilling of the observe of working with facts. but in so doing it brings to the forefront the capabilities of people that understand what they want to get from the records and what the solutions could definitely portend when it comes to enterprise possibilities. To get to that point however, there has to be an equal absorption of existing technologies into new enhancements that in a single step both decrease the entry element of the consumer interface, and due to this fact lift the opportunity degree for brand new users to take advantage of what's now attainable.

Making companies a seamless entity

part of that technique at the moment requires all providers to well known that attaining seamless collaboration with all complementary - and sometimes competing - providers is a pre-requisite of growing pre-engineered, off-the-shelf service building blocks tht can be pulled together to create new facts exploitation capabilities in the democratized world.

This fashion become highlighted by SAS co-founder and CEO, Dr Jim Goodnight in a post-event e mail alternate:

KPMG is among a number of strategic companions that we're working with to carry options. KPMG is a protracted-time accomplice with SAS and has made a major dedication in dollars and elements to Microsoft.  It is simply herbal that the three organizations would triangulate for fulfillment.

Goodnight changed into hurry to aspect out that the power towards information democratization didn't imply de-skilling any part of information science. in reality, the ability for a much wider range of people to supply effective visualizations and analytics would increase their potential to add precise value to their personal work:

We see it as a way to boost the dimension of the analytics ability pool in groups and scale facts-pushed choice-making without needing to dramatically boost the number of information scientists. by using constructing capabilities corresponding to top-rated-practices templates, computerized evaluation and undeniable-language interpretability into their equipment, they make it viable for clients to do analyses that prior to now would have required advanced skills. This frees up statistics scientists to work on incredibly complex initiatives and serve as a ideal-practices crew.

certainly he wired that one crucial element of statistics democratization will be the over-using magnitude of conserving rigorous data and analytic governance, in addition to making certain on-going team of workers working towards on most effective practices for evaluation. He sees this as crucial to make certain the right questions are asked, the right statistics is used, and that in the end the work leads to usable outcomes and superior decisions.

The SAS/Microsoft relationship is a protracted-standing one that all started existence specializing in know-how collaboration, however later getting into share go-to-market goals. This latest revamp of the partnership takes that latter point to a brand new level. From the SAS aspect of view, Microsoft brings some straightforward, but valuable aspects to the birthday party: it still holds sway over nearly all of person work environments, no longer just with workplace, but the entire server purposes as neatly.

All of these are now core to Microsoft’s Azure cloud service. mix this with the manner the international pandemic has brought enormous impetus to the need for businesses to digitally transform their operations and develop into much more mutable – with the agility to change and adjust to altering market wants – and it stands out as one of the most leading platforms on which records democratization will also be made to work. Goodnight informed me:

groups world wide are moving to the cloud to innovate and flow quicker towards their business goals. As a part of this transition, many customers want to migrate their SAS analytic workloads to Azure to enhance efficiency and value-effectivity. To supply a seamless adventure and help organizations accelerate their cloud transformation initiatives, SAS and Microsoft are working collectively to ensure that SAS products and options may also be efficiently deployed and run with ease on Azure and the other Microsoft cloud options, including Microsoft 365, Dynamics 365 and the vigour Platform.

Serving the wants of the citizen analyst

Candidates for the position of ‘citizen analyst’ may also be discovered by means of the million amongst its current user base, working with the numerous hundreds of corporations that might effortlessly make the most the democratized information if the correct extra equipment can be found. that is what SAS is aiming at with its analytical tools, pre-engineered, company-concentrated applications and more advantageous natural language user interface tools so that it will help damage down the communications obstacles between the ‘language’ of information science and its software/capabilities out within the true world.

this is where KPMG, one more partner of lengthy standing, may find itself enjoying a crucial role. The pair intend to establish a few Cloud Acceleration facilities masking North the us, Europe and the Asia Pacific vicinity. it is definitely possible to peer these as facilities of records democratization, with the intention of helping SAS clients to get up and operating within the cloud as without problems and rapidly as possible.

KPMG and SAS will work at the side of these users to build multi-disciplinary teams that may center of attention on user specifics and how to get the top-quality out of the expertise in order to meet their business dreams. the two have already developed a few largely financial sector-oriented pre-packaged solutions. These will consistently require tailoring to fit a shopper-selected requirement in place of full on engineering, enabling them to get into production with a solution more straight away.

With Christian Rast, KPMG’s world Head of know-how and knowledge, quoted as mentioning the brand new facilities will raise the existing options portfolio, new additions to these pre-engineered company options, with an information democratic agenda, will soon start to appear.

A key SAS part in all this may be the new release of its core equipment, to be called Viya 4. This aren't purchasable except late 2020 and should characteristic what the business calls a ‘re-imagined’, cloud native architecture that has been principally designed with the automation of facts preparation, desktop learning and mannequin deployment advancements in mind. The aim is to increase productiveness by widening the supply of analytical supplies to those with different skillsets. It also makes extended use of APIs to make it less difficult for purposes developers to collaborate with facts science teams.

here's aimed at featuring a versatile and efficient method to work with analytical workloads the use of an structure designed specially to work with containers and micro-capabilities. it is going to permit clients greater operational agility by using decoupling analytics from the environments they run in, so that services will also be scaled up right now based on demands from the workloads.

tell me some thing significant

one of the key elements of Viya in its position because the platform on which records democratization can be developed is the supply of a herbal Language era (NLG) consumer interface to the facts and the analytics. now not best can it's optimized to enable users to pose questions the usage of their personal taxonomies and acquire answers in that taxonomy, making the choice-making technique some distance faster and greater correct, it'll additionally add facets comparable to automation through Auto-textual content Analytics (AutoTA), and through the availability of herbal language explanations of the way it arrived at the recommendations it has made. This gives clients with the information mandatory to optimise the evaluation approaches and make enhanced decisions. in keeping with Goodnight:

apart from riding core business choices, SAS's natural Language capabilities also permit speaking the results of complex analytics returned to the person in an easy-to-consider manner for richer insights. Examples consist of an automatic clarification function to supply key tips concerning the components that predict pursuits akin to subscribers churning, or why are customers proposing excessive satisfaction rankings.

NLG has been part of the SAS atmosphere for a while, mostly within the form of natural Language Studio. This has now been revamped and re-branded as SAS conversation dressmaker and is deliberate to be launched later this 12 months to coincide with the liberate of Viya four:

it'll additional support the natural language capabilities of SAS Viya via a conversational interface, inserting analytics in the arms of extra clients, and empowering purchasers to create their personal conversational experiences.

My take

In plenty the equal manner that the historic-fashion typing pool changed into democratized with the aid of observe processing methods, the time has truly come for analytics to shake off its black paintings status and develop into an everyday device of the company government and anyone else with facts-primarily based choice making at the core of their work. it is for this reason no shock that SAS Institute, as some of the lengthy-standing gorillas of the records evaluation jungle, should still be on the forefront of merchandising the theory.

but it surely is interesting to see it additionally enjoying an element in what may well be an immense exchange within the method functions are dropped at, and targeted via, conclusion users. records democratization cannot be offered with the aid of one enterprise – not for each possible user software at any expense. it is going to require partnerships of complementary vendors and repair providers that may create the seamless taking part functions that characteristic as a single entity for clients. certainly, it may now not be lengthy earlier than companies like KPMG become the positive brokers that form and manipulate such entities.    


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