Clinical SAS Programmer
Clinical SAS Programmer Interview Questions and Answers
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Q1. data demo; set demo1; where age<14; where weight>80; run: what is the mistake in this code? kind of this question not the same one
The code has two 'where' statements which is not allowed in SAS.
Remove one of the 'where' statements to correct the code.
Combine the conditions using 'and' or 'or' operators if both conditions need to be applied.
Q2. In DM what kind of information will stored and what are the variables we have in DM
In DM, information related to study subjects, visits, assessments, and other clinical trial data is stored. Variables include subject ID, visit number, date/time, and results.
DM stands for Data Management in clinical trials
Information stored includes subject demographics, study visits, lab results, adverse events, etc.
Variables in DM can include subject ID, visit number, date/time, results, treatment group, etc.
Example: Subject ID - 001, Visit Number - 1, Date - 01/01/2022, L...read more
Q3. What are the supervisory functions why would we call them as supervisory function
Supervisory functions are tasks related to managing and overseeing the work of others in a team or organization.
Supervisory functions include planning, organizing, staffing, directing, and controlling.
These functions are called supervisory because they involve overseeing and managing the work of subordinates.
Examples of supervisory functions in a clinical SAS programming role include assigning tasks to team members, monitoring progress, and providing guidance and feedback.
Sup...read more
Q4. x=1+.+2+7 y=sum(1,.,2,7) have to explain what the difference is above two codes working
The first code calculates the sum of 1, 2, and 7 separately, while the second code calculates the sum of 1, 2, and 7 as a whole.
Code x=1+.+2+7 calculates the sum of individual numbers (1, 2, 7) separately.
Code y=sum(1,.,2,7) calculates the sum of all numbers (1, 2, 7) together.
The first code will result in x=1+2+7=10, while the second code will result in y=1+2+7=10.
Q5. What is Clinical SAS?
Clinical SAS is a specialized software used in the pharmaceutical industry for data analysis and reporting in clinical trials.
Clinical SAS is used for managing, analyzing, and reporting data from clinical trials.
It helps in generating tables, listings, and graphs to summarize trial data.
Clinical SAS is essential for ensuring data quality and regulatory compliance in clinical research.
It is commonly used in pharmaceutical companies, contract research organizations (CROs), and ...read more
Q6. Clinical SAS Salary Ranges For beginers
Clinical SAS salary ranges for beginners vary depending on location, experience, and employer.
Salary ranges can vary based on geographic location, with higher salaries typically found in major cities.
Experience level also plays a significant role in determining salary, with more experienced programmers earning higher salaries.
Employer type, such as pharmaceutical companies or research institutions, can also impact salary ranges.
On average, entry-level Clinical SAS Programmers...read more
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Q7. Use of Clinical SAS?
Clinical SAS is used for analyzing clinical trial data to ensure drug safety and efficacy.
Used for statistical analysis of clinical trial data
Generates tables, listings, and graphs for reporting
Helps in identifying trends and patterns in data
Ensures data integrity and regulatory compliance
Q8. wht is Clinical sas?
Clinical SAS is a specialized software used in the pharmaceutical industry for analyzing clinical trial data.
Clinical SAS is used for statistical analysis and reporting of clinical trial data.
It helps in generating tables, listings, and graphs to summarize the results of clinical studies.
Clinical SAS programmers work with data from clinical trials to ensure accuracy and compliance with regulatory standards.
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Q9. Future of clinical
The future of clinical research is promising with advancements in technology, personalized medicine, and data analytics.
Advancements in technology such as AI and machine learning are revolutionizing clinical trials and data analysis.
Personalized medicine is becoming more prevalent, leading to more targeted and effective treatments.
Data analytics is playing a crucial role in identifying trends, patterns, and insights from large datasets to improve patient outcomes.
Virtual clin...read more
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