Comprehensive Guide to SAS Functions

SAS FUNCTIONS

SAS functions are utilized to manipulate and transform data, perform statistical calculations, explore data quality, and create new variables. They provide a convenient way to extract specific information, convert data types, and reformat values. 

SAS functions also assist in aggregating data, calculating summary statistics, and conducting statistical analysis. They play a crucial role in data exploration, identifying missing values, and converting character variables. Additionally, SAS functions enable the application of conditional logic, allowing for the creation of derived variables and data transformation.

What are SAS functions

SAS functions are pre-defined routines in SAS programming that perform specific operations on data. They can manipulate and transform data, calculate summary statistics, and generate derived variables. SAS functions provide various capabilities, including extracting specific information from variables, converting data types, and performing mathematical operations. They are essential for data manipulation, exploration, and analysis in SAS programming. SAS functions simplify complex calculations and enable efficient data processing, ultimately aiding decision-making and generating valuable insights. The SAS System provides an extensive library of built-in functions. 

Syntax of function 

New_Var = Funtion_Name (Req_argument1 .., Opt_argument1 ....N); 

Features of SAS functions

A SAS statement identifies a function using its name, function argument(s), and parentheses around the function arguments.

SAS functions are designed to optimize data processing. They are typically implemented in a way that allows SAS to execute them efficiently, even when working with large datasets.

SAS functions have a consistent syntax, which makes them easier to learn and use. They typically follow the format function_name(argument1, argument2, ...), where you provide the necessary arguments within the parentheses.

SAS functions seamlessly integrate with other SAS components, such as procedures, formats, and macros.

SAS functions cover a wide array of statistical analyses. You can use functions for hypothesis testing, regression analysis, probability distributions, etc.

SAS functions are designed for efficiency, making them suitable for processing large datasets. 

SAS functions for character data allow you to manipulate strings, concatenate, trim, extract substrings, and perform pattern matching and replacement.

The arguments for any given function can be 

♦ Variables---Y = ABS(Var_Name) ; 

♦ Constants---X = SQRT(9562) ; 

♦ Expressions---- Z = MAX(Pre-Post) ; 

♦ Functions ---Q = Left(Trim(Str));

Arithmetic Functions 

Arithmetic functions in SAS are built-in tools that perform mathematical operations on numeric values. These functions enable you to conduct calculations, manipulate data, and derive insights from numerical data within SAS programs. Examples of arithmetic functions include SUM (to find the sum of values), MEAN (to calculate the average), MIN (to identify the minimum value), MAX (to find the maximum value), and more. These functions are essential for SAS's data analysis, statistical modeling, and data transformation tasks.

ABS Function

The ABS function is called absolute value because it returns the magnitude or size of a number without considering its direction or sign. It gives the distance of the number from zero on a number line, which is always a positive value. Therefore, it provides an absolute or definite value of a number, regardless of whether it is positive or negative.

Data _NULL_; 

FILE ‘E:\nulrpt.txt’; 

Val= -17; 

Abs_Val = ABS (Val); 

PUT Abs_Val =; 

Run;

According to the clinical studies, Patient visits are organized according to Protocol. In study X, Visits are planned on Day 1, Day 30, Day 60, and Day 120 for Visit 3, Visit 4, Visit 5, and Visit 6, respectively (As per Protocol). A day window period is permitted for patients.

DATA _NULL_: The Data set name _NULL_ is a unique keyword. The workspace does not store the _NULL_ Data set. The keyword deactivates the standard automatic output generated after the Data step. Writing output to reports or files is its usual use. 

FILE statement: The FILE statement in SAS is used to specify the location and properties of an external file that you want to read from or write to within a SAS program. It allows you to define the file's name, location, access mode (e.g., reading or writing), and other attributes. The FILE statement is commonly used in DATA steps and with various SAS procedures to import data from external files, export data to external files, or manipulate data stored in external files. It plays a crucial role in data integration and exchange between SAS and other data sources, such as text files, spreadsheets, or databases.

PUT statement: The PUT statement in SAS is used to write data or text to an external file or the SAS log. It allows you to format and output data from a SAS program, creating customized reports or exporting data in a specific format. The PUT statement helps generate structured text files, create data extracts, and produce user-friendly output in the SAS log for debugging and documentation purposes.

MOD Function

The MOD function is a mathematical operation that calculates the remainder when one number is divided by another. It is commonly used in computer programming and data analysis to determine cyclic patterns or group data into specific intervals.

Syntax: New_Var=MOD (Argument1, Argument2); 

 Argument-1: is a numeric constant, variable, or expression that specifies the dividend. 

 Argument-2: is a numeric constant, variable, or expression that specifies the divisor. 

Data Test; 

Val= MOD (22, 4);

Run; 

We created a Test dataset with a variable VAL by executing the above step. The data value of this variable is 2, which is the remainder of the division.

SAS functions are robust tools in the SAS programming language that enable data manipulation, transformation, and analysis. With many functions available, SAS users can perform complex calculations, handle missing values, format data, extract information, and more. These functions enhance the functionality and efficiency of SAS programs, allowing users to process and analyze data for various applications effectively.