SAS provides several functions to test for missing values but in this post we will focus on MISSING(), CMISS() and NMISS() functions. The NMISS() function is reserved for numeric variables. The MISSING() and CMISS() functions can be used with either character or numeric variables.    The CMISS() and NMISS() functions are designed by SAS to count the number of arguments with missing values whereas the MISSING function checks whether or not a variable is missing. The MISSING(), CMISS(), and    NMISS() functions provide a simple approach to check for missing values and these functions let you write few lines of code by avoiding large if-statements when you need to check for missing values in several values at the same time. MISSING() function is very useful when you need to check any variable has a missing value or not, but not sure if it’s a character or numeric? MISSING function works for either character or numeric variables and it also checks for the speci...

USE OF THE “STUDY DAY” VARIABLES The permissible Study Day variables (--DY, --STDY, and --ENDY) describe the relative day of the observation starting with the reference date as Day 1. They are determined by comparing the date portion of the respective date/time variables (--DTC, --STDTC, and --ENDTC) to the date portion of the Subject Reference Start Date (RFSTDTC from the Demographics domain). The Subject Reference Start Date (RFSTDTC) is designated as Study Day 1. The Study Day value is incremented by 1 for each date following RFSTDTC. Dates prior to RFSTDTC are decremented by 1, with the date preceding RFSTDTC designated as Study Day -1 (there is no Study Day 0). This algorithm for determining Study Day is consistent with how people typically describe sequential days relative to a fixed reference point, but creates problems if used for mathematical calculations because it does not allow for a Day 0. As such, Study Day is not suited for use in subsequent numerical computations...