Why does sas mean missing

In this article, we will discuss different methods for handle missing values with both character and numeric variables. Ways to remove records with missing values will be discussed and we will provide some tips and tricks on how to easily count or flag missing values in your data.

Finally we will demonstrate different strategies you can use to summarize and report on the presence of missing values. Along the way, examples will be provided to illustrate the different methods for handling missing values and show how different SAS Procedures deal with missing values.

Some of the associated options which affect how SAS procedures behavior with missing values will also be discussed. In particular, the main topics covered include:. Before we continue, make sure you have access to SAS Studio. It's free! The HEART dataset in particular contains a variety of character and numeric variables which contain missing values.

This datasets which serve as great practice for gaining a better understanding on how to handle missing values in your SAS datasets. All variables in SAS fall under one of two variable types, character or numeric. Within these two variable types, missing values are handled slightly differently. With character variables, missing variables are denoted with a blank.

With numeric variables, a missing value is denoted with a period. In SAS code, the period [. CLASS dataset, which contains the list of students in a class and some basic information about them. In the code below, we create a new dataset, WORK. Sometimes, you simply want to remove records which contain missing values for a particular variable in your dataset.

HEART dataset, which contains various health and demographic variables about different people. In this example, we are going to remove all records with a missing value for the DeathCause variable. In this example, we are going to remove all records with a missing value for the AgeCHDdiag variable using the following code:.

Looking at the Output Data shown partially below, you can see that any records with a blank for AgeCHDdiag have been removed, and the total number of rows is now only In large datasets with many variables you are not very familiar with, it is easy to lose track of which variables are numeric and which are character.

When transforming or creating SAS variables, the first part of the code should deal with the case where variables are missing. SAS version 8 introduced a new function, MISSING, that accepts either a character or numeric variable as the argument and returns the value 1 if the argument contains a missing value or zero otherwise. As such, the code above can be improved as follows:. Even if you think that a variable should not contain any missing values, you should always write your code under the assumption that there may be missing values.

Explore the three tracks and full agenda items. IF, SQL vs. Sign In. Turn on suggestions. Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. Showing results for. Search instead for. Try this out How can I do this?

Can anyone please help? They are as follows : dot-underscore. A through. Z Not case sensitive Sorting Order : dot- underscore is the lowest valued missing value. After the dot-underscore, comes the dot, and then the dot-A. The dot-Z is the highest valued missing value. Run the following code and see how SAS treats them missing value. Check for missing numeric values.