You can use the **CMISS** function in SAS to count the number of missing values in each row of a dataset.

Here is one common way to use this function in practice:

**data new_data;
set my_data;
total_missing = cmiss(of team -- assists);
run;**

This particular example creates a new dataset called **new_data** that includes a column called **total_missing** that counts the number of missing values in each row between the columns named **team** and **assists**.

The following example shows how to use this syntax in practice.

**Example: Use CMISS in SAS to Count Number of Missing Values in Each Row**

Suppose we have the following dataset in SAS called **my_data** that contains information about various basketball players:

**/*create dataset*/
data my_data;
input team $ points assists;
datalines;
Cavs 12 5
Cavs 14 7
Warriors 15 9
. 18 9
Mavs 31 7
Mavs . 5
. . 3
Celtics 36 9
Celtics 40 7
;
run;
/*view dataset*/
proc print data=my_data;**

Notice that several rows have missing values.

We can use the **CMISS** function to count the number of missing values in each row:

The following examples show how to use each method in practice with the following dataset in SAS:

**/*create new dataset that counts number of missing values in each row*/
data new_data;
set my_data;
total_missing = cmiss(of team -- assists);
run;**

The new column called **total_missing** displays the number of missing values in each row.

For example:

- The first row contains
**0**missing values. - The second row contains
**0**missing values. - The third row contains
**0**missing values. - The fourth row contains
**1**missing value.

And so on.

**Note**: You can find the complete documentation for the SAS **CMISS** function here.

**Additional Resources**

The following tutorials explain how to perform other common tasks in SAS:

How to Count Missing Values in SAS

How to Remove Rows with Missing Values in SAS

How to Replace Missing Values with Zero in SAS