Question: How Do You Replace Missing Values In SAS?

How do you remove missing values in SAS?

To remove records that have a missing value for a particular character variable, you simply need to use an IF statement to check for blanks, followed by a THEN DELETE statement.

In this example, we are going to remove all records with a missing value for the DeathCause variable..

Is missing in SAS Data step?

The MISSING function enables you to check for either a character or numeric missing value, as in: if missing(var) then do; In each case, SAS checks whether the value of the variable in the current observation satisfies the condition specified. If it does, SAS executes the DO group.

Does Proc mean missing values?

PROC MEANS excludes missing values for the analysis variables before calculating statistics. … If a FREQ variable value is missing or nonpositive, PROC MEANS excludes the observation from the analysis. If a WEIGHT variable value is missing, PROC MEANS excludes the observation from the analysis.

How do you remove duplicate observations in SAS?

The Sort Procedure with the NODUPKEY option is the simplest and most common way of removing duplicate values in SAS. Simply specify the NODUPKEY option in the PROC SORT statement. In the BY statement, specify the variables by which you want to remove duplicates.

How do you impute missing values?

The following are common methods:Mean imputation. Simply calculate the mean of the observed values for that variable for all individuals who are non-missing. … Substitution. … Hot deck imputation. … Cold deck imputation. … Regression imputation. … Stochastic regression imputation. … Interpolation and extrapolation.

What does period mean in SAS?

In SAS Missing values for numeric variables (including date variables) appear as a period. SAS treats numeric nulls as equal to “the lowest possible number” (essentially negative infinity) when sorting a numeric field. SAS datasets will have a period as a value for missing data.

What to do with missing values?

And here are seven things you can do about that missing data: Listwise Deletion: Delete all data from any participant with missing values. If your sample is large enough, then you likely can drop data without substantial loss of statistical power.

What percentage of missing data is acceptable?

@shuvayan – Theoretically, 25 to 30% is the maximum missing values are allowed, beyond which we might want to drop the variable from analysis. Practically this varies.At times we get variables with ~50% of missing values but still the customer insist to have it for analyzing.

How does SAS deal with missing values?

Numeric missing values are represented by a single period (.). Character missing values are represented by a single blank enclosed in quotes (‘ ‘). Special numeric missing values are represented by a single period followed by a single letter or an underscore (for example .

How do you include missing values in proc means?

A simple and quick method to check the number of missing values in a table is to use PROC MEANS with the NMISS option: proc means data = hmeq nmiss; run; Note that only variables with a numeric format can be analyzed with this method.

How do you replace missing values with 0 in SAS?

proc stdize data=Miss_Values out=ProcStdizeMethod reponly missing=0; run; By default, PROC STDIZE standardizes the input data by some location and scale parameter. However, we can suppress the standardization with the REPONLY Option. This option ensures that we are only to replace missing values and nothing else.

What is Call Missing in SAS?

A relatively new call routine in SAS 9.1, CALL MISSING, allows you to set any number of character or numeric variables to a SAS missing value in one call. The syntax of this call routine is as follows: … where arg1, arg2, argn are the names of character or numeric variables.

Which SAS function can be used to detect missing values in a variable?

function cmissNumber of missing values in each observation For example, we can use SAS function cmiss to store the number of missing values from both numeric and character variables in each observation.