Standardization in SAS/STAT – PROC STDIZE


1. Objective

In our last tutorial, we discussed SAS Post Processing Procedures. Today, we will discuss Standardization in SAS/STAT. We will also cover the procedure used in SAS/STAT Standardization: PROC STDIZE with example & syntax.

So, let’s start with Standardization in SAS/STAT.

Standardization in SAS/STAT - PROC STDIZE

Standardization in SAS/STAT – PROC STDIZE

2. What is Standardization in SAS/STAT?

In our dataset, we always find our variables on different scales. Through the use of standardization in SAS/STAT, our goal is to put those different variables on the same scale. The standard score also called as a z-score is an important statistic because it allows us to calculate the probability of a score occurring within our normal distribution and allows you to compare scores between different types of variables. In statistics, if we want to standardize the variables, we calculate the mean and standard deviation for a particular variable. Then, for each observed value of the variable, we subtract the mean and divide by the standard deviation.

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This process also produces standard scores that tell us the number of standard deviations above or below the mean of the entire data under which a specific observation falls. For example, a standardized value of 3 indicates that the observation falls 3 standard deviations above the mean.

3. SAS/STAT Standardization Procedures

Following procedures used to compute standardization in SAS/STAT, of a sample data. Let us explore it.

a. PROC STDIZE

The STDIZE procedure in SAS/STAT is used to standardize numeric variables of our dataset where a location measure is subtracted from the original measure and is then divided with a scale measure. It encompasses all the measure standardization methods such as median, mean, standard deviation, range etc. Like the various procedures used for finding quantiles, PROC STDIZE can also be used to find quantiles in our dataset. It has 18 standardization methods to choose from and can also perform weighted standardization.

A Syntax of PROC STDIZE-

PROC STDIZE DATASET<options>;
VAR variables ;
By variable;

The PROC STDIZE statement is required.

PROC STDIZE Example-

proc stdize data=sashelp.cars method=std pstat;
   var horsepower;
   by make;
run;

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Standardization in SAS/STAT - PROC STDIZE

SAS/STAT Standardization – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

SAS/STAT Standardization – PROC STDIZE

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Standardization in SAS/STAT - PROC STDIZE

SAS/STAT Standardization – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

Standardization in SAS/STAT – PROC STDIZE

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Standardization in SAS/STAT - PROC STDIZE

Standardization in SAS/STAT – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

Standardization in SAS/STAT – PROC STDIZE

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Standardization in SAS/STAT - PROC STDIZE

SAS Standardization – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

SAS Standardization – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

SAS Standardization – PROC STDIZE

Standardization in SAS/STAT - PROC STDIZE

PROC STDIZE

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The PROC STDIZE in the above example uses the mean of the sample as the location measure and the standard deviation of the sample as the scale measure for standardizing. The PSTAT option inside the method= option displays a table containing these two measures.

So, this was all about standardization in SAS/STAT Tutorial. Hope you like our explanation.

4. Conclusion

As a result, we studied standardization in SAS/STAT and the procedure used in SAS/STAT Standardization: PROC STDIZE with syntax & example. Stay tuned for next SAS/STAT tutorial: SAS/STAT Interview Questions. Till, if you have a doubt, feel free to ask in the comment section.

Related Topic- SAS/STAT Longitudinal Data Analysis Procedures

For reference

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