# Robust Regression in SAS/STAT – 3 Best Procedures

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## 1. Objective

In the last article, we discussed SAS Power and Sample Size Analysis. Today, we will be looking at another type of analysis, called Robust Regression in SAS/STAT and how can we use SAS/STAT robust regression. Our focus here will be to understand the SAS/STAT robust regression Procedures: PROC QUANTREG, PROC QUANTSELECT, and PROC ROBUSTREG with example & syntax.
So, let’s begin with Robust Regression in SAS/STAT.

## 2. What is Robust Regression in SAS/STAT?

Robust regression is designed to overcome the limitations, which are arises from traditional parametric and non-parametric methods. Robust regression in SAS/STAT is a form of regression analysis. It is also similar to least squares regression, is a technique used for those datasets in which the variables and the features exhibit a non-linear trajectory and the assumptions that form the basis of the dataset are likely to change in future.
Let’s discuss Important SAS/STAT Longitudinal Data Analysis Procedures
Robust regression in SAS/STAT is a statistical procedure used for modeling a regressor in the presence of an outlier in the dataset and can also support any anomalous detection. It can be used along with many machine learning and computing approaches such as :

1. Linear regression
2. Markovian logic
3. Fuzzy system
4. Expectation maximization algorithm.

## 3. SAS/STAT Robust Regression Procedures

Following procedures to compute robust regression in SAS/STAT of a sample data. Let us explore it.

### a. PROC ROBUSTREG

SAS ROBUSTREG procedure in SAS/STAT is used to detect outliers. Outliers are basically observations that lie very far or at an abnormal distance from our population. In the presence of these outliers, stable results are provided by limiting the influence of these outliers.
The robust regression in SAS/STAT cater to three different classes of problems:

• Problems with outliers in the X space
• Outliers in the Y direction
• Outliers in both the Y direction and the X space

A Syntax of PROC ROBUSTREG-

```PROC ROBUSTREG  DATASET<options>;
CLASS variables;
MODEL dependent-variables = effects </ options>;```

The PROC ROBUSTREG  and MODEL statements are required.
PROC ROBUSTREG Example-

```proc robustreg data=sashelp.class;
class name;
model age=height;
run;```

### b. PROC QUANTREG

We have already discussed this procedure in detail in SAS/STAT Quantile Regression tutorial.

### c. PROC QUANTSELECT

We have already discussed this procedure in detail in SAS/STAT Quantile Regression tutorial.

## 4. Conclusion

Hence, we complete one more analysis in SAS/STAT journey, Robust Regression in SAS/STAT. In conclusion, we saw different procedures used in SAS/STAT Robust Regression: PROC QUANTREG, PROC QUANTSELECT, and PROC ROBUSTREG with Syntax & examples. Still, if you have any doubt, ask in the comment box.