# 30 Latest SAS-STAT Logical Interview Questions and Answers

## 1. SAS-STAT Logical Interview Questions

In our previous SAS-STAT tutorial, we discussed **Top 30 SAS-STAT Interview Questions**. In this article, we provide 30 latest SAS-STAT Logical Interview Questions. These logical questions are asked in SAS interviews.

So, Let’s start 30 Tricky SAS-STAT Logical Interview Questions.

## 2. Top Latest SAS-STAT Logical Interview Questions

After, discussing SAS-STAT Interview Question first part, we are ready to face this SAS-STAT Logical Interview Questions and Answers.

**Q1. Explain the statements used in the below example.**

proc glimmix data=sashelp.iris; class species; model age=weight; random age=weight; run;

The CLASS statement instructs the technique to treat the variables species as type variables. The version announcement in the example shown above specifies the reaction variable as a pattern proportion by means of the use of the occasions/trials approach.

the solution option inside the version declaration requests a listing of the answers for the constant-consequences parameter estimates.

The RANDOM statement specifies that a random intercept is drawn one at a time and independently for each center in the take a look at.

**Q2. What is the PROC MIXED procedure in SAS STAT used for?**

The PROC blended system in SAS/STAT fits specific blended models. mixed version have the capability to allow for one of a kind assets of variation in information, it lets in for one of a kind variances for corporations and takes into account correlation structure of repeated measurements.

**Q3. Write a sample program using PROC MIXED procedure including all the required statements?**

proc mixed data=SASHELP.IRIS plots=all; class species; model petallength= /; run;

**Q4. What is the error in the example below?**

proc mixed data=SASHELP.IRIS plots=all; model petallength= /; class species; run;

The MODEL statement must appear after the CLASS statement always.

**Q5. What is the difference between PROC HPMIXED and PROC NLMIXED?**

Through the PROC HPMIXED method, we can specify a linear combined version with variance factor structure, to estimate the covariance parameters via constrained maximum chance.

The PROC NLMIXED suits nonlinear blended models—that is, models in which each fixed and random outcomes enter nonlinearly.

**Q6. What does the PARMS statement in PROC NLIMIXED procedure do?**

The PARMS statement in the NLMIXED procedure is used to identify the unknown parameters and their starting values.

**Q7. Explain the statements used in the example below.**

proc nlmixed data=CARS; parms b1=220 b2=500 b3=310 s2u=100 s2e=60; model X ~ normal(num/den,s2e); random u1 ~ normal(0,s2u) subject=NUMBER; run;

The MIXED MODEL statement defines the dependent variable and its conditional distribution given the random effects. Here a normal (Gaussian) conditional distribution is specified.

The RANDOM statement defines the single random effect to be u1, and specifies that it follow a normal distribution with mean 0 and variance s2u. The SUBJECT= statement in the RANDOM statement is used to define a variable which will indicate when the random effect obtains new realizations.

**Read More About SAS Mixed Model Procedures in detail**

**Q8. What are the different procedures used for multivariate analysis in SAS STAT?**

**Q9. What is the difference between CANCORR and CORR procedures in SAS STAT?**

PROC CANCORR in SAS/STAT is used for canonical correlation of data.

The PROC CORR procedure produces Pearson correlation coefficients of continuous numeric variables.

**Q10. Explain the PROC PRINCOMP statement with syntax.**

PRINCOMP stands for principal component analysis. The principal component analysis comes under SAS multivariate analysis and is a technique through which we examine relationships among several variables.

PROC PRINCOMP dataset <OPTIONS>; VAR variables;

**Follow this link to know more about Multivariate Analysis Procedure – SAS/STAT**

**SAS-STAT Logical Interview Questions for Freshers. Q- 2,3,5,6,8,9**

**SAS-STAT Logical Interview Questions for Experience. Q- 1,4,7,10**

**Q11. What is the error in the example below?**

proc factor data=SASHELP.CLASS; var name ; run;

In the PROC FACTOR procedure, the variables mentioned in the VAR statement should be numeric in nature.

**Q12. What are the two separate forms of input to the CORRESP procedure?**

There are two forms in which, one form is contained inside the TABLES statement and the other is contained inside the VAR statement. Each time you run PROC CORRESP, you must specify either the TABLES or the VAR statement, but not both.

Specify the TABLES statement if you are using raw, categorical data, the levels of which define the rows and columns of a table.

Specify the VAR statement if your data is already in tabular form.

**Q13.What is multidimensional scaling and how can we perform it in SAS STAT?**

It comes under the class of methods that help us find out the coordinates of a set of objects that are in space and have a specified dimensionality. PROC MDS is used for this.

**Q14. What are the three methods provided by PROC PRINQUAL to perform market research?**

These methods are:

- Maximum total variance, or MTV
- Minimum generalized variance, or MGV
- Maximum average correlation, or MAC

**Q15. What does the SOLVE option with TRANSREG procedure signify?**

The SOLVE algorithm option inside the TRANSREG procedure requests a direct solution for both the transformation and the parameter estimates. For many models, PROC TRANSREG with the SOLVE option can produce exact results without iteration.

**Read More about PROC TRANSREG in detail**

**Q16. Explain the following example.**

proc nlin data=sashelp.cars method=gauss; parms hosepower=135 cylinders=6; model mpg_highway = (horsepower/cylinders); run;

The METHOD=option directs PROC NLIN to use the GAUSS iterative method.

The PARMS statement declares the parameters and specifies their initial values.

**Q17. Which procedure in SAS STAT use for structural equation modeling (SEM)?**

PROC CALIS in SAS/STAT is used for structural equation modeling (SEM). It can perform an exploratory and confirmatory factor analysis of any order.

**Q18. Explain the significance of arrows in the PATH statement of PROC CALIS procedure.**

In the PATH model specification, all the one-headed arrows in the path diagram are represented as path entries in the PATH statement, with entries separated by commas. In each path entry, you specify a pair of variables and the direction of the path (either <=== or ===>), followed by a path coefficient, which is either a fixed constant or a parameter with a name in the specification.

**Q19.What are the steps for multiple imputations?**

To perform multiple imputations, we need to follow some steps. These are-

Generate imputed samples using PROC MI.

Estimate the parameters for each imputed sample by using some statistical procedure.

Combine the estimation from the imputed samples by using PROC MIANALYZE.

**Q20. How can we perform model selection in SAS STAT?**

There are two procedures in SAS STAT, PROC GLMSELECT and PROC QUANTSELECT for performing model selection.

**SAS-STAT Logical Interview Questions for Freshers. Q- 12,14,17,18,21**

**SAS-STAT Logical Interview Questions for Experience. Q- 11,13,15,16,19,20**

**Q21. What is a robust regression in SAS STAT?**

*Robust regression technique in SAS/STAT** *is a form of* *** regression analysis technique** that is basically designed to cater to and overcome limitations that arise from both parametric and non-parametric methods. It is similar to least squares regression, is a technique for those datasets in which the features exhibit a non-linear trajectory and the variables and the assumptions, form the basis of datasets are likely to change in future.

**Q22. What three different classes of problems does ROBUSTREG procedure cater to?**

The robust regression techniques cater to three different classes of problem:

- Problem with outliners in the X space.
- Outliers in the Y direction.
- Outliners in both the Y direction and the X space.

**Let’s Explore Robust Regression in SAS/STAT **

**Q23. What is the difference between KRIGE2D and SIM2D procedures in SAS STAT?**

The krige2d procedure performs spatial prediction of any spatial point reference data. The basic function is kriging whereas sim2d procedure also produces a spatial simulation but for a Gaussian field.

**Q24. How can continuous variables include in the SPP procedure?**

In a spatial analysis, CONTINUOUS variables term field variables and are associated with a spatial trend. They include in the SPP procedure by using the TREND statement.

**Q25.What are the required statements in a PROC VARIOGRAM procedure?**

The PROC VARIOGRAM, COMPUTE, and COORDINATE statements require.

**Q26. What are the features offered by PROC IRT procedure?**

Enables different items to have different response models

Performs multiple-group analysis,

Performs analysis such as exploratory and multidimensional

Uses the method of maximum likelihood to estimate factor scores

**Q27. What is**** psychometric analysis?**

A psychometric analysis is one of the many analysis procedures in which the tests are psychological in nature as well as measurements to ensure that the obtained values are trusted and valid. A psychometric analysis is performed through using instruments that are used to measure attitudes, human behavior, abilities, or personality traits in order to improve these traits or to make sure that the results being delivered are true.

**Let’s Learn SAS/STAT Psychometric Analysis Procedure**

**Q28. What are the different procedures used for Survival analysis in SAS STAT****?**

**Read More About SAS Survival Analysis Procedures **

**Q29. What does the QUANTILE= option in QUANTREG procedure do?**

The QUANTILE=option in the QUANTREG procedure used to request an estimate of the quantile process for each regression parameter after which it displays plots for each quantile.

**Q30. ****What is the syntax for QUANTLIFE procedure?**

PROC QUANTLIFE DATASET <options>; CLASS <variables>; MODEL response = <effects> </ options>;

**Follow this link to know about Quantile Regression in SAS/STAT in detail**

**SAS-STAT Logical Interview Questions for Freshers. Q- 21,22,23,24,25**

**SAS-STAT Logical Interview Questions for Experience. Q- 26,27,28,29,30**

So, this all about SAS-STAT Logical Interview Questions and Answers. Hope you like our explanation.

## 3. Conclusion

Hence, these were some of the most important SAS-STAT logical interview questions, that are frequently asked. We will come back with more interesting topics. Till then stay tuned and post your doubts in the comments section below.

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