{"id":15322,"date":"2018-05-12T09:15:23","date_gmt":"2018-05-12T09:15:23","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=15322"},"modified":"2021-12-05T22:00:02","modified_gmt":"2021-12-05T16:30:02","slug":"quantile-regression-in-sas","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/quantile-regression-in-sas\/","title":{"rendered":"Quantile Regression in SAS\/STAT – 3 Easy Procedures"},"content":{"rendered":"

In this SAS\/STAT Tutorial<\/strong>, we are going to study another type of analysis, called Quantile Regression in SAS\/STAT and how can we used Quantile Regression in SAS\/STAT. Moreover, we will discuss SAS Quantile Regression Procedures:\u00a0PROC QUANTLIFE, PROC QUANTREG, and PROC QUANTSELECT with examples and syntax.<\/p>\n

So, let’s start with Quantile Regression in SAS\/STAT.<\/p>\n

What is SAS\/STAT Quantile Regression?<\/h3>\n

The staggering amount of data and it\u2019s complexity in research and business analytics requires versatile, efficient and scalable methods of building statistical and predictive models. Through the process of quantile regression, we fit some conditional quantiles of the response variable along with a generalized linear model that does not take a parametric form; in other words, it gives you information that you would not obtain in the first place from any basic regression methods.<\/p>\n

Quantile regression in SAS\/STAT provides insights into various applications such as risk management. Furthermore, SAS quantile regression is also capable of modeling the entire conditional distribution which is an important part of many applications.<\/p>\n

The main advantage of SAS quantile regression over other regression procedures is its flexibility for modeling data that is heterogeneous in nature and that has conditional distributions.<\/p>\n

Procedures for Quantile Regression in SAS\/STAT<\/h3>\n

Following procedures are used to compute quantile regression in SAS\/STAT of a sample data. Let us explore it.<\/p>\n

a. PROC QUANTLIFE<\/h4>\n

The QUANTLIFE procedure in SAS\/STAT quantile regression analysis for data by using methods that are based on generalizations of two estimators namely the Kaplan-Meier and the Nelson-Aalen. It creates an output data set that contains function estimates for every set of covariates.<\/p>\n

It also supports different hypothesis tests<\/strong> for the regression parameter and automatically creates survival plots, quantile process plots, and conditional quantile plots.
\nA Syntax of PROC QUANTLIFE-<\/strong><\/p>\n

PROC QUANTLIFE DATASET <options>;\r\nCLASS <variables>;\r\nMODEL response\u00a0=\u00a0<effects> <\/ options>;<\/pre>\n
PROC QUANTLIFE\u00a0Example-<\/strong><\/p>\n
ods graphics on;\r\nproc quantlife data=sashelp.class\u00a0 log plots=all seed=12567;\r\nclass name;\r\nmodel age=height weight \/ quantile=(0.25 0.5 0.4 0.75);\r\nrun;<\/pre>\n
 <\/p>\n
\"Quantile<\/a>
SAS\/STAT Quantile Regression –\u00a0PROC QUANTLIFE<\/p><\/div>\n
\"Quantile<\/a>
SAS\/STAT Quantile Regression –\u00a0PROC QUANTLIFE<\/p><\/div>\n
\"Quantile<\/a>
SAS\/STAT Quantile Regression –\u00a0PROC QUANTLIFE<\/p><\/div>\n
\"Quantile<\/a>
SAS\/STAT Quantile Regression –\u00a0PROC QUANTLIFE<\/p><\/div>\n
\"Quantile<\/a>
SAS\/STAT Quantile Regression –\u00a0PROC QUANTLIFE<\/p><\/div>\n
b. PROC QUANTREG<\/h4>\n
The QUANTREG procedure in SAS\/STAT uses quantile regression to model the effects of covariates on quantiles of a response variable by creating an output data set that contains the parameter estimates for all quantiles.<\/p>\n
We can also perform different hypothesis tests such as ANOVA<\/strong>, t-tests<\/strong>, and also obtain specific nonlinear transformations. The output data set contains a set of predicted values, estimated errors, and other statistics.
\nA Syntax of PROC QUANTREG-<\/strong><\/p>\n
PROC QUANTREG dataset <options>;\r\nCLASS <variables>;\r\nMODEL response\u00a0=\u00a0<effects> <\/ options>;<\/pre>\n
The PROC QUANTREG and MODEL statements are required.
\nPROC QUANTREG Example-<\/strong><\/p>\n
ods graphics on;\r\nproc quantreg data=sashelp.class ;\r\nclass name;\r\nmodel age=height weight \/ quantile=(0.25 0.5 0.4 0.75) plots= all;\r\nrun;<\/pre>\n
Here, QUANTILE=option requests an estimate of quantile process for each regression parameter and displays plots for each quantile.<\/p>\n
\"Quantile<\/a>
SAS Quantile Regression –\u00a0PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
SAS Quantile Regression –\u00a0PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
SAS Quantile Regression –\u00a0PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
SAS Quantile Regression –\u00a0PROC QUANTREG<\/p><\/div>\n
 <\/p>\n
\"Quantile<\/a>
Quantile Regression in SAS\/STAT – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
Quantile Regression in SAS\/STAT – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
Quantile Regression in SAS\/STAT – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
Quantile Regression in SAS\/STAT – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
Quantile Regression in SAS\/STAT – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
SAS Quantile Regression – PROC QUANTREG<\/p><\/div>\n
\"Quantile<\/a>
SAS Quantile Regression – PROC QUANTREG<\/p><\/div>\n
c. PROC QUANTSELECT<\/span><\/h4>\n
We have already discussed this procedure in detail in SAS\/STAT Model Selection tutorial<\/strong><\/a>.
\nThis was all\u00a0about SAS\/STAT Quantile Regression Tutorial. Hope you like our explanation<\/b>.<\/p>\n
Conclusion<\/h3>\n
Hence, this was a complete description of the procedures for quantile regression in SAS\/STAT:\u00a0PROC QUANTLIFE, PROC QUANTREG, and PROC QUANTSELECT with syntax and examples.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this SAS\/STAT Tutorial, we are going to study another type of analysis, called Quantile Regression in SAS\/STAT and how can we used Quantile Regression in SAS\/STAT. Moreover, we will discuss SAS Quantile Regression...<\/p>\n","protected":false},"author":6,"featured_media":15326,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[56],"tags":[10082,10083,10084,10086,11091,12222,12357,14075,14076,14077],"class_list":["post-15322","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sas-stat","tag-proc-quantlife","tag-proc-quantlife-example","tag-proc-quantreg","tag-proc-quantselect","tag-quantile-regression-in-sas","tag-sas-quantile-regression","tag-sasstat-quantile-regression","tag-syntax-of-proc-quantlife","tag-syntax-of-proc-quantreg","tag-syntax-of-proc-quantselect"],"yoast_head":"\nQuantile Regression in SAS\/STAT - 3 Easy Procedures - DataFlair<\/title>\n<meta name=\"description\" content=\"SAS\/STAT Quantile Regression Tutorial-Procedure for Quantile Regression in SAS\/STAT:ROC QUANTLIFE,PROC QUANTREG,PROC QUANTSELECT with examples & syntax\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/quantile-regression-in-sas\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Quantile Regression in SAS\/STAT - 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