{"id":13900,"date":"2018-05-05T12:20:44","date_gmt":"2018-05-05T12:20:44","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=13900"},"modified":"2021-12-05T22:30:56","modified_gmt":"2021-12-05T17:00:56","slug":"stat-exact-inference","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/stat-exact-inference\/","title":{"rendered":"Learn SAS\/STAT Exact Inference with 5 Procedures"},"content":{"rendered":"

In our previous articles, we looked at different types of analysis and the procedures used for performing them, today we will be looking at what is an exact inference in SAS\/STAT<\/strong>. Moreover, we will also cover how SAS\/STAT\u00a0Exact Inference is used.<\/p>\n

Finally, we will focus on understanding different procedures:\u00a0PROC LOGISTIC, PROC GENMOD, PROC FREQ, PROC NPAR1WAY, and PROC MULTTEST that can be used for SAS\/STAT\u00a0Exact Inference through the use of examples.
\nSo, let’s start with SAS\/STAT Exact Inference.<\/p>\n

What is SAS\/STAT Exact Inference?<\/h3>\n

Modern statistical methods rely heavily on nonparametric techniques for comparing two or more populations. These techniques generate p-values without making any distributional assumptions about the populations being compared. They rely, however, on an asymptotic theory that is valid only, if the sample sizes are reasonably large and well balanced across the populations.<\/p>\n

For small, sparse, skewed, or heavily tied data, the asymptotic theory may not be valid. In such cases, SAS\/STAT exact inference methods are used.<\/p>\n

Procedures for Exact Inference in SAS\/STAT<\/h3>\n

Following procedures are used to perform SAS\/STAT exact inference of a sample data. Each procedure has a different syntax and is used with different type of data in different contexts. Let us explore each one of these.<\/p>\n

a. PROC MULTTEST<\/h4>\n

The MULTTEST procedure in SAS\/STAT\u00a0Exact Inference is used to remove the multiple testing problems. This problem arises when you perform many hypothesis tests<\/strong> on the same data set. PROC MULTTEST approaches the multiple testing problems by adjusting the\u00a0p<\/em>-values from a family of hypothesis tests.<\/p>\n

It handles data arising from a multivariate one-way ANOVA model.
\nPROC MULTTEST Syntax-<\/strong><\/p>\n

PROC MULTTEST<<\/pre>\n
options > ; \u00a0Class variable; \u00a0Test name <options> ;
\nPROC MULTTEST Example-<\/strong><\/p>\n
title 'multtest procedure';\r\ndata cars;\r\n\u00a0\u00a0 input origin$ airbags1-airbags4;\r\n\u00a0\u00a0 datalines;\r\nindia\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 0\r\namerica\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\r\nrussia\u00a0\u00a0 \u00a0\u00a01\u00a0\u00a0 0\u00a0\u00a0 0\u00a0\u00a0 0\r\nbrazil\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\r\nchina\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 0\u00a0\u00a0 0\r\njapan\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 0\r\neurope\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 1\u00a0\u00a0 0\r\nsingapore\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 0\u00a0\u00a0 0\r\naustralia\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 0\u00a0\u00a0 1\r\ndubai\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 1\r\ngermany\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\r\ncanada\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 1\r\nparis\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 1\u00a0\u00a0 1\r\negypt\u00a0\u00a0\u00a0\u00a0\u00a0 1\u00a0\u00a0 1\u00a0\u00a0 0\u00a0\u00a0 1\r\npakistan\u00a0\u00a0 0\u00a0\u00a0 0\u00a0\u00a0 1\u00a0\u00a0 1\r\n;\u00a0\r\nods graphics on;\r\nproc multtest bootstrap nsample=1000 seed=41287\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 plots=ALL;\r\n\u00a0\u00a0 class origin;\r\n\u00a0 test ca(airbags1-airbags4);\r\n\u00a0\u00a0 contrast 'Trend' 0 1 2;\r\nrun;<\/pre>\n
This analysis uses the\u00a0BOOTSTRAP option to adjust the\u00a0p<\/em>-values. The\u00a0NSAMPLE=option requests 1000 samples for the bootstrap analysis, and the starting seed for the random number generator is 41287.
\nThe\u00a0PLOTS=option displays a visual summary of the unadjusted and adjusted\u00a0p<\/em>-values against each test.<\/p>\n
The\u00a0CLASS statement is used to specify the grouping variable, origin. The\u00a0ca(airbags1-airbags4)\u00a0specification in the\u00a0TEST statement requests a Cochran-Armitage linear trend test for all 4 characteristics.
\nThe\u00a0CONTRAST statement gives the coefficients for the linear trend test.<\/p>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference –\u00a0PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference In SAS\/STAT-\u00a0PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in STAT –\u00a0PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in SAS\/STAT -PROC MULTTEST<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in STAT\u00a0– PROC MULTTEST<\/p><\/div>\n
b. PROC NPAR1WAY<\/span><\/h4>\n
NPAR1WAY stands for non-parametric one-way analysis. PROC NPAR1WAY provides a standard analysis of variance on the raw data, empirical distribution function statistics, pair-wise multiple comparison analysis, and stratified analysis. It provides tests that use the raw input data as scores.<\/p>\n
When the data are classified into two samples, tests are based on simple linear rank statistics. When the data are classified into more than two samples, tests are based on one-way analysis of variance (ANOVA) statistics.<\/p>\n
PROC NPAR1WAY\u00a0Syntax<\/strong>–<\/p>\n
PROC \u00a0NPAR1WAY dataset <options>;\u00a0\r\n\u00a0Class <classification variable> ;\u00a0\r\nVar <dependent variable>;<\/pre>\n
PROC NPAR1WAY Example-<\/strong><\/p>\n
title'NPAR1WAY Procedure';\r\nproc npar1way data=SASHELP.CARS;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 class Origin;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 var MPG_Highway;\r\nrun;<\/pre>\n
When no analysis options are specified in the PROC NPAR1WAY statement, the ANOVA, WILCOXON, MEDIAN, VW, SAVAGE, and EDF options are invoked by default. Below is the output of these analyses.<\/p>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in SAS\/STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
 <\/p>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in SAS\/STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in SAS\/STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference – PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in SAS\/STAT-\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Exact Inference –\u00a0PROC NPAR1WAY<\/p><\/div>\n
\"SAS\/STAT<\/a>
Exact Inference in\u00a0SAS\/STAT –\u00a0PROC NPAR1WAY<\/p><\/div>\n
c. PROC FREQ<\/span><\/h4>\n
We have already discussed this procedure in detail. You can refer to the following link for the complete tutorial<\/a><\/strong>.<\/p>\n
d. PROC GENMOD<\/h4>\n
We have already discussed this procedure in detail. You can refer to the following link for the complete tutorial<\/a><\/strong>.<\/p>\n
e. PROC LOGISTIC<\/h4>\n
We have already discussed this procedure in detail. You can refer to the following link for the complete tutorial<\/a><\/strong>.
\nSo, this was all\u00a0about SAS\/STAT Exact Inference Tutorial. Hope you like our explanation<\/b>.<\/p>\n
Conclusion<\/h3>\n
Hence, in this tutorial,\u00a0we studied what is Exact Inference in SAS\/STAT. Moreover, we have discussed the procedures used for performing SAS\/STAT Exact Inference:\u00a0PROC LOGISTIC, PROC GENMOD, PROC FREQ, PROC NPAR1WAY, and PROC MULTTEST with their syntax and examples.\u00a0Furthermore, if you have any query, feel free to ask in the comment section.<\/p>\n","protected":false},"excerpt":{"rendered":"
In our previous articles, we looked at different types of analysis and the procedures used for performing them, today we will be looking at what is an exact inference in SAS\/STAT. Moreover, we will...<\/p>\n","protected":false},"author":6,"featured_media":13931,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[56],"tags":[4233,10014,10023,10050,10057,10058,10059,10064,10065,10066,12339],"class_list":["post-13900","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sas-stat","tag-exact-inference-in-stat","tag-proc-freq","tag-proc-genmod","tag-proc-logistic","tag-proc-multtest","tag-proc-multtest-example","tag-proc-multtest-syntax","tag-proc-npar1way","tag-proc-npar1way-example","tag-proc-npar1way-syntax","tag-sasstat-exact-inference"],"yoast_head":"\nLearn SAS\/STAT Exact Inference with 5 Procedures - DataFlair<\/title>\n<meta name=\"description\" content=\"What is SAS\/STAT Exact Inference-procedure for Exact inference in SAS\/STAT: PROC LOGISTIC,PROC GENMOD,PROC NPAR1WAY, PROC FREQ,PROC MULTTEST,syntax, example\" \/>\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\/stat-exact-inference\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Learn SAS\/STAT Exact Inference with 5 Procedures - 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