From the course: SAS Essential Training: 2 Regression Analysis for Healthcare Research

Introduction to the course - SAS Tutorial

From the course: SAS Essential Training: 2 Regression Analysis for Healthcare Research

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Introduction to the course

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- Hi, I'm Monica Wahi. Welcome to my course, SAS Essential Training Regression Analysis for Healthcare Research. So, we are going full speed ahead from the first course in the series to this course. In the previous course, you created your hypotheses, designed and created an analytic dataset, and conducted a descriptive analysis. Now, in this course, we are going to keep using that analytic dataset you created in the previous course to conduct a linear regression analysis followed by a logistic regression analysis. I will teach you how to make the regressions and how to present and interpret both models. And as always, there are some bonus tips at the end. In the last course, we used a lot of data steps to make our analytic file and we also used a lot of PROC freaks to complete our descriptive analysis. SAS performed for us, but it is in this course where SAS's star will really shine SAS is a regression star. If they had a Hollywood for statistical software, SAS would be in it. Why is SAS so great for regression? A few reasons. First, as you will see in this course, the output for both linear and logistic regression is both thorough and clear. The default output provides a range of useful calculations and it's easy to add options to request additional output. And it's easy to run models over and over again, meaning it's easy to run iterative models. I'm careful when I say that because once a reviewer though I said interactive. I really mean iterative, like over and over again. SAS is great for that.

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