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Showing posts with the label linear models

Common Practice (misuse of) Moderation in Regression

An updated version of this post can be found here>> ... or how I stopped trusting standardized coefficients. Say you want to know how perceived importance of job security is related to feelings of job satisfaction. Let's also say that you suspect that this relationship might differ between Gen-X-ers and millennials with their MTV and their hip-hop. So you conduct a survey, asking 100 Gen-X-ers and 100 millennials to rank how important they think job security is when job searching and their current job satisfaction. You then plug your data into a 2-step hierarchical regression to test the moderating effect of Generation on the effect of Job Security in your favorite stats program (If you're a Gen-X-er, SPSS. If you're a millennial, or a reasonable human being, R). You find: Step 1: Term Estimate SE t Value p-value (Intercept) 4.400 0.39 11.20 <.001 Group [Millennial] 0.575 ...

What ARE the Assumptions of Linear Regression?

An updated version of this post can be found here>> When you assume   you make an ass out of you and me. We all know the assumptions of linear regression. Or at least we think we do. I mean, we learned them at some point, right? Well - at the very least we definitely know that there are assumptions!