# Implementation and Interpretation of Fixed versus Random Effects

I am reading an article which uses a simple least squares model to measure the effect of a prevention campaign on methamphetamine use (http://www.ncbi.nlm.nih.gov/pubmed/20638737). In its second equation, it uses state fixed effects in an OLS model to capture the effect of living in each state.

Meth ~ constant + Betas*Attributes + State1Beta*State1 + ... +
StateZBeta * StateZ


I have two questions:

1. Is the only difference between using random and fixed effects in this instance the distribution in which the values fall (ie, a random effect would have a mean of 0 and a normal distribution)? And,
2. How does this jive with the interpretation that random effects are intercept shifts, and fixed effects are slope shifts?
• It is the first time I see the interpretation you mention in the second question. Could you give a reference? – mpiktas Oct 2 '12 at 2:42