Prerequisites: 

Familiarity with R; completed a basic statistics course in regression modeling; taken SURV 623 or SURV 630

Description: 

Surveys reflect the opinions or facts researchers are after only partly – the other part will be measurement error, which can seriously bias analyses of interest. To remove such biases it is essential to estimate the extent of measurement error in survey variables, which is precisely the goal of statistical measurement error modeling. In this course, we will discuss how measurement error can be defined, how its presence can be detected using specialized data collection designs and models, and how to perform error-corrected statistical analyses of substantive interest.