Weights in large scale assessments

In class, I’ve talked about using weights in large scale assessments. I’ve provided a bit of intuition about using weights and why they are important. Here’s some R syntax to go along with the example I discussed. Imagine there are two schools in one school district. You are asked what is the average score on some measure of students in the district. There are only two schools (school A and B) and their size varies (School A = 100, School B = 1,000).

Why Weight?

I’ve spoken a bit about how using weights is important when analyzing national/statewide datasets. The weights are used so the sample generalizes to a particular population (note: we are interested in making inferences about the population, not the sample). This is important because at times, in national datasets, certain subpopulations (e.g., Hispanic or Asian students) are oversampled to ensure that the sample size is large enough for subgroup analysis. Without using weights, certain groups may be overrepresented (or underrepresented).