Weight Concentration Explorer
Explore how unequal nonnegative weights reduce the weight-only effective sample size.
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Explore weight concentration with fictional examples. Equal weights give the entered sample size; concentration reduces the weight-only effective size.
Calculation results
Entered weights: 4; positive weights: 4
Weight-only effective n: 3
Effective / entered n: 75%; weight-only n / effective n: 1.33333
Assumptions and limits
Kish weight-only effective n = (sum of weights)² / sum of squared weights. This concentration diagnostic ignores clustering, stratification, finite-population corrections and associations between weights and outcomes. It is not the effective sample size for every survey estimator and cannot supply a valid confidence interval. All weights must be nonnegative and at least one positive; zero-weight entries remain in the entered n. Multiplying all weights by the same positive constant leaves the result unchanged. Use up to 200 synthetic weights, not patient records. Weights are not estimated or calibrated here.
svyweight: weight-only effective sample size · Read the practical guide · Download blank worksheet (TXT)