Clustered data

Clustered data are grouped observations for which measurements in the same group may be dependent, as with repeated measurements on one subject.

Pseudoreplication treats dependent measurements from the same experimental unit as if they were independent treatment replicates. It exaggerates the effective sample size and commonly makes standard errors too small. In the pot example of replication in experimental design, counting twelve leaves per group as twelve independent treatment replicates ignores the four containing pots. The variance of nested measurements quantifies the resulting understatement of uncertainty. Nested measurements themselves are useful; pseudoreplication is the error of using them as independent replicates for the wrong level of inference.^[ref]