Blocking is an experimental design method used to reduce confounding.
Similar to two group matching/pairing
Blocking is similar to the pairing/matching method (e.g. paired t test) where pairs of observations are matched up to prevent confounding factors (e.g. age, sex) from hiding a real difference between two groups (e.g. treatment and control).
General heterogeneity
In general terms, blocking compensates for situations where known factors (e.g. age, sex) other than treatment group status are likely to affect what is being observed in the study. In other words, the analytical method accounts for the fact that the experimental units (e.g. people/subjects studied) are not homogeneous with regard to factors (other than treatment group status) likely to affect outcome.
Design
The randomized block design takes account of known factors that affect outcome/response but are not of primary interest. The two steps in randomized block design are:
1. 1. 1. Collect together homogeneous experimental units (e.g. people) into a block.
2. 2. 2. Assign treatments at random to the experimental units within a block.
Treatment (i, 1 to k) | |||||
1 | 2 | ... | k | ||
Block (j, 1 to b:) | 1 | Yij | |||
2 | |||||
3 | |||||
. | |||||
b |
Examples
StatsDirect calculates ANOVA for randomized block designs in two way and repeated observation two way situations.
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