3.94 FAQ-332 What is balanced design in repeated measure analysis?

Last Update: 12/26/2018

Repeated measures analysis, in which the same measure is collected several times in a single group of subjects, requires input data to follow balanced design in analysis.

Balanced design means that each level of the factors has the same sample size. Take the following dataset as an example.

Subject Factor1 Factor2 Data
1 aa cc 8.5
1 aa dd 11
2 aa cc 8.5
2 aa dd 10.5
3 aa cc 9.5
3 aa dd 12
1 bb cc 9
1 bb dd 12.5
2 bb cc 9
2 bb dd 11.5
3 bb cc 10
3 bb dd 13

Factor1 and Factor2 both have 2 levels, and thus the combination of levels is 4: aa*cc, aa*dd, bb*cc, bb*dd.

At the same time, you can see all these 4 combinations have 1 (the same) observation for each subject.

In this case, the dataset follow balanced design, meets the input data requirement of repeated measure anova

Following feature in Origin require input data follow balanced design:


Before Origin 2015, one-way and two-way repeated measure ANOVA also require data to follow balanced design.

From Origin 2015, missing values in data are excluded in one/two way repeated measure ANOVA list-wise to force data to be balanced, and mixed designed ANOVA supports unbalanced design data

Keywords:ANOVA, friedman, repeated measure