## The Annals of Statistics

### Universally optimal crossover designs under subject dropout

Wei Zheng

#### Abstract

Subject dropout is very common in practical applications of crossover designs. However, there is very limited design literature taking this into account. Optimality results have not yet been well established due to the complexity of the problem. This paper establishes feasible, as well as necessary and sufficient conditions for a crossover design to be universally optimal in approximate design theory in the presence of subject dropout. These conditions are essentially linear equations with respect to proportions of all possible treatment sequences being applied to subjects and hence they can be easily solved. A general algorithm is proposed to derive exact designs which are shown to be efficient and robust.

#### Article information

Source
Ann. Statist., Volume 41, Number 1 (2013), 63-90.

Dates
First available in Project Euclid: 5 March 2013

https://projecteuclid.org/euclid.aos/1362493040

Digital Object Identifier
doi:10.1214/12-AOS1074

Mathematical Reviews number (MathSciNet)
MR3059410

Zentralblatt MATH identifier
1347.62168

Subjects
Primary: 62K05: Optimal designs
Secondary: 62J05: Linear regression

#### Citation

Zheng, Wei. Universally optimal crossover designs under subject dropout. Ann. Statist. 41 (2013), no. 1, 63--90. doi:10.1214/12-AOS1074. https://projecteuclid.org/euclid.aos/1362493040

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