Crossover study
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In
Randomized, controlled crossover experiments are especially important in health care. In a randomized clinical trial, the subjects are randomly assigned to different arms of the study which receive different treatments. When the trial has a repeated measures design, the same measures are collected multiple times for each subject. A crossover trial has a repeated measures design in which each patient is assigned to a sequence of two or more treatments, of which one may be a standard treatment or a placebo.
Nearly all crossover are designed to have "balance", whereby all subjects receive the same number of treatments and participate for the same number of periods. In most crossover trials each subject receives all treatments, in a random order.
Statisticians suggest that designs should have four periods, which is more efficient than the two-period design, even if the study must be truncated to three periods.[1][2] However, the two-period design is often taught in non-statistical textbooks, partly because of its simplicity.
Analysis
The data is analyzed using the
In most longitudinal studies of human subjects,
Advantages
A crossover study has two advantages over both a
Second,
Optimal crossover designs are discussed in the graduate textbook by Jones and Kenward and in the review article by Stufken. Crossover designs are discussed along with more general repeated-measurements designs in the graduate textbook by Vonesh and Chinchilli.
Limitations and disadvantages
These studies are often done to improve the symptoms of patients with
Crossover studies often have two problems:
First is the issue of "order" effects, because it is possible that the order in which treatments are administered may affect the outcome. An example might be a drug with many adverse effects given first, making patients taking a second, less harmful medicine, more sensitive to any adverse effect.
Second is the issue of "carry-over" between treatments, which confounds the estimates of the treatment effects. In practice, "carry-over" effects can be avoided with a sufficiently long "wash-out" period between treatments. However, planning for sufficiently long wash-out periods requires expert knowledge of the dynamics of the treatment, which is often unknown.
See also
- Design of experiments
- Glossary of experimental design
- Randomized controlled trial
- Survival analysis
- N of 1 trial
- Single-subject design
Notes
References
- M. Bose and A. Dey (2009). Optimal Crossover Designs. World Scientific. ISBN 978-9812818423
- D. E. Johnson (2010). Crossover experiments. WIREs Comp Stat, 2: 620-625. [1]
- Jones, Byron; Kenward, Michael G. (2014). Design and Analysis of Cross-Over Trials (Third ed.). London: Chapman and Hall. ISBN 978-0412606403.
- K.-J. Lui, (2016). Crossover Designs: Testing, Estimation, and Sample Size. Wiley.
- Najafi Mehdi, (2004). Statistical Questions in Evidence Based Medicine. New York: Oxford University Press. ISBN 0-19-262992-1
- D. Raghavarao and L. Padgett (2014). Repeated Measurements and Cross-Over Designs. Wiley. ISBN 978-1-118-70925-2
- D. A. Ratkowsky, M. A. Evans, and J. R. Alldredge (1992). Cross-Over Experiments: Design, Analysis, and Application. Marcel Dekker. ISBN 978-0824788926
- Senn, S. (2002). Cross-Over Trials in Clinical Research, Second edition. Wiley. ISBN 978-0-471-49653-3
- Stufken, J. (1996). "Optimal Crossover Designs". In Ghosh, S.; ISBN 978-0-444-82061-7.
- Vonesh, Edward F.; Chinchilli, Vernon G. (1997). "Crossover Experiments". Linear and Nonlinear Models for the Analysis of Repeated Measurements. London: Chapman and Hall. pp. 111–202. ISBN 978-0824782481.