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A crossover study, also referred to as a crossover trial, is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). While crossover studies can be observational studies, many important crossover studies are controlled experiments, which are discussed in this article. Crossover designs are common for experiments in many scientific disciplines, for example psychology, education, pharmaceutical science, and medicine. 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 randomized clinical trial is a repeated measures design, the same measures are collected multiple times for each subject. A crossover clinical trial is a repeated measures design in which each patient is randomly assigned to a sequence of treatments, including at least two treatments (of which one "treatment" may be a standard treatment or a placebo). Nearly all crossover designs have "balance", which means that all subjects should receive the same number of treatments and that all subjects participate for the same number of periods. In most crossover trials, in fact, each subject receives all treatments. Statisticians suggest that designs have four periods, a design which allows studies to be truncated to three periods while still enjoying greater efficiency than the two-period design.〔Vonesh & Chinchilli (1997)〕〔Jones & Kenward (2003)〕 However, the two-period design is often taught in non-statistical textbooks, partly because of its simplicity. ==Clinical trial protocol specifies the statistical analysis== The data are analyzed using the statistical method that was specified in the clinical trial protocol, which needs to have been approved by the appropriate institutional review boards and regulatory agencies before the trial could begin. Again, the clinical trial protocols specify the method of statistical analysis. Most clinical trials are analyzed using repeated-measurements anova (analysis of variance) or mixed models that include random effects. In most longitudinal studies of human subjects, patients may withdraw from the trial or become "lost to follow-up" (due e.g. to moving abroad or to dying from another disease). There are statistical methods for dealing with such missing-data and "censoring" problems. An important method analyzes the data according to the principle of the intention to treat. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「crossover study」の詳細全文を読む スポンサード リンク
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