Crossover design is very popular for a study of new and developmental drugs. However this design tends to be misused regardless of whether it is suitable for underlying research questions. Method: Given that in clinical practice 2x2 cross over is the most commonly used design, the Hills-Arbitrage approach is suggested to analyze data. Furthermore, we propose fitting a linear mixed model and then conducting a likelihood ratio test to yield a single p-value on data with multiple time points

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... each stratum. Finding: Applying these methods to a real data, we evaluate effect of glucagon-like peptide 1 (GLP-1) on women with polycystic ovarian syndrome (PCOS). Despite absence of statistically significant results, this study as the first study to explore direct administration of GLP-1 to PCOS women is nevertheless clinically meaningful. Not only does it show a longer washout period is desired, but also it suggests GLP-1 may have the same positive effect on PCOS as MET does. Improvement: A larger parallel study is warranted, and clinicians and biostatisticians should collaborate more so that data can be analyzed appropriately and interpreted from both statistical and clinical points of view.