Experimental crossover designs are widely used in medicine, agriculture, and other areas of the biological sciences. Due to the characteristics of the crossover design, each experimental unit has longitudinal observations and the presence of drag effects on the response variable. There is no package in {R} that clearly models data from crossover designs. The {CrossCarry} package presented in this paper allows testing any crossover design as long as the observed response variable belongs to the exponential family, regardless of whether or not there is a washout period. It also allows modeling repeated measurements within each period and extends the correlation structures used in the generalized estimating equations. The family of correlation structures is built that takes into account the particularities of the design, that is, the correlation between and within the periods. It also includes a parametric component for modeling treatment effects and a non-parametric component for modeling time effects and carry-over effects. The non-parametric component is estimated from splines inserted into the generalized estimation equations.

翻译：实验性交叉设计广泛应用于医学、农业及其他生物科学领域。由于交叉设计的特性，每个实验单元具有纵向观测数据，且响应变量存在延滞效应。目前{R}语言中尚无明确建模交叉设计数据的软件包。本文提出的{CrossCarry}包支持测试任意交叉设计，前提是观测到的响应变量属于指数族分布，无论是否存在清洗期。该包还允许对每个周期内的重复测量进行建模，并扩展了广义估计方程中使用的相关结构。其构建的相关结构族充分考虑了设计的特殊性，即周期间及周期内的相关性。此外，该包包含用于建模处理效应的参数化组件，以及用于建模时间效应和携带效应的非参数化组件。非参数化组件通过插入到广义估计方程中的样条进行估计。