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用于医学、农业和其他生物科学领域。由于交叉设计的特性,每个实验单位具有纵向观测数据,响应变量存在拖尾效应。没有一个明确建模交叉设计数据的{R}软件包。本文介绍的{CrossCarry}软件包可测试任何交叉设计,只要观察到的响应变量属于指数家族,无论是否有清除期。它还允许建模每个时期内的重复测量,并扩展了广义估计方程中使用的相关结构。构建了一系列相关结构的家族,它考虑了设计的特点,即周期之间和周期内的相关性。它还包括用于建模治疗效应的参数部分和用于建模时间效应和携带效应的非参数部分。非参数部分是通过插入到广义估计方程中的样条来估计的。