arXiv subjects

C. A. Martinez

Publications and source records attributed to C. A. Martinez.

3 recordsLinked to original sources

arXiv2025

CrossCarry: An R package for the analysis of data from a crossover design with GEE

Crossover designs are widely applied in medicine, agriculture, and other biological sciences, yet their analysis remains challenging due to longitudinal observations within each unit and the presence of carry-over effects. Despite their prevalence, there is no comprehensive R package dedicated to the statistical modeling of crossover data. The CrossCarry package addresses this gap by providing a flexible and open-source framework for analyzing any crossover design with response variables from the exponential family, with or without washout periods. It extends the generalized estimating equations (GEE) methodology by incorporating correlation structures specifically tailored to crossover data, capturing both within- and between-period dependencies. Moreover, CrossCarry integrates a parametric component for treatment effects and a nonparametric spline-based component for time and carry-over effects. This combination allows users to model complex correlation patterns and temporal structures with minimal coding effort. By offering a domain-independent implementation of advanced statistical methodology, CrossCarry facilitates reproducible research and promotes the reuse of robust analytical tools across disciplines. Its potential applications span medical trials, agricultural field experiments, and other areas where crossover designs are essential, thus contributing to broader scientific discovery and cross-domain methodological standardization.

stat.CO↗

arXiv2022

Semi-parametric generalized estimating equations for repeated measurements in cross-over designs

A model for cross-over designs with repeated measures within each period was developed. It is obtained using an extension of generalized estimating equations that includes a parametric component to model treatment effects and a non-parametric component to model time and carry-over effects; the estimation approach for the non-parametric component is based on splines. A simulation study was carried out to explore the model properties. Thus, when there is a carry-over effect or a functional temporal effect, the proposed model presents better results than the standard models. Among the theoretical properties, the solution is found to be analogous to weighted least squares. Therefore, model diagnostics can be made adapting the results from a multiple regression. The proposed methodology was implemented in the data sets of the crossover experiments that motivated the approach of this work: systolic blood pressure and insulin in rabbits.

stat.ME↗

arXiv2022

A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures

In this study, we propose a family of correlation structures for crossover designs with repeated measures for both, Gaussian and non-Gaussian responses using generalized estimating equations (GEE). The structure considers two matrices: one that models between-period correlation and another one that models within-period correlation. The overall correlation matrix, which is used to build the GEE, corresponds to the Kronecker between these matrices. A procedure to estimate the parameters of the correlation matrix is proposed, its statistical properties are studied and a comparison with standard models using a single correlation matrix is carried out. A simulation study showed a superior performance of the proposed structure in terms of the quasi-likelihood criterion, efficiency, and the capacity to explain complex correlation phenomena/patterns in longitudinal data from crossover designs

stat.ME↗