A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures
In this paper, 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 th...
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Springer Nature
2024
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| Acceso en línea: | https://link.springer.com/article/10.1007/s00362-022-01391-z http://hdl.handle.net/20.500.12324/39372 https://doi.org/10.1007/s00362-022-01391-z |
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RepoAGROSAVIA39372 |
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dspace |
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Corporación Colombiana de Investigación Agropecuaria |
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Repositorio AGROSAVIA |
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Inglés |
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Carry-over effect Cross-over design Generalized estimating equations Kronecker correlation Overdispersion count data Ecuaciones Dispersión Métodos estadísticos Ganadería y especies menores http://aims.fao.org/aos/agrovoc/c_8bc08746 http://aims.fao.org/aos/agrovoc/c_2333 http://aims.fao.org/aos/agrovoc/c_7377 |
| spellingShingle |
Carry-over effect Cross-over design Generalized estimating equations Kronecker correlation Overdispersion count data Ecuaciones Dispersión Métodos estadísticos Ganadería y especies menores http://aims.fao.org/aos/agrovoc/c_8bc08746 http://aims.fao.org/aos/agrovoc/c_2333 http://aims.fao.org/aos/agrovoc/c_7377 Martinez Niño, Carlos Alberto Cruz, N. A. Melo, O. O. A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures |
| description |
In this paper, 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. |
| format |
article |
| author |
Martinez Niño, Carlos Alberto Cruz, N. A. Melo, O. O. |
| author_facet |
Martinez Niño, Carlos Alberto Cruz, N. A. Melo, O. O. |
| author_sort |
Martinez Niño, Carlos Alberto |
| title |
A correlation structure for the analysis of Gaussian and
non-Gaussian responses in crossover experimental designs with repeated measures |
| title_short |
A correlation structure for the analysis of Gaussian and
non-Gaussian responses in crossover experimental designs with repeated measures |
| title_full |
A correlation structure for the analysis of Gaussian and
non-Gaussian responses in crossover experimental designs with repeated measures |
| title_fullStr |
A correlation structure for the analysis of Gaussian and
non-Gaussian responses in crossover experimental designs with repeated measures |
| title_full_unstemmed |
A correlation structure for the analysis of Gaussian and
non-Gaussian responses in crossover experimental designs with repeated measures |
| title_sort |
correlation structure for the analysis of gaussian and
non-gaussian responses in crossover experimental designs with repeated measures |
| publisher |
Springer Nature |
| publishDate |
2024 |
| url |
https://link.springer.com/article/10.1007/s00362-022-01391-z http://hdl.handle.net/20.500.12324/39372 https://doi.org/10.1007/s00362-022-01391-z |
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AT martinezninocarlosalberto acorrelationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures AT cruzna acorrelationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures AT melooo acorrelationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures AT martinezninocarlosalberto correlationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures AT cruzna correlationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures AT melooo correlationstructurefortheanalysisofgaussianandnongaussianresponsesincrossoverexperimentaldesignswithrepeatedmeasures |
| _version_ |
1808107755876122624 |
| spelling |
RepoAGROSAVIA393722024-05-21T03:02:21Z A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures Martinez Niño, Carlos Alberto Cruz, N. A. Melo, O. O. Carry-over effect Cross-over design Generalized estimating equations Kronecker correlation Overdispersion count data Ecuaciones Dispersión Métodos estadísticos Ganadería y especies menores http://aims.fao.org/aos/agrovoc/c_8bc08746 http://aims.fao.org/aos/agrovoc/c_2333 http://aims.fao.org/aos/agrovoc/c_7377 In this paper, 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. 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