2026-06-30T03:14:17Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1045172025-03-18T12:22:17Zcom_20.500.14352_14col_20.500.14352_15

00925njm 22002777a 4500 dc Alonso Revenga, Juana María author Martín Apaolaza, Nirian author Pardo Llorente, Leandro author 2020-08-15 Traditionally, the Dirichlet-multinomial distribution has been recognized as a key model for contingency tables generated by cluster sampling schemes. There are, however, other possible distributions appropriate for these contingency tables. This paper introduces new statistics capable of testing log-linear modeling hypotheses with distributional unspecification, when the individuals of the clusters are possibly homogeneously correlated. An estimator for the intracluster correlation coefficient, valid for different cluster sizes, plays a crucial role in the construction of the goodness-of-fit test-statistics. Alonso-Revenga, Martín y Pardo (2020) «New statistics to test log-linear modeling hypothesis with no distributional specifications and clusters with homogeneous correlation», Journal of Computational and Applied Mathematics, 374. 0377-0427 10.1016/J.CAM.2020.112757 https://hdl.handle.net/20.500.14352/104517 1879-1778 https://doi.org/10.1016/j.cam.2020.112757 https://www.sciencedirect.com/science/article/pii/S0377042720300480?via%3Dihub New statistics to test log-linear modeling hypothesis with no distributional specifications and clusters with homogeneous correlation