In the case of frequency data, traditional discussions such as Rao (1973, pages 355-363, 391-412) consider asymptotic properties of maximum likelihood estimates and chi-square statistics under the assumption that all expected cell frequencies become large. If log-linear models are applied, these asymptotic properties may remain applicable if the sample size is large and the number of cells in the table is large, even if individual expected cell frequencies are small. Conditions are provided for asymptotic normality of linear functionals of maximum-likelihood estimates of log-mean vectors and for asymptotic chi-square distributions of Pearson and likelihood ratio chi-square statistics.
Publié le : 1977-11-14
Classification:
Contingency tables,
log-linear models,
maximum likelihood,
chi-square tests,
asymptotic properties,
62E20,
62F05,
62F10,
62F25
@article{1176344001,
author = {Haberman, Shelby J.},
title = {Log-Linear Models and Frequency Tables with Small Expected Cell Counts},
journal = {Ann. Statist.},
volume = {5},
number = {1},
year = {1977},
pages = { 1148-1169},
language = {en},
url = {http://dml.mathdoc.fr/item/1176344001}
}
Haberman, Shelby J. Log-Linear Models and Frequency Tables with Small Expected Cell Counts. Ann. Statist., Tome 5 (1977) no. 1, pp. 1148-1169. http://gdmltest.u-ga.fr/item/1176344001/