Log-Linear Models for Doubly Sampled Categorical Data Fitted by the EM Algorithm
- 1 September 1985
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 80 (391) , 663
- https://doi.org/10.2307/2288482
Abstract
Double-sampling experiments can be expressed as incomplete multiway contingency tables and analyzed by using techniques appropriate for fitting log-linear models. The framework described can be applied to experiments with any number of factors and measurement devices. Maximum likelihood estimation via the EM algorithm leads to straightforward expressions for covariances of estimates of the parameters and functions of the parameters.Keywords
This publication has 0 references indexed in Scilit: