%0 Journal Article
%T On the Estimation of Parameters and Best Model Fits of Log Linear Model for Contingency Table
%A Cecilia N. Okoli
%A Sidney I. Onyeagu
%A George A. Osuji
%J Open Access Library Journal
%V 2
%N 1
%P 1-11
%@ 2333-9721
%D 2015
%I Open Access Library
%R 10.4236/oalib.1101189
%X In
this paper, we proposed the
generalized method and
algorithms developed for estimation of parameters and best model fits of log
linear model for <i>n</i>-dimensional
contingency table. For purpose of this work, the method was used to
provide parameter estimates of log-linear
model for three-dimensional contingency table. In estimating parameter
estimates and best model fit, computer programs in R were developed for the
implementation of the algorithms. The iterative proportional
fitting procedure was used to find the parameter estimates and goodness of fits
of the log linear model. Akaike information criteria (AIC) and Bayesian
information criteria (BIC) were used to check the adequacy of the model of the
best fit. Secondary data were used for illustration and the result obtained
showed that the best model fit for three-dimensional
contingency table had a generating
class: [CA, AB]. This showed that the best model fit had sufficient evidence to fit the
data without loss of information. This model also revealed that breed was independent of chick loss given
age. The best model in harmony with the hierarchy
principle is&nbsp;<b>Log<i>m</i><sub><em>ijk</em></sub><sub>£½</sub><i>¦Ì</i></b><sub>£«</sub><b><i>¦Ì<sub>C</sub></i></b><sub>(<i>i</i>)£«</sub> <b><i>¦Ì<sub>A</sub></i></b><sub>(<i>j</i>)£«</sub> <b><i>¦Ì<sub>B</sub></i></b><sub>(<i>k</i>)£«</sub> <b><i>¦Ì<sub>CA</sub></i></b><sub>(<i>ij</i>)£«</sub> <b><i>¦Ì<sub>AB</sub></i></b><sub>(<i>jk</i>)</sub>.
%K Hierarchical Log Linear Models
%K Categorical Data
%K Contingency Table
%K Likelihood Ratio Test  Statistic
%K AIC
%K BIC
%K Interaction
%U http://www.oalib.com/paper/3131192