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Log-linear models for contingency tables
| Content Provider | Scilit |
|---|---|
| Author | Everitt, Brian S. |
| Copyright Year | 1992 |
| Description | The previous chapters have dealt almost exclusively with hypothesis testing techniques for the analysis of contingency tables. In this chapter an alternative approach w i l l be considered, namely that of fitting models and estimating the parameters i n the models. T h e term model refers to some 'theory' or conceptual framework about the observations, and the parameters in the model represent the 'effects' that part icular variables or combinat ions of variables have in determining the values taken by the observations. Such an approach is common i n many branches of statistics such as regression analysis and the analysis of variance. M o s t c o m m o n are linear models which postulate that the expected values of the observations are given by a linear combina t ion of a number of parameters. Techniques such as maximum l ike l ihood and least squares may be used to estimate the parameters, and estimated parameter values may then be used in identifying which variables are of greatest importance i n 'predicting' the observed values. Book Name: The Analysis of Contingency Tables |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2006-0-06267-1&isbn=9780429170867&doi=10.1201/b15072-9&format=pdf |
| DOI | 10.1201/b15072-9 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 1992-02-01 |
| Access Restriction | Open |
| Subject Keyword | Book Name: The Analysis of Contingency Tables Mathematical Psychology Values Linear Models Techniques Contingency Tables Estimate the Parameters |
| Content Type | Text |
| Resource Type | Chapter |
