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E B Moser

Publications and source records attributed to E B Moser.

2 recordsLinked to original sources

Exploring contingency tables with correspondence analysis.

An algorithm for correspondence analysis is described and implemented in SAS/IML (SAS Institute, 1985a). The technique is shown, through the analysis of several biological examples, to supplement the log-linear models approach to the analysis of contingency tables, both in the model identification and model interpretation stages of analysis. A simple two-way contingency table of tumor data is analyzed using correspondence analysis. This example emphasises the relationships between the parameters of the log-linear model for the table and the graphical correspondence analysis results. The technique is also applied to a three-way table of survey data concerning ulcer patients to demonstrate applications of simple correspondence analysis to higher dimensional tables with fixed margins. Finally, the diets and foraging behaviors of birds of the Hubbard Brook Forest are each analyzed and then a simultaneous display of the two separate but related tables is constructed to highlight relationships between the tables.

Algorithms

Biological applications of the SAS system: an overview.

The SAS system provides biologists with a flexible, easy to use software package for data analysis. Through a combination of data management tools, a wide variety of pre-programmed procedures for sorting, graphing, and statistical analysis and a sophisticated programming language, SAS software can perform all analytical needs for most problems. The recent availability of SAS software on mainframes other than IBM, and more recently on the microcomputer, means that most scientists can have access to the software. In this review we discuss the structure of the SAS language and demonstrate its power in the analysis of biological problems. Although to a lesser extent now than originally, the SAS system is statistically oriented and a working knowledge of statistics is recommended before using its statistical capabilities. However, all biologists will find its data management and summarization capabilities very useful.

Biology