How Multiple Regression Models Can Be Written to Better Reflect the Complexity of First and Second LanguageAcquisition Research: An Attempt to Limit Type VI Error

Abstract

The purpose of this paper is to show how multiple regression models can be written to investigate and to better reflect the complexity of four major research themes in first and second language acquisition research in order to limit Type VI error. The four major themes were selected because of their importance to their respective fields, their multidimensional nature, and the interdisciplinary research influence on them. Each theoretical perspective examined in this paper brings with it its own research methodology, and; thus, the need for a paper that demonstrates how multiple regression models can be written to investigate four of the major foci of first and second language acquisition research to better reflect the complexity of language acquisition research.