Benefits of Multilevel Modelling for Age-Related Research

The purpose of this chapter is two-fold: first, to make a case for alternatives to conventional quantitative research methodologies in age-related research; and second, to outline the main benefits of multilevel modelling (MLM) for our study as we see them.

In recent years, the general linear model (a family of statistical models that assumes a normal distribution, among other features, e.g. t-tests, analysis of variance [ANOVA] or multiple regression models, see Cohen [1968] and Plonsky [2013] – not to be confused with generalised linear models!) has been critically evaluated, and numerous limitations of empirical efforts in second language acquisition (SLA) have been documented (e.g. Norris & Ortega, 2000; Oswald & Plonsky, 2010; Plonsky, 2011; Plonsky & Gass, 2011; Plonsky & Oswald, 2015). In her meta-analysis of 524 empirical articles, Lazaraton (2005: 214) pointed out three main problems with the paradigm shift from qualitative to quantitative approaches that have been taking place in applied linguistics in general over the last few decades: (1) the general linear model is used (she fears) ‘in violation of at least some of the assumptions of the procedure’ (see also de Bot, 2011: 125), such as the inclusion of correlated data in linear models; (2) a great deal of the research becomes obscure for all but the most statistically literate; and (3) using high-powered parametric procedures may tempt one to overgeneralise results to other contexts or to other language users, when, in fact, many research designs do not use random selection from a population or random assignment to groups, but rather employ selected intact groups of a very limited demographic profile. Lazaraton (2005: 209) concludes that the whole discipline of applied linguistics seems to be struggling with a redefinition of its research goals, methods and paradigms, as can be seen in terms of the growing reversion to qualitative methods, increasingly pointed questions about the importance of research in this field and the continuing exploration of alternatives.