The application of multilevel, multivariate modelling to orthodontic research data

Objective To demonstrate the use of multilevel multivariate modelling in th e evaluation of multiple outcome dental data. Basic research design Multipl e outcome dental research data are used to illustrate the problems of analy sing such complex information structures - i.e. several outcomes clustered within subjects. Appropriate and statistically efficient methods of data an alysis are proposed and illustrated step-by-step. The data structure is ana lysed using multilevel multivariate regression techniques and this process is discussed in comparison to conventional single-level multiple regression . Participants Questionnaire data were obtained from an orthognathic study of 84 subjects seeking treatment and 106 'non-treatment' controls (full det ails of which are reported elsewhere). Results Multivariate multiple regres sion analysis demonstrated a number of advantages over separate single-leve l multiple regression approaches, including a gain in statistical efficienc y and greater insight into: a) the role of (significant) explanatory variab les and b) outcome variable interactions. Multilevel multivariate analysis reduced the risk of both Type I and Type II statistical errors. Conclusions The study demonstrates the benefit of multilevel multivariate modelling ov er conventional single-level techniques for statistical analysis of multipl e outcome data. As a result of ongoing technical developments in the power, speed and memory of modern PCs, multilevel multivariate regression can now be undertaken with relative ease. Consequently, researchers are better equ ipped to analyse such complex data structures, particularly within dentistr y where multivariate data are common.