Research design and statistics in biomechanics and motor control

Biomechanics and motor control researchers measure how the body moves and interacts with its environment. The aim of this review paper is to consider some key issues in research methods in biomechanics and motor control. The review is organized into four sections: proposing, conducting, analysing and reporting research. In the first of these, we emphasize the importance of defining a worthy research question and of planning the study before its implementation to prevent later difficulties in the analysis and interpretation of data. In the second section, we cover selection of trial sizes and suggest that using three trials or more may be beneficial to provide more 'representative' and valid data. The third section on analysis of data concentrates on effect size statistics, qualitative and numerical trend analysis and cross-correlations. As sample sizes are often small, the use of effect size is recommended to support the results of statistical significance testing. In using cross-correlations, we recommend that scatterplots of one variable against the other, with the identified time lag included, be inspected to confirm that the linear relationship assumption underpinning this statistic is met and, if appropriate, that a linearity transformation be applied. Finally, we consider important information related to the issues above that should be included when reporting research. We recommend reporting checks or corrections for violations of underpinning assumptions, and the effect of these checks or corrections, to assist in advancing knowledge in biomechanics and motor control.