Statistical power and measurement requirements in studies comparing observed postures between groups
(English)Manuscript (preprint) (Other academic)
Ergonomics studies comparing working postures and movements between independent groups are often based on observations. The present paper derives and exemplifies procedures for estimating the statistical power of such studies, addressing the effect of different strategies for allocating observations within and between observers. In the simple case of one observer rating the postures of all subjects in the study one or multiple times, a simple t-test is appropriate for testing the group difference, while statistical models acknowledging rating differences between observers are needed when multiple observers are involved. In the one-observer case, analytical power calculations are feasible, while a parametric bootstrapping approach is suggested and practiced in the paper for the multiple-observers case. Using empirical data from a previous study of postures among hairdressers observed from video recordings (percentages of time with the right upper arm elevated less than 15° and more than 90°), the study demonstrates that a considerable gain in power can be obtained by having one observer doing multiple repeated observations as compared to rating postures only once. Distributing a certain number of video recordings between multiple observers resulted in a loss of power when a simple t-test was used to test the group difference, but the comparison could be accomplished without loss of power if all observers were involved in rating both of the compared groups and the statistical model used to analyze data acknowledged variability in rating between observers. When different observers assessed the two compared groups, power decreased considerably. Thus, the study gives guidance for efficient design of posture observation studies comparing groups, as well as for appropriate statistical procedures for analyzing the data.
sample size, observation, ergonomic intervention, method variance
Environmental Health and Occupational Health
Research subject Occupational and Environmental Medicine
IdentifiersURN: urn:nbn:se:umu:diva-59117OAI: oai:DiVA.org:umu-59117DiVA: diva2:551062