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Statistical power and measurement requirements in studies comparing observed postures between groups
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
Högskolan i Gävle, Centrum för belastningsskadeforskning.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

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.

Keyword [en]
sample size, observation, ergonomic intervention, method variance
National Category
Environmental Health and Occupational Health
Research subject
Occupational and Environmental Medicine
Identifiers
URN: urn:nbn:se:umu:diva-59117OAI: oai:DiVA.org:umu-59117DiVA: diva2:551062
Available from: 2012-09-10 Created: 2012-09-10 Last updated: 2012-09-11Bibliographically approved
In thesis
1. Efficient strategies for collecting posture data using observation and direct measurement
Open this publication in new window or tab >>Efficient strategies for collecting posture data using observation and direct measurement
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Effektiva strategier för insamling av data om arbetsställningar geom observation och direkta mätning
Abstract [en]

Relationships between occupational physical exposures and risks of contracting musculoskeletal disorders are still not well understood; exposure-response relationships are scarce in the musculoskeletal epidemiology literature, and many epidemiological studies, including intervention studies, fail to reach conclusive results. Insufficient exposure assessment has been pointed out as a possible explanation for this deficiency. One important aspect of assessing exposure is the selected measurement strategy; this includes issues related to the necessary number of data required to give sufficient information, and to allocation of measurement efforts, both over time and between subjects in order to achieve precise and accurate exposure estimates. These issues have been discussed mainly in the occupational hygiene literature considering chemical exposures, while the corresponding literature on biomechanical exposure is sparse. The overall aim of the present thesis was to increase knowledge on the relationship between data collection design and the resulting precision and accuracy of biomechanical exposure assessments, represented in this thesis by upper arm postures during work, data which have been shown to be relevant to disorder risk.

Four papers are included in the thesis. In papers I and II, non-parametric bootstrapping was used to investigate the statistical efficiency of different strategies for distributing upper arm elevation measurements between and within working days into different numbers of measurement periods of differing durations. Paper I compared the different measurement strategies with respect to the eventual precision of estimated mean exposure level. The results showed that it was more efficient to use a higher number of shorter measurement periods spread across a working day than to use a smaller number for longer uninterrupted measurement periods, in particular if the total sample covered only a small part of the working day. Paper II evaluated sampling strategies for the purpose of determining posture variance components with respect to the accuracy and precision of the eventual variance component estimators. The paper showed that variance component estimators may be both biased and imprecise when based on sampling from small parts of working days, and that errors were larger with continuous sampling periods. The results suggest that larger posture samples than are conventionally used in ergonomics research and practice may be needed to achieve trustworthy estimates of variance components.

Papers III and IV focused on method development. Paper III examined procedures for estimating statistical power when testing for a group difference in postures assessed by observation. Power determination was based either on a traditional analytical power analysis or on parametric bootstrapping, both of which accounted for methodological variance introduced by the observers to the exposure data. The study showed that repeated observations of the same video recordings may be an efficient way of increasing the power in an observation-based study, and that observations can be distributed between several observers without loss in power, provided that all observers contribute data to both of the compared groups, and that the statistical analysis model acknowledges observer variability. Paper IV discussed calibration of an inferior exposure assessment method against a superior “golden standard” method, with a particular emphasis on calibration of observed posture data against postures determined by inclinometry. The paper developed equations for bias correction of results obtained using the inferior instrument through calibration, as well as for determining the additional uncertainty of the eventual exposure value introduced through calibration.

In conclusion, the results of the present thesis emphasize the importance of carefully selecting a measurement strategy on the basis of statistically well informed decisions. It is common in the literature that postural exposure is assessed from one continuous measurement collected over only a small part of a working day. In paper I, this was shown to be highly inefficient compared to spreading out the corresponding sample time across the entire working day, and the inefficiency was also obvious when assessing variance components, as shown in paper II. The thesis also shows how a well thought-out strategy for observation-based exposure assessment can reduce the effects of measurement error, both for random methodological variance (paper III) and systematic observation errors (bias) (paper IV).

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2012. 47 p.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1519
Keyword
Exposure assessment, arm elevation, exposure variability, variance components, random effects model, precision, bias, sample size, sample allocation, calibration, bootstrapping
National Category
Environmental Health and Occupational Health
Research subject
Occupational and Environmental Medicine
Identifiers
urn:nbn:se:umu:diva-59132 (URN)978-91-7459-469-0 (ISBN)
Public defence
2012-10-02, NA320, Umeå Universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2012-09-11 Created: 2012-09-10 Last updated: 2012-09-11Bibliographically approved

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