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Accounting for measurement error: a critical but often overlooked process

Harris, Edward F. and Smith, Richard N. (2009) Accounting for measurement error: a critical but often overlooked process. Archives of Oral Biology, 54 (Supplement 1). S107-S117. ISSN 1879-1506 (Online); 0003-9969 (Print)

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Abstract

Because of instrument imprecisions and human inconsistencies, measurements are not free of error. Technical error of measurement (TEM) is the variability encountered among dimensions when the same specimens are measured at multiple sessions. A goal of a data collection regimen is to minimize TEM. The few studies that actually quantify TEM— regardless of discipline—report that it is substantial and can affect results and inferences. Objective: This paper reviews some statistical approaches for identifying and controlling TEM. Statistically, TEM is part of the residual (―unexplained‖) variance in a statistical test, so accounting for TEM—which requires repeated measurements—enhances the chances of finding a statistically significant difference if one exists. Methods: It has been the author’s intention to perform a thorough review and discuss statistical design relating to types of error and statistical approaches to error accountability. This paper address’ issues of landmark location, validity, technical and systematic error, ANOVA, scaled measures and correlation coefficients in order to guide the reader towards correctly identify true experimental differences. Conclusions: Researchers commonly infer characteristics about populations from comparatively restricted study samples. Most inferences are statistical, and, aside from concerns about adequately accounting for known sources of variation with the research design, an important source of variability is measurement error. Variability in locating landmarks that define variables is obvious in odontometrics, cephalometrics and anthropometry, but 4 the same concerns about measurement accuracy and precision extend to all disciplines. With increasing accessibility to computer-assisted methods of data collection, the ease of incorporating repeated measures into statistical designs has improved. Accounting for this technical source of variation increases the chance of finding biologically true differences when they exist.

Item Type:Article
Additional Information:Issue date: December 2009. Available online: 31 July 2008. Special supplement on International Workshop on Oral Growth and Development.
Uncontrolled Keywords:Measurement error; Reliability; Validation; Correlation
Subjects:R Medicine > RK Dentistry
Departments, Research Centres and Related Units:Academic Faculties, Institutes and Research Centres > Faculty of Medicine > School of Dental Sciences
DOI:10.1016/j.archoralbio.2008.04.010
Related URLs:
Refereed:Yes
Status:Published
ID Code:1022
Deposited On:20 Oct 2009 10:13
Last Modified:24 Apr 2012 16:17

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