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Statistical concepts in the interpretation of serial bone densitometry.

The precision of a measurement can be expressed as the variance of multiple measurements. The coefficient of variation is a dimensionless expression of precision that is prevalent in the radiology literature. However, the coefficient of variation has important limitations. The question whether measured change is significant arises whenever any quantitative clinical parameter is followed over time. When serial bone mineral density measurements are made, change is commonly estimated as the slope of a line fitted to the serial data by linear regression. Confidence intervals for change based on this method usually assume that the precision error in measurement remains constant over time and that change is truly linear. Estimates of long-term precision may be elusive, and if constant, may vary for different individuals. If separate measurement precisions are known or are indeed constant, one can assess the level of statistical agreement of longitudinal data to linear, or other theoretical, models.

Absorptiometry, Photon↗

Problems of correlations between explanatory variables in multiple regression analyses in the dental literature.

Multivariable analysis is a widely used statistical methodology for investigating associations amongst clinical variables. However, the problems of collinearity and multicollinearity, which can give rise to spurious results, have in the past frequently been disregarded in dental research. This article illustrates and explains the problems which may be encountered, in the hope of increasing awareness and understanding of these issues, thereby improving the quality of the statistical analyses undertaken in dental research. Three examples from different clinical dental specialties are used to demonstrate how to diagnose the problem of collinearity/multicollinearity in multiple regression analyses and to illustrate how collinearity/multicollinearity can seriously distort the model development process. Lack of awareness of these problems can give rise to misleading results and erroneous interpretations. Multivariable analysis is a useful tool for dental research, though only if its users thoroughly understand the assumptions and limitations of these methods. It would benefit evidence-based dentistry enormously if researchers were more aware of both the complexities involved in multiple regression when using these methods and of the need for expert statistical consultation in developing study design and selecting appropriate statistical methodologies.

Data Interpretation, Statistical↗