How to Report Reliability in Orthodontic Research

Proper statistical analysis is an absolutely essential tool for both clinicians and researchers attempting to implement evidence-based decisions. When analyzing reliability, statistical graphical representation is the best method. Other previously published error studies of 2D measurements, such as cephalometric landmarks, have inappropriately applied one-dimensional approaches, such as linearor angular measurements. The aim of this present article is to illustrate a graphic presentation method that can be applied to two-dimensional (2D) data sets. We propose that this 2D visualization technique, that can visualize errors in both xand y axes simultaneously, should be utilized when reporting the reliability of a 2D data set. Our prediction error analysis of soft tissue changes after orthognathic surgery will be presented as an example. By applying different colors to each ellipse, this method can also identify any between-group differences that may be present. INTRODUCTION (Background) Reliability studies are conducted in experimental or survey situations to assess the level of observer variability in the measurement procedures to be used in data acquisition and/or investigation. 1 Several related measurements may be taken on a single individual. For example, measurements of the teeth, dentition, jaw bone, and soft tissue covering are correlated (or clustered). A problem may arise if clustered observations are erroneously treated and analyzed as separate (independent or non-clustered) observations. 2-6 Orthodontics, a unique specialty in dentistry, also has unique problems with which conventional methods cannot properly deal. This is because orthodontic treatment involves numerous variables within the dentition, skeletal configuration, and soft tissue responses which are all clustered within an individual. Therefore, to properly consider the correlation among variables, a more sophisticated method than the ordinary analysis and/or interpretation method should be applied. 7-9 (Raising an issue)The commonly utilized orthodontic cephalometric points, which have xand y Cartesiancoordinates (axes), are examples of measurements that should not be considered separately but asclustered data sets. Let us suppose that we need to know the identification error of a specificcephalometric landmark, or, by using cephalometric analyses, we are going to measure the accuracy ofpredicting an orthognathic surgical result. In these cases, we are analyzing deviations between predictedand actual results. An issue may arise since the location of a cephalometric landmark has twoManuscript (no author identifiers please)Click here to view linked References