Evaluation of the predictive impact of cephalometric variables: logistic regression and ROC curves = Beurteilung der prädiktiven Wertigkeit kephalometrischer Variablen : logistische Regressionen und ROC-Kurven

In the context of orthodontic treatment planning, the decisions to be made are often affected by the assumption of future growth patterns, especially the direction of mandibular rotation. Using longitudinally available lateral cephalograms from the Belfast Growth Study, it was examined whether, on t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Lux, Christopher J. (VerfasserIn) , Conradt, Christian (VerfasserIn) , Stellzig-Eisenhauer, Angelika (VerfasserIn) , Komposch, Gerda (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: March 1999
In: Journal of orofacial orthopedics
Year: 1999, Jahrgang: 60, Heft: 2, Pages: 95-107
ISSN:1615-6714
DOI:10.1007/BF01298960
Online-Zugang:Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1007/BF01298960
Verlag, lizenzpflichtig, Volltext: https://link.springer.com/article/10.1007/BF01298960
Volltext
Verfasserangaben:Christopher J. Lux, Christian Conradt, Angelika Stellzig, Gerda Komposch
Beschreibung
Zusammenfassung:In the context of orthodontic treatment planning, the decisions to be made are often affected by the assumption of future growth patterns, especially the direction of mandibular rotation. Using longitudinally available lateral cephalograms from the Belfast Growth Study, it was examined whether, on the basis of the cephalometric variables at the ages of 7, 9 and 11, the direction of mandibular rotation can be predicted in the respective subsequent 4-year intervals. For statistical analysis of this problem, logistic regression models were applied to describe and quantify the influence of potential explanatory variables on the direction of mandibular rotation (dependent variable). In addition, graphical methods taken from the field of medical diagnostics were applied for prediction and for determination of predictive accuracy.
Beschreibung:Gesehen am 10.03.2021
Beschreibung:Online Resource
ISSN:1615-6714
DOI:10.1007/BF01298960