A Geometric Approach to Nonlinear Regression Diagnostics with Applications to matched Case-Control Studies

A Geometric Approach to Nonlinear Regression Diagnostics with Applications to matched Case-Control Studies

A geometric approach is described for the detection of influential points in nonlinear regression. This work extends and gives geometric interpretation to recent results in logistic regression diagnostics. An application of this approach to matched case-control studies is discussed.

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Annals of statistics 1984-09, Vol.12 (3), p.816-826
Hauptverfasser: Moolgavkar, Suresh H., Lustbader, Edward D., Venzon, David J.
Format: Artikel
Sprache:eng
Schlagworte:
62F99
62P10
Approximation
Case control studies
Covariance matrices
diagnostics
hat matrix
influential observations
Inner products
Least squares
Linear regression
logistic regression
Mathematical vectors
Matrices
Maximum likelihood estimation
Maximum likelihood estimators
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A geometric approach is described for the detection of influential points in nonlinear regression. This work extends and gives geometric interpretation to recent results in logistic regression diagnostics. An application of this approach to matched case-control studies is discussed.
ISSN:0090-5364
2168-8966
DOI:10.1214/aos/1176346704