TY  - INPR
A1  - Liero, Hannelore
A1  - Liero, Matthias
T1  - Testing the acceleration function in life time models
N2  - The accelerated life time model is considered. First, test procedures for testing the parameter of a parametric acceleration function is investigated; this is done under the assumption of parametric and nonparametric baseline distribution. Further, based on nonparametric estimators for regression functions tests are proposed for checking whether a parametric acceleration function is appropriate to model the influence of the covariates. Resampling procedures are discussed for the realization of these methods. Simulations complete the considerations.
T3  - Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint - 2006, 03 
Y1  - 2006
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-49405
ER  - 
TY  - GEN
A1  - Mühlenbruch, Kristin
A1  - Kuxhaus, Olga
A1  - Pencina, Michael J.
A1  - Boeing, Heiner
A1  - Liero, Hannelore
A1  - Schulze, Matthias Bernd
T1  - A confidence ellipse for the Net Reclassification Improvement
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
N2  - The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.
KW  - risk assessment
KW  - risk model
KW  - model comparison
KW  - reclassification
KW  - confidence intervals
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427371
SN  - 1866-8372
IS  - 825
SP  - 299
EP  - 304
ER  - 
TY  - JOUR
A1  - Mühlenbruch, Kristin
A1  - Kuxhaus, Olga
A1  - Pencina, Michael J.
A1  - Boeing, Heiner
A1  - Liero, Hannelore
A1  - Schulze, Matthias Bernd
T1  - A confidence ellipse for the Net Reclassification Improvement
JF  - European journal of epidemiology
N2  - The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.
KW  - Risk assessment
KW  - Risk model
KW  - Model comparison
KW  - Reclassification
KW  - Confidence intervals
Y1  - 2015
U6  - https://doi.org/10.1007/s10654-015-0001-1
SN  - 0393-2990
SN  - 1573-7284
VL  - 30
IS  - 4
SP  - 299
EP  - 304
PB  - Springer
CY  - Dordrecht
ER  -