Ke, Y;
Fu, B;
Zhang, W;
(2016)
Semi-varying coefficient multinomial logistic regression for disease progression risk prediction.
Statistics in Medicine
, 35
(26)
pp. 4764-4778.
10.1002/sim.7034.
Preview |
Text
Ke_Semi-varying coefficient multinomial logistic regressionAAM.pdf Download (522kB) | Preview |
Abstract
This paper proposes a risk prediction model using semi-varying coefficient multinomial logistic regression. We use a penalized local likelihood method to do the model selection and estimate both functional and constant coefficients in the selected model. The model can be used to improve predictive modelling when non-linear interactions between predictors are present. We conduct a simulation study to assess our method’s performance and the results show that the model selection procedure works well with small average numbers of wrong-selection or missing-selection. We illustrate the use of our method by applying it to classify the patients at baseline into different risk groups in future disease progression. We use a leave-one-out cross-validation method to assess its correct prediction rate and propose a recalibration framework to evaluate how reliable are the predicted risks.
Type: | Article |
---|---|
Title: | Semi-varying coefficient multinomial logistic regression for disease progression risk prediction |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/sim.7034 |
Publisher version: | http://dx.doi.org/10.1002/sim.7034 |
Language: | English |
Additional information: | This is the peer reviewed version of the following article: Ke, Y; Fu, B; Zhang, W; (2016) Semi-varying coefficient multinomial logistic regression for disease progression risk prediction. Statistics in Medicine , 35 (26) pp. 4764-4778, which has been published in final form at http://dx.doi.org/10.1002/sim.7034. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving |
Keywords: | Model selection;multinomial logistic regression; penalized likelihood; risk prediction; varying coefficients |
UCL classification: | UCL |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1493623 |
Archive Staff Only
![]() |
View Item |