2015•ICSA - International Conference on Statistics and Analytics 2019Requires access

SURVIVAL ANALYSIS WITH EXTENDED COX MODEL ABOUT DURABILITY DEBTOR EFFORTS ON CREDIT RISK

Iwan Kurniawan, Anang Kurnia, Bagus Sartono

Open publisher page 1 citations

Abstract

The application of survival analysis on the data of credit motorcycle financing experiencing bad loans after the credit starts early, with sixteen covariates were considered. The model used in survival analysis is the Cox proportional hazard models. Cox models have the assumption that the proportional hazard assumption. Extended Cox models selected to improve cox proportional hazard models when one or more covariates did not meet the assumption of proportional hazards. Extended cox models is an extension of cox models that involve time-dependent variables. Covariates that do not meet the proportional hazards assumption in the Cox models diinteraksikan extended with functions appropriate time, in order to obtain time-dependent covariates. So on the model covariates that are not dependent on time and time dependent covariates. The parameters of these covariates estimated using partial maximum likelihood method. To determine whether the extended Cox model is a suitable model for the data in a particular case, likelihood ratio test was used. The results indicate that extended Cox models with functions time appropriate, provide the best model.Keywords : Credit Risk, Survival Analysis, Cox Proportional Hazard , Extended Cox Model

About this research paper

What this paper is about

The application of survival analysis on the data of credit motorcycle financing experiencing bad loans after the credit starts early, with sixteen covariates were considered. The model used in survival analysis is the Cox proportional hazard models. Cox models have the assumption that the proportional hazard assumption. Extended Cox models selected to improve cox proportional hazard models when one or more covariates did not meet the assumption of proportional hazards. Extended cox models is an extension of cox models that involve time-dependent variables. Covariates that do not meet the proportional hazards assumption in the Cox models diinteraksikan extended with functions appropriate time, in order to obtain time-dependent covariates. So on the model covariates that are not dependent on time and time dependent covariates. The parameters of these covariates estimated using partial maximum likelihood method. To determine whether the extended Cox model is a suitable model for the data in a particular case, likelihood ratio test was used. The results indicate that extended Cox models with functions time appropriate, provide the best model.Keywords : Credit Risk, Survival Analysis, Cox Proportional Hazard , Extended Cox Model

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The application of survival analysis on the data of credit motorcycle financing experiencing bad loans after the credit starts early, with sixteen covariates were considered. The model used in survival analysis is the Cox proportional hazard models. Cox models have the assumption that the proportional hazard assumption. Extended Cox models selected to improve cox proportional hazard models when one or more covariates did not meet the assumption of proportional hazards. Extended cox models is an extension of cox models that involve time-dependent variables. Covariates that do not meet the proportional hazards assumption in the Cox models diinteraksikan extended with functions appropriate time, in order to obtain time-dependent covariates. So on the model covariates that are not dependent on time and time dependent covariates. The parameters of these covariates estimated using partial maximum likelihood method. To determine whether the extended Cox model is a suitable model for the data in a particular case, likelihood ratio test was used. The results indicate that extended Cox models with functions time appropriate, provide the best model.Keywords : Credit Risk, Survival Analysis, Cox Proportional Hazard , Extended Cox Model

Key concepts: Proportional hazards model, Covariate, Econometrics, Statistics, Survival analysis, Accelerated failure time model, Hazard, Hazard ratio

Related papers

Back to paper searchBrowse research topicsOriginal source
SURVIVAL ANALYSIS WITH EXTENDED COX MODEL ABOUT DURABILITY DEBTOR EFFORTS ON CREDIT RISK — Research Paper | ScholarLens