Cutpoint determination methods in competing risks subdistribution model
In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a com...
| Main Authors: | , , , |
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| Format: | Article |
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Penerbit ukm
2009
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| _version_ | 1796927465708322816 |
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| author | Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar, |
| author_facet | Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar, |
| author_sort | Noor Akma Ibrahim, |
| collection | UKM |
| description | In the analysis involving clinical and psychological data, by transforming a continuous
predictor variable into a categorical variable, usually binary, a more interpretable model can
be established. Thus, we consider the problem of obtaining a threshold value of a continuous
covariate given a competing risk survival time response using a binary partitioning algorithm
as a way to optimally partition data into two disjoint sets. Five cutpoint determination methods
are developed based on regression of competing risks subdistribution. Simulation results show
that the deviance method has the desired properties. Permutation test is used to assess the level
of significance and bootstrap confidence interval is obtained for the optimal cutpoint. The
deviance method is applied to determine cutpoint of age for a real dataset |
| first_indexed | 2024-03-06T03:44:31Z |
| format | Article |
| id | ukm.eprints-1926 |
| institution | Universiti Kebangsaan Malaysia |
| last_indexed | 2024-03-06T03:44:31Z |
| publishDate | 2009 |
| publisher | Penerbit ukm |
| record_format | dspace |
| spelling | ukm.eprints-19262011-06-20T03:32:11Z http://journalarticle.ukm.my/1926/ Cutpoint determination methods in competing risks subdistribution model Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar, In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. Five cutpoint determination methods are developed based on regression of competing risks subdistribution. Simulation results show that the deviance method has the desired properties. Permutation test is used to assess the level of significance and bootstrap confidence interval is obtained for the optimal cutpoint. The deviance method is applied to determine cutpoint of age for a real dataset Penerbit ukm 2009-07 Article PeerReviewed Noor Akma Ibrahim, and Abdul Kudus, and Isa Daud, and Mohd. Rizam Abu Bakar, (2009) Cutpoint determination methods in competing risks subdistribution model. Journal of Quality Measurement and Analysis, 5 (1). pp. 103-117. ISSN 1823-5670 http://www.ukm.my/~ppsmfst/jqma/index.html |
| spellingShingle | Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar, Cutpoint determination methods in competing risks subdistribution model |
| title | Cutpoint determination methods in competing risks
subdistribution model
|
| title_full | Cutpoint determination methods in competing risks
subdistribution model
|
| title_fullStr | Cutpoint determination methods in competing risks
subdistribution model
|
| title_full_unstemmed | Cutpoint determination methods in competing risks
subdistribution model
|
| title_short | Cutpoint determination methods in competing risks
subdistribution model
|
| title_sort | cutpoint determination methods in competing risks subdistribution model |
| work_keys_str_mv | AT noorakmaibrahim cutpointdeterminationmethodsincompetingriskssubdistributionmodel AT abdulkudus cutpointdeterminationmethodsincompetingriskssubdistributionmodel AT isadaud cutpointdeterminationmethodsincompetingriskssubdistributionmodel AT mohdrizamabubakar cutpointdeterminationmethodsincompetingriskssubdistributionmodel |