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Visual research on the trustability of classical variable selection methods in Cox regression

Nihal ATA TUTKUN [1] , Yasemin KAYHAN ATILGAN [2]

Multivariate models such as the Cox regression model, if developed carefully, are powerful tools for making prognostic prediction which are frequently used in studies of clinical outcomes. Many applications require a large number of variables to be modelled by using a relatively small patient sample. Determination of the important variables in a model is critical to understand the behaviour of phenomena as the independent variables contribute the most to the outcome. From a practical perspective, a small subset of independent variables are usually selected from a large data set without the loss of any predictive efficiency. Automatic variable selection algorithms in scientific studies are commonly used for obtaining interpretable and practically applicable models. However, the careless use of these methods may lead to statistical problems. The performance of the generated models may be poor due to the violation of assumption, omission of the important variables, problems of overfitting, and the problem of multicollinearity and outliers. In order to enhance the accuracy of a model, it is essential to explore the data and its main characteristics before making any statistical inference. This study suggests an approach for acquiring a trustworthy model selection procedure for survival data by performing classical variables selection methods, accompanied by a graphical visualization method, namely robust coplot. Thus, it enables us to investigate the discrimination of observations, clusters of the variables and clusters of the observations that are highly characterized by a particular variable in a one graph. We present an application of combined method, as an integral part of statistical modelling, on survival data on multiple myeloma to show how coplot results are used in automatic variable selection algorithm in Cox regression model-building.
Cox regression model, graphical visualization, multidimensional scaling, robust coplot, variable selection
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Birincil Dil en İstatistik ve Olasılık İstatistik Orcid: 0000-0001-5204-680XYazar: Nihal ATA TUTKUN (Sorumlu Yazar)Kurum: HACETTEPE UNIVERSITYÜlke: Turkey Orcid: 0000-0002-2612-7216Yazar: Yasemin KAYHAN ATILGAN Kurum: HACETTEPE UNIVERSITYÜlke: Turkey Yayımlanma Tarihi : 2 Nisan 2020
 Bibtex @araştırma makalesi { hujms630402, journal = {Hacettepe Journal of Mathematics and Statistics}, issn = {2651-477X}, eissn = {2651-477X}, address = {}, publisher = {Hacettepe Üniversitesi}, year = {2020}, volume = {49}, pages = {869 - 886}, doi = {10.15672/hujms.630402}, title = {Visual research on the trustability of classical variable selection methods in Cox regression}, key = {cite}, author = {ATA TUTKUN, Nihal and KAYHAN ATILGAN, Yasemin} } APA ATA TUTKUN, N , KAYHAN ATILGAN, Y . (2020). Visual research on the trustability of classical variable selection methods in Cox regression. Hacettepe Journal of Mathematics and Statistics , 49 (2) , 869-886 . DOI: 10.15672/hujms.630402 MLA ATA TUTKUN, N , KAYHAN ATILGAN, Y . "Visual research on the trustability of classical variable selection methods in Cox regression". Hacettepe Journal of Mathematics and Statistics 49 (2020 ): 869-886 Chicago ATA TUTKUN, N , KAYHAN ATILGAN, Y . "Visual research on the trustability of classical variable selection methods in Cox regression". Hacettepe Journal of Mathematics and Statistics 49 (2020 ): 869-886 RIS TY - JOUR T1 - Visual research on the trustability of classical variable selection methods in Cox regression AU - Nihal ATA TUTKUN , Yasemin KAYHAN ATILGAN Y1 - 2020 PY - 2020 N1 - doi: 10.15672/hujms.630402 DO - 10.15672/hujms.630402 T2 - Hacettepe Journal of Mathematics and Statistics JF - Journal JO - JOR SP - 869 EP - 886 VL - 49 IS - 2 SN - 2651-477X-2651-477X M3 - doi: 10.15672/hujms.630402 UR - https://doi.org/10.15672/hujms.630402 Y2 - 2020 ER - EndNote %0 Hacettepe Journal of Mathematics and Statistics Visual research on the trustability of classical variable selection methods in Cox regression %A Nihal ATA TUTKUN , Yasemin KAYHAN ATILGAN %T Visual research on the trustability of classical variable selection methods in Cox regression %D 2020 %J Hacettepe Journal of Mathematics and Statistics %P 2651-477X-2651-477X %V 49 %N 2 %R doi: 10.15672/hujms.630402 %U 10.15672/hujms.630402 ISNAD ATA TUTKUN, Nihal , KAYHAN ATILGAN, Yasemin . "Visual research on the trustability of classical variable selection methods in Cox regression". Hacettepe Journal of Mathematics and Statistics 49 / 2 (Nisan 2020): 869-886 . https://doi.org/10.15672/hujms.630402 AMA ATA TUTKUN N , KAYHAN ATILGAN Y . Visual research on the trustability of classical variable selection methods in Cox regression. Hacettepe Journal of Mathematics and Statistics. 2020; 49(2): 869-886. Vancouver ATA TUTKUN N , KAYHAN ATILGAN Y . Visual research on the trustability of classical variable selection methods in Cox regression. Hacettepe Journal of Mathematics and Statistics. 2020; 49(2): 886-869.

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