A Detection Measure of Outliers Based on Forward Search Approach for Cox-Regression Model
Abstract
This paper focuses on identifying possible outliers based on Cox regression model. Forward search
method has been applied in several studies involving regression-based models such as linear
regression and generalized linear model. The method starts with a pre-selected subset of a data set.
The method moves forward through the data by adding observations one by one and progressive
changes in values of statistics are noted. In this paper, we extend the application of forward search in
survival data analysis. Currently, graphical methods are used to detect any significant changes in
values of the statistics. We propose a measure which may aid us in determining observations that are
outlier.
method has been applied in several studies involving regression-based models such as linear
regression and generalized linear model. The method starts with a pre-selected subset of a data set.
The method moves forward through the data by adding observations one by one and progressive
changes in values of statistics are noted. In this paper, we extend the application of forward search in
survival data analysis. Currently, graphical methods are used to detect any significant changes in
values of the statistics. We propose a measure which may aid us in determining observations that are
outlier.
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PDF (Bahasa Indonesia)DOI: https://doi.org/10.29313/jstat.v8i2.984
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