International Journal of Statistics and Applied Mathematics
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2022, Vol. 7, Issue 6, Part B

Impact of missing complete at random data in survival analysis


Author(s): Pavithra V and Kannan R

Abstract: The problem of missing data deserves special attention because it refers to the case where not all data were obtained as intended in the study design. In survival analysis researchers are faced with the problem of identifying subjects for each follow-up visit and in some situations; may not obtain observations about the subject of the study. As a result, there will be a lack of data in some studies and this poses a major challenge for the analysis. In general, missing data analysis deals with replacement and missing data with deletion. In this paper may tried missing complete at random with deletion and Imputation techniques and focuses on the study is to find out the survival probability rate and final outcome of the Breast Cancer patients by the method of Kaplan-Meier, Cox Proportional Hazard Model, Minimum Survival probability, Maximum Survival Probability.

Pages: 122-128 | Views: 214 | Downloads: 10

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How to cite this article:
Pavithra V, Kannan R. Impact of missing complete at random data in survival analysis. Int J Stat Appl Math 2022;7(6):122-128.
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