Estimation of Survival Time of HIV/ AIDS Patients While Reducing the Number of Predictors Using a Partial Correlation/ Association Technique
Gurprit Grover
and Anurag Sharma*Department of Statistics, University of Delhi, Delhi- 110007, India
Corresponding Author E-mail : anuragsharma532@gmail.com
Abstract: A number of techniques have been developed for variable reduction in the survival analysis. However, none of those techniques take into consideration the correlation among the predictors. This paper focuses on the reducing the number of predictors using the concept of partial correlation/ association and then estimating the survival time of HIV/ AIDS patients while. Partial correlation is preferred over pairwise correlation & multiple correlation as pairwise correlation takes into account only the linear relationship between two predictors at a time and multiple correlation may give misleading results if one variable is numerically related to other variable and both the variables again are taken simultaneously to find the association/ correlation. This can be avoided by controlling the confounding variable using partial correlation coefficient. Partial correlation is used to assess the correlation between a continuous predictor and a categorical predictor when the controlling variable is also categorical. ANCOVA is used to determine the association between two categorical predictors when the controlling variable is also categorical. AFT models are used to estimate survival times with/ without reduction in the number of predictors. It is observed that the estimated survival times are not affected by the reduction of predictors from 11 to 4. Also, the estimates obtained by the new proposed technique are found to be more efficient than the existing methods.
Keywords: AIDS; AFT; ANCOVA; HIV Back to TOC