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An Example of Survival Analysis Data Applied to Covid-19

Authors:
  • Fulbright Roster and Syracuse University
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The present survival analysis is intended to illustrate the power that this statistical technique can offer to Covid-19 data studies. We analyze a data set that simulates patients in an ICU Ventilator (such Data Set was created to help illustrate the survival analysis). We start our analysis by considering only the patient Time to Death or Exit (recovery) of a Ventilator. We then include covariates (Comorbidity information) for each Ventilator patient. We considered Patient age, the number of Comorbidities2, and weather the end of their Time in Ventilator was caused by death, or by a recovery. Then, using such information, we analyze (1) the probability of survival of a Patient, given the Time in Ventilator, their age, and Comorbidities; and (2) the strength and direction (if any) of the effects of the different covariates, in the patient’s ICU Ventilator sojourn.
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A Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. First, multivariate goodness-of-fit methods and non-normal alternatives are classified according to their characteristics. Then, a measurement tool is defined, validated, and used to assess the performance of the methods, which are then ranked by type of alternative they best detect. Finally, Monte Carlo-derived empirical critical values for the 8 procedures, valid when samples are too small to invoke asymptotic theory, are provided.
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Romeu, J. L. 1978. Analisis y Clasificacion de Fuentes de Informacion, mediante métodos estadisticos. Revista de Ingenieria Civil. Vol. 4. Havana, Cuba. Available in the Internet: https://web.cortland.edu/romeu/DiscrAnalClasFuentesGvnDap.pdf
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