Cox proportional hazard model

Cox proportional hazard model

(koks),
a statistical model used in survival analysis to demonstrate the multiplicative effect of several designated study factors, showing that this effect does not change over time. It was invented by the British statistician D. R. Cox.
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TABLE 1: Estimated hazard ratios (HR) and 95% pointwise confidence intervals from two Cox proportional hazard model fits.
We estimated the risk of outcome associated with [U.sub.Na] using a Cox proportional hazard model. The effect of interaction of some variables on the relationship between [U.sub.Na] and survival was examined by adding a corresponding interaction term in the model.
In a log binomial analysis adjusted for factors such as socioeconomic status and educational attainment, female youth in the VIP program group had a greater risk than their counterparts in the control group of experiencing a pregnancy event by age 20 (relative risk, 1.4); the finding was the same in a Cox proportional hazard model that adjusted for the same factors.
Cox proportional hazard model was performed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for admission serum TC levels.
suggested a general definition of the [R.sup.2] statistic that may be employed for Cox proportional hazard model as follows:
We begin with a multivariable model that contains all variables which were significant in the univariate Cox proportional hazard model at the 20-25 percent level.
Selected variables in univariate analysis were entered in a stepwise multivariate Cox proportional hazard model to determine independent contributions of predictors for the primary endpoint.
Cox proportional hazard model for suicide with mental disorders diagnoses as risk factors, adjusted for socio-demographic andjob related characteristics (Estimated effects of socio-demographic andjob related characteristics) parameter standard variable effect estimate error Gender Female v.
Table 3 depicts Cox proportional hazard model of relationship between timing of first marriage and region collapsed into North and South.
In a Cox proportional hazard model that further adjusted for the interval between PPI start to CDI attack or last follow-up, however, the association between PPI use and CDI was significant only for group 2 (hazard ratio, 1.94, P less than .001) and not group 3 (HR, 1.22, P = .25), said Dr.