Journal de biométrie et biostatistique

Survival Functions under Proportional Hazards Model

Abstract

Jianrong Wu

A statistical hypothesis is a hypothesis that is testable on the basis of observed data modeled as the realized values taken by a collection of random variables.[1] A set of data is modelled as being realized values of a collection of random variables having a joint probability distribution in some set of possible joint distributions. The hypothesis being tested is exactly that set of possible probability distributions. A statistical hypothesis test is a method of statistical inference. An alternative hypothesis is proposed for the probability distribution of the data, either explicitly or only informally. The comparison of the two models is deemed statistically significant if, according to a threshold probability—the significance level—the data would be unlikely to occur if the null hypothesis were true. A hypothesis test specifies which outcomes of a study may lead to a rejection of the null hypothesis at a pre-specified level of significance, while using a pre-chosen measure of deviation from that hypothesis (the test statistic, or goodness-of-fit measure).