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The relationship between treatment effect and the hazard ratio is given as . A statistically important, but practically insignificant effect can produce a large hazard ratio, e.g. a treatment increasing the number of one-year survivors in a population from one in 10,000 to one in 1,000 has a hazard ratio of 10.
The hazard ratio is the quantity (), which is = in the above example. From the last calculation above, an interpretation of this is as the ratio of hazards between two "subjects" that have their variables differ by one unit: if P i = P j + 1 {\displaystyle P_{i}=P_{j}+1} , then exp ( β 1 ( P i − P j ) = exp ( β 1 ( 1 ...
A hazard quotient is the ratio of the potential exposure to a substance and the level at which no adverse effects are expected. If the Hazard Quotient is calculated to be less than 1, then no adverse health effects are expected as a result of exposure. If the Hazard Quotient is greater than 1, then adverse health effects are possible.
The summary output also gives upper and lower 95% confidence intervals for the hazard ratio: lower 95% bound = 1.15; upper 95% bound = 3.26. Finally, the output gives p-values for three alternative tests for overall significance of the model:
A concept closely-related but different [2] to instantaneous failure rate () is the hazard rate (or hazard function), (). In the many-system case, this is defined as the proportional failure rate of the systems still functioning at time t {\displaystyle t} (as opposed to f ( t ) {\displaystyle f(t)} , which is the expressed as a proportion of ...
The Nelson–Aalen estimator is a non-parametric estimator of the cumulative hazard rate function in case of censored data or incomplete data. [1] It is used in survival theory, reliability engineering and life insurance to estimate the cumulative number of expected events. An "event" can be the failure of a non-repairable component, the death ...
Breaking down every bodily reaction of what occurs during and after the consuming the good ol' fizzy stuff.
If the hazard ratio is , there are total subjects, is the probability a subject in either group will eventually have an event (so that is the expected number of events at the time of the analysis), and the proportion of subjects randomized to each group is 50%, then the logrank statistic is approximately normal with mean () and variance 1. [4]