Let \(b\) be the hazard ratio of two survival curves. Cox's
proportional hazard model allows you to test hypotheses about the value of \(b\).

Power Calculation Parameters

To input multiple values, seperate them by a comma.

{{ this.errors }}

Power Calculation Explanation

Solve For

The unknown you are interested in solving for.

N

The sample size used to test the hypothesis.

Alpha

The \(\alpha\) (Type I error rate) level of the hypothesis test.

Power

The power (1 - Type II error rate) of the hypothesis test.

Hazard Ratio

The hazard ratio being tested, \(b\).

Treatment Proportion

The proportion of subjects that recieve the treatment.

Proportion Visible

The proportion of event that are observed (1 minus the proportion that are censored).

Margin

The margin is a value the effect size needs to exceed to be meaningful. For hypotheses of equivalence, the margin must be greater than 0, or the calculation will not be solvable. For one sided tests, a margin is less than 0 implies a non-inferiority hypothesis. Otherwise, a superiority hypothesis is implied. Read More

Hypothesis

There are three types of hypotheses that can be tested: two-sided, one-sided and equivalence. Tests of equivalence must include a margin if the unknown and null means are equal. Read More