epi.sssupc: Sample size for a parallel superiority trial, continuous outcome

Description

Sample size for a parallel superiority trial, continuous outcome.

Usage

epi.sssupc(treat, control, sigma, delta, n, power, r = 1, nfractional = FALSE, 
   alpha)

Value

A list containing the following:

n.total: the total number of study subjects required.
n.treat: the required number of study subject in the treatment group.
n.control: the required number of study subject in the control group.
delta: the equivalence limit, as entered by the user.
power: the specified or calculated study power.

Arguments

treat: the expected mean of the outcome of interest in the treatment group.
control: the expected mean of the outcome of interest in the control group.
sigma: the expected population standard deviation of the outcome of interest.
delta: the equivalence limit, expressed as the absolute change in the outcome of interest that represents a clinically meaningful difference. For a superiority trial the value entered for delta must be greater than or equal to zero.
n: scalar, the total number of study subjects in the trial.
power: scalar, the required study power.
r: scalar, the number in the treatment group divided by the number in the control group.
nfractional: logical, return fractional sample size.
alpha: scalar, defining the desired alpha level.

References

Chow S, Shao J, Wang H (2008). Sample Size Calculations in Clinical Research. Chapman & Hall/CRC Biostatistics Series, page 61.

Julious SA (2004). Sample sizes for clinical trials with normal data. Statistics in Medicine 23: 1921 - 1986.

Pocock SJ (1983). Clinical Trials: A Practical Approach. Wiley, New York.

Wang B, Wang H, Tu X, Feng C (2017). Comparisons of superiority, non-inferiority, and equivalence trials. Shanghai Archives of Psychiatry 29, 385 - 388. DOI: 10.11919/j.issn.1002-0829.217163.

Examples

Run this code

## EXAMPLE 1:
## A pharmaceutical company is interested in conducting a clinical trial
## to compare two cholesterol lowering agents for treatment of patients with
## congestive heart disease (CHD) using a parallel design. The primary 
## efficacy parameter is the concentration of high density lipoproteins
## (HDL). We consider the situation where the intended trial is to test 
## superiority of the test drug over the active control agent. Sample 
## size calculations are to be calculated to achieve 80% power at the
## 5% level of significance.

## In this example, we assume that if treatment results in a 5 unit 
## (i.e., delta = 5) increase in HDL it is declared to be superior to the
## active control. Assume the standard deviation of HDL is 10 units and 
## the HDL concentration in the treatment group is 20 units and the 
## HDL concentration in the control group is 20 units.

epi.sssupc(treat = 20, control = 20, sigma = 10, delta = 5, n = NA, 
   power = 0.80, r = 1, nfractional = FALSE, alpha = 0.05)

## A total of 100 subjects need to be enrolled in the trial, 50 in the 
## treatment group and 50 in the control group.

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