epiR (version 0.9-82)

epi.supc: Estimate the sample size for a parallel superiority trial, continuous outcomes

Description

Computes the sample size for a parallel superiority trial with a continuous outcome variable.

Usage

epi.supc(treat, control, sd, delta, n, r = 1, power, alpha)

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.

sd

the expected population standard deviation of the outcome of interest.

delta

the equivalence limit, expressed as a proportion.

n

scalar, the total number of study subjects in the trial.

r

scalar, the number in the treatment group divided by the number in the control group.

power

scalar, the required study power.

alpha

scalar, defining the desired alpha level.

Value

A list containing one or more of the following:

n.treat

the required number of study subject in the treatment group.

n.control

the required number of study subject in the control group.

n.total

the total number of study subjects required.

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.

Examples

## 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.supc(treat = 20, control = 20, sd = 10, delta = 5, n = NA, 
   r = 1, power = 0.80, 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.