biostats (version 1.1.1)

sample_size: Sample Size Calculation for Clinical Trials

Description

Calculates the sample size needed in a clinical trial based on study design and statistical parameters using standard formulas for hypothesis testing (Chow, S. 2017).

Usage

sample_size(
  sample = c("one-sample", "two-sample"),
  design = NULL,
  outcome = c("mean", "proportion"),
  type = c("equality", "equivalence", "non-inferiority", "superiority"),
  alpha = 0.05,
  beta = 0.2,
  x1 = NULL,
  x2 = NULL,
  SD = NULL,
  delta = NULL,
  dropout = 0,
  k = 1
)
# S3 method for sample_size
print(x, ...)

Value

An object of class "sample_size" containing the calculated sample size and study parameters.

Arguments

sample

Character string indicating whether one or two samples need to be calculated. Options: "one-sample" or "two-sample".

design

Character string indicating study design when sample = "two-sample". Options: "parallel" or "crossover". Default: NULL for one-sample tests.

outcome

Character string indicating the type of outcome variable. Options: "mean" or "proportion".

type

Character string indicating the type of hypothesis test. Options: "equality", "equivalence", "non-inferiority", or "superiority".

alpha

Numeric parameter indicating the Type I error rate (significance level). Default: 0.05.

beta

Numeric parameter indicating the Type II error rate (1 - power). Default: 0.20.

x1

Numeric value of the mean or proportion for group 1 (treatment group).

x2

Numeric value of the mean or proportion for group 2 (control group or reference value).

SD

Numeric value indicating the standard deviation. Required for mean outcomes and crossover designs with proportion outcomes. Default: NULL.

delta

Numeric value indicating the margin of clinical interest. Required for non-equality tests. Must be negative for non-inferiority and positive for superiority/equivalence. Default: NULL.

dropout

Numeric value indicating the discontinuation rate expected in the study. Must be between 0 and 1. Default: 0.

k

Numeric value indicating the allocation ratio (n1/n2) for two-sample tests. Default: 1.

x

An object of class "sample_size".

...

Further arguments passed to or from other methods.

Methods (by generic)

• print(sample_size): Print method for objects of class "sample_size".

References

Chow, S.-C., Shao, J., Wang, H., & Lokhnygina, Y. (2017). Sample Size Calculations in Clinical Research (3rd ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781315183084

Examples

# Two-sample parallel non-inferiority test for means with 10% expected dropout
sample_size(sample = 'two-sample', design = 'parallel', outcome = 'mean',
            type = 'non-inferiority', x1 = 5.0, x2 = 5.0, 
            SD = 0.1, delta = -0.05, k = 1, dropout = 0.1)
            
# One-sample equivalence test for means
sample_size(sample = "one-sample", outcome = "mean", type = "equivalence",
            x1 = 0, x2 = 0, SD = 0.1, delta = 0.05)