Sample Size Calculation for PICOT-Based Study Designs

Provides sample size calculators for the study designs covered by the PICOT framework, including cross-sectional, case-control, cohort, superiority, non-inferiority, and equivalence clinical trials, and diagnostic test accuracy studies, following Bhardwaj et al. (2024) . Calculations are performed using the 'epiR' package as a validated computational backend. Includes a 'shiny' application with a PICOT-based design wizard, an interactive sensitivity plot, and automatically generated Methods-section text for manuscripts.

PICOTsize

PICOTsize is an R package and Shiny app for calculating sample sizes across the study designs covered by the PICOT framework: cross-sectional, case-control, cohort, superiority/non-inferiority/ equivalence clinical trials, and diagnostic test accuracy studies.

It follows the sample size formulas described in Bhardwaj et al. (2024), Determination of sample size for various study designs in medical research: A practical primer, J Family Med Prim Care, using epiR as a validated computational backend rather than reimplementing formulas from scratch. Every calculation is checked against the paper’s own worked examples – see the Validation tab in the app, or the package vignette, for a full comparison and an explanation of the handful of places where this package’s output differs from the paper (and why).

Installation

You can install the development version of PICOTsize from GitHub with:

# install.packages("remotes")
remotes::install_github("AtefehRashidi/PICOTsize")

Using the package directly

Every calculation is available as a plain R function, independent of the Shiny app:

library(PICOTsize)

calc_crosssectional_binary(
  p = 0.30,
  precision = 0.05,
  dropout_rate = 0.10
)

Launching the app

library(PICOTsize)
run_app()

Reference

Bhardwaj R, Agrawal U, Vashist P, Manna S. Determination of sample size for various study designs in medical research: A practical primer. J Family Med Prim Care. 2024;13:2555-61.

Contributing

Contributions are welcome! If you find a bug, have a suggestion, or would like to request a new feature, please open an issue on the GitHub repository.