PASSED: Calculate Power and Sample Size for Two Sample Tests

Jinpu Li; Ryan P. Knigge; Kaiyi Chen; Emily V. Leary

doi:10.32614/RJ-2021-094

PASSED: Calculate Power and Sample Size for Two Sample Tests

Jinpu Li, Ryan P. Knigge, Kaiyi Chen, Emily V. Leary

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis.

Original language	English (US)
Pages (from-to)	542-560
Number of pages	19
Journal	R Journal
Volume	13
Issue number	2
DOIs	https://doi.org/10.32614/RJ-2021-094
State	Published - 2021
Externally published	Yes

Bibliographical note

Funding Information:
The authors gratefully acknowledge Dr. Richard Madsen, Professor Emeritus of Statistics University of Missouri - Columbia, for his contribution and interest in this topic. Funding for this project was provided by NIH R34AR074209A (Co-I Leary) and the Thompson Laboratory for Regenerative Orthopaedics, University of Missouri - Columbia.

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© 2021,R Journal.All Rights Reserved

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PY - 2021

Y1 - 2021

N2 - Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis.

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PASSED: Calculate Power and Sample Size for Two Sample Tests

Abstract

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