Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size

Research output: Contribution to journalReview article

3 Citations (Scopus)

Abstract

Statistical power is the ability to detect a significant effect, given that the effect actually exists in a population. Like most statistical concepts, statistical power tends to induce cognitive dissonance in hepatology researchers. However, planning for statistical power by an a priori sample size calculation is of paramount importance when designing a research study. There are five specific empirical components that make up an a priori sample size calculation: the scale of measurement of the outcome, the research design, the magnitude of the effect size, the variance of the effect size, and the sample size. A framework grounded in the phenomenon of isomorphism, or interdependencies amongst different constructs with similar forms, will be presented to understand the isomorphic effects of decisions made on each of the five aforementioned components of statistical power.

Original languageEnglish (US)
Article number8920418
JournalScientifica
Volume2016
DOIs
StatePublished - Jan 1 2016

Fingerprint

Causality
Sample Size
Research Design
Cognitive Dissonance
Aptitude
Gastroenterology
sampling
statistical concept
planning
researchers
Research Personnel
Outcome Assessment (Health Care)
Research
Population
effect
calculation

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences(all)
  • Environmental Science(all)
  • Medicine(all)

Cite this

Causality in Statistical Power : Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size. / Heidel, Robert.

In: Scientifica, Vol. 2016, 8920418, 01.01.2016.

Research output: Contribution to journalReview article

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