### 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 language | English (US) |
---|---|

Article number | 8920418 |

Journal | Scientifica |

Volume | 2016 |

DOIs | |

State | Published - Jan 1 2016 |

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### 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.

Research output: Contribution to journal › Review article

}

TY - JOUR

T1 - Causality in Statistical Power

T2 - Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size

AU - Heidel, Robert

PY - 2016/1/1

Y1 - 2016/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85016687641&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016687641&partnerID=8YFLogxK

U2 - 10.1155/2016/8920418

DO - 10.1155/2016/8920418

M3 - Review article

AN - SCOPUS:85016687641

VL - 2016

JO - Scientifica

JF - Scientifica

SN - 2090-908X

M1 - 8920418

ER -