Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size
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...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Scientifica |
| Online Access: | http://dx.doi.org/10.1155/2016/8920418 |
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| author | R. Eric Heidel |
| author_facet | R. Eric Heidel |
| author_sort | R. Eric Heidel |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1736e10d309a474ba51780cd5e7d48ee |
| institution | Kabale University |
| issn | 2090-908X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Scientifica |
| spelling | doaj-art-1736e10d309a474ba51780cd5e7d48ee2025-02-03T01:23:03ZengWileyScientifica2090-908X2016-01-01201610.1155/2016/89204188920418Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample SizeR. Eric Heidel0Department of Surgery, Office of Medical Education, Research, and Development, University of Tennessee Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN 37920, USAStatistical 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.http://dx.doi.org/10.1155/2016/8920418 |
| spellingShingle | R. Eric Heidel Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size Scientifica |
| title | Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size |
| title_full | Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size |
| title_fullStr | Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size |
| title_full_unstemmed | Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size |
| title_short | Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size |
| title_sort | causality in statistical power isomorphic properties of measurement research design effect size and sample size |
| url | http://dx.doi.org/10.1155/2016/8920418 |
| work_keys_str_mv | AT rericheidel causalityinstatisticalpowerisomorphicpropertiesofmeasurementresearchdesigneffectsizeandsamplesize |