Proportionally Reducing Sample-Size Requirements by Increasing Dependent-Variable Reliability
| Autor: | Frank J. Winn, Stephen J. Morrissey, Alvah C. Bittner |
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| Rok vydání: | 2003 |
| Předmět: |
Variables
media_common.quotation_subject 05 social sciences 030229 sport sciences Reliability engineering Medical Terminology 03 medical and health sciences 0302 clinical medicine Sample size determination Independent samples Statistics 0501 psychology and cognitive sciences Sensitivity (control systems) Constant (mathematics) 050107 human factors Reliability (statistics) Medical Assisting and Transcription Mathematics media_common |
| Zdroj: | Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 47:2000-2004 |
| ISSN: | 1071-1813 2169-5067 |
| DOI: | 10.1177/154193120304701811 |
| Popis: | Increasing dependent-variable reliability ρ(y,y) proportionally reduces both sample-size requirements and costs of independent-groups studies. This result is analytically considered in terms of the classical Z-test comparison of two means representing independent samples of size ( N). Analysis reveals that the dependent-variable reliability directly trades-off with sample-size in its impacts on sensitivity, so that constant statistical-power is maintained by reducing sample-size with a proportionally increased ρ(y,y). Two illustrations (reflecting sample-size and associated cost reductions of up to 50% or more) are presented of the value of systematic efforts to enhance reliability: (a) Integrating performance measures in evaluation of worker exposure-effects, and (b) Quality and preferences in new-product development. Test-Retest Reliability analyses are recommended as means to evaluate (1) Potential for enhancing statistical-power via increases in ρ(y,y) and (2) Impacts of attempts to increase statistical-power via increases in dependent-variable reliability (ρ(y,y)). |
| Databáze: | OpenAIRE |
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