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ERIC Number: EJ1110578
Record Type: Journal
Publication Date: 2016-Aug
Pages: 12
Abstractor: As Provided
ISSN: EISSN-1531-7714
Measurement Error and Equating Error in Power Analysis
Phillips, Gary W.; Jiang, Tao
Practical Assessment, Research & Evaluation, v21 n9 Aug 2016
Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of statistical tests. The overall finding is that measurement error and equating error reduce power and inflate sample size requirements. It is recommended that researchers, where appropriate, incorporate these sources of error in conducting power analysis. If either of these two sources of error are present in the data but not accounted for in the power analysis, then power will be underestimated and sample size requirements will be underestimated.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A