Carrie R Houts1, Michael C Edwards2,3, R J Wirth2, Linda S Deal4. 1. Vector Psychometric Group, LLC., 847 Emily Lane, Chapel Hill, NC, 27516, USA. crhouts@vpgcentral.com. 2. Vector Psychometric Group, LLC., 847 Emily Lane, Chapel Hill, NC, 27516, USA. 3. The Ohio State University, Columbus, OH, USA. 4. Pfizer, Inc., Collegeville, PA, USA.
Abstract
INTRODUCTION: There has been a notable increase in the advocacy of using small-sample designs as an initial quantitative assessment of item and scale performance during the scale development process. This is particularly true in the development of clinical outcome assessments (COAs), where Rasch analysis has been advanced as an appropriate statistical tool for evaluating the developing COAs using a small sample. METHODS: We review the benefits such methods are purported to offer from both a practical and statistical standpoint and detail several problematic areas, including both practical and statistical theory concerns, with respect to the use of quantitative methods, including Rasch-consistent methods, with small samples. CONCLUSIONS: The feasibility of obtaining accurate information and the potential negative impacts of misusing large-sample statistical methods with small samples during COA development are discussed.
INTRODUCTION: There has been a notable increase in the advocacy of using small-sample designs as an initial quantitative assessment of item and scale performance during the scale development process. This is particularly true in the development of clinical outcome assessments (COAs), where Rasch analysis has been advanced as an appropriate statistical tool for evaluating the developing COAs using a small sample. METHODS: We review the benefits such methods are purported to offer from both a practical and statistical standpoint and detail several problematic areas, including both practical and statistical theory concerns, with respect to the use of quantitative methods, including Rasch-consistent methods, with small samples. CONCLUSIONS: The feasibility of obtaining accurate information and the potential negative impacts of misusing large-sample statistical methods with small samples during COA development are discussed.
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