2008
DOI: 10.1186/1471-2288-8-33
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Rasch fit statistics and sample size considerations for polytomous data

Abstract: Background: Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this … Show more

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Cited by 273 publications
(224 citation statements)
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References 21 publications
(22 reference statements)
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“…In a successful Rasch analysis, there is only one dimension, called the Rasch dimension, captured by the Rasch model and there should be no presence of subdimensions in the principal component analysis. An eigenvalue of the first factor (the Rasch dimension) greater than three or an eigenvalue of each item greater than 1.4 suggests that additional subdimensions are likely to be present [13,21]. No items were identified as unacceptably correlated during this process.…”
Section: Validation Processmentioning
confidence: 99%
“…In a successful Rasch analysis, there is only one dimension, called the Rasch dimension, captured by the Rasch model and there should be no presence of subdimensions in the principal component analysis. An eigenvalue of the first factor (the Rasch dimension) greater than three or an eigenvalue of each item greater than 1.4 suggests that additional subdimensions are likely to be present [13,21]. No items were identified as unacceptably correlated during this process.…”
Section: Validation Processmentioning
confidence: 99%
“…For the Rasch analysis, a random subsample of 400 respondents was used, as there is evidence that some Rasch fit statistics for polytomous scales such as the CORE-OM are dependent on sample size and larger samples can have a higher chance of type 1 errors. 73 The Rasch results were validated on an additional random subsample of 400 respondents.…”
Section: Developing the Health-state Classificationmentioning
confidence: 99%
“…Bond and Fox (2007) noted the incumbent difficulties in formulating definitive cut-off points where items may be regarded as so misfitting as to warrant exclusion. Central to much debate among various researchers, these pertain to a balancing of interpreting t-values relative to the magnitudes of both fit statistics and sample size (Bond & Fox, 2007;Smith, Rush, Fallowfield, Velikova & Sharpe, 2008). Bond and Fox (2007: 243) do, however, offer "reasonable item mean square ranges" for rating scales (likert/survey) such as those used in this investigation, of 0.6 to 1.4.…”
Section: Resultsmentioning
confidence: 99%