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| 강건한 내용 타당도 평가× | 강건한 문항 분석× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1975 (base); 2000s–2010s (robust extensions) | 1980s–2000s |
| 창시자≠ | Grounded in Lawshe (1975) CVR framework; robust extensions draw on Huber, Wilcox, and robust statistics tradition | Robust methods tradition (Huber, Hampel, Tukey); applied to item analysis by Wilcox and colleagues |
| 유형≠ | Validity evidence / expert judgement procedure with outlier-resistant aggregation | Diagnostic / item-level evaluation |
| 원전≠ | Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. link ↗ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| 별칭≠ | robust CVR, outlier-resistant content validity, robust content validity index, robust expert-panel validation | robust item statistics, outlier-resistant item analysis, robust classical item analysis |
| 관련≠ | 6 | 5 |
| 요약≠ | Robust content validity assessment applies outlier-resistant statistical methods to the aggregation of expert panel ratings in content validation studies. By detecting and down-weighting idiosyncratic or extreme rater judgements, it yields Content Validity Ratio (CVR) and Content Validity Index (CVI) estimates that reflect the consensus of the panel more accurately than standard averaging when one or a few raters deviate sharply from the group. | Robust item analysis applies outlier-resistant statistical methods to the evaluation of individual test or scale items. Instead of classical means and Pearson correlations — both sensitive to extreme scores — it uses trimmed means, Winsorized correlations, or M-estimators to obtain item difficulty and item-total discrimination indices that remain stable when respondent distributions are skewed or contaminated by outliers. |
| ScholarGate데이터셋 ↗ |
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