Vertaile menetelmiä

	Robust Content Validity Assessment	Konvergentti validiteetti
Tieteenala	Psykometriikka	Psykometriikka
Menetelmäperhe	Latent structure	Latent structure
Syntyvuosi	1975 (base); 2000s–2010s (robust extensions)	1959
Kehittäjä	Grounded in Lawshe (1975) CVR framework; robust extensions draw on Huber, Wilcox, and robust statistics tradition	Donald T. Campbell & Donald W. Fiske
Tyyppi	Validity evidence / expert judgement procedure with outlier-resistant aggregation	Validity evidence / construct validation
Alkuperäislähde	Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575.	Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.
Rinnakkaisnimet	robust CVR, outlier-resistant content validity, robust content validity index, robust expert-panel validation	convergent construct validity, convergence validity, AVE-based convergent validity
Liittyvät	6	4
Tiivistelmä	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.	Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and the Average Variance Extracted (AVE) statistic in SEM-based scale validation.