Comparar métodos

	Análisis Robusto de Ítems	Análisis de Fiabilidad Robusta
Campo	Psicometría	Diseño experimental
Familia	Latent structure	Process / pipeline
Año de origen	1980s–2000s	1980s–1990s (integration formalized in engineering literature)
Autor original	Robust methods tradition (Huber, Hampel, Tukey); applied to item analysis by Wilcox and colleagues	Synthesized from Taguchi robust design and classical reliability theory (Kececioglu, Taguchi)
Tipo	Diagnostic / item-level evaluation	Quantitative reliability engineering method
Fuente seminal	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	Kececioglu, D. (1991). Reliability Engineering Handbook (Vol. 1). Prentice Hall. ISBN: 978-0137720774
Alias	robust item statistics, outlier-resistant item analysis, robust classical item analysis	RRA, reliability robustness analysis, uncertainty-aware reliability analysis, robust probabilistic reliability
Relacionados	5	4
Resumen	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.	Robust reliability analysis is an engineering method that combines classical reliability estimation with robustness principles to quantify and improve system dependability in the presence of parameter uncertainty and variability. Rather than assuming fixed input values, it propagates distributions of noise factors through a reliability model to produce probability-of-failure estimates that remain valid across a range of operating conditions and manufacturing tolerances.