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Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Robustní analýza položek×Robustní analýza spolehlivosti×
OborPsychometrikaPlánování experimentů
RodinaLatent structureProcess / pipeline
Rok vzniku1980s–2000s1980s–1990s (integration formalized in engineering literature)
TvůrceRobust methods tradition (Huber, Hampel, Tukey); applied to item analysis by Wilcox and colleaguesSynthesized from Taguchi robust design and classical reliability theory (Kececioglu, Taguchi)
TypDiagnostic / item-level evaluationQuantitative reliability engineering method
Původní zdrojWilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838Kececioglu, D. (1991). Reliability Engineering Handbook (Vol. 1). Prentice Hall. ISBN: 978-0137720774
Další názvyrobust item statistics, outlier-resistant item analysis, robust classical item analysisRRA, reliability robustness analysis, uncertainty-aware reliability analysis, robust probabilistic reliability
Příbuzné54
ShrnutíRobust 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.
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ScholarGatePorovnat metody: Robust Item Analysis · Robust Reliability Analysis. Získáno 2026-06-15 z https://scholargate.app/cs/compare