Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise Robusta de Itens× | Differential Item Functioning× | |
|---|---|---|
| Área | Psicometria | Psicometria |
| Família | Latent structure | Latent structure |
| Ano de origem≠ | 1980s–2000s | 1970s–1993 |
| Autor original≠ | Robust methods tradition (Huber, Hampel, Tukey); applied to item analysis by Wilcox and colleagues | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Tipo≠ | Diagnostic / item-level evaluation | Item-level bias detection |
| Fonte seminal≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Outros nomes≠ | robust item statistics, outlier-resistant item analysis, robust classical item analysis | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Relacionados | 5 | 5 |
| Resumo≠ | 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. | Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development. |
| ScholarGateConjunto de dados ↗ |
|
|