difNLR: DIF and DDF Detection by Non-Linear Regression Models, Version 1.4.1
Result description
The difNLR package v 1.3.0 contains Differential Item Functioning (DIF) detection method based on non-linear regression for binary items. Both uniform and non-uniform DIF effects can be detected when considering one focal group. Package also includes models for DIF detection among ordinal items and for detection of Differential Distractor Functioning (DDF) among nominal items. Available under GPL-3 licence.
Keywords
differential item functioningdifferential distractor functioningitem analysisnon-linear regressionlogistic regression
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
difNLR: DIF and DDF Detection by Non-Linear Regression Models, Version 1.4.1
Original language description
The difNLR package v 1.3.0 contains Differential Item Functioning (DIF) detection method based on non-linear regression for binary items. Both uniform and non-uniform DIF effects can be detected when considering one focal group. Package also includes models for DIF detection among ordinal items and for detection of Differential Distractor Functioning (DDF) among nominal items. Available under GPL-3 licence.
Czech name
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Czech description
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Classification
Type
R - Software
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
GA21-03658S: Theoretical foundations of computational psychometrics
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Internal product ID
difNLR - Version 1.4.1
Technical parameters
R software package
Economical parameters
Umožňuje zadavatelům znalostních a psychologických testů provádět analýzu férovosti testů a jejich binárních, ordinálních a nominálních položek. Obsahuje nové metody založené na zobecnění logistické regresi. Nová verze nabízí predikci, různé parametrizace a vylepšenou grafickou reprezentaci výsledků.
Owner IČO
67985807
Owner name
Ústav informatiky AV ČR, v. v. i.
Basic information
Result type
R - Software
OECD FORD
Statistics and probability
Year of implementation
2022