|
|
|
|
LEADER |
01000caa a22002652 4500 |
001 |
JST047115955 |
003 |
DE-627 |
005 |
20240621131851.0 |
007 |
cr uuu---uuuuu |
008 |
150324s2005 xx |||||o 00| ||eng c |
035 |
|
|
|a (DE-627)JST047115955
|
035 |
|
|
|a (JST)3701298
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Van den Noortgate, Wim
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Assessing and Explaining Differential Item Functioning Using Logistic Mixed Models
|
264 |
|
1 |
|c 2005
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a Computermedien
|b c
|2 rdamedia
|
338 |
|
|
|a Online-Ressource
|b cr
|2 rdacarrier
|
520 |
|
|
|a Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model uniform DIF, treating the item effects and their interaction with groups (DIF) as random. In a similar way, the group effects can be modeled as random instead of fixed, if the groups can be considered a random sample from a population of groups. The models can, furthermore, be adapted easily for modeling DIF over individual persons rather than over groups, or for modeling the differential functioning of groups of items instead of individual items. It is shown that the logistic mixed model approach is not only a comprehensive and economical way to detect these different kinds of DIF, it also encourages us to explore possible explanations of DIF by including group or item covariates in the model.
|
540 |
|
|
|a Copyright 2005 American Educational Research Association and the American Statistical Association
|
650 |
|
4 |
|a Differential Item Functioning
|
650 |
|
4 |
|a Item Bias
|
650 |
|
4 |
|a Item Response Theory
|
650 |
|
4 |
|a Logistic Mixed Models
|
650 |
|
4 |
|a Random Effects
|
650 |
|
4 |
|a Business
|x Business economics
|x Commercial production
|x Production resources
|x Resource management
|x Logistics
|
650 |
|
4 |
|a Information science
|x Information analysis
|x Data analysis
|x Regression analysis
|x Multilevel models
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Measures of variability
|x Statistical variance
|
650 |
|
4 |
|a Education
|x Formal education
|x Pedagogy
|x Educational methods
|x Educational testing
|x Test bias
|
650 |
|
4 |
|a Applied sciences
|x Research methods
|x Modeling
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Analytics
|x Analytical estimating
|x Maximum likelihood estimation
|
650 |
|
4 |
|a Mathematics
|x Mathematical values
|x Mathematical variables
|x Mathematical independent variables
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical results
|x Errors in statistics
|x Standard error
|
650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Algebra
|x Coefficients
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical distributions
|x Distribution functions
|x Probability distributions
|x Gaussian distributions
|x Teacher's Corner
|
655 |
|
4 |
|a research-article
|
700 |
1 |
|
|a De Boeck, Paul
|e verfasserin
|4 aut
|
773 |
0 |
8 |
|i Enthalten in
|t Journal of Educational and Behavioral Statistics
|d SAGE Publishing, 1976
|g 30(2005), 4, Seite 443-464
|w (DE-627)477533302
|w (DE-600)2174169-4
|x 19351054
|7 nnns
|
773 |
1 |
8 |
|g volume:30
|g year:2005
|g number:4
|g pages:443-464
|
856 |
4 |
0 |
|u https://www.jstor.org/stable/3701298
|3 Volltext
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_JST
|
912 |
|
|
|a GBV_ILN_11
|
912 |
|
|
|a GBV_ILN_20
|
912 |
|
|
|a GBV_ILN_22
|
912 |
|
|
|a GBV_ILN_23
|
912 |
|
|
|a GBV_ILN_24
|
912 |
|
|
|a GBV_ILN_26
|
912 |
|
|
|a GBV_ILN_31
|
912 |
|
|
|a GBV_ILN_32
|
912 |
|
|
|a GBV_ILN_39
|
912 |
|
|
|a GBV_ILN_40
|
912 |
|
|
|a GBV_ILN_60
|
912 |
|
|
|a GBV_ILN_62
|
912 |
|
|
|a GBV_ILN_63
|
912 |
|
|
|a GBV_ILN_65
|
912 |
|
|
|a GBV_ILN_69
|
912 |
|
|
|a GBV_ILN_70
|
912 |
|
|
|a GBV_ILN_73
|
912 |
|
|
|a GBV_ILN_74
|
912 |
|
|
|a GBV_ILN_90
|
912 |
|
|
|a GBV_ILN_95
|
912 |
|
|
|a GBV_ILN_100
|
912 |
|
|
|a GBV_ILN_101
|
912 |
|
|
|a GBV_ILN_105
|
912 |
|
|
|a GBV_ILN_110
|
912 |
|
|
|a GBV_ILN_120
|
912 |
|
|
|a GBV_ILN_121
|
912 |
|
|
|a GBV_ILN_138
|
912 |
|
|
|a GBV_ILN_150
|
912 |
|
|
|a GBV_ILN_151
|
912 |
|
|
|a GBV_ILN_152
|
912 |
|
|
|a GBV_ILN_161
|
912 |
|
|
|a GBV_ILN_165
|
912 |
|
|
|a GBV_ILN_171
|
912 |
|
|
|a GBV_ILN_187
|
912 |
|
|
|a GBV_ILN_206
|
912 |
|
|
|a GBV_ILN_213
|
912 |
|
|
|a GBV_ILN_224
|
912 |
|
|
|a GBV_ILN_230
|
912 |
|
|
|a GBV_ILN_250
|
912 |
|
|
|a GBV_ILN_281
|
912 |
|
|
|a GBV_ILN_285
|
912 |
|
|
|a GBV_ILN_293
|
912 |
|
|
|a GBV_ILN_370
|
912 |
|
|
|a GBV_ILN_374
|
912 |
|
|
|a GBV_ILN_602
|
912 |
|
|
|a GBV_ILN_636
|
912 |
|
|
|a GBV_ILN_647
|
912 |
|
|
|a GBV_ILN_702
|
912 |
|
|
|a GBV_ILN_2001
|
912 |
|
|
|a GBV_ILN_2003
|
912 |
|
|
|a GBV_ILN_2005
|
912 |
|
|
|a GBV_ILN_2006
|
912 |
|
|
|a GBV_ILN_2007
|
912 |
|
|
|a GBV_ILN_2008
|
912 |
|
|
|a GBV_ILN_2009
|
912 |
|
|
|a GBV_ILN_2010
|
912 |
|
|
|a GBV_ILN_2011
|
912 |
|
|
|a GBV_ILN_2014
|
912 |
|
|
|a GBV_ILN_2015
|
912 |
|
|
|a GBV_ILN_2018
|
912 |
|
|
|a GBV_ILN_2020
|
912 |
|
|
|a GBV_ILN_2021
|
912 |
|
|
|a GBV_ILN_2025
|
912 |
|
|
|a GBV_ILN_2026
|
912 |
|
|
|a GBV_ILN_2027
|
912 |
|
|
|a GBV_ILN_2031
|
912 |
|
|
|a GBV_ILN_2034
|
912 |
|
|
|a GBV_ILN_2036
|
912 |
|
|
|a GBV_ILN_2037
|
912 |
|
|
|a GBV_ILN_2038
|
912 |
|
|
|a GBV_ILN_2039
|
912 |
|
|
|a GBV_ILN_2043
|
912 |
|
|
|a GBV_ILN_2044
|
912 |
|
|
|a GBV_ILN_2048
|
912 |
|
|
|a GBV_ILN_2049
|
912 |
|
|
|a GBV_ILN_2050
|
912 |
|
|
|a GBV_ILN_2055
|
912 |
|
|
|a GBV_ILN_2056
|
912 |
|
|
|a GBV_ILN_2057
|
912 |
|
|
|a GBV_ILN_2059
|
912 |
|
|
|a GBV_ILN_2061
|
912 |
|
|
|a GBV_ILN_2064
|
912 |
|
|
|a GBV_ILN_2065
|
912 |
|
|
|a GBV_ILN_2068
|
912 |
|
|
|a GBV_ILN_2070
|
912 |
|
|
|a GBV_ILN_2086
|
912 |
|
|
|a GBV_ILN_2088
|
912 |
|
|
|a GBV_ILN_2093
|
912 |
|
|
|a GBV_ILN_2098
|
912 |
|
|
|a GBV_ILN_2106
|
912 |
|
|
|a GBV_ILN_2107
|
912 |
|
|
|a GBV_ILN_2108
|
912 |
|
|
|a GBV_ILN_2110
|
912 |
|
|
|a GBV_ILN_2111
|
912 |
|
|
|a GBV_ILN_2112
|
912 |
|
|
|a GBV_ILN_2113
|
912 |
|
|
|a GBV_ILN_2116
|
912 |
|
|
|a GBV_ILN_2118
|
912 |
|
|
|a GBV_ILN_2119
|
912 |
|
|
|a GBV_ILN_2122
|
912 |
|
|
|a GBV_ILN_2125
|
912 |
|
|
|a GBV_ILN_2129
|
912 |
|
|
|a GBV_ILN_2143
|
912 |
|
|
|a GBV_ILN_2144
|
912 |
|
|
|a GBV_ILN_2145
|
912 |
|
|
|a GBV_ILN_2147
|
912 |
|
|
|a GBV_ILN_2148
|
912 |
|
|
|a GBV_ILN_2152
|
912 |
|
|
|a GBV_ILN_2153
|
912 |
|
|
|a GBV_ILN_2158
|
912 |
|
|
|a GBV_ILN_2190
|
912 |
|
|
|a GBV_ILN_2193
|
912 |
|
|
|a GBV_ILN_2232
|
912 |
|
|
|a GBV_ILN_2336
|
912 |
|
|
|a GBV_ILN_2446
|
912 |
|
|
|a GBV_ILN_2470
|
912 |
|
|
|a GBV_ILN_2507
|
912 |
|
|
|a GBV_ILN_2522
|
912 |
|
|
|a GBV_ILN_2548
|
912 |
|
|
|a GBV_ILN_2705
|
912 |
|
|
|a GBV_ILN_2889
|
912 |
|
|
|a GBV_ILN_2890
|
912 |
|
|
|a GBV_ILN_2935
|
912 |
|
|
|a GBV_ILN_2947
|
912 |
|
|
|a GBV_ILN_2949
|
912 |
|
|
|a GBV_ILN_2950
|
912 |
|
|
|a GBV_ILN_4012
|
912 |
|
|
|a GBV_ILN_4035
|
912 |
|
|
|a GBV_ILN_4037
|
912 |
|
|
|a GBV_ILN_4046
|
912 |
|
|
|a GBV_ILN_4112
|
912 |
|
|
|a GBV_ILN_4125
|
912 |
|
|
|a GBV_ILN_4126
|
912 |
|
|
|a GBV_ILN_4242
|
912 |
|
|
|a GBV_ILN_4246
|
912 |
|
|
|a GBV_ILN_4249
|
912 |
|
|
|a GBV_ILN_4251
|
912 |
|
|
|a GBV_ILN_4277
|
912 |
|
|
|a GBV_ILN_4305
|
912 |
|
|
|a GBV_ILN_4306
|
912 |
|
|
|a GBV_ILN_4307
|
912 |
|
|
|a GBV_ILN_4313
|
912 |
|
|
|a GBV_ILN_4322
|
912 |
|
|
|a GBV_ILN_4323
|
912 |
|
|
|a GBV_ILN_4324
|
912 |
|
|
|a GBV_ILN_4325
|
912 |
|
|
|a GBV_ILN_4326
|
912 |
|
|
|a GBV_ILN_4328
|
912 |
|
|
|a GBV_ILN_4333
|
912 |
|
|
|a GBV_ILN_4335
|
912 |
|
|
|a GBV_ILN_4338
|
912 |
|
|
|a GBV_ILN_4346
|
912 |
|
|
|a GBV_ILN_4367
|
912 |
|
|
|a GBV_ILN_4393
|
912 |
|
|
|a GBV_ILN_4700
|
912 |
|
|
|a GBV_ILN_4753
|
951 |
|
|
|a AR
|
952 |
|
|
|d 30
|j 2005
|e 4
|h 443-464
|