International Review of Industrial and Organizational Psychology

More documents

Recommendations

Info

220 INTERNATIONAL REVIEW OF INDUSTRIAL AND ORGANIZATIONAL PSYCHOLOGY 2003(Cattell & Cattell, 1960–1961), also failed to reduce group differences. In the1980s effective statistical methods for identifying individual items in teststhat might be more difficult for a particular group were developed (Dorans &Kulick, 1986; Holland & Wainer, 1993). This is generally referred to asdifferential item functioning or DIF.DIF findings are often difficult to interpret, because of the many comparisonsrequired for a single test. Type-1 errors can be a major problem unlesssignificance levels are increased to such an extent that only the very largesteffect sizes can be identified. Generally studies have found a small number ofDIF items in tests of cognitive ability. These items do not always favour thehigher scoring group, and removing them has only a small impact on overallgroup differences. However, the use of DIF techniques, together withfocused reviewing for fairness, has become a standard part of test developmentprocesses. While this may have had only a minor impact on groupdifferences, it has certainly led to more acceptable content in modern testscompared with those developed in the past.Positive DIF findings are often difficult to explain, but have sometimesbeen related to familiarity with item content and the verbal complexity of theitems. However, beyond the influence of having the test language as one’sprimary language, there is little information about how cultural differencesaffect test performance (Sackett et al., 2001). Scheunemann and Gerritz(1990) studied verbal items from the SAT and GRE. They found mixedeffects across the two tests, but there was a trend for Blacks to find itemswith science-based content more difficult than Whites. Freedle and Kostin(1997) showed that Black examinees were more likely to answer difficultverbal items on the GRE and the SAT correctly when compared withequally able White examinees, but the Black examinees were less likely toget the easy items right. Freedle and Kostin (1997) suggested that this mightbe because the easier items possessed multiple meanings more familiar toWhite examinees, whose culture was more dominant in the test items andthe educational system. The use of homographs (words that have more thanone meaning for the same spelling) in tests has also been cited as a feature,although when non-native English-speakers were removed from the analyses,few DIF items remained, suggesting that the differences were due tolanguage problems (Schmitt & Dorans, 1990).Mains-Smith and Abram (2000) looked at DIF on the UK Navy tests butfound no consistent explanation for items flagged. Removing flagged itemshad a negligible impact on test score differences.Recently Raju and colleagues have developed a new technique (DFIT) forcomparing differential functioning both at the item and the test level (Jones& Raju, 2000; Oshma, Raju, & Flowers, 1997; Raju, van der Linden, & Fleer,1995). This combined IRT-based approach identifies differences in scores atdifferent ability levels when the test is standardized using the majority andminority data, having first removed potential DIF items. As the procedure
ETHNIC GROUP DIFFERENCES AND MEASURING COGNITIVE ABILITY 221looks at differences by score it is possible to focus on those differences aroundthe cut-off score being used in a selection process, rather than average differences.Thus items that impact differences most in this score range can beremoved.Construct equivalenceOne interpretation of positive DIF findings would be that those items weremeasuring different constructs for the groups compared. If enough items areimplicated, the test itself might be seen as measuring a different construct.This is part of the Cleary definition of fairness; that is, tests should bemeasuring the same thing for every group (Cleary, 1966). Consideration ofequivalence of constructs is part of the work of a test-developer and is rarelypublished in the peer-reviewed literature. Wing (1980) reports similar reliabilitiesfor all groups for a battery of cognitive ability tests.Schmitt and Mills (2001) examined the intercorrelations of two series ofmeasures for majority and minority job-applicants. Structural equationmodelling showed that while the structure of the measures from a simulationwere similar for the two groups, scores from a set of more traditional paperand-penciltests showed greater variance for the Black group compared withthe White group. Hattrup, Schmitt, and Landis (1992) looked at the factorstructure of a series of six tests among applicants for entry-level manufacturingposts for different subgroups. Structural equation modelling revealedthat the same models showed best fit in all subgroups, but in general fit wasbetter for White groups than for Black or Hispanic applicants. te Nijenhuisand van der Flier (1997) found similar structures for the Dutch GATB testsfor the majority and minority groups.UK data from test publishers suggests similar test reliabilities for ethnicminority and White groups. However, where differences do occur they tendto indicate lower reliability for ethnic minority groups. This is sometimes,but not always, related to lower score variance for these groups (SHL Group,2002).There is no strong evidence that there are differences in construct validityfor tests for different ethnic groups. However, we found no systematicstudies of equivalence in this area.Cultural equivalenceHelms (1992) argues that cognitive ability tests lack cultural equivalence.She suggests they assess White g rather than African or Hispanic g, andtherefore that Whites may be expressing their abilities in the biological orenvironmental styles of their group, whereas Blacks are not. Helms (1992)suggests that score differences may be due to a cultural bias inherent in thetests and lists a large number of hypotheses relating to ways in which
Page 5 and 6:
CONTENTSAbout the EditorsList of Co
Page 7 and 8:
CONTRIBUTORSHelen Baron82 Evershot
Page 9 and 10:
EDITORIAL FOREWORDThe 2003 volume o
Page 11 and 12:
2 INTERNATIONAL REVIEW OF INDUSTRIA
Page 13 and 14:
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
10 INTERNATIONAL REVIEW OF INDUSTRI
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
ä92 INTERNATIONAL REVIEW OF INDUST
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
100 INTERNATIONAL REVIEW OF INDUSTR
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
Page 139 and 140:
Chapter 4RESEARCH ON INTERNETRECRUI
Page 141 and 142:
RESEARCH ON INTERNET RECRUITING AND
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
Page 161 and 162:
Page 163 and 164:
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176: 168 INTERNATIONAL REVIEW OF INDUSTR
Page 197 and 198: Chapter 6ETHNIC GROUP DIFFERENCES A
Page 199 and 200: ETHNIC GROUP DIFFERENCES AND MEASUR
Page 225: ETHNIC GROUP DIFFERENCES AND MEASUR
Page 245 and 246: Chapter 7IMPLICIT KNOWLEDGE ANDEXPE
Page 247 and 248: IMPLICIT KNOWLEDGE AND EXPERIENCE I
Page 263 and 264: ääIMPLICIT KNOWLEDGE AND EXPERIEN
Page 277 and 278:
IMPLICIT KNOWLEDGE AND EXPERIENCE I
Page 279 and 280:
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
Page 287 and 288:
INDEX16PF Questionnaire see Sixteen
Page 289 and 290:
INDEX 283Edelman, L.B. 6editing 43-
Page 291 and 292:
INDEX 285language skills 197-200, 2
Page 293 and 294:
INDEX 287relationships 103-4, 107,
Page 295 and 296:
INDEX 289Wood, S. 15Work Addiction
Page 297 and 298:
292 CONTENTS OF PREVIOUS VOLUMES8.
Page 299 and 300:
294 CONTENTS OF PREVIOUS VOLUMESMas
Page 301 and 302:
296 CONTENTS OF PREVIOUS VOLUMESVOL
show all

International Review of Industrial and Organizational Psychology

Create successful ePaper yourself

Delete template?

Save as template?