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Assessing dissimilarity relations under missing data conditions: Evidence from computer simulations.

2007· article· en· 2,007 citations· W2029374995 on OpenAlex· 10.1037/0021-9010.92.5.1414

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Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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Opus teacher head0.429
GPT teacher head0.496
Teacher spread
0.066 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

The extensive research examining relations between group member dissimilarity and outcome measures has yielded inconsistent results. In the present research, the authors used computer simulations to examine the impact that a methodological feature of such research, participant nonresponse, can have on dissimilarity-outcome relations. Results suggest that using only survey responders to calculate dissimilarity typically results in underestimation of true dissimilarity effects and that these effects can occur even when response rates are high.

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The record

Venue
Journal of Applied Psychology
Topic
Gender Diversity and Inequality
Field
Social Sciences
Canadian institutions
University of GuelphWestern University
Funders
Social Sciences and Humanities Research Council of Canada
Keywords
PsychologyOutcome (game theory)Missing dataSocial psychologyStatisticsEconometricsMathematics
Has abstract in OpenAlex
yes