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相同测试，更高分数：运用嵌套逻辑斯蒂克项目反应理论模型提高在线简短智力招募测试的可靠性。

Same Test, Better Scores: Boosting the Reliability of Short Online Intelligence Recruitment Tests with Nested Logit Item Response Theory Models.

作者信息

Storme Martin, Myszkowski Nils, Baron Simon, Bernard David

机构信息

IESEG School of Management, 59800 Lille, France.

LEM-CNRS 9221, 59800 Lille, France.

出版信息

J Intell. 2019 Jul 10;7(3):17. doi: 10.3390/jintelligence7030017.

DOI:10.3390/jintelligence7030017
PMID:31295911
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6789760/
Abstract

Assessing job applicants' general mental ability online poses psychometric challenges due to the necessity of having brief but accurate tests. Recent research (Myszkowski & Storme, 2018) suggests that recovering distractor information through Nested Logit Models (NLM; Suh & Bolt, 2010) increases the reliability of ability estimates in reasoning matrix-type tests. In the present research, we extended this result to a different context (online intelligence testing for recruitment) and in a larger sample ( N = 2949 job applicants). We found that the NLMs outperformed the Nominal Response Model (Bock, 1970) and provided significant reliability gains compared with their binary logistic counterparts. In line with previous research, the gain in reliability was especially obtained at low ability levels. Implications and practical recommendations are discussed.

摘要

由于需要简短而准确的测试，在线评估求职者的一般心理能力存在心理测量学上的挑战。最近的研究（Myszkowski & Storme，2018）表明，通过嵌套逻辑模型（NLM；Suh & Bolt，2010）恢复干扰项信息可以提高推理矩阵类型测试中能力估计的可靠性。在本研究中，我们将这一结果扩展到了不同的情境（招聘在线智力测试）和更大的样本（N = 2949名求职者）。我们发现，嵌套逻辑模型优于名义反应模型（Bock，1970），并且与二元逻辑模型相比，在可靠性方面有显著提高。与先前的研究一致，可靠性的提高尤其在低能力水平上获得。本文讨论了研究结果的意义和实际建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2f7/6789760/19cb9f172784/jintelligence-07-00017-g010.jpg
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本文引用的文献

1
Making sense of Cronbach's alpha.理解克朗巴哈系数。
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2
The Alleged Crisis and the Illusion of Exact Replication.所谓的危机与精确复制的幻象。
Perspect Psychol Sci. 2014 Jan;9(1):59-71. doi: 10.1177/1745691613514450.
3
Role of test motivation in intelligence testing.测试动机在智力测验中的作用。
J Intell. 2020 Nov 19;8(4):39. doi: 10.3390/jintelligence8040039.
4
Regularized Latent Class Analysis for Polytomous Item Responses: An Application to SPM-LS Data.多分类项目反应的正则化潜在类别分析：在SPM-LS数据中的应用
J Intell. 2020 Aug 14;8(3):30. doi: 10.3390/jintelligence8030030.
5
A Mokken Scale Analysis of the Last Series of the Standard Progressive Matrices (SPM-LS).标准渐进矩阵最后系列（SPM-LS）的莫肯量表分析。
J Intell. 2020 May 6;8(2):22. doi: 10.3390/jintelligence8020022.
6
How Much Is in the Distractor? Re-Thinking Item-Analysis of Multiple-Choice Items.干扰项中有多少内容？重新思考多项选择题的项目分析。
J Intell. 2020 Mar 9;8(1):11. doi: 10.3390/jintelligence8010011.
Proc Natl Acad Sci U S A. 2011 May 10;108(19):7716-20. doi: 10.1073/pnas.1018601108. Epub 2011 Apr 25.
4
Choking under pressure and working memory capacity: when performance pressure reduces fluid intelligence.压力下的窒息感与工作记忆容量：当表现压力降低流体智力时。
Psychon Bull Rev. 2006 Dec;13(6):1005-10. doi: 10.3758/bf03213916.
5
Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement.将项目反应理论（IRT）模型应用于问卷的开发、评估和完善。
Qual Life Res. 2007;16 Suppl 1:5-18. doi: 10.1007/s11136-007-9198-0. Epub 2007 Mar 21.
6
When high-powered people fail: working memory and "choking under pressure" in math.当位高权重者失败时：工作记忆与数学领域的“压力下发挥失常”
Psychol Sci. 2005 Feb;16(2):101-5. doi: 10.1111/j.0956-7976.2005.00789.x.
7
General mental ability in the world of work: occupational attainment and job performance.职场中的一般智力：职业成就与工作表现。
J Pers Soc Psychol. 2004 Jan;86(1):162-73. doi: 10.1037/0022-3514.86.1.162.