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用于特定学习障碍识别的认知差异模型:心理测量局限性的模拟

Cognitive discrepancy models for specific learning disabilities identification: Simulations of psychometric limitations.

作者信息

Taylor W Pat, Miciak Jeremy, Fletcher Jack M, Francis David J

机构信息

Texas Institute for Measurement, Evaluation, and Statistics.

出版信息

Psychol Assess. 2017 Apr;29(4):446-457. doi: 10.1037/pas0000356. Epub 2016 Aug 8.

Abstract

Few studies have investigated specific learning disabilities (SLD) identification methods based on the identification of patterns of processing strengths and weaknesses (PSW). We investigated the reliability of SLD identification decisions emanating from different achievement test batteries for 1 method to operationalize the PSW approach: the concordance/discordance model (C/DM; Hale & Fiorello, 2004). Two studies examined the level of agreement for SLD identification decisions between 2 different simulated, highly correlated achievement test batteries. Study 1 simulated achievement and cognitive data across a wide range of potential latent correlations between an achievement deficit, a cognitive strength and a cognitive weakness. Latent correlations permitted simulation of case-level data at specified reliabilities for cognitive abilities and 2 achievement observations. C/DM criteria were applied and resulting SLD classifications from the 2 achievement test batteries were compared for agreement. Overall agreement and negative agreement were high, but positive agreement was low (0.33-0.59) across all conditions. Study 2 isolated the effects of reduced test reliability on agreement for SLD identification decisions resulting from different test batteries. Reductions in reliability of the 2 achievement tests resulted in average decreases in positive agreement of 0.13. Conversely, reductions in reliability of cognitive measures resulted in small average increases in positive agreement (0.0-0.06). Findings from both studies are consistent with prior research demonstrating the inherent instability of classifications based on C/DM criteria. Within complex ipsative SLD identification models like the C/DM, small variations in test selection can have deleterious effects on classification reliability. (PsycINFO Database Record

摘要

很少有研究基于处理优势和劣势模式(PSW)的识别来探究特定学习障碍(SLD)的识别方法。我们研究了1种将PSW方法操作化的方法(即一致性/不一致性模型,C/DM;Hale & Fiorello,2004)从不同成就测试组合得出的SLD识别决策的可靠性。两项研究考察了2种不同的模拟且高度相关的成就测试组合在SLD识别决策上的一致程度。研究1模拟了成就缺陷、认知优势和认知劣势之间各种潜在的潜在相关性的成就和认知数据。潜在相关性允许在指定的认知能力和2个成就观察的可靠性水平上模拟案例水平的数据。应用C/DM标准,并比较2种成就测试组合得出的SLD分类的一致性。在所有条件下,总体一致性和负一致性都很高,但正一致性较低(0.33 - 0.59)。研究2分离了测试可靠性降低对不同测试组合得出的SLD识别决策一致性的影响。2种成就测试的可靠性降低导致正一致性平均下降0.13。相反,认知测量的可靠性降低导致正一致性平均略有增加(0.0 - 0.06)。两项研究的结果都与先前的研究一致,这些研究表明基于C/DM标准的分类具有内在的不稳定性。在像C/DM这样复杂的个体内差异SLD识别模型中,测试选择的微小差异可能对分类可靠性产生有害影响。(《心理学文摘数据库记录》

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