Pooling Data Across Transparently Different Groups of Key Informants: Measurement Equivalence and Survey Research

M. Rungtusanatham; C. H. Ng; X. Zhao; T. S. Lee

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Pooling Data Across Transparently Different Groups of Key Informants: Measurement Equivalence and Survey Research

机译：跨不同关键信息组透明地汇总数据：测量当量和调查研究

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we prescribe and demonstrate, with the total quality management? customer satisfaction relationship, the procedural steps for evaluating the seven subdimensions of measurement equivalence. In conclusion, we highlight methods that should be adopted, before data collection, to minimize the risk of violating measurement equivalence. After data collection and for the instances when the empirical assessment for measurement equivalence advises against pooling of such data, we also offer suggestions for analyzing such data and presenting associated statistical results.

机译：我们规定和演示全面的质量管理？客户满意度关系，评估测量等效性的七个子类别的程序步骤。总之，我们重点介绍了在数据收集之前应采用的方法，以最大程度地减少违反测量等效性的风险。在收集数据之后，以及对于当量的经验评估建议不要合并此类数据的情况下，我们还提供了分析此类数据并提供相关统计结果的建议。

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来源
《Decision Sciences》 |2008年第1期|p.115-145|共31页
作者
M. Rungtusanatham; C. H. Ng; X. Zhao; T. S. Lee;
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作者单位

Operations and Management Science Department, Carlson School of Management, University of Minnesota-Twin Cities, 321 19th Avenue South, Minneapolis, MN 55455;

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原文格式 PDF
正文语种 eng
中图分类决策学;
关键词
data pooling; measurement equivalence; survey research; and total quality management;

机译：数据池;测量当量;调查研究;全面质量管理;

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Pooling Data Across Transparently Different Groups of Key Informants: Measurement Equivalence and Survey Research

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