Meta-analysis in marketing when studies contain multiple measurements
Meta-analysis in marketing when studies contain multiple measurements
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DOI：
10.1023/a:1011117103381
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发表时间：
2001-05-01
影响因子：
3.6
通讯作者：
Pieters, RGM
中科院分区：
文献类型：
--
作者：
Bijmolt, THA;Pieters, RGM
市场营销中的大多数荟萃分析包含的研究本身包含对焦点效应的多个测量。本文通过对蒙特卡洛研究中的合成数据集的分析和对已发布的营销数据集的重新分析，比较了处理多个测量值的替代程序。我们表明，选择的程序来处理多个测量是决不是微不足道的，它的结果和来自荟萃分析的概括的有效性的影响。使用完整测量集的程序优于以单个值代表每个研究的程序，将所有测量值视为独立的常用方法表现相当好，但不是首选。我们表明，在荟萃分析中考虑多个测量的最佳程序明确涉及嵌套错误结构，即，在测量水平和研究水平，这在营销荟萃分析中还没有实践过。
Most meta-analyses in marketing contain studies which themselves contain multiple measurements of the focal effect. This paper compares alternative procedures to deal with multiple measurements through the analysis of synthetic data sets in a Monte Carlo Study and a re-analysis of a published marketing data set. We show that the choice of procedure to deal with multiple measurements is by no means trivial and that it has implications for the results and for the validity of the generalizations derived from meta-analyses. Procedures that use the complete set of measurements outperform procedures that represent each study by a single value, The commonly used method of treating all measurements as independent performs reasonably well but is not preferable. We show that the optimal procedure to account for multiple measurements in meta-analysis explicitly deals with the nested error structure, i.e., at the measurement level and at the study level, which has not been practiced before in marketing meta-analyses.