著者
豊田 秀樹 川端 一光 中村 健太郎 片平 秀貴
出版者
日本行動計量学会
雑誌
行動計量学 (ISSN:03855481)
巻号頁・発行日
vol.34, no.1, pp.101-110, 2007 (Released:2007-05-30)
参考文献数
15
被引用文献数
1 1 1

This study proposes the adoption of a neural network as an alternative to logistic regression analysis, which is conventionally used to estimate the propensity score (Rosenbaum & Rubin, 1983). Moreover, covariates that are frequently obscured are presented.Considering the response pattern to a mail survey by random sampling as a criterion, we examined how is the response pattern to a Web survey by purposive selection rectified using the propensity score. The propensity score was estimated using the subjects' demographic variables as covariates.The results of adopting a neural network were compared with those of the logistic regression analysis. As a result, the accuracy of bias reduction by the threelayer neural networks was found to be greater than that by the logistic regression analysis.In addition, detailed contents of the covariates were presented, and a decision tree was produced to examine the influence of covariates on allocation of the subjects to survey forms.
著者
豊田 秀樹 福中 公輔 川端 一光 片平 秀貴
出版者
日本行動計量学会
雑誌
行動計量学 (ISSN:03855481)
巻号頁・発行日
vol.35, no.1, pp.91-101, 2008 (Released:2009-04-07)
参考文献数
13
被引用文献数
1

In this study, a secondary factor analysis of multiple populations with a structured mean was applied to the independent, and mean values were decomposed into common and unique components. In this manner, a method for discovering the most effective model was proposed. In order to ensure the practical effectiveness of this method, the data of Brand Japan from 2004 to 2006 was analyzed. This data was composed of 1,000 brands and 15 variables. As a result, some models fitted to the data well in all variations of models, and the best model could be decided by interpreting meanings. This model was applied to the brand data, and factor scores were calculated for every construct. Characteristics of every brand were discovered by observing its movement.