USE OF THE LOGIT SCALING APPROACH TO TEST FOR RANK-ORDER AND FATIGUE EFFECTS IN STATED PREFERENCE DATA

被引:142
作者
BRADLEY, M
DALY, A
机构
[1] Hague Consulting Group, GJ Den Haag, 2585
关键词
DISCRETE CHOICE ANALYSIS; LOGIT ANALYSIS; MODELING; RANKED DATA; STATED PREFERENCE; SURVEY DESIGN;
D O I
10.1007/BF01098791
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The scaling approach is a statistical estimation method which allows for differences in the amount of unexplained variation in different types of data which can then be used together in analysis. In recent years, this approach has been tested and recommended in the context of combining Stated Preference and Revealed Preference data. The paper provides a description of the approach and a historical overview. The scaling approach can also be used to identify systematic differences in the variance of choices within a single Stated Preference data set due to the way in which the hypothetical choice situations are presented or the responses are obtained. The paper presents the results of two case studies - one looking at rank order effect and the other at fatigue effect. Scale effects appear to exist in both cases: the amount of unexplained variance is shown to increase as rankings become lower, and as the number of pairwise choices completed becomes greater. The implications of these findings for the use of SP ranking tasks and repeated pairwise choice tasks are discussed.
引用
收藏
页码:167 / 184
页数:18
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