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Ordered logit analysis for selectively sampled data

Authors: Fok, D.; Franses, Ph.H.B.F.; Cramer, J.S.;

Ordered logit analysis for selectively sampled data

Abstract

When customers are classified into ordered categories, which are defined from the outset, it may happen that the majority belongs to a single category. If a market researcher is interested in the correlation between the classification and individual characteristics, the natural question is whether one needs to collect data for all customers in that particular category. We address this question for the ordered logit model. We show that there is no need to consider all those customers. All that is required is a simple modification of the log-likelihood, which is based on Bayes' rule. We illustrate our proposed method on simulated data and on data concerning risk profiles of customers of an investment bank.

Keywords

Bayes' rule, ordered logit model, selective sampling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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