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The order-restricted association model: two estimation algorithms and issues in testing. (English) Zbl 1306.62414

Summary: This paper presents a row-column (RC) association model in which the estimated row and column scores are forced to be in agreement with an a priori specified ordering. Two efficient algorithms for finding the order-restricted maximum likelihood (ML) estimates are proposed and their reliability under different degrees of association is investigated by a simulation study. We propose testing order-restricted RC models using a parametric bootstrap procedure, which turns out to yield reliable \(p\) values, except for situations in which the association between the two variables is very weak. The use of order-restricted RC models is illustrated by means of an empirical example.

MSC:

62P15 Applications of statistics to psychology
62F40 Bootstrap, jackknife and other resampling methods

Software:

AS 253; bootstrap; CML
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References:

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