If the response of an individual or item in a study is restricted to one of a fixed set of possible values, we say that the response is polytomous.
Examples of polytomous data include blood type (A, B, AB, O,…), food testing, measures of mental and physical well-being, variables arising in social science research.
Based on these investigations it will be established that simply some models of a class of models for polytomous variables can be distinct as stochastic dimension models.
In summary, the two main aims of this paper are (1) to describe models for polytomous variables as stochastic dimension models and to examine the depiction, uniqueness, and meaningfulness trouble in this division of models; (2) to show how stochastic measurement theory can direct the collection of a model for polytomous variables. Therefore, the class of models developed by Marsh and Grayson is described in the next section and is transferred to an analogous class of models for polytomous response variables. Then, the probabilistic foundations of models for polytomous variables are explained. After that, models for polytomous variables are defined as stochastic measurement models and the representation, distinctiveness, and meaningfulness problems are examined. Furthermore, the meaning of different models will be explained on the basis of the measurement theoretical investigations and a small empirical example. Finally, the consequences of these investigations will be discussed.
Hence, this concludes the definition of Polytomous Variable along with its overview.
This article has been researched & authored by the Business Concepts Team. It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.
Browse the definition and meaning of more similar terms. The Management Dictionary covers over 1800 business concepts from 5 categories.