Results 281 to 290 of about 5,782,543 (332)

Ordinal Outcome Variables

2019
A commonly undervalued and mistreated type of outcome variable is the ordinal one. Two common types of mistreatment are treating ordinal variables as interval/ratio level outcome variables (frequently in linear models) and, in other cases, as multicategory nominal outcome variables. Multicategory nominal outcome variables are covered in Chap.
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Multivariate Analysis of Ordinal Variables

American Journal of Sociology, 1975
This article examines the assumptions underlying two multivariate strategies commonly used in analyzing ordinal data. Both strategies employ as a descriptive tool the ordinary multiple regression algorithms; the crucial difference between the two is that the first, ordinal strategy, uses the matrix of Kendall's 's as the building block of multivariate ...
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Ordinal Variables in Microeconometric Models

1993
Microeconometric models have become an important tool of econometric analysis since micro data were made available and computer programs gave the necessary computing assistance. In particular probit, Tobit, and duration models have been successfully applied to problems in many fields of economic research.1As in linear regression models the distribution
Martin Kukuk, Gerd Ronning
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Statistical Models for Ordinal Variables.

Contemporary Sociology, 1995
Mark von Tress, Clifford C. Clogg, Edward S. Shihadeh   +2 more
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On the Nonlinearity of Homogeneous Ordinal Variables

2011
The paper aims at evaluating the nonlinearity existing in homogeneous ordinal data with a one-dimensional latent variable, using Linear and NonLinear Principal Components Analysis. The results of a simulation study with Probabilistic and Monte Carlo gauges show that, when variables are linearly related, a source of nonlinearity can affect each single ...
CARPITA, Maurizio, MANISERA, Marica
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HierarchicalCUBModels for Ordinal Variables

Communications in Statistics - Theory and Methods, 2012
Hierarchical CUB models are a generalization of CUB models in which parameters are allowed to be random. The main feature that distinguishes such proposal from the standard one is the modeling of variation among groups. We illustrate the usefulness of these hierarchical structures by discussing model specification, inferential issues, and empirical ...
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Extending the approaches to polarization ordering of ordinal variables

Journal of Economic Inequality, 2020
S. Sarkar, Sattwik Santra
semanticscholar   +1 more source

Mediation Analysis for Ordinal Outcome Variables

2015
This study compared four methods with respect to three factors, namely sample size, size of mediating effects, and the number of categories of the outcome variable, as based on the work of MacKinnon, to analyze the mediation effects for ordinal outcome variables.
Hongyun Liu, Yunyun Zhang, Fang Luo
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Comparing classifiers for ordinal variables

2020
To choose a single category of a qualitative variable using its predicted probability distribution is the final task to solve a classification problem. In this study, five predictive criteria are proposed and compared with the modal one, which is the standard criterion.
Silvia Golia, Maurizio Carpita
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Bipolar mean for ordinal variables

2005
This paper proposes, for ordinal variables, a new type of mean called bipolar mean, that is a frequency distribution with the total size n concentrated on one category or on two consecutive categories. The bipolar mean is coherent with the usual statistics dominance that is based on the retro-cumulative frequencies.
MAFFENINI, WALTER, ZENGA, MICHELE
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