Results 251 to 260 of about 470,038 (304)
Some of the next articles are maybe not open access.
Asymmetry for ordinal variables
Statistica & Applicazioni : V, 2, 2007, 2007This paper proposes, for ordinal variables, and index of asymmetry based on the cumulative and retrocumulative frequencies. The paper shows that this new index has a connection with the bipolar mean, recently introduced by Maffenini and Zenga(2006).
openaire +2 more sources
Regression Models with Ordinal Variables
American Sociological Review, 1984Most discussions of ordinal variables in the sociological literature debate the suitability of linear regression and structural equation methods when some variables are ordinal. Largely ignored in these discussions are methods for ordinal variables that are natural extensions of probit and logit models for dichotomous variables.
Christopher Winship, Robert D. Mare
openaire +1 more source
A Latent Variable Model for Ordinal Variables
Applied Psychological Measurement, 2000A full-information maximum likelihood method for fitting a multidimensional latent variable model to a set of ordinal observed variables is discussed. This method is an implementation of a general class of models for ordinal variables, and for regression models with one ordinal dependent variable and all explanatory variables observed.
openaire +1 more source
Multisample Analysis of Multivariate Ordinal Categorical Variables
Multivariate Behavioral Research, 2002We study a multiple group model with ordinal categorical observed variables that are manifestations of underlying normal variables. When the objective of an analysis is to compare the locations and dispersions of the underlying continuous variables in different groups, traditional approaches use exact linear constraints on thresholds across groups to ...
Wai-Yin, Poon, Fung-Chu, Tang
openaire +2 more sources
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.
openaire +1 more source
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.
openaire +1 more source
Multivariate Analysis of Ordinal Variables
American Journal of Sociology, 1975This 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 ...
openaire +1 more source
Ordinal Variables in Microeconometric Models
1993Microeconometric 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
openaire +1 more source
Regression for ordinal variables without underlying continuous variables
Information Sciences, 2006Several techniques exist nowadays for continuous (i.e. numerical) data analysis and modeling. However, although part of the information gathered by companies, statistical offices and other institutions is numerical, a large part of it is represented using categorical variables in ordinal or nominal scales.
V TORRA +3 more
openaire +1 more source
Statistical Models for Ordinal Variables.
Contemporary Sociology, 1995Mark von Tress +2 more
+4 more sources
On the Nonlinearity of Homogeneous Ordinal Variables
2011The 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
openaire +2 more sources