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Ordinal regression

About: Ordinal regression is a research topic. Over the lifetime, 1879 publications have been published within this topic receiving 65431 citations.


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TL;DR: The extensive computational experiments performed on a set of benchmark optimization problems reveal that EMOSOR is able to bias an evolutionary search towards a part of the Pareto front being the most relevant to the DM, outperforming in this regard the state-of-the-art interactive evolutionary hybrids.

14 citations

Journal ArticleDOI
TL;DR: Southern population of Iranian Southern population does not accept family physician as the first point of interaction with the health system, and they prefer to go to public hospitals directly, thus their acceptance of health care is low.
Abstract: INTRODUCTION: Health systems aimed to increase health utilization. Habits and behavior about using health facilities, which is called health-seeking behavior, are different among different cultures and influenced by different factors. The present study is aimed at investigating Iranian Southern population health-seeking behavior and its influencing factors. MATERIALS AND METHODS: A sample of 397 people was selected using proportional stratified random sampling for this cross-sectional study. They were asked to fill a questionnaire about their health-seeking behaviors (seeking treatment, inattention to treatment, and self-medication) and socioeconomic factors. Data were analyzed using regression models including linear, ordinal, and logistic regressions. RESULTS: Near 80% of participants reported self-medication and most of them prefer public hospitals as their first point of contact with health system compared to others such as family physician. Using linear regression revealed seeking treatment has significant relationship with age (P = 0.037), living place (P = 0.018), and having complementary insurance (P = 0.013). Self-medication behavior has relation with age (P = 0.015), gender (P = 0.039), education years (P = 0.031), living place (P = 0.005), having complementary insurance (P = 0.001), and satisfaction with health-care providers (P = 0.003) in logistic regression. Using ordinal regression, it was found that inattention to treatment has a relation with education years (P = 0.044), living place (P = 0.042), having complementary insurance (P = 0.049), and severity of illness (P = 0.031). conclusion: Southern population does not accept family physician as the first point of interaction with the health system, and they prefer to go to public hospitals directly. Moreover, self-medication is a prevalent behavior among the population and thus their acceptance of health care is low. Based on the findings, it can be suggested providing more satisfying health care, increasing insurance coverage, and informing population could lead to better utilization of health-care services.

14 citations

Journal ArticleDOI
TL;DR: In this paper, a collective choice function (CCF) is proposed as a generator of several compromise consensuses, which can be straightforwardly transformed into easily computable goal programming models.
Abstract: In this paper a collective choice function (CCF), formulated within a p-metric distance function framework, is proposed as a generator of several compromise consensuses. Even though, the proposed CCF is not smooth, it is however demonstrated that it can be straightforwardly transformed into easily computable goal programming models. Finally, several cases of individual preferences aggregation are obtained by providing different interpretations of the CCF parameters: ordinal and complete information, ordinal and partial information and a cardinal case through ‘pairwise’ comparison matrices. Copyright © 2009 John Wiley & Sons, Ltd.

14 citations

Journal ArticleDOI
TL;DR: This article developed a typology of asymmetric, proportionate reduction in error (PRE) measures for describing the relationship between a nominal or an ordinal independent variable (X) and a dependent variable (Y).
Abstract: Many variables of concern to sociologists are ordinally measured. Evaluating causal theoretical statements involving such variables requires refined asymmetric measures of association. We develop a typology of asymmetric, proportionate reduction in error (PRE) measures for describing the relationship between a nominal or an ordinal independent variable (X) and an ordinal dependent variable (Y). Measures are classified according to prediction rule and method for handling ties in estimating predictive error. This scheme is used to compare several existing measures of association (Y, d'y , and 0) and to derive two new measures. The typology yields three sets of paired measures useful for assessing relationships in terms of departure from monotonicity. This usage is analogous to the use of r2 and E2 to evaluate linearity and nonlinearity. Many variables of interest to sociologists are measured ordinally. Ordinal variables are characterized by (a) an ordering principle according to which "greater than" and "less than" comparisons can be made and (b) the absence of a standard measuring unit in which scale values are expressed. These variables may emerge in at least three ways. First, some variables such as Bogardus' social distance scale or any Guttman scale are intrinsically ordinal. Second, a potential interval scale may be measured on a questionnaire in terms of crude ordered categories. Third, an apparent interval scale may be used as a manifest indicator of an underlying variable to which it is only assumed to be monotonically related (Somers, a). We think that ordinal scales and theoretical statements describing

14 citations

Journal ArticleDOI
TL;DR: The authors investigated how students who have grown up using the SI (Systeme International d'Unites) (metric) or US customary (USC) systems of units for everyday use differ in their knowledge of scale and measurement.
Abstract: Following a sociocultural perspective, this study investigates how students who have grown up using the SI (Systeme International d'Unites) (metric) or US customary (USC) systems of units for everyday use differ in their knowledge of scale and measurement. Student groups were similar in terms of socioeconomic status, curriculum, native language transparency of number word structure, type of school, and makeup by gender and grade level, while varying by native system of measurement. Their performance on several tasks was compared using binary logistic regression, ordinal logistic regression, and analysis of variance, with gender and grade level as covariates. Participants included 17 USC-native and 89 SI-native students in a school in Mexico, and 31 USC-native students in a school in the Midwestern USA. SI-native students performed at a significantly higher level estimating the length of a metre and a conceptual task (coordinating relative size and absolute size). No statistically significant differences w...

14 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023102
2022191
202188
202093
201979
201873