Logistic Regression Models for Ordinal Response Variables

O’Connell, Ann A.

doi:10.4135/9781412984812

Cited by 413 publications

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“…If the H-L goodness-of-fit test is greater than 0.05, as wanted for well-fitting model, then one fails to reject the null hypothesis that there is no difference between the observed and model-predicted value (O'Connell 2005). This implies that the model's estimates fit the data at an acceptable level.…”

Section: Data Analysis and Discussionmentioning

confidence: 98%

“…It means that on the average the model's predictors could explain 77.4% in the variation of the smoothing practices. This percentage indicates a moderately strong relationship of 77.4% between the predictors and the prediction (O'Connell 2005).…”

Section: Data Analysis and Discussionmentioning

confidence: 99%

“…If the value of Exp (B) exceeds 1 then the predicted probability of occurrence increases, conversely ifExp(B) value is less than 1, any increase in the corresponding predictor leads to thedecrease of the predicted probability (O'Connell 2005). For example, the Exp (B) value associated with DEBT in the 2011.…”

Section: Data Analysis and Discussionmentioning

confidence: 99%

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The effect of non-recurring item transactions on the possibility of firms to smooth income: the case of Indonesian listed firms

Trisanti¹

2013

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Section: Data Analysis and Discussionmentioning

confidence: 98%

Section: Data Analysis and Discussionmentioning

confidence: 99%

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The effect of non-recurring item transactions on the possibility of firms to smooth income: the case of Indonesian listed firms

Trisanti¹

2013

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“…It is worth to mention that among the types of ordinal logistic regression models, the proportional odds model is one of the most popular statistical tools for the data analysis on clinical and epidemiological researches, because of the simplicity of its interpretation (Hosmer & Lemeshow, 2000;O'Connell, 2006;Kleinbaum & Klein, 2010;O'Connell & Liu, 2011). For such reason, this method was used for this study which allowed to evidence the impact of third molars, in probability terms, on the lower anterior crowding magnitude.…”

Section: Discussionmentioning

confidence: 99%

Incidence of Lower Anterior Third Molars on Dental Crowding. A New Approach

Vergara

Solano

Bustillo

2017

Int. J. Odontostomat.

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LLINÁS, H. J. & BUSTILLO, J. M.Lower anterior third molar impact on dental crowding. A new approach. Int. J. Odontostomat., 11(3):327-332, 2017.ABSTRACT: This paper main objective is to estimate the level of association between lower anterior crowding and the presence of lower third molars on study models and panoramic dental radiographs of patients treated by the Orthodontics Postgraduate Students at the Dentistry Faculty at the University of Cartagena (Cartagena de Indias, Colombia) and also other dental and radiographs care centers in Cartagena de Indias. It was made using a cross-sectional study at the Dentistry Faculty at the University of Cartagena and others dental care centers in the city. There were 366 study models and panoramic dental radiographs selected by strict inclusion/exclusion criteria for patients. An instrument that includes age, gender, presence or absence of third molars, position of third molars according to Winter's classification, stage of formation of the third molars according to Nolla's classification, and crowding magnitude according to Harfin's classification was used. Data were analyzed based on frequency distributions and proportions; inferential analysis was performed through proportional odds model using the software package IBM SPSS Statistics v23. It was found that the patients with Nolla 6 from the right side are more likely to have mild-moderate crowding magnitude than patients with Nolla 10 on that same side. In conclusion, this research provides as main result the implication of the eruption of the lower third molars and particularly those erupting in mesioangular and horizontal positions in the anterior crowding (AA).

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“…First, seven hypotheses were derived from the process-based model of policing. Secondly, the hypotheses were tested using the multiple binominal logistic regressions due to the ordinal nature of the main dependent variable of the study (O'Connell, 2006).…”

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confidence: 99%

Public assistance of police during criminal investigations: Russian experience

Semukhina

2014

Police Practice and Research

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This study examines the high levels of public unwillingness to assist police in criminal investigations in Russia. Variables of public trust of police, fear of crime, victimization, and prior contact with police are used to explain this phenomenon. Also included in the study are variables of police fear and avoidance of police. The findings suggest that higher levels of distrust in, as well as fear and avoidance of police are strong predictors of citizens' unwillingness to assist police in Russia. The paper discusses potential implications of these findings for the 2011 police reform in Russia.

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Logistic Regression Models for Ordinal Response Variables

Cited by 413 publications

References 0 publications

The effect of non-recurring item transactions on the possibility of firms to smooth income: the case of Indonesian listed firms

The effect of non-recurring item transactions on the possibility of firms to smooth income: the case of Indonesian listed firms

Incidence of Lower Anterior Third Molars on Dental Crowding. A New Approach

Public assistance of police during criminal investigations: Russian experience

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