Ordinal logistic regression models
Application in Quality of Life Studies
Bibliographic Data
| ID | 5271611 |
|---|---|
| Authors | Mery Natali Silva Abreu (0000-0002-6691-3537, Universidade Federal de Minas Gerais), Arminda Lucia Siqueira (Universidade Federal de Minas Gerais), Clareci Silva Cardoso (0000-0003-0689-1644, Universidade Federal de Minas Gerais), Waleska Teixeira Caiaffa (0000-0001-5043-4980, Universidade Federal de Minas Gerais) |
| Year | 2008 |
| Volume | 24 |
| Issue | suppl 4 |
| Pages | s581-s591 |
| Publication date | 2008-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Cadernos de Saude Publica (JOURNAL) |
| Journal identifiers | ISSN: 0102-311X • E-ISSN: 1678-4464 |
| Publisher | FapUNIFESP (SciELO) (PUBLISHER) |
| DOI | 10.1590/s0102-311x2008001600010 |
| PMID | 18797732 |
| OpenAlex | W2110074738 |
| SciELO | S0102-311X2008001600010 |
| Language | EN |
| Citations received | 12 |
| References cited | 18 |
Quality of life has been increasingly emphasized in public health research in recent years. Typically, the results of quality of life are measured by means of ordinal scales. In these situations, specific statistical methods are necessary because procedures such as either dichotomization or misinformation on the distribution of the outcome variable may complicate the inferential process. Ordinal logistic regression models are appropriate in many of these situations. This article presents a review of the proportional odds model, partial proportional odds model, continuation ratio model, and stereotype model. The fit, statistical inference, and comparisons between models are illustrated with data from a study on quality of life in 273 patients with schizophrenia. All tested models showed good fit, but the proportional odds or partial proportional odds models proved to be the best choice due to the nature of the data and ease of interpretation of the results. Ordinal logistic models perform differently depending on categorization of outcome, adequacy in relation to assumptions, goodness-of-fit, and parsimony
Categorical variable · Econometrics · Goodness of fit · Inference · Logistic regression · Odds · Ordered logit · Ordinal data · Ordinal regression · Statistical inference · Statistical model · Statistics · Advanced Statistical Methods and Models · Artificial Intelligence · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
Multimorbidity and health-related quality of life among patients attending chronic outpatient medical care in Bahir Dar, Northwest Ethiopia
Medical insurance policy organized by Chinese government and the health inequity of the elderly
Developing a methodology for assessing livability potential
The Impact of Livelihood Assets on the Food Security of Farmers in Southern Iran during the Covid-19 Pandemic
Capability inequality
How do anthropogenic factors define flood risk perception of vulnerable communities? Evidence from Kelani River Lower Basin, Colombo, Sri Lanka
Determinants of Social Inclusion of Agricultural Labourers in Rural Haryana, India
Land tenure security and investment
Unresolved Issues
Contextual variations in perceived social values of ecosystem services of urban parks
Health-related quality of life and working conditions among nursing providers
Estudo caso-controle com resposta multinomial
Classification And Regression Trees
Applied Logistic Regression
Partial Proportional Odds Models for Ordinal Response Variables
Regression and Ordered Categorical Variables
Assessing Proportionality in the Proportional Odds Model for Ordinal Logistic Regression
Regression Models for Ordinal Data
Qualidade de vida e saúde
Factors associated with low quality of life in schizophrenia
Qualidade de vida e dimensão ocupacional na esquizofrenia
| Citations per year | 0.75 |
|---|---|
| Citation span | 2010 - 2026 (17) |
| Highly cited | No |