scholarly journals A COMPARISON OF POLYTOMOUS MODEL WITH PROPORTIONAL ODDS AND NON-PROPORTIONAL ODDS MODEL ON BIRTH SIZE CASE IN INDONESIA

2021 ◽  
Vol 14 (1) ◽  
pp. 79-88
Author(s):  
Yenni Kurniawati ◽  
Anang Kurnia ◽  
Kusman Sadik
Keyword(s):  
Risk Factors ◽  
Significant Influence ◽  
Alternative Model ◽  
Goodness Of Fit ◽  
Proportional Odds Model ◽  
Birth Size ◽  
Proportional Odds ◽  
Proportional Odds Assumption ◽  
Deviance Test ◽  
And Gender

The proportional odds model (POM) and the non-proportional odds model (NPOM) are very useful in ordinal modeling. However, the proportional odds assumption is often violated in practice. In this paper, the non-proportional odds model is chosen as an alternative model when the proportional odds assumption is not violated. This paper aims to compare Proportional Odds Model (POM) and Non-Proportional Odds Model (NPOM) in cases of birth size in Indonesia based on the 2017 Indonesian Demographic and Health Survey (IDHS) data. The results showed that in the POM there was a violation of the proportional odds assumption, so the alternative NPOM model was used. NPOM had better use than POM. The goodness of fit shows that the deviance test failed to reject H0, and the value of Mac Fadden R2 is higher than POM. The risk factors that have a significant influence on all categories of birth size are the residence and gender of the child.

scholarly journals Ordinal logistic regression models: application in quality of life studies

2008 ◽  
Vol 24 (suppl 4) ◽  
pp. s581-s591 ◽  
Author(s):  
Mery Natali Silva Abreu ◽  
Arminda Lucia Siqueira ◽  
Clareci Silva Cardoso ◽  
Waleska Teixeira Caiaffa
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Regression Models ◽  
Goodness Of Fit ◽  
Ordinal Logistic Regression ◽  
Proportional Odds Model ◽  
Outcome Variable ◽  
Proportional Odds ◽  
Logistic Regression Models

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.

scholarly journals Modelling Hypertension and Risk Factors among Adults Using Ordinal Logistics Regression Model

2020 ◽  
Author(s):  
Monday Osagie Adenomon ◽  
Daniel Owoicholofu John
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Goodness Of Fit ◽  
Adult Population ◽  
Model Fitting ◽  
Data Sets ◽  
Intervention Programme ◽  
Rate Test ◽  
And Gender ◽  
One Year

There is high prevalence of hypertension and is rapidly increasing around the world, despite the intervention programme implemented, this study aimed at estimating the prevalence rate, test of association between hypertension and risk factors and model hypertension rate. Data used was obtained from the health record of Federal Medical Centre, Keffi from January 2016 – January 2019. Ordinal logistic regression model was used; Model Fitting Information, Goodness-of-Fit, Pseudo R-Square and Test of Parallel Lines are fitted to the data sets to test the accuracy and correctness of the model. The results indicated that the overall prevalence of hypertension rate is high at 36.4%, among the adult population, body mass index and gender are statistically significant, and Age is not significant in the study. Individuals that are overweight are more likely to be hypertensive compare to other weights. At age 40 – 49 years which have the highest rate of 26.5% and the odd ratio is 0.75 compared to others. One year increase in age 30 – 39, the cumulative odd of being hypertensive is 0.91 while other independent variables are held constant. The odd ratio of female being hypertensive is 0.85, therefore the females are more likely to be hypertensive with 54.4% compared to the males at 45.6% . There is no presence of multicolinearity among the variables and Logit models were formulated to calculate probabilities of the various possible outcomes.

scholarly journals Comparison of Antimicrobial Resistant Neisseria gonorrhea to Ceftriaxone and Ciprofloxacin using Partial Proportional Odds Model for patients seen at the University Teaching Hospital in Lusaka, Zambia

2019 ◽  
Author(s):  
PRISCILLA KAPOMBE ◽  
LUNGOWE SITALI ◽  
PATRICK MUSONDA
Keyword(s):  
Risk Factors ◽  
Teaching Hospital ◽  
Susceptibility Testing ◽  
Proportional Odds Model ◽  
University Teaching ◽  
Proportional Odds ◽  
Neisseria Gonorrhea ◽  
Partial Proportional Odds Model ◽  
The University ◽  
Ethical Clearance

Abstract Background Neisseria gonorrhea, the causative agent of Gonorrhea, has developed antibiotic resistance to the “last-line” Cephalosporin’s, Quinolones and Macrolides which is cause for concern. In Zambia, despite recommendations of discontinued use, Ciprofloxacin is used for treatment. The lack of an active surveillance system, appropriate and structured data management and analysis tools magnifies the problem because resistance patterns cannot be monitored. The study aimed to ascertain effectiveness of Ciprofloxacin a Quinolone in comparison with Ceftriaxone a Cephalosporin, in treatment of Gonorrhea using Susceptibility testing; and to identify possible risk factors associated with resistance. Methods Study design was parallel non-inferior quasi experimental study. Patients at the University Teaching Hospital with discharge and Gonorrhea symptoms who gave consent, were recruited. Fishers Exact Test for associations was used. Data was analyzed using Ordinal logistic regression as the Susceptibility was at 3 levels; Susceptible, Intermediate or Resistant with an assumed Ordinal nature. Proportionality assumption was checked, and when violated Partial Proportional Odds Model was used instead. Results A total of 104 isolates were obtained. The overall proportion of patients who had Susceptible, Intermediate and Resistant results were: 49 (47.1%), 55 (52.9%) and 0 (0) for Ceftriaxone and 70 (68.0%), 10 (9.7%) and 22 (22.3%) for Ciprofloxacin respectively. Adjusted estimates in partial Proportional Odds model showed that, Males were 4.1 (95% CI; 1.8, 9.4, p-value=0.001) times more likely to have Intermediate or Susceptible results compared to Resistance than females, or they were more likely to have Susceptible compared to Resistance or Intermediate result compared to females. Ciprofloxacin was 70% less likely than Ceftriaxone of having susceptible or intermediate results compared to resistance and this could be as high as 90% and as high as 40% p-values <0.001). Conclusion Level of Ciprofloxacin resistance detected from the Susceptibility testing, shows it is not an effective treatment for Gonorrhea. Ceftriaxone remains a satisfactory option for first-line treatment of Gonorrhea at UTH. Risk factors identified to be associated with resistance in this study were being female and use of Ciprofloxacin. Ethical Clearance Ethical clearance was obtained from University of Zambia Biomedical Ethics Research Committee (UNZABREC Ref # 033-06-17).

scholarly journals Associated risk factors of underweight among under-five children in Ethiopia using multilevel ordinal logistic regression model

2021 ◽  
Vol 21 (1) ◽  
pp. 362-72
Author(s):  
Nigussie Adam Birhan ◽  
Denekew Bitew Belay
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Proportional Odds Model ◽  
Proportional Odds ◽  
Under Five ◽  
Single Level ◽  
Under Five Children ◽  
Under Nutrition ◽  
Partial Proportional Odds Model ◽  
Associated Risk Factors

Background: Malnutrition is associated with both under nutrition and over nutrition which causes the body to get improp- er amount of nutrients to maintain tissues and organ function. Under nutrition is the result of insufficient intake of food, poor utilization of nutrients due to illnesses, or a combination of these factors. The purpose of this study was to identify associated risk factors and assess the variation of underweight among under-five children of different regions in Ethiopia. Methods: Ethiopian Demography and Health Survey (EDHS-2016) weight-to-age data for under-five children is used. In order to achieve the objective of this study; descriptive, single level and multilevel ordinal logistic regression analysis were used. Results: From a total of 8935 children about 8.1% were severely underweight, 17.1% were moderately underweight and 74.8% were normal. The test of heterogeneity suggested that underweight varies among region and multilevel ordinal model fit data better than single level ordinal model. Conclusion: Educational level of mother, religion, birth order, type of birth, sex of child, mother body mass index, birth size of child, existence of diarrhea for last two weeks before survey, existence of fever for last two weeks before survey, duration of breast feeding, age child and wealth index had significant effect on underweight among under-five children in Ethiopia. The finding revealed that among the fitted multilevel partial proportional odds model, the random intercept model with fixed coefficients is appropriate to assess the risk factors of underweight among under-five children in Ethiopia. The findings of this study have important policy implications. The government should work closely with both the private sector and civil society to teach women to have sufficient knowledge, awareness and mechanisms of improving under-five under- weight for children’s wellbeing. Keywords: Underweight; Partial proportional odds model; Multilevel partial proportional odds model; under-five children.

scholarly journals Exploring the Fundamental Risk Factors of Child Malnutrition: An Application of Proportional Odds Model (POM)

2021 ◽  
Vol 11 (2) ◽  
pp. 113-119
Author(s):  
Rida Ayyaz ◽  
Muhammad Asad Meraj ◽  
Fakhar Mustafa
Keyword(s):  
Risk Factors ◽  
Nutritional Status ◽  
Maternal Education ◽  
Economic Status ◽  
Significant Risk ◽  
Proportional Odds Model ◽  
World Health ◽  
P Value ◽  
Proportional Odds ◽  
Chi Square

Background: This study was designed with the objective to evaluate the fundamental risk factors of malnutrition among children in Lahore city and its outskirts, Pakistan. Methods: Data of four hundred and five children with age group less than 5 years was collected from Children hospital and Jinnah hospital, Lahore. We used weight-for-height anthropometric index, designed by World Health Organization (WHO), to measure the nutritional status of children. Preliminary analysis was performed by using Pearson Chi-square and Gamma statistics to check the association between factors (demographic, socio-economic and health related variables) and response variable i.e., nutritional status. Then, proportional odds model (POM) was fitted to the information collected. Results: Of 405 children included in the study, 33% (135) were found malnourished, whereas, approximately 67% (270) were found nourished. Findings of the study revealed that child’s age, maternal education level, socio-economic status, maternal age at the birth of child, low birth spacing, status of antenatal-postnatal care, incomplete vaccinations, exclusive breastfeeding, prevalence of fever, cough and recurrent episodes of diarrhea were the significant risk factors of malnutrition. Prevalence of acute respiratory infection (ARI) was turned out to be insignificant risk factor.  In this study, parallel lines assumption was satisfied and proportional odds model was fitted well with p-value greater than 5% level of significance. Conclusion: This paper highlights the significant risk factors that are affecting the child’s health. Recognizing and understanding the identified risk factors would be very helpful in prevention of malnutrition in Pakistan.

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