scholarly journals Application of Multinomial Logistic Regression Model on Factors That Affects The Need for Children Among Ethiopian Women

2021 ◽  
Author(s):  
Habitu Liyew Molla ◽  
Turufat Seifu Moges
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Reproductive Age ◽  
Multinomial Logistic Regression Model ◽  
Desire For Children ◽  
First Marriage ◽  
Age At First Marriage ◽  
Living Children

Abstract Background: Need for children (desire for children), is one of the major factors influencing the population dynamics. Like other fertility preferences, it is not fixed but changes over the family life course in respect to actual fertility experiences and outcomes. The objective of this study was to identify socio-economic and demographic factors that affect the need for another child (desire for more children) among Ethiopian women of reproductive age (15-49).Methods: The study was based on Ethiopian Demographic and Health Survey (EDHS), 2016 data. A total of 15,683 women with complete information were considered in the study. A Multinomial Logistic Regression Model, a family of generalized non-linear models, were used to identify determinant factors for the need to children (desire for children) among women in Ethiopia using STATA 14 and SPSS 23.Results: Results showed that among the reproductive age women’s 65.51% were need to have childe, and their average age was 25.05, 27.18% were don’t like to have child and their average age was 35.73, the rest 7.31% of the women were not decide where they need children or not and their average age was 24.8. From multinomial logistic regression model, Region, contraception using (for yes 0.658293 (0.58889, 0.73586) for undecided 0.6310024 (0.50151, 0.79394)), marital status, age of women (for yes 0.896552 (0.88968, 0.90348) for undecided 0.9282431 (0.91632, 0.94033)), number of living children, religion, age at first marriage ( for yes1.057528 (1.04363, 1.07161) for undecided 1.041 (1.01434, 1.06836)), wealth index, women’s employment and women’s education were significant effect on the need for children among Ethiopian women.Conclusions: This study was based on a nationwide large sample demographic and survey conducted by the Ethiopian Statistical Agency. The study has empirically investigated and identified the determinants factors that affect the need for children among Ethiopian women. The multinomial logistic regression model analysis identified that variables such as marital status, contraception using, number of living children, age at first marriage and age of women play vital role in deciding on weather women need to have children or not. Region contraceptive using women’s employment, women’s education level and number of living children have negatively associated with outcome variable.

scholarly journals Burden and predictors ofStaphylococcus aureusandS. pseudintermediusinfections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3198 ◽  
Author(s):  
Daniel N. Qekwana ◽  
James Wabwire Oguttu ◽  
Fortune Sithole ◽  
Agricola Odoi
Keyword(s):  
South Africa ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Risk Of Infection ◽  
Multinomial Logistic Regression Model ◽  
Tract Infections ◽  
Veterinary Hospital ◽  
Isolated Species

BackgroundStaphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between variousStaphylococcusinfections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa.MethodsRecords of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections.ResultsTwenty-seven percent of the samples tested positive forStaphylococcusspp. The species ofStaphylococcusidentified wereS. pseudintermedius(19.0%),S. aureus(3.8%),S. epidermidis(0.7%) andS. felis(0.1%). The remaining 2.87% consisted of unspeciatedStaphylococcus. Distribution of the species by age of dog showed thatS. pseudintermediuswas the most common (25.6%) in dogs aged 2–4 years whileS. aureuswas most frequent (6.3%) in dogs aged 5–6 years.S. pseudintermedius(34.1%) andS. aureus(35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection withStaphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive forS. pseudintermediuscompared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive forS. aureusthan those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive forS. pseudintermediusthan those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive forS. pseudintermediuscompared to those <2 years of age. The risk of infection withS. pseudintermediusorS. aureuswas significantly higher in ear canal and skin specimens compared to other specimens.ConclusionsThe findings suggest thatS. pseudintermediusandS. aureuswere the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with bothStaphylococcusspecies investigated. Significant increasing temporal trend was observed forS. pseudintermediusbut notS. aureus. This information is useful for guiding clinical decisions as well as future research.

Diachronic frame analysis

2019 ◽  
Vol 11 (1) ◽  
pp. 43-78
Author(s):  
James Law
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Frame Analysis ◽  
Semantic Change ◽  
Frame Semantics ◽  
Multinomial Logistic Regression Model ◽  
Grammatical Category

Abstract Frame Semantics offers a valuable perspective on mechanisms of semantic change, particularly metonymy. However, corpus-based frame analysis has rarely been applied to diachronic data. The potential of this approach is illustrated with a diachronic description of the Purpose frame in French, based on 1,429 tokens of 17 frame-evoking words. Metonymic mappings in the frame allow Means and Medium to replace Agent. A multinomial logistic regression model shows that usage of these mappings has increased since 1600 and is conditioned by genre and the frequency and grammatical category of the frame-evoking word. The approach may inform how metonymy leads to lexicalized semantic change.

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