Read this paper if you want to learn logistic regression

Fernandes, Antônio Alves Tôrres; Filho, Dalson Britto Figueiredo; Rocha, Enivaldo Carvalho da; Nascimento, Willber

doi:10.1590/1678-987320287406en

Cited by 32 publications

(19 citation statements)

References 39 publications

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“…Logit regression model use the maximum likelihood estimation method to fit a binary or ordinal dependent variable [ 50 , 51 ]. In this study, the dependent variable is binary in nature, coded 1 for willingness to be vaccinated and 0 otherwise.…”

Section: Methodsmentioning

confidence: 99%

Factors Influencing Willingness to Be Vaccinated against COVID-19 in Nigeria

Oyekale

2022

IJERPH

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Vaccines have been historically used to address some pressing health problems in the world. COVID-19 presents no exception, although vaccine hesitancy remains a major bottleneck in some countries. This study analyzed the factors influencing willingness to be vaccinated against COVID-19 in Nigeria. The data are from the 10th wave of COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) that was conducted in 2021. The data were analyzed with Logit regression. The result showed that the national acceptance rate of COVID-19 vaccine was 85.29%. The North East had the highest acceptance rate (96.14%), while the South East (71.80%) had the lowest value. Rural areas had higher vaccine acceptance rates of 87.80% as compared against 81.41% for urban areas. Logit regression result showed that urban residents in the South East zone and the South South zone were not too worried about contracting COVID-19 or not worried at all about contracting COVID-19, saw COVID-19 as not much of a threat to household finance or COVID-19 as not a threat at all to households’ finances, which significantly reduced the log odds of residents’ willingness to be vaccinated against COVID-19 (p < 0.05). However, age, the COVID-19 preventive compliance index and needing medical services significantly increased the log odds of the willingness to be vaccinated against COVID-19 vaccines (p < 0.05). Addressing the COVID-19 pandemic in Nigeria through vaccination requires significant interventions for ensuring regional and sectoral balances in vaccine acceptability through interventions and programmes for promoting individuals’ perception of health risk and vulnerability.

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Section: Methodsmentioning

confidence: 99%

Factors Influencing Willingness to Be Vaccinated against COVID-19 in Nigeria

Oyekale

2022

IJERPH

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“…The omnibus test in Table 6 tests whether the successive models in the iterative steps of the regression are better than the initial base model of the iterative process. As the P values are highly significant, this indicates that the parameter estimates obtained after the iterative process are much better than an initial model (Fernandes et al 2021;Larry and Bradley 1991). Again, the likelihood in Table 7 shows a comparison of the final model of the iterative process with the initial raw model: the higher this number, the more expressive is the improvement (Fernandes et al 2021).…”

Section: Resultsmentioning

confidence: 98%

“…As the P values are highly significant, this indicates that the parameter estimates obtained after the iterative process are much better than an initial model (Fernandes et al 2021;Larry and Bradley 1991). Again, the likelihood in Table 7 shows a comparison of the final model of the iterative process with the initial raw model: the higher this number, the more expressive is the improvement (Fernandes et al 2021). We estimated the R 2 using two methods: a more conservative one (Cox and Snell 1968) and a more extensive one (Nagelkerke 1991).…”

Section: Resultsmentioning

confidence: 98%

Anticompetitive practices on public procurement: Evidence from Brazilian electronic biddings

Sampaio¹,

Figueiredo²,

Puzon³

2022

WIDER Working Paper

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analysis and policy advice with the aim of promoting sustainable and equitable development. The Institute began operations in 1985 in Helsinki, Finland, as the first research and training centre of the United Nations University. Today it is a unique blend of think tank, research institute, and UN agency-providing a range of services from policy advice to governments as well as freely available original research.The Institute is funded through income from an endowment fund with additional contributions to its work programme from Finland, Sweden, and the United Kingdom as well as earmarked contributions for specific projects from a variety of donors.

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“…To enable efficient categorization utilizing this new form of sample data, a novel feature selection method has been introduced. Fernandes Et.al [6] proposed the most appropriate statistical technique for dealing with dichotomous dependent variables and presented in their work logistic regression to assess the impact of corruption scandals on the chances of reelection of candidates running for the Brazilian Chamber of Deputies (2014). They demonstrated the computational implementation in R and discussed the substantive interpretation of the results.…”

Section: Literature Surveymentioning

confidence: 99%

Recognizing Fake Headlines Using Clustering Algorithms

Sowjanya¹

2022

MSEA

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The credibility of the news sources has hit a new low during the COVID-19. Hence, it is necessary to check for facts before trusting the news. Clustering is extremely important for analysing data, making predictions, and overcoming data abnormalities. So, in this work, the two most prominent clustering algorithms, K-Means and K-Medoids, are tested on a dataset, and K-Means outperforms k-Medoid. We now utilized supervised classification methods like Logistic Regression, K-Nearest Neighbours, and Support Vector classifier to train on the same news headlines we used for clustering with the 'Prediction' column, and then chosen the technique with the highest accuracy. The Support Vector Classifier had the maximum accuracy of 94.93 percent, according to the test. We have developed is a hybrid model consisting of an unsupervised K Means clustering algorithm and a supervised Support Vector classification algorithm. The K Means algorithm organizes the news headlines into clusters by capturing the usage of certain words and the support vector algorithm learns from those clusters to predict the categories into which the unseen news headlines belong to.

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Read this paper if you want to learn logistic regression

Cited by 32 publications

References 39 publications

Factors Influencing Willingness to Be Vaccinated against COVID-19 in Nigeria

Factors Influencing Willingness to Be Vaccinated against COVID-19 in Nigeria

Anticompetitive practices on public procurement: Evidence from Brazilian electronic biddings

Recognizing Fake Headlines Using Clustering Algorithms

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