Importance of Assessing the Model Adequacy of Binary Logistic Regression

Sarkar, Saroje Kumar; Midi, Habshah

doi:10.3923/jas.2010.479.486

Cited by 34 publications

(24 citation statements)

References 22 publications

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“…The cross-referencing method has been used in many previous studies [1,[15][16][17][18]45]. Inadequate models can give misleading or incorrect inferences [26]. Our study showed that the use of this simple method should be discouraged because it distorts the HIV death estimate in various demographic groups.…”

Section: Discussionmentioning

confidence: 82%

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Correcting and estimating HIV mortality in Thailand based on 2005 verbal autopsy data focusing on demographic factors, 1996-2009

Chutinantakul

Tongkumchum

Bundhamcharoen

et al. 2014

Popul Health Metrics

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Background: It is known that death registry (DR) underestimates HIV deaths. The objectives of this study were to examine under-reporting/misclassification and to estimate HIV mortality in Thailand during 1996-2009 from a model based on 2005 verbal autopsy (VA) data. Methods: Logistic regression was used to predict HIV deaths from the VA dataset with and without demographic covariates. This full model was then used to predict individual HIV deaths from the DR dataset of provinces in which VA was conducted. The proportions in the remaining provinces were predicted from spatial interpolation based on coefficients of the VA provinces.

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Section: Discussionmentioning

confidence: 82%

“…Area under the ROC curve (AUC) measures the performance of a model and represents model accuracy [26,27]. A cut-off point in the curve, where the predicted number of HIV deaths equals the observed value in the VA dataset (512 cases), was used to report sensitivity and specificity of the model.…”

Section: Data Sources and Managementmentioning

confidence: 99%

Correcting and estimating HIV mortality in Thailand based on 2005 verbal autopsy data focusing on demographic factors, 1996-2009

Chutinantakul

Tongkumchum

Bundhamcharoen

et al. 2014

Popul Health Metrics

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“…The individual probability of an AE was calculated by logistic and log-logistic regression analyses. All predictor variables that are useful in predicting the response variable were included [25]. The Wald test was used to determine statistical significance for each of the independent variables.…”

Section: Methodsmentioning

confidence: 99%

Impulse Oscillometry as a Predictor of Asthma Exacerbations in Young Children

et al. 2016

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Background: In a post-hoc analysis of a pediatric asthma study, we identified the predictors of asthma exacerbations (AEs) and related them to forced expiratory volume (FEV₁), the FEV₁/FVC ratio, and bronchial hyperresponsiveness (BHR). Objectives: We sought to detect predictors of AEs in a prospective study that utilizes impulse oscillometry (IOS) and to compare the results to previously determined predictors. Methods: A moderate AE was defined as an increased use of salbutamol during coughing episodes. Pulmonary function and BHR were measured during symptom- and medication-free periods. Additionally, allergen testing and IOS were included. To calculate the sensitivity and specificity of AE detection, a receiver-operating characteristic (ROC) curve was plotted, and accuracy was measured with the area under the ROC curve (AUC). A logistic regression analysis was used to predict the probability of an exacerbation. Results: Seventy-five pediatric patients (4-7 years of age) with intermittent asthma were included. In 69 patients, the following cut-off values demonstrated the best sensitivity and specificity combination for predicting an AE: FEV₁ 103.2% (AUC 0.62), BHR (PD₂₀methacholine) 0.13 mg (AUC 0.61), and, in 54 children, Rrs5 0.78 kPa × l^-1 × s (AUC 0.80). Logistic regression analysis demonstrated that the combination of all parameters predicted the individual risk of AEs with an accuracy of 86%. Conclusions: IOS, a simple method, predicted the probability of AEs in young children. Airway resistance, measured by IOS, was superior to FEV₁ and methacholine testing. The current data suggest that peripheral airway obstruction is present during symptom-free periods and that these children more likely experience AEs.

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“…Specifically, suppose (y 1 , y 2 …y n ) be the n independent random observations corresponding to the random variables (Y 1 , Y 2 ……Yn). Since the Y i is a Bernoulli random variable, the probability function of Y i is f i (Y i ) = π i Yi (1-π i ) 1-yi ; Y i = 0 or 1; i = 1, 2,..., n, since Y's are assumed to be independent, the joint probability function or likelihood function is given by [7]:…”

Section: Model Specificationmentioning

confidence: 99%

Determinants of Food Access of Old People in Dire Dawa City, Ethiopia: An Ordinal Logistic Regression Analysis

Bemanjo¹

2017

SJAMS

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Abstract:Although Ethiopia is a young country with 46 per cent of the population under the age of 14, over five per cent of the 81 million Ethiopians are aged 60 years or more. This proportion of older persons is anticipated to nearly double to nine per cent by 2050. There are several factors that could hinder old people access to food such as income, health status, household size, disability and others (HAIE, 2011). This objective of this study was to assess the old people access to food and its determinants in Dire Dawa city. Total samples of 947 old people were taken by using cluster sampling over proportional allocation to each kebele. Quantitative and qualitative data has been collected from aged persons in Dawit Aid for Aged persons Association, Asegedech Association and other appropriate enumeration areas. The descriptive analysis resulted that 72.76% were members of the associations. Most (74.3%) members of the organization have medium and above food access. Additionally their life have been improved in terms of obtaining medical, clothing and counseling service after they joined the organizations. The ordinal logistic regression identified income source, occupation, owning a house and type of membership organization as determinants of daily food access for the elderly.

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Importance of Assessing the Model Adequacy of Binary Logistic Regression

Cited by 34 publications

References 22 publications

Correcting and estimating HIV mortality in Thailand based on 2005 verbal autopsy data focusing on demographic factors, 1996-2009

Correcting and estimating HIV mortality in Thailand based on 2005 verbal autopsy data focusing on demographic factors, 1996-2009

Impulse Oscillometry as a Predictor of Asthma Exacerbations in Young Children

Determinants of Food Access of Old People in Dire Dawa City, Ethiopia: An Ordinal Logistic Regression Analysis

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