[PDF] Top 20 An Investigation of Malaria Predictors Using Logistic Regression Model
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An Investigation of Malaria Predictors Using Logistic Regression Model
... Although malaria is a disease which is considered the most deadly killer especially to children less than 5 years mainly of African countries, there exists no statistical model for the analysis of its ... See full document
5
Some new proposed ridge parameters for the logistic regression model
... calculated using a fairly low number of predictor variables (2 and 4 is the most common selected value of p) (Mansson et ...an investigation where more variables are considered to see the effect of ... See full document
14
Online Full Text
... another investigation showed homelessness and old age with OR ...as predictors of high risk patient to fail ...multiple logistic regression model to verify predictors of ... See full document
6
Computational Algorithms for Penalized Logistic Regression with Categorical Predictors and Random Effect Logistic Models.
... parameters using appropriately smaller complete data ...and model reduction will decrease the amount of data augmentation, which will increase computational ... See full document
92
Prediction and detection models for acute kidney injury in hospitalized older adults
... tasks using different machine learning methods trained on large patient data of hospital ...models, logistic regression performed the best. This model found certain comorbidities and drug ... See full document
11
Acute hospital-based services utilisation during the last year of life in New South Wales, Australia: methods for a population-based study
... important predictors of good clinical response were identified by logistic regression with backward elimination (selection level ...final model, including OR, 95% CI, and p values are ...the ... See full document
8
Effect Modeling of Count Data Using Logistic Regression with Qualitative Predictors
... ative predictors are appropriate for modeling and ...categorical predictors were not fully discussed. He did mention that logistic regression should include qualitative explanatory variables, ... See full document
16
Nonparametric bootstrapping for multiple logistic regression model using R
... The coefficient standard errors reported by glm rely on asymptotic approximations and may not be trustworthy. Therefore, let us turn to the bootstrap. Here we want to fit a regression model with re- sponse ... See full document
5
Time loss due to dental problems and treatment in the Canadian population: analysis of a nationwide cross-sectional survey
... Univariable logistic regressions were conducted to produce unadjusted odds ratios (OR) for reporting time ...Multivariable logistic regression was then conducted to determine which variables were ... See full document
11
Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements
... these predictors plus age and gender to predict maximum creatinine results during Day 2 and Day ...assessed model perform- ance and creatinine predictability by masking creatinine results from a test fold ... See full document
12
Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study
... predictive model for early rehospitalisation in preterm ...relevant predictors were included in the ...ten predictors in the primary predictive logistic regression model for ... See full document
11
Cancer Absolute Risk Projection with Incomplete Predictor Variables
... of predictors with hazard rates obtained from different sources, where the relative hazard function is often approximated by an odds ratio ...risk predictors, it is very common that data for standard risk ... See full document
141
LOGISTIC REGRESSION MODEL FOR PREDICTION OF BANKRUPTCY
... prediction using logistic regression model for the year 2010 gives 5 banks at failure level which includes the four banks classified under classification ... See full document
15
An Application on Multinomial Logistic Regression Model
... Multinomial Logistic Regression model which is one of the important methods for categorical data ...This model deals with one nominal/ordinal response variable that has more than two ... See full document
21
A computational approach to compare regression modelling strategies in prediction research
... produced using each approach, seen in Additional file 2, due to the minimal amount of shrinkage that was ap- plied, and the similarity between the development and validation ...built using bootstrap-derived ... See full document
10
Comparative Analysis of Machine Learning Algorithms for their Effectiveness in Churn Prediction in the Telecom Industry
... various model presented in the paper had good accuracy rate but the Logistic regression model on the balanced data has the highest area under the curve, which by convention proves to be the ... See full document
5
An Application of Bootstrapping in Logistic Regression Model
... classical logistic regression model, and performed both parametric and non-parametric bootstrap for estimating confidence interval of parameters for logis- tic model and odds ... See full document
9
Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data
... polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of ... See full document
11
A brief intervention is sufficient for many adolescents seeking help from low threshold adolescent psychiatric services
... using a semi-structured checklist. This checklist was formed for clinical purposes in order to standardize the information collected from adolescents and parents. During the interview, data were collected on the ... See full document
10
Churn Analysis in Telecommunication Using Logistic Regression
... not using the technical support are possible to churn, this might be due to the lack of knowledge about the services that are provided by the telecom so it is very important to highlight the kind of customer ... See full document
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