Multivariate Logistic regression model for COPD with
Multivariate Logistic Regression
... As expected, age has a strong effect, with an odds ratio of 1.035 per year, or 1.035 10 = 1.41 per decade (95% CI per year of (1.013, 1.058), so (1.138, 1.757) per decade). Typ also has a very strong effect, with a CI of ...
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Multivariate logistic regression analysis using multilevel model
... linear regression models is the statistical independence of ...general regression models may not be ...utilizes multivariate logistic regression model using a multilevel ...
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Bayesian Logistic Regression Model with Integrated Multivariate Normal Approximation for Big Data
... Chapter 4 Application 4.1 Health Status Data The source of the data should be reliable. To apply the Integrated Multivariate Normal Approximation (IMNA) Logistic method, we need binary response variable and ...
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Outcomes of High-Risk Pregnancies in Northern Iran: Multivariate Logistic Regression Model
... High-risk pregnant mothers are women with history of chronic diseases (diabetes mellitus, hypertension, cardiovascular disorders, …), history of abortion or stillbirt[r] ...
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Multivariate logistic regression with incomplete covariate and auxiliary information
... the multivariate regression parameters, and their corresponding standard ...joint multivariate approach over the marginal approach for individual outcomes is that in the multivariate case, we ...
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LOGISTIC REGRESSION MODEL FOR PREDICTION OF BANKRUPTCY
... paper model was developed using stepwise logistic regression with financial ratios to make bankruptcy ...prior model are better than two year prior model for the purpose of prediction ...
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An Application of Bootstrapping in Logistic Regression Model
... 4. Conclusions The bootstrap technique used for estimation and testing produced flexible results. Most of the results were similar to the classical results established under probability theory. From the classical ...
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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 ...
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Predictive factors for infertility of women: an univariate and multivariate logistic regression analysis
... present study, the univariate and multivariate logistic regression showed that the husband’s education could be considered as a predictor of female infertility. In most cases, higher income levels ...
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A Logistic Regression Model of Determiner Omission in PPs
... Turning to the representation of syntactic ar- gument structure of the noun, we find that the coefficients of D EP -S, D EP -NP, and D EP -PP re- ceive positive values throughout. The presence of syntactic complements ...
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A mixed-eects multinomial logistic regression model
... multinomial logistic regression model is described for analysis of clustered or longitu- dinal nominal or ordinal response ...The model is parameterized to allow exibility in the choice of ...
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Estimation of the logistic regression model for company bankruptcy
... When creating the training set an application is made of the standard statistical approach – the collection from the population of a random sample of companies, followed by a de- scription for each company and the class ...
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Logistic Regression
... of model performance on development and validation samples using Lorentz curve – Gini and Lorentz curves The industrial standard measures for assessing the predictive power of a model are the Gini and the ...
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A New Aware Context Collaborative Filtering Approach by Applying Multivariate Logistic Regression Model into General User Pattern
... inference model which supports the aware-context recommendation ...discovers multivariate logistic regression model by mining both traditional rating data and contextual ...data. ...
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Geographical variation of unmet medical needs in Italy: a multivariate logistic regression analysis
... services. Logistic regression results suggest that some population groups are more vulnerable than others to experiencing unmet health needs and to reporting some categories of ...
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Septic shock : providing early warnings through multivariate logistic regression models
... The early warning system (EWS), a multivariate logistic regression model, provided prior warnings for the onset of hypotension despite fluid resuscitation (HDFR) with [r] ...
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Multivariate Logistic Regression Analysis of Complex Survey Data with Application to BRFSS Data
... marginal multivariate approach using GEE techniques (Liang and Zeger, 1986; Prentice, 1988; Lipsitz et ...to model the relationship of multiple responses with explanatory variables, and the associa- tion ...
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Multivariate Regression Model to Predict Failure of Pipelines
... statistical model to predict probability of pipeline failure in the forthcoming decade was developed by processing the data through the JMP software to get the significant parameters contributing to ...proposed ...
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The importance of univariate logistic regression analysis in logistic regression analysis
... for logistic regression ...data logistic regression being with the dependent variable having a data structure with a two-level or multi-level categorical, has an important place in the ...
On modified skew logistic regression model and its applications
... Introduction Regression methods are usually used for studying the relationship between a re- sponse variable and one or more explanatory ...the logistic regression model, also known as logit ...
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