Stepwise Selection
Application of Multivariate Methods for Assessment of Variations in Rivers/Streams Water Quality in Niger State, Nigeria
... Table 5 shows that Escherichia coli, magnesium, total dissolved solids and total coliform were the contributing parameters for discriminating among the three groups for the spatial variation of water quality parameters. ...
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Variable selection strategies and its importance in clinical prediction modelling
... the stepwise selection method, the most common method for variable selection that permits using both forward and backward procedures iteratively in model ...a stepwise selection proce- ...
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Statistical Modelling of CO2 Emissions in Malaysia and Thailand
... and stepwise selection method, the model selection criteria process is ...forward selection model ...and stepwise regression model ...
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On the Evaluation of the Wrapper Technique for Feature Selection in Discriminant Analysis
... feature selection in discriminant analysis is a challenging one, particularly in this era of availability of big ...and stepwise selection procedures) have been evaluated and through the use of ...
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Quantifying the Relationship between Adaptive Traits and Agro-climatic Conditions
... for the two response variables (Days to Healing and Days to Maturity), independently. It is important to make sure that the assumptions of the model are satisfied. Violation of any of the model assumptions might possibly ...
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A randomized controlled trial to compare a restrictive strategy to usual care for the effectiveness of cholecystectomy in patients with symptomatic gallstones (SECURE trial protocol)
... with stepwise selection for laparo- scopic ...discriminative selection tool for cholecystectomy is ...and stepwise selection for surgery can improve patient outcomes with a reduced ...
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Real life results in using 5-ASA for maintaining mild to moderate UC patients in Japan, a multi-center study, OPTIMUM Study
... by stepwise selection in the Cox regression model: age, sex, BMI, duration of disease, classification by the extent of lesion, classifica- tion by clinical course, smoking habit, drinking habit, ...
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Clustering of the Values of a Response Variable and Simultaneous Covariate Selection Using a Stepwise Algorithm
... model selection criterion for which a test of significance is available can be used in addition to Wilks’ Lambda and where forward covariate inclu- sion was replaced by stepwise ...
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Association of shared decision making with type of breast cancer surgery: a cross sectional study
... We computed univariate regressions of the effects of each of the dichotomously categorized SDM variables and other potential indicators upon receiving a mastectomy. We used multiple logistic regression analysis with ...
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A comparative assessment of variable selection methods in urban water demand forecasting
... variable selection procedure is to identify the correct predictor variables, which have an important influence on the response variable and could provide robust model ...variable selection methods such as ...
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Statistical Analysis of the Factors Affecting Inflation in Pakistan
... Pakistan. Stepwise linear Regression, backward elimination and forward selection procedure has been applied through SPSS statistical package to test the significance of relationship of producer price index, ...
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Model structure selection in powertrain calibration and control
... both stepwise regres- sion and orthogonal least squares(OLS) techniques can be applied to the torque and air/fuel ratio model ...of stepwise regression method and the OLS approach can achieve better ...
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Demographic Variables Predicting Psychological Distress among Pregnant Women in Makurdi Metropolis, Benue State, Nigeria
... the stepwise version of regression analysis meant to remove variables that had no contribution at all to psychological distress did not remove any of the other demographic ...
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Modelling the effects of the weather on admissions to UK trauma units : a cross sectional study
... Multivariate regression models for adult and paediatric admission counts were developed using stepwise regression, with forward selection and backward elimination, to select a subset of [r] ...
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Genetic worth and stability of selection indices in rice (Oryza sativa L.)
... Selection index theory was originally defined as a linear function of traits. The index is a linear weighted function of observations of an individual or its relatives that aims to rank the population for breeding ...
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The evaluation of the implementation of primary school standard curriculum: the world of science and technology subject
... For inferential analysis, multiple regression (Stepwise) is used to determine the inherent ties in linear between some independent variables with dependent variables (Alias 1999; Borg & Gall 1983; Mohd Majid ...
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... a stepwise regression ...and stepwise regression analysis were used to assess the variation of the structure of the ...Item selection was a key step in questionnaire ...analysis, stepwise ...
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The Development of an Alternative Method for the Sovereign Credit Rating System Based on Adaptive Neuro Fuzzy Inference System
... The main purpose of this article is to determine the factors affecting credit rating and to develop the credit rating system based on statistical methods, fuzzy logic and artificial neural network. Variables used in this ...
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Model selection in Medical Research: A simulation study comparing Bayesian Model Averaging and Stepwise Regression
... built-in selection method ("Occam’s window”) in Bayesian model averaging chose the null model or mod- els with just a few variables whereas stepwise regression chose models with many ...
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Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study
... The LASSO, the most well-known sparse learning technique, predicted DR most efficiently. ROC analysis supported that the LASSO model had a statistically sig- nificant improvement in predicting DR. This finding is ...
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