Regression analysis.
Overview
Works: | 277 works in 103 publications in 103 languages |
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Titles
Methods and applications of linear models :regression and the analysis of variance /
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Applied regression analysis and other multivariable methods /David G. Kleinbaum ... [et al.].
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Seemingly unrelated regression equations models :estimation and inference /
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An introduction to computational statistics :regression analysis /
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Statistical tools for nonlinear regression :a practical guide with S-PLUS examples /
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Applied linear statistical models :regression, analysis of variance, and experimental designs /
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Plots, transformations, and regression :an introduction to graphical methods of diagnostic regression analysis /
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Regression modeling strategies :with applications to linear models, logistic regression, and survival analysis /
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Expert trading systems :modeling financial markets with kernel regression /
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Student solutions manual to accompany Introduction to linear regression analysis, third edition /
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Methods and applications of linear models :regression and the analysis of variance /
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Quantitative methods in population health :extensions of ordinary regression /
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Regression with social data :modeling continuous and limited response variables /
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Applied multiple regression/correlation analysis for the behavioral sciences /
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Fitting models to biological data using linear and nonlinear regression :a practical guide to curve fitting /
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Regression models for categorical and limited dependent variables /
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Statistical models for the social and behavioural sciences :multiple regression and limited-dependent variable models /
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Nonparametric regression and generalized linear models :a roughness penalty approach /
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Extending the linear model with R :generalized linear, mixed effects and nonparametric regression models /
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Regression models for categorical dependent variables using Stata /
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Linear and nonlinear models :fixed effects, random effects, and mixed models /
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Statistical tools for nonlinear regression :a practical guide with S-PLUS and R examples /
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Fixed effects regression methods for longitudinal data using SAS /
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Decision trees for business intelligence and data mining :using SAS Enterprise Miner /
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Introduction to mixed modelling :beyond regression and analysis of variance /
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Data analysis using regression and multilevel/hierarchical models /
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Introduction to mixed modelling :beyond regression and analysis of variance /
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Regression methods in biostatistics :linear, logistic, survival, and repeated measures models /
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Recent Advances in Linear Models and Related AreasEssays in Honour of Helge Toutenburg /
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Clinical prediction modelsa practical approach to development, validation, and updating /
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Statistical tools for nonlinear regressiona practical guide with S-PLUS and R examples /
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Student solution manual to accompany Introduction to linear regression analysis, fourth edition, Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining /
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Modelling spatial processesthe identification and analysis of spatial relationships in regression residuals by means of Moran's I /
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Statistical modelling and regression structuresfestschrift in honour of Ludwig fahrmeir /
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Circular and linear regressionfitting circles and lines by least squares /
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Running regressions :a practical guide to quantitative research in economics, finance and development studies /
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Circular and linear regression :fitting circles and lines by least squares /
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Operationalizing dynamic pricing modelsbayesian demand forecasting and customer choice modeling for low cost carriers /
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Regression methods in biostatisticslinear, logistic, survival, and repeated measures models /
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Multivariable model-building :a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables /
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Applications of linear and nonlinear modelsfixed effects, random effects, and total least squares /
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Bayesian smoothing and regression for longitudinal, spatial and event history data
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Multivariable model-buildinga pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables /
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Introduction to mediation, moderation, and conditional process analysis :a regression-based approach /
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Regression, ANOVA, and the general linear model :a statistics primer /
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The GVAR HandbookStructure and Applications of a Macro Model of the Global Economy for Policy Analysis /
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Multivariate nonparametric regression and visualization :with R and applications to finance /
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Analysis of variance and regression :multiple decision theoretic approach /
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Model-based recursive partitioning with adjustment for measurement errorapplied to the Cox's Proportional Hazards and Weibull Model /
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Design of experiments in nonlinear models :asymptotic normality, optimality criteria and small-sample properties /
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Adaptive tests of significance using permutations of residuals with R and SAS
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Introduction to mixed modellingbeyond regression and analysis of variance /
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Regression modeling strategieswith applications to linear models, logistic and ordinal regression, and survival analysis /
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Vector generalized linear and additive modelswith an implementation in R /
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Model-free prediction and regressiona transformation-based approach to inference /
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Solutions manual to accompany Introduction to linear regression analysis.
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Adaptive tests of significance using permutations of residuals with R and SAS /
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Introduction to mediation, moderation, and conditional process analysis :a regression-based approach /
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Matching, regression discontinuity, difference in differences, and beyond /
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Regression analysis :statistical modeling of a response variable /
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Interaction effects in linear and generalized linear models :examples and applications using Stata /
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Clinical prediction modelsa practical approach to development, validation, and updating /
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Statistical regression and classification :from linear models to machine learning /
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Identifiability and regression analysis of biological systems modelsstatistical and mathematical foundations and R scripts /
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Effective statistical learning methods for actuaries.II,Tree-based methods and extensions
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Beyond multiple linear regression :applied generalized linear models and multilevel models in R /
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Regression analysis in medical research :for Starters and 2nd Levelers /
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Statistical regression modeling with Rlongitudinal and multi-level modeling /
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Quantitative comparison of the issue yield of green bonds and conventional bonds
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Applications of linear and nonlinear modelsfixed effects, random effects, and total least squares /
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Modern survival analysis in clinical researchCox regressions versus accelerated failure time models /
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Applied linear regression for business analytics with Ra practical guide to data science with case studies /
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Generalized linear mixed models with applications in agriculture and biology
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Regression-based normative data for psychological assessmenta hands-on approach using R /
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