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Applied Multiple Imputation: Advantages, Pitfalls, New Developments and Applications in R

, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically;

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Applied Multiple Imputation

, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically;

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Multiple Imputation of Missing Data Using SAS

Find guidance on using SAS for multiple imputation and solving common missing data issues.Multiple Imputation of Missing Data Using SAS;

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Multiple Imputation of Missing Data in Practice

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple;

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Applied Bayesian Modeling and Causal Inference from Incomplete Data Perspectives

, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real--world examples which do not feature in many;

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Statistical Methods for Handling Incomplete Data

Updated with a new chapter on Data Integration Now includes a chapter on Advanced Topics, including kernel ridge regression imputation;

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Multiple Imputation in Practice

used under Windows, Linux, and Mac, and with software packages like SAS, SPSS, Stata, and R, or as a stand-alone tool. This book will be;

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Multiple Imputation in Practice

can be used under Windows, Linux, and Mac, and with software packages like SAS, SPSS, Stata, and R, or as a stand-alone tool. This;

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Flexible Imputation of Missing Data, Second Edition

standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general;

Vergelijkbare producten zoals Flexible Imputation of Missing Data, Second Edition

Flexible Imputation of Missing Data, Second Edition

standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general;

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Applied Missing Data Analysis in the Health Sciences

traditional techniques for missing data inference including likelihood-based, weighted GEE, multiple imputation, and Bayesian methods and applies the;

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Applied Biotechnology in Genetic Engineering, Pharmaceuticals and Agriculture

, drug discovery and development, and agriculture. The chapters included in this book elucidate new techniques and their applications in a;

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Flexible Imputation of Missing Data

data problems in disguise. Over the last 20 years, I have applied multiple imputation in a wide variety of projects. I believe the time is ripe;

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Bioanalytical Separations

is bioanalysis, in this case specifically meaning the analysis of drugs and their metabolites in biological fluids.- Discusses new;

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Linear Models with R

. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business;

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Advanced R Statistical Programming and Data Models

including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R;

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Advances in Neurochemistry Research

capillary and ultra-HPLC and will discusses the advantages and pitfalls of those approaches applied to brain monoamine monitoring.;

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Bayesian Hierarchical Models

and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal;

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Bayesian Hierarchical Models

hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and;

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Multiple Imputation For Nonresponse In Surveys

imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique;

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Current Trends and Future Developments on (Bio-) Membranes

Technology provides updates on new progress in membrane processes due to various challenges and how many industrial companies and academic centers;

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Current Trends and Future Developments on (Bio-) Membranes

- Challenges and Opportunities illustrates the application of membrane technology used in separation processes, along with the advantages of membranes;

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Applied Longitudinal Analysis

of the American Statistical Association Features newly developed topics and applications of the analysis of longitudinal data Applied;

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Generalized Linear Models with Random Effects

the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It;

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Lattice Boltzmann And Gas Kinetic Flux Solvers

the lattice Boltzmann and the gas kinetic flux solvers (LBFS or GKFS). LBFS and GKFS combine advantages of both Navier-Stokes (N-S) solvers;

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Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition

the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It;

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Construction Versus Choice in Cognitive Measurement

accountability, and placement. This book's multi-disciplinary perspective identifies the potential advantages and pitfalls of these new assessment forms;

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