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Statistical Methods for Handling Incomplete Data

in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and;

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The EM Algorithm and Related Statistical Models

Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for;

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Analysis of Incomplete Multivariate Data

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions;

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Analysis of Incomplete Multivariate Data

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions;

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Statistical Analysis of Circular Data

. Statistical methods for handling such data have developed rapidly in the last twenty years, particularly data display, correlation, regression and;

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Mathematical Problems in Data Science

and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets;

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Statistical Analysis with Missing Data

methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple;

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Query Processing over Incomplete Databases

general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing;

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Analysis Of Longitudinal Data

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Incomplete Categorical Data Design

Response Techniques for Sensitive Questions in Surveys is the first book on non-randomized response designs and statistical analysis methods. The;

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Incomplete Categorical Data Design

Response Techniques for Sensitive Questions in Surveys is the first book on non-randomized response designs and statistical analysis methods. The;

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Statistical Methods for Engineers and Scientists

This work details the fundamentals of applied statistics and experimental design, presenting a unified approach to data handling that;

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Statistical Methods for Engineers and Scientists

This work details the fundamentals of applied statistics and experimental design, presenting a unified approach to data handling that;

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Missing Data

Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables;

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Handbook of Missing Data Methodology

been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook;

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Longitudinal Data Analysis

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight;

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Statistics For The Biosciences

Statistical techniques for the presentation and analysis of biological data are indispensable tools for the biologist. The purpose of this;

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Mixed Effects Models for Complex Data

studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate;

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Mixed Effects Models for Complex Data

studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate;

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Analysis Of Longitudinal Data 2nd

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Statistical Methods in Agriculture and Experimental Biology, Second Edition

An introductory text for scientists working in agriculture and experimental biology, Statistical Methods in Agriculture and Experimental;

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Analyzing Longitudinal Clinical Trial Data: A Practical Guide

authors provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data;

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Analyzing Longitudinal Clinical Trial Data: A Practical Guide

provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data. Topics;

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Principles of Statistical Data Handling

University GENERAL Principles of Statistical Data Handling deals with the most neglected aspect of implementing a quantitative research design;

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Practical Statistical Methods

an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting;

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Practical Statistical Methods

an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting;

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Statistical and Data Handling Skills in Biology

Statistical and Data Handling Skills in Biology puts statistics into context to show biology students the relevance of statistical analysis;

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