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Joint Modeling of Longitudinal and Time-to-Event Data

variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling;

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Joint Modeling of Longitudinal and Time-to-Event Data

variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling;

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Joint Models of Longitudinal a

-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint;

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Techniques Of Event History Modeling

frequently used with longitudinal data, in particular, discrete-time and continuous-time event history data. Techniques of Event History Modeling;

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Techniques of Event History Modeling

frequently used with longitudinal data, in particular, discrete-time and continuous-time event history data. Techniques of Event History Modeling;

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Dynamic Analysis in the Social Sciences

longitudinal data from the selection and collection of appropriate variables to the most effective ways to analyze and present data for publication;

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Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data

Analysis for Longitudinal and Time-Series Image Data, STIA 2014, held in conjunction with MICCAI 2014 in Boston, MA, USA, in September 2014. The 7;

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Event History Modeling

models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened;

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Event History Modeling

models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened;

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Time Series Analysis for the Social Sciences

models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened;

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Dynamical Biostatistical Models

measures and time-to-event data. It also explores the possibility of unifying these models through a stochastic process point of view and;

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Simulation Conceptual Modeling

commonly used conceptual modeling techniques and methods include; Data Flow Modeling, Entity Relationship Modeling, Event-Drive Process Chain;

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Multilevel and Longitudinal Modeling with IBM SPSS

This book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED;

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Multilevel and Longitudinal Modeling with IBM SPSS

This book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED;

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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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Longitudinal Analysis

to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual;

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Longitudinal Analysis

to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual;

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Nonparametric Regression Methods For Longitudinal Data Analysis

nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling;

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Longitudinal Multivariate Psychology

time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social;

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Longitudinal Multivariate Psychology

time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social;

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Generalized Latent Variable Modeling

response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data;

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Advanced Survival Models

experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event;

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Advanced Survival Models

experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event;

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Multivariate Generalized Linear Mixed Models Using R

sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from;

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Multilevel and Longitudinal Modeling with PASW / SPSS

This is the first book to demonstrate how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Version 18. The;

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Analyzing Longitudinal Clinical Trial Data: A Practical Guide

Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest;

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Analyzing Longitudinal Clinical Trial Data: A Practical Guide

Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest;

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