latent markov models for longitudinal data

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Latent Markov Models For Longitudinal Data

Author : Francesco Bartolucci
ISBN : 9781466583719
Genre : Mathematics
File Size : 70. 90 MB
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Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB® routines used for the examples are available on the authors’ website. The book provides you with the essential background on latent variable models, particularly the latent class model. It discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the assumptions of the basic version of the latent Markov model and introduce maximum likelihood estimation through the Expectation-Maximization algorithm. They also cover constrained versions of the basic latent Markov model, describe the inclusion of the individual covariates, and address the random effects and multilevel extensions of the model. After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference. As longitudinal data become increasingly relevant in many fields, researchers must rely on specific statistical and econometric models tailored to their application. A complete overview of latent Markov models, this book demonstrates how to use the models in three types of analysis: transition analysis with measurement errors, analyses that consider unobserved heterogeneity, and finding clusters of units and studying the transition between the clusters.

Multilevel Latent Markov Models For Nested Longitudinal

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File Size : 64. 44 MB
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Longitudinal Research With Latent Variables

Author : Kees van Montfort
ISBN : 9783642117602
Genre : Mathematics
File Size : 87. 68 MB
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Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk ̈ og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences. Indeed, the central va- ables that social and behavioural theories deal with, can hardly ever be identi?ed as observed variables. Statistical modelling has to take account of measurement - rors and invalidities in the observed variables and so address the underlying latent variables. Moreover, during the past decades it has been widely agreed on that serious causal modelling should be based on longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent years. Many comprehensive panel data sets as, for example, on human development and voting behaviour have become available for analysis. The number of publications based on longitudinal data has increased immensely. Papers with causal claims based on cross-sectional data only experience rejection just for that reason.

Longitudinal Data Analysis

Author : Professor Catrien C J H C J H Bijleveld
ISBN : 1446231585
Genre : Analysis of variance
File Size : 72. 69 MB
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By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.

Estimating Response Variance From Latent Markov Models

Author : Barry Bye
ISBN : UOM:39015018976673
Genre : Disability evaluation
File Size : 77. 97 MB
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An Introduction To Longitudinal Research

Author : Elisabetta Ruspini
ISBN : 9781134510627
Genre : Reference
File Size : 70. 94 MB
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One of the major changes in the social science research landscape in recent years has been the introduction of computerised panel surveys in Europe and the US which make longitudinal data widely available to graduate students for the first time. Elisabetta Ruspini here provides a concise yet comprehensive introduction to the issues involved in this kind of research. This book: * Defines the concept of longitudinal research * Gives guidance on sources of longitudinal data in Europe and the US and their strengths and weaknesses * Discusses the choices that need to be made in this kind of research - for instance the advantages and disadvantages of certain types of research data and of different types of analysis * Highlights some of the problems involved, e.g. the issue of comparability within longitudinal research

Building Models For Marketing Decisions

Author : P. S. H. Leeflang
ISBN : 0792377729
Genre : Business & Economics
File Size : 74. 70 MB
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With advances in information technology and expertise in modeling, IRI introduced model-based services in the US that explain and predict essential parts of the marketplace. ACNielsen followed, and marketing researchers have been developing increasingly valid, useful and relevant models of marketplace behavior ever since. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performances. Building Models for Marketing Decisions, Second Edition describes up-dated marketing models that managers can use as an aid in decision making.

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