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This new volume reviews longitudinal models and analysis procedures
for use in the behavioral and social sciences. Written by
distinguished experts in the field, the book presents the most
current approaches and theories, and the technical problems that
may be encountered along the way. Readers will find new ideas about
the use of longitudinal analysis in solving problems that arise due
to the specific nature of the research design and the data
available. Divided into two parts, Longitudinal Models in the
Behavioral and Related Sciences opens with the latest theoretical
developments. In particular, the book addresses situations that
arise due to the categorical nature of the data, issues related to
state space modeling, and potential problems that may arise from
network analysis and/or growth-curve data. The focus of part two is
on the application of longitudinal modeling in a variety of
disciplines. The book features applications such as heterogeneity
on the patterns of a firm's profit, on house prices, and on
delinquent behavior; non-linearity in growth in assessing cognitive
aging; measurement error issues in longitudinal research; and
distance association for the analysis of change. Part two clearly
demonstrates the caution that should be taken when applying
longitudinal modeling as well as in the interpretation of the
results. Longitudinal Models in the Behavioral and Related Sciences
is ideal for advanced students and researchers in psychology,
sociology, education, economics, management, medicine, and
neuroscience.
Over the past few decades the role of statistics in the evaluation
and interpretation of clinical data has become of paramount
importance. As a result the standards of clinical study design,
conduct and interpretation have undergone substantial improvement.
This book describes various ways of approaching and interpreting
the data produced by clinical trial studies, with a special
emphasis on the essential role that biostatistics plays in clinical
trials. The book includes 18 carefully reviewed chapters on recent
developments in clinical trials and their statistical evaluation,
with each chapter providing one or more examples involving typical
data sets, enabling readers to apply the proposed procedures. The
chapters employ a uniform style to enhance comparability between
the approaches.
After Karl Joreskog's first presentation in 1970, Structural
Equation Modelling or SEM has become a main statistical tool in
many fields of science. It is the standard approach of factor
analytic and causal modelling in such diverse fields as sociology,
education, psychology, economics, management and medical sciences.
In addition to an extension of its application area, Structural
Equation Modelling also features a continual renewal and extension
of its theoretical background. The sixteen contributions to this
book, written by experts from many countries, present important new
developments and interesting applications in Structural Equation
Modelling. The book addresses methodologists and statisticians
professionally dealing with Structural Equation Modelling to
enhance their knowledge of the type of models covered and the
technical problems involved in their formulation. In addition, the
book offers applied researchers new ideas about the use of
Structural Equation Modeling in solving their problems. Finally,
methodologists, mathematicians and applied researchers alike are
addressed, who simply want to update their knowledge of recent
approaches in data analysis and mathematical modelling."
After Karl JAreskog's first presentation in 1970, Structural
Equation Modelling or SEM has become a main statistical tool in
many fields of science. It is the standard approach of factor
analytic and causal modelling in such diverse fields as sociology,
education, psychology, economics, management and medical sciences.
In addition to an extension of its application area, Structural
Equation Modelling also features a continual renewal and extension
of its theoretical background. The sixteen contributions to this
book, written by experts from many countries, present important new
developments and interesting applications in Structural Equation
Modelling. The book addresses methodologists and statisticians
professionally dealing with Structural Equation Modelling to
enhance their knowledge of the type of models covered and the
technical problems involved in their formulation. In addition, the
book offers applied researchers new ideas about the use of
Structural Equation Modeling in solving their problems. Finally,
methodologists, mathematicians and applied researchers alike are
addressed, who simply want to update their knowledge of recent
approaches in data analysis and mathematical modelling.
This new volume reviews longitudinal models and analysis procedures
for use in the behavioral and social sciences. Written by
distinguished experts in the field, the book presents the most
current approaches and theories, and the technical problems that
may be encountered along the way. Readers will find new ideas about
the use of longitudinal analysis in solving problems that arise due
to the specific nature of the research design and the data
available. Divided into two parts, Longitudinal Models in the
Behavioral and Related Sciences opens with the latest theoretical
developments. In particular, the book addresses situations that
arise due to the categorical nature of the data, issues related to
state space modeling, and potential problems that may arise from
network analysis and/or growth-curve data. The focus of part two is
on the application of longitudinal modeling in a variety of
disciplines. The book features applications such as heterogeneity
on the patterns of a firm's profit, on house prices, and on
delinquent behavior; non-linearity in growth in assessing cognitive
aging; measurement error issues in longitudinal research; and
distance association for the analysis of change. Part two clearly
demonstrates the caution that should be taken when applying
longitudinal modeling as well as in the interpretation of the
results. Longitudinal Models in the Behavioral and Related Sciences
is ideal for advanced students and researchers in psychology,
sociology, education, economics, management, medicine, and
neuroscience.
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