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Analysis of Repeated Measures Data (Hardcover, 1st ed. 2017)
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Analysis of Repeated Measures Data (Hardcover, 1st ed. 2017)
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This book presents a broad range of statistical techniques to
address emerging needs in the field of repeated measures. It also
provides a comprehensive overview of extensions of generalized
linear models for the bivariate exponential family of
distributions, which represent a new development in analysing
repeated measures data. The demand for statistical models for
correlated outcomes has grown rapidly recently, mainly due to
presence of two types of underlying associations: associations
between outcomes, and associations between explanatory variables
and outcomes. The book systematically addresses key problems
arising in the modelling of repeated measures data, bearing in mind
those factors that play a major role in estimating the underlying
relationships between covariates and outcome variables for
correlated outcome data. In addition, it presents new approaches to
addressing current challenges in the field of repeated measures and
models based on conditional and joint probabilities. Markov models
of first and higher orders are used for conditional models in
addition to conditional probabilities as a function of covariates.
Similarly, joint models are developed using both
marginal-conditional probabilities as well as joint probabilities
as a function of covariates. In addition to generalized linear
models for bivariate outcomes, it highlights extended
semi-parametric models for continuous failure time data and their
applications in order to include models for a broader range of
outcome variables that researchers encounter in various fields. The
book further discusses the problem of analysing repeated measures
data for failure time in the competing risk framework, which is now
taking on an increasingly important role in the field of survival
analysis, reliability and actuarial science. Details on how to
perform the analyses are included in each chapter and supplemented
with newly developed R packages and functions along with SAS codes
and macro/IML. It is a valuable resource for researchers, graduate
students and other users of statistical techniques for analysing
repeated measures data.
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