eBook - PDF
Multivariate Generalized Linear Mixed Models Using R
- 304 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Multivariate Generalized Linear Mixed Models Using R
About this book
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R.A Un
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Information
8
Multivariate
Generalized
Linear
Mixed
Models
Using
R
the
number
of
male
deaths
due
to
malignant
melanoma
(
deaths
)
and
a
mean-centred
measure
of
the
UVB
dose
reaching
the
earth’s
surface
(
uvb
)
by
year
in
county
i
within
region
j
of
nation
k
.
The
univariate
mixed
models
discussed
in
Chapters
2
to
10
is
gen-
eralized
to
multivariate,
in
particular
bivariate,
models
in
Chapter
11.
Chapter
12
describes
models
required
to
analyze
event
history
data,
with
specific
reference
to
duration
models,
renewal
models
and
competing
risk
models.
How
to
handle
stayers
and
non-susceptibles
through
the
use
of
endpoints
is
considered
in
Chapter
13.
Chapter
14
addresses
the
issue
of
state
dependence,
outlines
the
initial
conditions
problem
and
considers
possible
solutions.
A
discussion
of
fixed
effects
versus
random
effects
in
the
linear
model
is
presented
in
Chapter
15.
The
book
concludes
with
two
appendices.
Appendix
A
provides
in-
structions
on
how
to
install
SabreR
and
discusses
the
structure
of
SabreR
commands.
Appendix
A
also
reviews
topics
of
general
interest,
including
quadrature
techniques,
estimation
methods,
and
presents
a
discussion
of
endogenous
versus
exogenous
variables.
Appendix
B
provides
an
intro-
duction
to
those
features
of
R
that
are
salient
to
the
use
of
SabreR.
Table of contents
- Front Cover
- Contents
- List of Figures
- List of Tables
- List of Applications
- List of Datasets
- Preface
- Acknowledgments
- 1. Introduction
- 2. Generalized linear models for continuous/interval scale data
- 3. Generalized linear models for other types of data
- 4. Family of generalized linear models
- 5. Mixed models for continuous/interval scale data
- 6. Mixed models for binary data
- 7. Mixed models for ordinal data
- 8. Mixed models for count data
- 9. Family of two-level generalized linear models
- 10. Three-level generalized linear models
- 11. Models for multivariate data
- 12. Models for duration and event history data
- 13. Stayers, non-susceptibles and endpoints
- 14. Handling initial conditions/state dependence in binary data
- 15. Incidental parameters: an empirical comparison of fixed effects and random effects models
- A. SabreR installation, SabreR commands, quadrature, estimation, endogenous effects
- B. Introduction to R for Sabre
- References
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Yes, you can access Multivariate Generalized Linear Mixed Models Using R by Damon Mark Berridge,Robert Crouchley in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.