Homework #2
STAT 437/837, Winter 2014
Assigned: 01-30-14
Due: 02-13-14, at start of class; include an appendix with your computer code
For the data analysis problems, cut and paste only the necessary output into your answers.
1. (11 points) Say you have b
Additive Mixed Models applied to the study of
red shrimp landings: comparison between
frequentist and Bayesian perspectives.
Valeria Mamouridis
January 14, 2011
Abstract
Relationships between Red shrimp landings in the Catalonian port of Barcelona and som
Homework #1
STAT 437/837, Winter 2014
Assigned: 01-16-14
Due: 01-30-14, at start of class; include an appendix with your computer code. For the data
analysis problems, cut and paste only the necessary output into your answers.
1. (18 points) Please explai
The Pennsylvania State University
The Graduate School
Department of Statistics
VARYING-COEFFICIENT MODELS: NEW MODELS, INFERENCE
PROCEDURES AND APPLICATIONS
A Thesis in
Statistics
by
Yang Wang
c 2007 Yang Wang
Submitted in Partial Fulllment
of the Require
3/30/2014
https:/onlinecourses.science.psu.edu/stat504/print/book/export/html/176
Published on STAT 504 - Analysis of Discrete Data
(https:/onlinecourses.science.psu.edu/stat504)
Home > 8.4 - The Proportional-Odds Cumulative Logit Model
8.4 - The Proporti
3/28/2014
R Data Analysis Examples: Mixed Effects Logistic Regression
HelptheStatConsultingGroupby
stat
>
r
>
dae
givingagift
>melogit.htm
R Data Analysis Examples: Mixed Effects Logistic Regression
Mixedeffectslogisticregressionisusedtomodelbinaryoutcome
3/28/2014
Introduction to Generalized Linear Mixed Models
HelptheStatConsultingGroupby
stat
>
mult_pkg
givingagift
>glmm.htm
Introduction to Generalized Linear Mixed Models
Background
Generalizedlinearmixedmodels(orGLMMs)areanextensionoflinearmixedmodelst
Generalized Linear Mixed Models
An Introduction for Tree Breeders and Pathologists
Fikret Isik, PhD
Quantitative Forest Geneticist,
Cooperative Tree Improvement Program, North Carolina State University
Statistic Session class notes
Fourth International Wo
Longitudinal Data Analysis
Lecture with introduction to
marginal models and GEE; more on PA vs. SS
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
February 25, 2014
marginal models fo
# eda-lecture.R: updated code for eda lecture for STAT 437/837, winter 2014
#
# last edited: 01-15-14 (update of eda-using-R lecture (lecture #3) on 01-14-14)
# read in dataset using read.csv:
# code that will work on Windows or Mac for reading in an Exce
# lmer-introduce-lecture.R: code for introduction to lmer function
#
for for STAT 437/837, winter 2017 (for 02-02-17
lecture, #10);
#
this will emulate prior lme function lecture, to a
point
#
# last edited: 02-01-17
# in order to use lmer, we need to loa
# lme-introduce-lecture.R: code for introduction to lme function
# for STAT 437/837, winter 2014 (01-21-14 lecture (#5)
#
# last edited: 01-20-14
# assume rats.lda dataframe has already been created
# remind what dataset looks like:
head(rats.lda)
> head
# glmm-gee-in-R-lecture.R: code for introduction to glmm (using lme4 package) and gee (using
# gee and geepack packages)
# in R for STAT 437/837, winter 2014 (02-27-14 lecture (#14)
#
# last edited: 02-26-14
library(lme4) # needed for glmer function
lib
# lmer-introduce-lecture.R: code for introduction to lmer function
# for for STAT 437/837, winter 2014 (for 01-28-14 lecture, #7);
# this will emulate prior lme function lecture, to a point
#
# last edited: 01-27-14
# in order to use lmer, we need to loa
# eda-lecture.R: updated code for eda lecture for STAT 437/837, winter 2014
#
# last edited: 01-15-14 (update of eda-using-R lecture (lecture #3) on 01-14-14)
# read in dataset using read.csv:
# code that will work on Windows or Mac for reading in an Exce
# lme-introduce-lecture.R: code for introduction to lme function
# for STAT 437/837, winter 2014 (01-21-14 lecture (#5)
#
# last edited: 01-20-14
# assume rats.lda dataframe has already been created
# remind what dataset looks like:
head(rats.lda)
> head
# lmer-introduce-lecture.R: code for introduction to lmer function
# for for STAT 437/837, winter 2014 (for 01-28-14 lecture, #7);
# this will emulate prior lme function lecture, to a point
#
# last edited: 01-27-14
# in order to use lmer, we need to loa
# glmm-gee-in-R-lecture.R: code for introduction to glmm (using lme4 package) and gee (using
# gee and geepack packages)
# in R for STAT 437/837, winter 2014 (02-27-14 lecture (#14)
#
# last edited: 02-26-14
library(lme4) # needed for glmer function
lib
Longitudinal Data Analysis
Second lecture on missing longitudinal data
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
March 27, 2014
ignorability
The full data likelihood contributi
Longitudinal Data Analysis
First lecture on missing longitudinal data
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
March 25, 2014
missing data in longitudinal studies
Data may be m
Longitudinal Data Analysis
Lecture #2 on estimation, and inference, in
linear mixed effects models
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
January 28, 2014
Estimation of the r
Longitudinal Data Analysis
First lecture on estimation in
linear mixed effects models
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
January 23, 2014
What have we seen so far and whe
Longitudinal Data Analysis
Lecture on inference and model assumptions in
linear mixed effects models
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
January 30, 2014
Model selection t
Longitudinal Data Analysis in Health Research
Exploratory data analysis
and simple and traditional methods
for longitudinal data
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
Januar
Longitudinal Data Analysis in Health Research
Introductory lecture on
longitudinal data analysis
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
January 7, 2014
introduction to cours
Stat 837 - Winter 2014 - Assignment 4
Assigned: 03-21-14
Due: 03-28-14, noon (slide under door in M3 4218)
This assignment is worth 9% of your nal grade. Your presentation will be a discussion and critique
of a journal article focused on statistical metho
Homework #1
STAT 437/837, Winter 2014
Assigned: 01-16-14
Due: 01-30-14, at start of class; include an appendix with your computer code. For the data
analysis problems, cut and paste only the necessary output into your answers.
1. (18 points) Please explai
Homework #3
STAT 437/837, Winter 2014
Assigned: 03-06-14
Due: 03-20-14, at start of class; include an appendix with your computer code
For the data analysis problems, cut and paste only the necessary output into your answers.
1. (16 points) Suppose, condi
Longitudinal Data Analysis in Health Research
Linear mixed effects model
for longitudinal data
STAT 437/837, Winter 2014
Instructor: Joel A. Dubin
Department of Statistics & Actuarial Science
University of Waterloo
January 14, 2014
Using the blood pressur