LaTeX processed

1. Project Requirements
Individual project with topics approved by the instructor
Word or LaTeX processed nal report with minimum eight double-spaced pages (in-
cluding tables, graphs, acknowledgement and references but excluding the cover page)
The nal report should include at least the following parts:
{ A cover page with the title of the project, name and student ID, and course
number (STAT 454 or STAT 854)
{ An abstract with no more than 100 words (on page 2, before all the sections)
{ An introduction section to outline the problem(s) to be addressed
{ A main section to give technical details
{ A section on simulation studies, with detailed description on the simulation model
and major results from the simulation
{ A nal section for additional and/or concluding remarks
{ Acknowledgement and references
The preferred program language for simulation is R. All computing codes are required
to be submitted online and the simulation program needs to be repeatable by the TAs
Select your topic

Some Old and Suggested Topics
You are free to choose any topic, not necessarily from the suggested ones listed below. Your
chosen topic needs to be relevant to the course and requires approval of the course instructor.
If you are not sure what to do, talk to the instructor.
A comparison among some basic sampling designs, such as SRSWOR, Stratied SR-
SWOR, single stage cluster sampling, two-stage sampling, with focus on point and
variance estimation and condence intervals.
A comparison among some PPS sampling methods, such as randomized systematic
PPS, Poisson sampling and PPS sampling with replacement.
An investigation on ratio and regression estimation under SRSWOR and Stratied
SRS, with focuses on point and variance estimation and condence intervals.
An investigation on central limit theorems under nite population sampling.
Estimation of the nite population distribution function and quantiles.
Jackknife and Bootstrap variance estimation for the ratio and regression estimators,
with focus on condence intervals.
Ratio and Regression estimation under two-phase sampling.
An investigation on model-based prediction approach for nite populations.
Calibration estimators and related variance estimation methods.
Empirical likelihood (EL) methods and EL ratio condence intervals.
Imputation for missing values: A comparison among alternative strategies.
Variance estimation under imputation for missing values
Regression analysis using complex survey data.
Logistic regression analysis using complex survey data.
Regression analysis using survey data with imputation to missing values.
Multiple frame surveys.
Telephone surveys.
Web-based surveys.
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