Technique-driven statistical analysis can be
like the blind men sent by the king to examine an elephant. The man who feels the leg says an elephant is
like a pillar, the one who feels the tails says it is like a rope, the one who
feels the tusk says it is like a pipe.
It is left to the king to integrate the accounts, which he does
masterfully (this tale is told by the king).
"Categorical Data - Applied Modeling,"
which approaches analysis from the data end - recognize the type of data you
have, and then assess what different techniques are appropriate. After taking
this course, students will know how to perform logistic regression (with both
binomial and multinomial response), probit, logit and loglinear analysis using
statistical software. Model diagnostics and interpretation of results are also
covered, and longitudinal analysis is introduced. A perfect course is Dr. Brian
Marx's "Categorical Data - Applied Modeling" online at Statistics.com.
For more details please visit at http://www.statistics.com/categorical2/.
Who Should Take This Course:
Any researcher or analyst who encounters
categorical data and needs to analyze or model it.
Course Program:
Course outline: The course is structured as follows
SESSION 1: Logistic Regression Review
- Interpretation of parameters
and odds ratio
- Standard errors
- Probit analysis
- Variable selection
- Multiple logistic regression
with categorical predictors
- Building and applying logit
models
- Model selection (backward
elimination)
- Model checking
- Sparse data
SESSION 2: Multicategory Logit Models
- Logistic regression with
multinomial response
- proportional odds models
SESSION 3: Loglinear Models for Contingency Tables
- Loglinear models for
independence
- Association
- 3-way and 4-way tables
- Connections
- Logit models
- Analysis of deviance
- Graphical modeling
- Linear by linear association
- Models for ordinal responses
SESSION 4: Model for Matched Pairs
- McNemar test
- Symmetry models
- Quasi-symmetry
- Ordinal quasi-symmetry
- Quasi-independence models
- Rater agreement
- Bradley-Terry model
Dr. Brian Marx is Professor of Statistics at
Louisiana State University, and has taught Categorical Data Analysis for over
ten years. He is currently serving as Chair of the Statistical Modelling
Society and is the Coordinating Editor of Statistical Modelling: An
International Journal. Dr. Marx has numerous publications in peer reviewed
journals.
You will be able
to ask questions and exchange comments with Dr. Brian Marx via a private
discussion board throughout the course. The courses take place
online at statistics.com in a series of 4 weekly lessons and assignments, and
require about 15 hours/week. Participate at your own convenience; there
are no set times when you must be online. You have the flexibility to work a
bit every day, if that is your preference, or concentrate your work in just a
couple of days.
For Indian
participants statistics.com accepts registration for its courses at special
prices in Indian Rupees through its partner, the Center for eLearning and
Training (C-eLT), Pune.
Call: 020 66009116
Websites:
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