[R] Two Courses from Insightful Corp.

[Frank E Harrell Jr]

I am presenting two courses for Insightful Corporation in Washington D.C. in June.  0.95 of the material presented is applicable to R.  The announcement from Insightful is found below.  -Frank Harrell
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The following two hands-on courses are being presented by Dr. Frank Harrell in Washington, DC. Reserve your seat now! Register for both courses and receive a 10% discount!

To Register:	- Web: http://www.insightful.com/services/register.asp
		- Email: kkelly at insightful.com
		- Call Kim Kelly at: 800-569-0123 x278

Course #1:
S-PLUS for Statistical Data Analysis & Graphics presented by Dr. Frank Harrell Jr.
(full description: http://www.insightful.com/services/course.asp?CID=26)
Dates:	June 19-21, 2002
City:	Washington, DC

This short course begins with a quick summary of the S-PLUS language and objects and a comparison of S-PLUS and SAS. This is followed by methods for inspecting, recoding, reshaping, and manipulating data, some of which use extensions of S-PLUS found in the freely available Hmisc library written by the instructor. Usage of S-PLUS for more advanced statistical methods such as simulation and bootstrapping is surveyed. Then basic sample size and power calculations are discussed, followed by an example using the Hmisc library to simulate power for the Cox-logrank test for comparing event times in a clinical trial in which drop-in, drop-out, and delayed treatment response are present. Then major emphasis is given to table making and S-PLUS and Hmisc graphical functions useful in everyday exploratory work and in presenting final summary statistics. 
The course concludes with discussion of some tools for making analyses reproducible, an important facit for regulatory and other scientific review of final results. Advantages of using S-PLUS in conjunction with the LATEX document processing / typesetting system for constructing reproducible statistical reports and hyperlinked PDF documents are discussed. 

Price:	Commercial:  $1500
	Government:  $1350
	Academic:    $1200

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Course #2:
Regression Modeling Strategies presented by Dr. Frank Harrell Jr.
(full description: http://www.insightful.com/services/course.asp?CID=27)
Dates:	June 24-26, 2002
City:	Washington, DC

The first part of the course presents the following elements of multivariable predictive modeling for a single response variable: using regression splines to relax linearity assumptions, perils of variable selection and overfitting, where to spend degrees of freedom, shrinkage, imputation of missing data, data reduction, and interaction surfaces. Then a default overall modeling strategy will be described. This is followed by methods for graphically understanding models (e.g., using nomograms) and using re-sampling to estimate a model's likely performance on new data. Then the freely available S-PLUS Design library will be overviewed. Design facilitates most of the steps of the modeling process. Next, statistical methods related to binary logistic models will be covered. 

Three of the following case studies will be presented: an exploration of voting tendencies over U.S. counties in the 1992 presidential election, an interactive exploration of the survival status of Titanic passengers, an interactive case study in developing a survival time model for critically ill patients, and a case study in Cox regression. In the hands-on computer lab students will develop, validate, and graphically describe multivariable regression models themselves. This short course will survey the advantages of modeling in randomized trials and will provide some guidance in developing a prospective statistical plan for use in a Phase III clinical trial. The methods covered in this course will apply to almost any regression model, including ordinary least squares, logistic regression models, and survival models. 

Price:	Commercial:  $1500
	Government:  $1350
	Academic:    $1200
-- 
Frank E Harrell Jr              Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine  http://hesweb1.med.virginia.edu/biostat

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