Hi Graeme;
I took the course about ten years ago. I did so after getting a Masters
in Epidemiology from the University of Washington and doing very well in
all my stats courses and submitting my thesis work on solving regression
problems with stratified sampling using bootstrap methods. So I think I
probably had a much more solid grounding in regression methods than the
average Datacamp customer. I found the course work and discussion very
useful. I already had a copy of Harrell's RMS text and had read much of
it before that class as well as applying several of the methods he
illustrated. It covered topics of validity in inference and modeling of
covariate functional relationships in much greater depth than I have
ever seen in any of the online material I have reviewed in the last ten
years. It was 4 days well spent and far cheaper than I could have gotten
from a typical consultation.
The typical online course work demonstrates the regression machinery but
very rarely gets into the issues of modeling splines or penalized
methods. Model comparison and assessment of validity is often given
cursory treatment. I continue to see questions on CrossValidated.com and
StackOverflow that demonstrate that the bulk of the self-learners or
distance learners have so far failed to acquire the knowledge base that
vould be acquired during Frank's course. I would advise someone who has
taken a Datacamp course in regression methods to take Frank's course as
the next step to being "statisitcally educated".
--
David.
On 3/24/19 2:42 AM, Graeme Davidson wrote:
Hi Frank,
As part of the R community, you will be aware that the vast majority of
knowledge regarding statistics such as linear modelling is online for free.
What makes this course worthy of payment compared to freely available
information and/or well structured fee paying courses such as DataCamp?
All the best
Graeme R Davidson PhD
Data and Insight Analyst
On 23 Mar 2019, at 14:41, Harrell, Frank E <f.harr...@vumc.org> wrote:
*Regression Modeling Strategies Short Course 2019*
Frank E. Harrell, Jr., Ph.D., Professor
Department of Biostatistics, Vanderbilt University School of Medicine
fharrell.com @f2harrell
*May 14-17, 2019* With Optional R Workshop May 13
9:00am - 4:00pm
Alumni Hall
Vanderbilt University
Nashville Tennessee USA
See http://biostat.mc.vanderbilt.edu/RMSShortCourse2019 for details.
The course includes statistical methodology, case studies, and use of
the R rms package. Emphasis is on developing predictive models, model
validation, and quantifying predictive accuracy, plus many more topics
including navigating the choice of statistical models vs. machine learning.
Frank E Harrell Jr Professor School of Medicine
Department of Biostatistics Vanderbilt University
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
