Regression Modeling Strategies and the R rms Package Short Course 2019

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Regression Modeling Strategies and the R rms Package Short Course 2019

Harrell, Frank E
*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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Re: Regression Modeling Strategies and the R rms Package Short Course 2019

Graeme Davidson
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 <[hidden email]> 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
>
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: Regression Modeling Strategies and the R rms Package Short Course 2019

Harrell, Frank E
You'll need to see hundreds of past course evaluations to see why, but a main reason is the learning environment we provide, with hours of discussion among participants occuring during the 4-day course.  This includes topics such as how to collaborate with non-statisticians especially when explaining the results of complex statistical models.  We also have discussions during the lunches in the dining hall next to the lecture room.  Many of the topics I cover are set by the participants during the week.  And all of the course handouts are freely available for everyone.

Frank


________________________________
Frank E Harrell Jr      Professor       School of Medicine

        Department of Biostatistics             Vanderbilt University


________________________________
From: Graeme Davidson <[hidden email]>
Sent: Sunday, March 24, 2019 04:42
To: Harrell, Frank E
Cc: [hidden email]
Subject: Re: [R] Regression Modeling Strategies and the R rms Package Short Course 2019

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 <[hidden email]> 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 https://nam05.safelinks.protection.outlook.com/?url=http%3A%2F%2Fbiostat.mc.vanderbilt.edu%2FRMSShortCourse2019&amp;data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&amp;sdata=8GcqD8no7%2FNJ2Ytw%2B0U7DwwKvs6flF2buPvuHc3ra%2Bc%3D&amp;reserved=0 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
>
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&amp;data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&amp;sdata=UTdWE%2BH9AAlL8XytaifKp7BdaLKYwK4zDzb%2B2TaCnRY%3D&amp;reserved=0
> PLEASE do read the posting guide https://nam05.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.R-project.org%2Fposting-guide.html&amp;data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&amp;sdata=CyHkkgXrAkPTxSh87JUEbvg%2BwmV8LhqZYgYoMWgyzak%3D&amp;reserved=0
> and provide commented, minimal, self-contained, reproducible code.

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: Regression Modeling Strategies and the R rms Package Short Course 2019

David Winsemius
In reply to this post by Graeme Davidson

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 <[hidden email]> 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
>>
>>
>> ______________________________________________
>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.