Presentations

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A selection of talks given by us over the last 4-5 years is provided for information(PowerPoint format). We see it as a possible basis for teaching material on the MFP approach and on related  topics and extensions. A summary and overview is given in the file MFP_overview.xls. We would be delighted to comment on teaching material on MFP developed by others, and to include such material on this website for the benefit of others.  Of course, credit will be given to the developers of the material.
Please note that the material is not new and results may have changed. Some details may not precisely represent our current thinking. Furthermore, there is considerable overlap between many of the presentations, and the technical level varies depending on the intended audience.  None of the talks includes a lot of mathematics and a * marks talks which contain hardly any mathematics. Feel free to select material from among the different talks.
Beside of material povided by others we will also add exercises ans solutions as soon as possible. All talks were given by one of us, but some of them had other co- authors. For simplicity, we only give our names in changing order.
Essentially all talks have an introduction to FPs and MFP (part of chapter 4 and 6)
References to additional chapters are given in the column "book chapters".








Nr. Presentation Slides Time Update Book Ch. Topics Slide No.         



1 Course 1- part 1 53 90 Feb 09 2 Building regression models- general issues sl. 7- 15






Methods for variable selection sl. 16- 29






Selection bias, shrinkage sl. 30- 43






Reporting sl. 46- 49
2 Course 1- part 2 75 90 Feb 09 3.7; 6.4; 5.5; Univariate smoothing problem sl. 10- 15





7.4; 8.7 FPs sl. 16- 32






MFP sl. 33- 41






Presentation sl. 42- 44






Robustness sl. 46- 52






Stability sl. 54- 58






Interaction (with treatment) sl. 59- 67






Software sl. 71- 73
3 General 65 90 Feb 09 2; 8.8 Regression models sl. 3- 15






Methods for variable Selection sl. 16- 23






Selection bias, shrinkage sl. 24- 34






Continuous Variables- Functional Form sl. 35- 45






MFP sl. 46- 55






Splines sl. 56- 58
4 MFP- 1 55 90 Feb 09 3.7; 4.13; 5.5 Curve Fitting sl. 9- 13






FPs sl. 14- 22






FP vs Splines sl. 23- 29






MFP sl. 30- 37






Robustness sl. 39- 40






Stability sl. 43- 47






Presentation sl. 48- 49
5 MFP- 2 29 40 Feb 09
Regression models sl. 4- 7






Variable Selection sl. 8- 10






Continuous Variables- Functional Form sl. 11- 13






FPmodels sl. 14- 20






MFP sl. 21- 23
6 MFP- 3 * 20
Feb 09 3.4 Continuous risk variables sl. 3- 10






FPmodels sl. 11- 17






MFP sl. 18- 20
7 Progn. Factors * 45 60 Feb 09 3.4; 7.4 Prognostic factor studies sl. 3- 7






Optimal Cutpoints sl. 8- 14






FP sl. 15- 26






Interaction (with treatment) sl. 27- 35






Reporting sl. 36- 42
8 Categorization * 25
Feb 09
Cutpoints sl. 2- 11






FP + MFPI sl. 12- 20
9 Interaction 83 90 Feb 09 7; 11.1 Regression models and model building sl. 3- 13






FP sl. 14- 20






MFP sl. 21- 30






Interactions







Binary sl. 33- 48






Two Continuous Variables sl. 49- 60






Time (non- proportiona) sl. 61- 76
10 MFPI 21 30 Feb 09 7.4; 7.8-7.10 STEPP sl. 5- 8






MFPI sl. 9- 19
11 MFPIgen 49 60 Feb 09 7.11; 7.3; 7.4 General issues in regression models sl. 3- 9






FP







univariate sl. 12- 18






multivariate sl. 19- 27






Interaction







Binary sl 30- 35






Two continuous sl. 36- 42
12 MFPT- 1 32 60 Feb 09 11.1 Non- PH sl. 4- 6






FP sl. 7- 12






MFPT sl. 15- 30
13 MFPT- 2 21 30 Feb 09 11.1 Non- PH sl. 4- 9






MFPT sl. 10- 16
14 MFPT- 3 * 20 30 Feb 09 11.1. Non- PH sl. 5- 10






MFPT sl. 11- 15
15
 Robustness
 17 25 Feb 09 5.5 nothing needed

16 MFPspike 22 19 Feb 09 4.15 Motivation sl. 2- 4






Theoretical results sl. 5- 8






FP spike sl. 11- 21