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Hope you've been having a good week.</div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">At the S3RI seminar today at 2 PM, we have Professor </span><span style="margin:0px; font-family:Calibri,Helvetica,sans-serif; font-size:12pt"><span style="color: rgb(0, 0, 0); text-align: center; background-color: rgb(255, 255, 255); display: inline !important;">Willi
Sauerbrei</span></span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> (</span><span style="margin:0px; font-family:Calibri,Helvetica,sans-serif; font-size:12pt"><span style="color: rgb(0, 0, 0); text-align: center; background-color: rgb(255, 255, 255); display: inline !important;">University
of Freiburg</span></span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">) giving a talk on</span></div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">"</span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Multivariable
regression modelling - Issues in selection of variables and functional forms of continuous variables.</span><span style="margin: 0px; font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">"</span></div>
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<div style="margin: 0px; background-color: white; color: black;"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">P</span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">lease
see below for the details of the talk and how to join the seminar online.</span></div>
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<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Hope to see you at the seminar later today!</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);"> </span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
<p style="background-color: white; margin-top: 0px; margin-bottom: 0px;"><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Kind regards,</span><span style="margin: 0px; font-size: 12pt; font-family: "Times New Roman", serif; color: black;"></span></p>
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</span><span style="margin: 0px; font-size: 12pt; font-family: Calibri, Helvetica, sans-serif; background-color: white; color: rgb(0, 0, 0);">Jessie</span></p>
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<p align="center" style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-bottom:13px; text-align:center">
<span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><b><span style="font-size:14.0pt"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Multivariable regression modelling - Issues in selection
of variables and functional forms of continuous variables </span></span></b><b><span style="font-size:14.0pt"><span style="font-family:"Times New Roman",serif"></span></span></b></span></span></p>
<p align="center" style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-bottom:13px; text-align:center">
<span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><span style="font-size:12.0pt"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Willi Sauerbrei</span><span style="font-family:"Times New Roman",serif"><sup><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">1</span></sup></span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">,
Edwin Kipruto</span><span style="font-family:"Times New Roman",serif"><sup><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">1</span></sup></span></span></span></span></p>
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<span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><sup><span lang="EN-US" style="font-size:12.0pt"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">1</span></span></sup><span lang="EN-US" style="font-size:12.0pt"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">Institute
of Medical Biometry and Statistics, University of Freiburg, Germany</span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-left:7px; text-align:justify">
<span style="font-size:12pt"><span style="line-height:115%"><span style="font-family:"Book Antiqua",serif"><span><span style="font-family:"Times New Roman",serif"></span></span></span></span></span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> </span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-bottom:13px; text-align:justify">
<span style="font-size:11pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">In deriving a multivariable regression
model for description, selection of variables and determination of functional forms for continuous variables are central issues. In a recent review of methods, TG2 of the STRATOS initiative identified seven methodological issues which require better understanding,
further research and more comparisons of methods proposed [1]. In this talk we briefly discuss issues related to selection bias and the role of shrinkage to correct for it, and modelling of continuous variables.
</span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-bottom:13px; text-align:justify">
<span style="font-size:11pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">The nonnegative garrote (NNG) [2]
combines variable selection and shrinkage, however, it is often ignored in practice because of its dependence on ordinary least squares estimates from the full model which performs poorly in high degree of multicollinearity and cannot be used for the analysis
of high-dimensional data. To extend the approach, other initial estimators have been proposed such as ridge or lasso estimators. In an example the performance of NNG will be compared with the lasso, adaptive lasso and relaxed lasso. </span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; text-align:justify">
<span style="font-size:12pt"><span style="line-height:150%"><span style="font-family:"Book Antiqua",serif"><span style="font-size:11.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">Although
severe weaknesses are known, categorisation or the assumption of a linear effect are still the most popular approaches to determine the functional form for continuous variables.
</span></span></span><span style="font-size:11.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">The multivariable fractional polynomial (MFP) approach combines variable selection
using backward elimination and function selection for continuous variables using fractional polynomial functions [3]</span></span></span><span style="font-size:11.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">.
</span></span></span><span lang="EN-US" style="font-size:11.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">Regression diagnostics, such as detection of influential points and
plots of residuals may reveal lack of fit or other peculiarities of a selected model. Single observations may be responsible for the selection of a linear, a monotonic non-linear or even a non-monotonic function. Using synthetic data we will discuss approaches
to identify influential points, consider model reproducibility and </span></span></span><span lang="EN-US" style="font-size:11.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">investigate
the effect of sample size on MFP models. We will show that with a sufficiently large sample size and a carefully check on regression diagnostics, MFP is a suitable approach to identify variables with a stronger effect and suitable functional forms for continuous
variables. </span></span></span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-left:7px; text-align:justify">
<span style="font-size:12pt"><span style="line-height:150%"><span style="font-family:"Book Antiqua",serif"><span lang="EN-US" style="font-size:11.0pt"><span><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> </span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; margin-bottom:13px; text-align:justify">
<span style="font-size:11pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span lang="DE" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">[1]
Sauerbrei W, Perperoglou A, Schmid M, Abrahamowicz M, Becher H, Binder H, Dunkler D, Harrell Jr.
</span></span></span><span lang="EN-US" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">FE, Royston P, Heinze G for TG2 of the STRATOS initiative (2020). State
of the art in selection of variables and functional forms in multivariable analysis - outstanding issues. Diagnostic and Prognostic Research, 4:3, 1-18.
</span></span></span><span lang="DE" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">DOI:
</span></span></span><span lang="DE" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">10.1186/s41512-020-00074-3</span></span></span><span lang="EN-US" style="font-size:10.0pt"><span></span></span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; text-align:justify">
<span style="font-size:12pt"><span style="line-height:150%"><span style="font-family:"Book Antiqua",serif"><span lang="EN-US" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">[2]</span></span></span></span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">
</span><span style="font-family:"Book Antiqua",serif"><span lang="EN-US" style="font-size:10.0pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">Breiman, L. (1995). Better subset regression
using the nonnegative garrote. Technometrics, 37(4), 373-384.</span></span></span></span></span></span></p>
<p style="margin-top: 0px; margin-bottom: 0px;font-family:"Segoe UI","Helvetica Neue",Helvetica,Arial,sans-serif; font-size:14px; text-align:justify">
<span style="font-size:12pt"><span style="line-height:150%"><span style="font-family:"Book Antiqua",serif"><span lang="EN-US" style="font-size:10.0pt"><span><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);"> </span></p>
<p style="margin-top: 0px; margin-bottom: 0px;text-align:justify"><span style="line-height:150%"><span lang="EN-US" style="font-family:"Book Antiqua",serif; font-size:10pt"><span><span style="font-family: Calibri, Helvetica, sans-serif; font-size: 12pt; line-height: normal; color: rgb(0, 0, 0);">[3]</span></span></span><span style="line-height: normal; color: rgb(0, 0, 0);"><font face="Calibri, Helvetica, sans-serif"><span style="font-size:12pt">
Royston, P., Sauerbrei, W. (2008): ‘Multivariable Model-Building – A pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables’. Wiley</span></font><br>
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