Future events

TUESDAY Statistics Seminar: Nicola Lunardon

Tuesday, March 28, 2017 - 14:15

Speaker: Nicola Lunardon, University of Milano-Bicocca

Title: On bias prevention and incidental parameters.

Abstract: Firth (1993, Biometrika) introduced the bias prevention approach with the aim to reduce the bias of the maximum likelihood estimator. It is shown that the methodology is also effective in reducing the sensitivity of the derived inferential procedures in models involving incidental parameters.

Location: 
Department of Mathematics, room Sverdrups plass (lunch area) on the 8th floor of Niels Henrik Abels hus

Wednesday Lunch: Steffen Sjursen

Wednesday, March 29, 2017 - 12:00

Speaker: Steffen Sjursen, Senior analyst, group risk modelling, DNB. PhD UiO: Stochastic Optimal Control and time changed Lévy noises.

Title: Calculating probability of default when available data varies greatly between different customers.

Abstract: TBA

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others

 

Location: 
Spiseriet, Norwegian Computing Center

THURSDAY Biostatistical Seminar: Georg Heinze

Thursday, March 30, 2017 - 14:15

Speaker: Georg Heinze, Professor, Center for Medical Statistics, Informatics, and Intelligent Systems (Section for Clinical Biometrics), Medical University of Vienna, Austria

Title: The multiple faces of shrinkage

Coffee/tea served from 14:15 and the talk will start around 14:30.

Abstract: Shrinkage is a result of overfitting, if regression models are estimated with small or sparse data sets.  In such situations predictions for new subjects are often ‘too extreme’ and their real outcomes are closer to an overall mean, i.e. they appear to be ‘shrunken’. Interestingly, ‘shrinkage’ is also often used to denote estimators that aim at anticipating shrinkage effects and preventing its occurrence. This duality has often caused confusion.

Shrinkage estimators can serve various purposes. Some methods were developed to optimize the calibration of prediction models. Other methods should reduce bias away from zero, which in logistic regression problems with small samples can be severe, but is absent, e.g., in linear regression. Another purpose could be to improve the accuracy, i.e., to reduce mean squared error of predictions or of effect estimates. Irrespective of their purpose, some of these methods can have a Bayesian motivation, where prior belief about possible values of common estimands such as log odds ratios is expressed as prior distributions centered at zero.

Shrinkage estimators can be constructed by maximizing a likelihood function penalized by an additional function of the parameters, which pulls estimates towards zero. Ridge and lasso regression are well-known examples, and so is Firth’s penalized likelihood. Other shrinkage estimators are constructed differently, e.g., estimating and applying post-estimation shrinkage factors by resampling methods. It is less well known that also classical variable selection methods can be interpreted as shrinkage estimators.

The talk will mainly focus on the setting of logistic regression with rare events. After a general introduction, we will compare shrinkage estimators by their assumed ‘pessimism’, i.e., the amount of overfitting that they anticipate (Kammer et al, 2017). Subsequently, we will investigate the improvement in accuracy of parameter estimates and predicted probabilities implicated with various shrinkage methods (Puhr et al, 2017). Finally, we will briefly discuss Bayesian noncollapsibility, i.e., likelihood penalization resulting in undesired anti-shrinkage, which can affect all well-known shrinkage estimators (Greenland, 2010; Geroldinger et al, 2017).

Organizer: Oslo Centre for Biostatistics and Epidemiology (OCBE), Research group in Statistics and Biostatistics, Dept. of Mathematics, UiO and Big Insight

Location: 
Domus Medica, room 2240 (Dep. of Biochemistry)

Wednesday Lunch: TBA

Wednesday, April 19, 2017 - 12:00

Speaker: TBA

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others

Location: 
Sverdrups plass (lunch area), 8th floor N. H. Abels hus, Department of Mathematics

Wednesday Lunch: TBA

Wednesday, May 3, 2017 - 12:00

Speaker: TBA

The lunch starts at 12:00, and the talk will start around 12:20.

 

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others

Location: 
Spiseriet, Norwegian Computing Center

THURSDAY Biostatistical Seminar: Cristopher Yau

Thursday, May 18, 2017 - 14:15

Speaker: Cristopher Yau, Reader in Computational Biology, Centre for Computational Biology, University of Birmingham, UK

Title: TBA

Coffee/tea served from 14:15 and the talk will start around 14:30.

Abstract: TBA

Organizer: Oslo Centre for Biostatistics and Epidemiology (OCBE), Research group in Statistics and Biostatistics, Dept. of Mathematics, UiO and Big Insight

Location: 
Domus Medica, room 2240 (Dep. of Biochemistry)

Wednesday Lunch: TBA

Wednesday, May 24, 2017 - 12:00

Speaker: TBA

The lunch starts at 12:00, and the talk will start around 12:20.

 

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others

Location: 
Sverdrups plass (lunch area), 8th floor N. H. Abels hus, Department of Mathematics