Events
Fri 1 Feb, '13- |
Algorithms & Computationally Intensive Inference SeminarsA1.01 |
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Mon 4 Feb, '13- |
SF@W SeminarsA1.01 |
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Tue 5 Feb, '13- |
Feynman-Kac Reading GroupC1.06 |
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Tue 5 Feb, '13- |
Young Researchers MeetingC0.06 Stats Common Rm |
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Wed 6 Feb, '13- |
Admissions InterviewsC0.06 Stats Common Rm & A1.01 |
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Thu 7 Feb, '13- |
Probability Reading GroupB1.12 (Maths) |
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Thu 7 Feb, '13- |
Staff LunchC0.06 Stats Common Rm |
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Thu 7 Feb, '13- |
RSS SeminarUniversity of BirminghamRebecca Turner (MRC Biostatistics Unit) Bias adjustment in evidence synthesis Policy decisions often require synthesis of evidence from multiple sources, and the source studies typically vary in rigour and in relevance to the target question. Rigour (or internal bias) reflects how well a study estimates its intended parameters. In a study comparing the effectiveness of two interventions, rigour varies according to use of randomisation, degree of blinding and attrition levels. Relevance (or external bias) reflects how similar the source study design is to the target setting, with respect to study population, outcomes and interventions. In this talk, methods for allowing for internal and external biases in evidence synthesis are presented, and illustrated through application to examples in antenatal care and obesity. A generic bias modelling approach allows decisions to be based on all available evidence, with less rigorous or less relevant evidence discounted using computationally simple methods. |
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Fri 8 Feb, '13- |
Algorithms & Computationally Intensive Inference SeminarsA1.01 |
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Mon 11 Feb, '13- |
SF@W SeminarsA1.01 |
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Tue 12 Feb, '13- |
Feynman-Kac Reading GroupC1.06 |
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Tue 12 Feb, '13- |
Probability Reading GroupC1.06 |
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Wed 13 Feb, '13- |
Admissions InterviewsC0.06 Stats Common Rm & A1.01 |
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Wed 13 Feb, '13- |
Midlands Probability Theory SeminarB3.02 (Maths) |
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Thu 14 Feb, '13- |
Eliciting Bayes Nets Talk by Ann Nicholson (MONASH)C1.06 |
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Fri 15 Feb, '13- |
Algorithms & Computationally Intensive Inference SeminarsA1.01 |
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Mon 18 Feb, '13- |
SF@W SeminarsA1.01 |
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Tue 19 Feb, '13- |
Probability Reading GroupC1.06 |
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Tue 19 Feb, '13- |
Young Researchers MeetingC0.06 Stats Common Rm |
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Wed 20 Feb, '13- |
Admissions InterviewsC0.06 Stats Common Rm & A1.01 |
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Thu 21 Feb, '13- |
CRiSM Seminar - Philip DawidA1.01Philip Dawid (University of Cambridge Theory and Applications of Proper Scoring Rules We give an overview of the theory of proper scoring rules, and some recent applications.
We have recently characterised those proper local scoring rules that can be computed without requiring the normalising constant of the density. This property is valuable for many purposes, including Bayesian model selection with improper priors.
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Thu 21 Feb, '13- |
WCA Lecture - David BowieMS.02Speaker: David Bowie (Hymans Robertson) Is investment risk irrelevant in actuarial work? |
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Fri 22 Feb, '13- |
Research Committee MtgC1.06 |
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Fri 22 Feb, '13- |
Algorithms & Computationally Intensive Inference SeminarsA1.01 |
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Fri 22 Feb, '13- |
Feynman-Kac Reading GroupC1.06 |
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Mon 25 Feb, '13- |
SF@W SeminarsA1.01 |
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Tue 26 Feb, '13- |
Probability Reading GroupC1.06 |
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Tue 26 Feb, '13- |
Young Researchers MeetingC0.06 Stats Common Rm |
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Wed 27 Feb, '13- |
Admissions InterviewsC0.06 Stats Common Rm & A1.01 |
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Wed 27 Feb, '13- |
Teaching CommitteeC1.06 |