MTH6157 - Survival Models - 2023/24
Topic | Name | Description |
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Week 1 : Introduction, Modelling Mortality | module introduction |
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Heterogeneity and the actuarial concept of Selection |
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short article here, full ONS report below |
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link to full Office for National Statistics report here, BBC News reporting above |
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article here, full Swiss Re report below |
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link to full Swiss Re Institute report here, article from The Actuary above |
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Why linear regression modelling does not work for survival models, example using National Life Tables data |
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Week 2 : Survival Model Concepts | ||
survival model concepts - you will also need to access the "demonstration" pdf's below to complete the notes |
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using R commands and functions for week 2 survival model concepts including exponential and Gompertz models |
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Week 3: Censoring and the Kaplan Meier Estimate | non-parametric approaches, censoring, Kaplan-Meier Estimate |
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Kaplan Meier in R |
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This is the question we went through live in the Thursday lecture - full R code and plot given here |
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Assessed Coursework 1 | You will need to download this csv file and load it into R for the coursework |
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Week 4: Proportional Hazard Models | ||
parametric modelling, covariate data, proportional hazards, Cox's PH model |
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maximum likelihood estimation in the exponential model |
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Cox's Proportional Hazard interpretation and calculations |
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CoxPHdataset.csv |
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questions on covariate data and Cox's PH model |
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Week 5: Markov Processes and Multi State Models | ||
Markov processes, 2-state and multi-state models |
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this is a challenging question on multi state models and their use in social security |
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Week 6: Statistical approximations to Multi State Models | Binomial and Poisson approximations to the Multi State model and model comparisons |
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based on week 5 material - two state and multi state models and their use in insurance |
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for more details on this question and alternative solutions see the recording of the lecture on Monday 30 Oct |
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Week 8: Exposed to Risk | exposed to risk |
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Past paper exposed to risk questions from this module and IFoA exam papers |
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will be used in Thursday lecture to practice calculating exposed to risk by census and then estimating the transition intensity by age |
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Assessed Coursework 2 | ||
Week 9: Statistical Tests | graduation and statistical tests |
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example problem question on the Chi-Squared test in R |
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This question was actually set as assessed coursework in 2022 |
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you will need this CSV file for the Additional R question above |
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This question was set as assessed coursework in 2022 |
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Week 10: Graduation Methods | weeks 9 and 10 |
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The question above should be answered as an exam-style question with calculator rather than Excel or R but the data is here in excel in case helpful |
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Week 11: Mortality Projections | Monday week 11, mortality projections methods |
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interpretation of the Lee Carter parameters |
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Week 12: Revision | This is the 2020 LSR paper from which we will use Q1,2,3,4 in the Monday revision session (Q5 is on GLM which has moved from this module to Stats Modelling 2 / Actuarial Statistics since 2020) |
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Note this was a 2 hour exam on campus Q5 relates to a topic no longer on the syllabus for this module - Generalised Linear Modelling |
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