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Stephen Richards

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Factors

In statistical terminology, a factor is a categorisation which contains two or more mutually exclusive values called levels.  These levels may have a natural order, in which case the variable is said to be an ordinal factor. 
Tags: factor, categorical factor, ordinal factor, binary factor, AIC, optimisation

Playing with scales

Mortality rates increase exponentially with age.  This can make comparisons difficult, as shown in Figure 1 below, which shows the period mortality rates for males in England and Wales at ten-year intervals. 
Tags: mortality, scale

How wrong could it be?

We have written previously about the importance of the independence assumption when modelling mortality for annuities and pensions. In a recent presentation to the Royal Statistical Society I showed the audience how life insurers deduplicate their annuity data and how they use postcodes to identify socio-economic status.
Tags: deduplication, mortality, annuities, geodemographics, Mosaic

Sweating your data assets

In recent years insurers have looked to making better use of the data they already have. The appeal is simple: if you have already collected the data, then it is like leaving money on the table if it is not being exploited to the full.
Tags: postcodes, geodemographics, smoking, missing data, P-squared

A dip in the data pool

In the distant past, individual insurers had relatively modest business volumes and the industry needed to pool its data to get an overall data set of sufficient credibility. In the U.K., the mechanism for pooling mortality data is the CMI. An earlier blog mentioned some challenges surrounding the changing volumes of data in the CMI assured lives data set.

Tags: CMI

Early retirements

Members of defined-benefit pension schemes can often retire early if they are in poor health.  Unsurprisingly, such ill-health retirements exhibit higher mortality rates than those who retire at the normal scheme age.

Tags: early retirement, missing data, Kaplan-Meier

Accelerating improvements in mortality

In February 2009 a variation on the Lee-Carter model for smoothing and projecting mortality rates was presented to the Faculty of Actuaries.  A key question for any projection model is whether the process being modelled is stable.  If the process is not stable, then a model assuming it is stable will give misleading projections.  Equally, a model which makes projections by placing a greater emphasis on recent data will be better able to identify a change in tempo of the underlying p

Tags: mortality improvements, force of mortality

Winter mortality

In previous posts we looked at seasonal fluctuations in mortality.  Since the UK is about to experience some particularly cold weather again, we will look at winter mortality in more detail.
Tags: season, influenza, winter

Logistical nightmares

A common Generalised Linear Model (GLM) for mortality modelling is logistic regression, also sometimes described as a Bernoulli GLM with a logistic link function.  This models mortality at the level of the individual, and models the rate of mortality over a single year. 
Tags: GLM, logistic regression

Double trouble

Scientists strongly prefer ideas and processes which have undergone anonymous peer review in published, refereed journals.
Tags: deduplication, duplicates, annuities