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"Life expectancy is also an aggregate measure FOR a population rather
than a property of an individual"

To be more precise it is " an aggregate measure OF a population FOR a hypothetical population"

So no inferences to an individual can be made because that population does not actually exist.

The hypothetical individual with a specific life expectancy ( or probability distribution thereof) would in their lifetime have to be exposed to all the age-specific mortality rates that exist today. But this could only happen if age-specific mortality rates remained unchanged throughout.

This is completely analogous to the total fertility rates are calculated (and usually misinterpreted).

maja z.


________________________________________
From: email list for Radical Statistics [[log in to unmask]] On Behalf Of John Bibby [[log in to unmask]]
Sent: 10 November 2010 15:35
To: [log in to unmask]
Subject: Re: Health inequality:

"Life expectancy is also an aggregate measure for a population rather
than a property of an individual"

.... I wonder .....?

or is it an aggregate for a sample, from which one can make inferences - to either a population or an individual.

If you think about it in a Bayesian manner where y depends upon theta, the inference can be  towards a population parameter theta, but it can also be towards a random value of y.

Within this lies the popular misconception that if a 90% confidence interval for the population mean is X, and if I am a member of that population, then my value is likely to lie in X with 90% probability.

JOHN BIBBY



On 10 November 2010 14:28, Moore, Robert <[log in to unmask]<mailto:[log in to unmask]>> wrote:
Is it an urban myth or do companies give better annuity rates to smokers?

[Do colleagues know that no less than the Astromer Royal (Edmund Halley - he of the comet) worked out the formula for calculating life annuity rates? It was given in a paper to the Royal Society in 1693. Not everyone knows that!]

Robert


Professor Robert Moore
School of Sociology and Social Policy
Eleanor Rathbone Building
The University of Liverpool
L69 7ZA

Telephone and fax: 44 (0) 1352 714456
________________________________________
From: email list for Radical Statistics [[log in to unmask]<mailto:[log in to unmask]>] On Behalf Of Paul Bivand [[log in to unmask]<mailto:[log in to unmask]>]
Sent: 10 November 2010 14:17
To: [log in to unmask]<mailto:[log in to unmask]>
Subject: Re: Health inequality:

To come back to the actuary thing - what they do is provide evidence for life assurance quotes and annuity quotes.

This leads on to whether insurance companies simply red-line deprived areas or provide quotes that are unaffordable where they think the risk of having to pay out life assurance might be too high.

Conversely, if they calculate a low life expectancy at retirement, then an annuity quote might be more generous (on the grounds they won't have to pay it).

As far as I recall, there has been work and controversy on insurance companies refusing to do business in deprived areas (worse now that the industrial life insurance business with agents collecting cash has collapsed).

Paul

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-----Original Message-----
From: email list for Radical Statistics [mailto:[log in to unmask]<mailto:[log in to unmask]>] On Behalf Of Michael Grayer
Sent: 10 November 2010 14:06
To: [log in to unmask]<mailto:[log in to unmask]>
Subject: Re: Health inequality:

This is great - you guys are all doing my thesis for me ;)

Life expectancy is also an aggregate measure for a population rather than a property of an individual. I've been doing some ecological analysis for my thesis (after having addressed some of the artefactual concerns about estimating life expectancy for tiny population sizes) using ecological socio-economic indicators such as IMD, a social fragmentation index, income deprivation inequality and ethnicity, which is definitely a start.

Michael.


On Wed, 2010-11-10 at 13:52 +0000, John Bibby wrote:
> Dave's point is sound (of course): income is a momentary measure. But
> life expectancies too use  momentary data (i.e. they may be
> interpreted in a longitudinal or cohort way, but are based on
> cross-sectional data).
>
>
> What measure of income or wealth is likely to correlate most highly
> with health measures? Whatever the answer to this question, we may be
> most interested in a measure of individual household capital at the
> time of each baby's birth.
>
>
> JOHN BIBBY
>
>
>
>
> On 10 November 2010 13:44, BYRNE D.S. <[log in to unmask]<mailto:[log in to unmask]>> wrote:
>         I would love to have something relating income level to life
>         expectancy but we cannot do that for a momentary point in the
>         life course which is what present income distribution data
>         measures. With longitudinal studies if we can built up life
>         course cases i.e. use data across the life course to construct
>         an income profile through life, then we would relate that to
>         life expectancy in a meaningful way. Somebody may be doing
>         this of course but I can’t think of any examples.
>
>
>
>         David Byrne
>
>
>
>         From: email list for Radical Statistics
>         [mailto:[log in to unmask]<mailto:[log in to unmask]>] On Behalf Of John Bibby
>         Sent: 10 November 2010 13:31
>
>
>         To: [log in to unmask]<mailto:[log in to unmask]>
>
>         Subject: Re: Health inequality:
>
>
>
>
>         I strongly recommend Michael's article -
>
>
> [http://epc2010.princeton.edu/abstractViewer.aspx?submissionId=100690]
>
>
>         I have read it quickly and will soon be looking at it again
>         (but then, I know nothing about demography).
>
>
>
>
>
>         I generally like percentiles rather than Pearsonian moments:
>         so why do we not use L50, the median of life-lengths, rather
>         than the expectancy, which is highly sensitive to extremes
>         including infant mortality, centenarians and data-errors? If I
>         had L10 and L90, that would have more meaning for me. (This is
>         separate from the question whether when comparing different
>         areas, one should go for the extremes or a percentile: again,
>         for me the 10th and 90th percentiles would be more interesting
>         than the extremes.)
>
>
>
>
>
>         I agree with Jane that this could be a suitable topic for the
>         Newsletter. But something more class-based would also be
>         interesting: can we compare L10 and L90 for those at Y10 and
>         Y90, the 10th and 90th percentiles of the
>         income-distribution? Thinking more abstractly we have P(L,Y)
>         which is the probability that somebody at the Y-th income
>         percentile expires at age L. What shape is this curve, and how
>         is it best summarised?
>
>
>
>
>
>         Sorry, I prefer posing questions rather than providing
>         answers.
>
>
>
>
>
>         JOHN BIBBY
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>         On 10 November 2010 10:27, Michael Grayer
>         <[log in to unmask]<mailto:[log in to unmask]>> wrote:
>
>         As John said: concentrating on extremes is not really helpful.
>         The
>         methodology used to calculate life expectancy (at least the
>         ones used by
>         ONS
>         [http://www.statistics.gov.uk/downloads/theme_other/GSSMethodology_No_33.pdf] and the health observatories [http://www.sepho.org.uk/download.aspx?urlid=9847&amp;urlt=1]) for such small areas introduces quite a few artefacts into the estimates. These predominantly manifest themselves in the form of over-estimates, because there is no upper bound placed on the length of survival in the final age group. I wrote a conference paper on this about a year ago which I hope to have published---you can read the conference proceedings version of it online [http://epc2010.princeton.edu/abstractViewer.aspx?submissionId=100690]. There probably is a real, substantive gap in life expectancy, but 16.8 years is most likely an over-estimate. A more conservative estimate would be provided by taking the inter-quartile range, or some other measure which drops the outliers.
>
>         As for smaller areas, well, we'd all love to have them, but
>         much smaller
>         scale than the ward-level and the numbers become so tiny that
>         it really
>         is an exercise in getting blood out of a stone. After all,
>         "life
>         expectancy" is a property of populations, not individuals, so
>         a
>         reasonable level of aggregation has to be maintained for the
>         figures to
>         be meaningful.
>
>         I hope this is helpful information.
>
>         Best wishes,
>         Michael.
>
>
>
>         On Wed, 2010-11-10 at 08:56 +0000, Martin Rathfelder wrote:
>         > I know about these thank you.  What I want are ward level
>         stats. Or
>         > smaller, I suppose, but the small area stats I have seen
>         were very
>         > difficult to use because they didn't relate to any
>         identifiable places.
>         >
>         > On 10/11/10 08:39, Potter, Lesley wrote:
>         > >
>         http://www.statistics.gov.uk/statbase/Product.asp?vlnk=8841
>         > >
>         > > There is a collection of resources on life expectancy
>         here, produced by
>         > > the Office for National Statistics,
>         > > Hope this is helpful,
>         > > Lesley
>         > >
>         > >
>         > > -----Original Message-----
>         > > From: email list for Radical Statistics
>         [mailto:[log in to unmask]<mailto:[log in to unmask]>]
>         > > On Behalf Of Martin Rathfelder
>         > > Sent: 10 November 2010 08:32
>         > > To: [log in to unmask]<mailto:[log in to unmask]>
>         > > Subject: Health inequality:
>         > >
>         > > There is, according to the local PCT, a 16.8 year gap in
>         life expectancy
>         > >
>         > > experienced by female residents who live in the
>         Macclesfield Town
>         > > Tytherington area compared to those living in Crewe's
>         Central and Valley
>         > >
>         > > area
>         > >
>         > > This sort of local inforamtion is very useful
>         politically.  Does anyone
>         > > know of, or is anyone capable of producing, a convenient
>         useful source
>         > > of such stuff?  Ideally showing the most extreme
>         disparities in close
>         > > proximity.
>         > >
>         > > I presume that the smaller the areas the greater the
>         disparities.  The
>         > > DPH in Huddersfield used to produce some good graphs
>         showing the
>         > > contrasts between the two sides of the same road.
>         > >
>         > > Martin Rathfelder
>         > > Director
>         > > Socialist Health Association
>         > > 22 Blair Road
>         > > Manchester
>         > > M16 8NS
>         > > 0161 286 1926
>         > > www.sochealth.co.uk<http://www.sochealth.co.uk>
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>         > --
>         > Martin Rathfelder
>         > Director
>         > Socialist Health Association
>         > 22 Blair Road
>         > Manchester
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