Comments on: Looking at Data

By: Jeremy

Jeremy — Fri, 16 Oct 2009 17:28:06 +0000

@13 – I wondered about the cusp issue. My presumption is that, given that I don’t think NORC really takes the ZODIAC variable that seriously, they just had some algorithm that always coded the same month/day of birth the same way, even if this might not be the fully astrologically correct way of doing it.

By: Alan Peakall

Alan Peakall — Fri, 16 Oct 2009 12:00:09 +0000

Jeremy,

If, as you say, the zodiac sign is processed data rather than raw data, is it possible that many of zodiac sign mismatches are a result of the encoding being done for the reporting year, rather than the birth year of the respondent? As the reporting years differ by an odd multiple of two years, the leap year cycle could skew half of those born on a cusp.

By: Jeremy

Jeremy — Fri, 16 Oct 2009 06:36:48 +0000

@2 – they don’t actually ask respondents their zodiac sign. They ask them their birthdate, which is then recoded to zodiac sign reflecting the interest some people have in debunking astrology. There were more one-sign differences in zodiac for ostensibly matching respondents than I would have guessed; I suspect this is less about slight misreports of birthday by respondents than about interviewer typing errors, but that’s a suspicion.

@6 – Given that the entire grant justification for doing the repeated interview was the possibility of doing panel analysis, it’s not a real possibility that NORC will not release the panel identifier. Their not having done so already is annoying, though.

By: Phil

Phil — Tue, 13 Oct 2009 21:35:44 +0000

I was subjected to a sort of Monty Python catechism the other day. “All right, Sir, just one more thing, could you tell me: Famous place…?” “Purley”, I replied, and he was prepared to process my query (which as it happened was “how can I give you some more money?”, so the ID-verification really was overkill).

What I think must have happened is that he read out the hint by mistake for the prompt – although obviously I’m not going to confide here what Purley is to me or I to Purley. (Not the obvious, I’ll say that.)

By: Tim B

Tim B — Tue, 13 Oct 2009 20:28:01 +0000

frances: “…I work in id management policy which is the odd thing.”

Id management policy. That’s something the world needs a lot more of, in my opinion.

By: frances

frances — Tue, 13 Oct 2009 20:07:24 +0000

boyfried? where did that come from

By: frances

frances — Tue, 13 Oct 2009 20:06:31 +0000

This is absolutely fascinating and proves to me [yet again] my ignorance – all I will add is I can never get through identity authentication routines by use of “known facts”. First boyfried, pet, school – whatever it is – I don’t think there is more then one instance in my memory bank but there must be as I always seem to fail the test whether internet or call centre. And I work in id management policy which is the odd thing. (Only item I saw in a suggested list of remembered facts I stood a chance with was mother’s Co-op divi number – but you hve to be UK & a certain age and class before that works.)

Human beings always complicate things

By: Barry

Barry — Tue, 13 Oct 2009 18:03:48 +0000

eudoxis 10.13.09 at 4:43 pm

“Data that are more “real”, like medical histories, present with the same problem. Merging patient information on a grid is impossible without a unique identifier. Greater accuracy is required, of course, but still, one would think that collecting and merging all the obvious fields would work.”

Depending on circumstances:

1) Some fields might (will) have missing data for one or the other wave.
2) Enough fields in data set 1 would have to have to also be in data set 2.
3) As I pointed out above, if there are a set of overlapping fields in the two data
sets, but there are errors in recording (recalling) the values, then that set of
values will not be the same for a person between the two data sets.

By: Ken Houghton

Ken Houghton — Tue, 13 Oct 2009 17:57:42 +0000

I fear Ray’s point—and Jeremy’s desire to avoid downtime—will keep them from now cross-referencing the respondents so that datamining can be used to see who l/i/e/d/changed their 2004 voting preference in 2008.

By: eudoxis

eudoxis — Tue, 13 Oct 2009 16:43:54 +0000

Data that are more “real”, like medical histories, present with the same problem. Merging patient information on a grid is impossible without a unique identifier. Greater accuracy is required, of course, but still, one would think that collecting and merging all the obvious fields would work.

By: Billikin

Billikin — Tue, 13 Oct 2009 14:44:53 +0000

“The real distinction between qualitative and quantitative is not widely appreciated. People think it has something to do with counting versus not counting, but this is a mistake. If the interpretive work necessary to make sense of things is immediately obvious to everyone, it’s qualitative data. If the interpretative work you need to do is immediately obvious only to experts, it’s quantitative data.”

That is funny. ;)

By: Barry

Barry — Tue, 13 Oct 2009 14:33:59 +0000

Recall errors would also contaminate things. If you’re matching on 10 remembered data points per person, a recall error rate of less than excellent would really mess you up.

By: Ray

Ray — Tue, 13 Oct 2009 14:28:13 +0000

I’m guessing there was a large difference between the answers to this question, “who they said they voted for in 2004” in 2006 and 2008.

Some of the other questions – marital status, employment, if they live in the same place – may have different answers in a later survey, because those things have changed. Zodiac sign and number of years mother went to school may not be remembered well. ‘Self-identified race’ is also obviously susceptible to change.

Including all of those fields is probably making things harder, not easier.

By: Ahistoricality

Ahistoricality — Tue, 13 Oct 2009 13:36:10 +0000

If the interpretive work necessary to make sense of things….

That’s almost funny.