US Civil Labor Force Disability & Accumulated Vaccine Doses: A Case Of Bent Regression?
A statistical side note for the Phinance Technologies humanities project for all those who like to debate the number of angels dancing on the head of a pin.
Now and then a Tweet catches my eye, and these two from the formidable Jonathan Engler of HART did just that:
The link to source may be found here.
I know this is a drop of the ‘good stuff’ because I asked Mrs Dee to look over my should at the screen and she gasped. She’s not a numbers person by any means but she instantly recognised a correlation when she saw one.
Having a cuppa already to hand I followed the Twitter thread in earnest and stumbled over this tree stump:
Now that is fair criticism indeed and a topic I covered way back on 5 July 2022 in an articled entitled Baking Better With Cochrane-Orcutt (part 1). Serial killers kill people and serial correlation kills analysis. You’ll need to read my series or digest some indigestible Wiki to grasp why but it all comes down to the assumption of independence of measure, being a ‘law’ that sits at the heart of a great deal of statistics.
The Law Of Jam Tarts
Accumulated anything, by definition, cannot meet the requirement of independence of measure since today’s figures will be dependent on yesterday’s figures and yesterday’s figures will be dependent on the day before that, and so on. For example, my accumulated jam tart total for Friday cannot possibly be lower than the value on Thursday. It can equal Thursday’s accumulated tally if I refuse to scoff any on Friday but that’s it. This presents a problem when we come to do an analysis that assumes Friday’s tally can be lower than Thursday’s. If we ignore this law of tarts we start seeing correlations when there aren’t any.
A Fig Roll Of The Imagination?
The question immediately leaps up as the whether Phinance Technologies have baked a blooper. Having dealt with problems like this for +30 years I smelled a decent result beneath those dancing angels and penned a rare Tweet:
OLSR *can* be performed but correlation will be inflated owing to lack of independence of measure. A simple matter to flip to autoregression techniques such as Cochrane-Orcutt, Prais-Winsten or Maximum Likelihood methods but these are not going to change the main finding.
Not content with nosing alone I whipped out my stats package and ran the towels over the data to confirm matters in a rigorous fashion.
Results
Here’s my replication of Phinance Technologies ordinary least squares linear regression (OLSR) in boring grey and black: