Concept

Ranking — where it appears

Ordering groups by an estimate and reading position as a result, as a league table does. With groups of unequal size the order depends on each group's precision as much as its effect, so a rank needs its own interval.

Named by 6 essays across 2 fields — each of them below, with the objects they name alongside it.

The ranking on the left, the weights on the right. Eight moving-average forecasts of an AR(1) at φ = 0.4895, the persistence at which the best of them exactly ties the 60-observation benchmark. On the left, each candidate's expected squared error in units of the series' own variance: the smallest belongs to L = 2, at 1.0156. On the right, the weight each carries in the variance-minimising combination of all eight — and the best of them carries 0.00000. The two ends of the family carry 1.0172 of the weight between them, and the combination they make is worth 0.7817, which is 23.0% below the best single forecast. Both columns are closed forms in φ. Which forecast to keep and which forecasts to use are different questions, and this is a set where the answers share nothing.

The weight that is a vector

Two forecasts have a best combination and one number describes it. Eight have a best combination too, and the vector describing it puts nothing at all on the forecast with the smallest mean squared error.

search · Rank
How many of a league table's top ten are small groups, ranked four ways. A hundred groups with sizes from 4 to 400, of which 36% have twenty units or fewer. Small groups make up 36.3% of the true top ten, 62.1% of the top ten by raw means, 13.4% by posterior means and 22.9% by the posterior chance of being in the top ten. The three rankings recover 4.43, 5.38 and 5.47 of the true top ten.

A league table of a hundred

A hundred groups with sizes from 4 to 400, and a top ten to publish. Ranked by their own means, small groups fill 62.1% of the top ten against their 36.3% share of the true top ten. Ranked by posterior means they fill 13.4%. The ranking built from each group's chance of being in the top ten recovers 5.47 of the true ten, the best of three and barely half; and the group ranked first could hold any rank from 1 to 31.

borrowed · Shrinkage
The bottom ten of a league table of a hundred when larger groups do better, size–effect slope 0.6. Groups of 4 to 400, true effects rising with log size at a slope of 0.6 population widths. The true bottom ten is 80.6% small groups. Ranked by their own means the bottom ten holds 4.28 of the true ten; pooled to one centre, 3.19, with 42.6% small groups; pooled to a centre that rises with size, 4.35, with 83.0%.

The small groups one centre protects

In a league table of a hundred groups where larger groups do better on average, pooling every group towards one centre overstates the small groups by half a population width — 0.501 — because it pulls them towards an average they are not part of. The top ten barely notices. The bottom ten, the list that flags poor performers, holds 3.19 of the true bottom ten when pooled to one centre and 4.28 when the groups are ranked by their own noisy means. Pooling towards a centre that rises with size restores 4.35 and puts the small groups back at the bottom where 80.6% of the true bottom ten sit.

borrowed · Shrinkage
How far each estimate of the small groups sits from their truth, when the size relation is flattening below the median size. The small groups' average true effect is −0.259. Their estimates are off on average by −0.012 (own means), +0.276 (one fitted centre), −0.173 (fitted line in log size), −0.025 (fitted quadratic in log size), −0.003 (the true relation).

The relation the table has to estimate

Pooling a league table's groups towards a centre that rises with size repaired the small groups' bias — when the size relation was known. Fitted from the table itself, a straight line in log size loses almost nothing: the small groups' error is 0.750 against 0.719 with the true relation. When the relation bends below the median size, the fitted line extrapolates the large groups' slope into the region where it is barely observed and misplaces the small groups by −0.173 if the relation flattens and +0.264 if it steepens — smaller than one centre's error, of either sign. A quadratic in log size removes nearly all of it, −0.025 and +0.014, and costs 0.025 in error when the relation was straight.

borrowed · Shrinkage
Every group's 90% rank interval in one league table whose size relation is steepening below the median size, with its true rank. A hundred groups from four to four hundred patients, ranked from their posterior under a fitted quadratic size relation whose uncertainty is drawn once per table. The groups of twenty patients or fewer have rank intervals 30.1 places wide on average, and 34 of their 36 true ranks fall inside; the groups of over a hundred, 32.1 places, with 27 of 30 inside.

A ranking with its uncertainty

A league table's reader wants a rank, and a rank interval inherits a fitted size relation's errors differently from an effect interval. When the relation steepens below the median size, a fitted line's 95% interval for a small group's effect covers 83.1% of the time; its 90% interval for the same group's rank covers 95.6%, because the line's error lifts the small groups into the crowded middle of the table, where rank intervals are wide. The error surfaces instead in the large groups' ranks, 87.6%, and in width: 36.9 places against the 27.3 the true relation needs. A quadratic's uncertainty has to be drawn once per table, since it moves every small group together — added group by group it over-covers at 92.8%.

borrowed · Shrinkage
How often a league table's own data choose a bent centre over a straight one. Over 400 tables of a hundred groups each. The quadratic's curvature coefficient is significant at 5% on 5.3% of tables whose relation is straight, 14.5% of tables whose relation is flattening below the median, 29.3% of tables whose relation is steepening below the median; its average AIC weight is 0.374, 0.456, 0.558.

A centre chosen by its own table

A league table that picks its centre's shape from its own data — a line unless a curvature test says otherwise — picks the line on 85.5% of tables whose relation flattens below the median, because the bend lives where the groups are smallest and noisiest. Its bottom ten then flags like the line's: 2.61 innocent small groups a table against 2.19 for a quadratic told the shape. Always fitting the quadratic costs 0.07 of a correctly flagged group when the relation is straight and matches the told answer when it bends, and a flag set by probability carries the choice through a mixture of the two.

borrowed · Shrinkage

Named alongside it

The objects these essays reach for when they reach for this one.

ShrinkageHierarchical modelLeague tablePartial poolingModel selectionParameter uncertaintyPosterior meanRegression to the meanAutocorrelationBenchmark forecastBias-varianceCombination weight

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