Selection on an extreme first measurement

ID: selection-on-an-extreme-first-measurement

Select units with first reading , keep that membership fixed, and measure the same units again. The first reading now has a truncated normal distribution. For a general finite threshold , write for the standard normal density and for the standard normal distribution function. Since ,
The tower property of conditional expectation lets us average the line over the selected group.[ref] At this gives
The average second reading is below the selection threshold even though every selected first reading exceeded it. This is a group expectation; any finite generated group's sample mean fluctuates around it. Selecting again on would define a different group and answer a different question.
The latent variable decomposition makes the apparent drop especially clear. Gaussian conditioning gives and . Thus
The first measurement error has zero unconditional mean, but positive selected mean. The second measurement error stays centered because it is independent of selection on . The persistent signal never changed.
Figure 1.
Selection captures an extreme first error while the persistent signal stays fixed
. Original synthetic repeated measurements, not actual measurements. Left: 40 generated units selected by ; orange trajectories move farther from zero. Right: analytic selected-group expectations decompose the first and second readings into persistent latent variable and measurement error. Black dots give generated group sample means after selecting from 60,000 synthetic units; their small departures from the bar totals reflect sampling variation. All selections use the first reading only. Details.

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