Selection Effects in Periodic X-ray Data from Maximizing Detection Statistics
Reed Essick

TL;DR
Selecting data to maximize pulsation detection statistics can introduce biases in parameter estimates and significance levels, affecting the interpretation of NICER pulsar observations.
Contribution
This paper demonstrates that the data selection procedure used in pulsation searches can bias results and alter significance estimates, highlighting the need for careful analysis.
Findings
Biases in mean count rate and pulsation amplitude due to data selection.
Altered null-distribution of the H-test affects significance estimates.
Estimated biases can impact neutron star radius constraints.
Abstract
The Neutron Star Interior Composition Explorer (NICER) records data of exceptional quality on the energy-dependent X-ray pulse profile of pulsars. However, in searching for evidence of pulsations, Guillot et al. (2019) introduce a procedure to select an ordered subset of the data that maximizes a detection statistic (the H-test). I show that this procedure can degrade subsequent analyses using an idealized model with a stationary expected count rates from both noise and signal. Specifically, the data-selection procedure biases the inferred mean count rate to be too low, biases the inferred pulsation amplitude to be too high, and that the size of these biases scales strongly with the amount of data that is rejected and the true signal amplitude. The procedure also alters the null-distribution of the H-test rendering nominal detection significance estimates overly optimistic. While the…
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