  Neutron stars are observed to undergo small, abrupt rotational speed-up. This
phenomenon is known as glitch. In pulsar timing observations, detection of a
neutron star glitch is constrained by the time of occurrence of the event
relative to entire observing span and observing cadences, time of occurrence of
preceding/subsequent glitches relative to observing cadences and the strength
of timing noise. Using the Yu et al. (2013) data sets, in this paper, we
analyse the observational selection in terms of detection probability. We
define partial probabilities for the constraints and use Monte Carlo method
with assuming glitches distribute uniformly to solve the complete probability
formula for both group case involving 157 pulsars and individual cases for each
of the seven pulsars with glitch numbers $\geqslant 5$. In the simulations,
numerical Bayesian inference is used for glitch identification. With the
derived detection probability density and observed results, we uncover glitch
size probability distribution embedded in the data for both the group and
individual cases. We find the most prominent correction occurred for
PSR~J1341$-$6220, in which exponent of the power-law model varies from the
observed $+0.7^{+1.4}_{-0.7}$ to $-0.4^{+1.0}_{-0.4}$. We suggest observers
determine the detection probability for glitch theories, e.g. the
self-organised criticality.
