Parameter estimation from galaxy survey data from the full-shape method depends on scale cuts and priors on effective-field theory (EFT) parameters. The effects of priors, including the so-called “prior volume” phenomenon, have been originally studied in Ivanov et al. [J. Cosmol. Astropart. Phys. 05 (2020) 042] and subsequent works. In this note, we repeat and extend these tests and also apply them to other priors used in the literature. We point out that, in addition to the “prior volume” effect, there is a more important effect that is largely overlooked: a systematic bias on cosmological parameters due to overoptimistic scale cuts. Unlike the prior volume effect, this is a genuine systematic bias due to two-loop corrections that does not vanish with better priors or with larger data volumes. Our study is based on the high-fidelity BOSS-like PT challenge simulation data, which offer many advantages over analyses based on synthetic data generated with fitting pipelines. We show that some analysis choices associated with the pybird code, especially the scale cuts, significantly bias parameter recovery, overestimating ${\sigma }_8$ by 5% (equivalent to $1\sigma$). The bias on measured EFT parameters is even more significant. The analysis choices associated with the class-pt code lead to much smaller ($\lesssim 1\%$) shifts in cosmological parameters based on their best-fit values.

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• Cosmological parameters
• Evolution of the Universe
• Large scale structure of the Universe