Current attempts at methodological reform in sciences come in response to an overall 9 lack of rigor in methodological and scientific practices in experimental sciences. However, some of 10 these reform attempts suffer from the same mistakes and over-generalizations they purport to 11 address. Considering the costs of allowing false claims to become canonized, we argue for more 12 rigor and nuance in methodological reform. By way of example, we present a formal analysis of 13 three common claims in the metascientific literature: (a) that reproducibility is the cornerstone of 14 science; (b) that data must not be used twice in any analysis; and (c) that exploratory projects are 15 characterized by poor statistical practice. We show that none of these three claims are correct in 16 general and we explore when they do and do not hold. 17 18 42 1 of 28 Manuscript submitted.an opportunity: reformers are in an opportune position to take criticism and self-correct before 43 allowing false claims to be canonized as methodological facts (Nissen et al., 2016). 44 In this paper we advocate for the necessity of statistically rigorous and scientifically nuanced 45 arguments to make proper methodological claims in the reform literature. Toward this aim, we 46 evaluate three examples of methodological claims that have been advanced and well-accepted (as 47 implied by the large number of citations) in the reform literature: 48 1. Reproducibility is the cornerstone of, or a demarcation criterion for, science. 49 2. Using data more than once invalidates statistical inference. 50 3. Exploratory research uses "wonky" statistics. 51 Each of these claims suffers from some of the problems outlined earlier and as a result, has 52 contributed to methodological half-truths (or untruths). We evaluate each claim using statistical 53 theory against a broad philosophical and scientific background. 54 While we focus on these three claims, we believe our call for rigor and nuance can reach 55 further with the following emphasis: Statistics is a formal science whose methodological claims 56 follow from probability calculus. Methodological claims are either proved mathematically or by 57 simulation before being advanced for the use of scientists. Most valid methodological advances 58 are incremental, and they rarely ever provide simple prescriptions to complex inference problems. 59 Norms issued on the basis of bold claims about new methods might be quickly adopted by empirical 60 scientists as heuristics and might alter scientific practices. However, advancing such reforms in the 61 absence of formal proofs is sacrificing rigor for boldness and can lead to unforeseeable scientific 62 consequences. We believe that hasty revolution may hold science back more than it helps move 63 it forward. We hope that our approach may facilitate scientific progress that stands on firm 64 ground-supported by theory or evidence. 65 Claim 1: Reproducibility is the cornerstone of, or a demarcation criterion 66 for, science. 67 A common asser...