Preregistration in infant research—A primer

Abstract

Preregistration, the act of specifying a research plan in advance, is becoming more common in scientific research. Infant researchers contend with unique problems that might make preregistration particularly challenging. Infants are a hard‐to‐reach population, usually yielding small sample sizes, they can only complete a limited number of trials, and they can be excluded based on hard‐to‐predict complications (e.g., parental interference, fussiness). In addition, as effects themselves potentially change with age and population, it is hard to calculate an a priori effect size. At the same time, these very factors make preregistration in infant studies a valuable tool. A priori examination of the planned study, including the hypotheses, sample size, and resulting statistical power, increases the credibility of single studies and adds value to the field. Preregistration might also improve explicit decision making to create better studies. We present an in‐depth discussion of the issues uniquely relevant to infant researchers, and ways to contend with them in preregistration and study planning. We provide recommendations to researchers interested in following current best practices.

18‐month‐olds fail to use recent experience to infer the syntactic category of novel words

“…Since infants are an especially hard‐to‐reach and to‐test population, the value of publishing a registered report might be even greater than in areas where recruitment and testing are easy. Several rounds of peer review would arguably improve the design and put in place safeguards for quality control, which would reduce the file‐drawer problem on the one hand, and the incentive to engage in questionable research practices on the other (see Havron, Bergmann & Tsuji, 2020, for best practice preregistration recommendations in infant studies).…”

Six solutions for more reliable infant research

“…In sum, optimizing approaches to data exclusion can increase observed effect size, without necessarily requiring testing more infants in total to achieve appropriate statistical power. Note that to avoid p-hacking, plans for data exclusion should be pre-registered (see Havron et al, 2020). At the same time, transparent exploration of the effects of different exclusion criteria, even if not pre-registered, could provide researchers with guidance in developing data exclusion plans for future studies.…”

Preregistration in experimental linguistics: applications, challenges, and limitations

“…A preregistration is a time-stamped document in which researchers specify how they plan to collect their data and/or how they plan to conduct their confirmatory analysis (e.g., Wagenmakers et al 2012, Nosek and Lakens 2014, see Marsden et al 2018b, Morgan-Short et al 2018, Havron et al 2020 for language-related research).…”

“…It also allows transparently tracking analytical flexibility and counteracting publication bias. Many authors have discussed the concept of preregistration across disciplines before (e.g., Wagenmakers et al 2012, Nosek andLakens 2014) and there are relevant discussions within the language sciences for second language research (Marsden et al 2018b, Morgan-Short et al 2018 and language acquisition research (Havron et al 2020). However, I think it is worth to reiterate applications, challenges, and limitations of preregistration for experimental linguistics at large.…”