Bayesian evidence synthesis as a flexible alternative to meta-analysis: A simulation study and empirical demonstration.

Synthesizing results across multiple studies is a popular way to increase the robustness of scientific findings. The most well-known method for doing this is meta-analysis. However, because meta-analysis requires conceptually comparable effect sizes with the same statistical form, meta-analysis may not be possible when studies are highly diverse in terms of their research design, participant characteristics, or operationalization of key variables. In these situations, Bayesian evidence synthesis may constitute a flexible and feasible alternative, as this method combines studies at the hypothesis level rather than at the level of the effect size. This method therefore poses less constraints on the studies to be combined. In this study, we introduce Bayesian evidence synthesis and show through simulations when this method diverges from what would be expected in a meta-analysis to help researchers correctly interpret the synthesis results. As an empirical demonstration, we also apply Bayesian evidence synthesis to a published meta-analysis on statistical learning in people with and without developmental language disorder. We highlight the strengths and weaknesses of the proposed method and offer suggestions for future research.

Cross-linguistic influence in simultaneous and early sequential bilingual children: a meta-analysis.

Although cross-linguistic influence at the level of morphosyntax is one of the most intensively studied topics in child bilingualism, the circumstances under which it occurs remain unclear. In this meta-analysis, we measured the effect size of cross-linguistic influence and systematically assessed its predictors in 750 simultaneous and early sequential bilingual children in 17 unique language combinations across 26 experimental studies. We found a significant small to moderate average effect size of cross-linguistic influence, indicating that cross-linguistic influence is part and parcel of bilingual development. Language dominance, operationalized as societal language, was a significant predictor of cross-linguistic influence, whereas surface overlap, language domain and age were not. Perhaps an even more important finding was that definitions and operationalisations of cross-linguistic influence and its predictors varied considerably between studies. This could explain the absence of a comprehensive theory in the field. To solve this issue, we argue for a more uniform method of studying cross-linguistic influence.

Testing the validity of the Cross-Linguistic Lexical Task as a measure of language proficiency in bilingual children.

The Cross-linguistic Lexical Task (CLT; Haman, Luniewska & Pomiechowska, 2015) is a vocabulary task designed to enable cross-linguistic comparisons both across and within (bilingual) children. In this paper we assessed the validity of the CLT as a measure of language proficiency in bilingual children, by determining the extent to which (i) age-matched, monolingual Spanish-speaking and Dutch-speaking children obtained similar scores, (ii) the CLT correlated with other measures of language proficiency in monolingual and bilingual children, and (iii) whether the factors underlying the CLT's construction, i.e., target words' estimated Age of Acquisition and Complexity Index, were predictive of children's scores. Our results showed that, while the CLT correlated with other measures and is therefore a valid means of tapping into language proficiency, caution is required when using it to compare children's language proficiency cross-linguistically, as scores for Dutch-speaking and Spanish-speaking monolinguals sometimes differed.