I propose a new model, ordered Beta regression, for continuous distributions with both lower and upper bounds, such as data arising from survey slider scales, visual analog scales, and dose–response relationships. This model employs the cut point technique popularized by ordered logit to fit a single linear model to both continuous (0,1) and degenerate [0,1] responses. The model can be estimated with or without observations at the bounds, and as such is a general solution for these types of data. Employing a Monte Carlo simulation, I show that the model is noticeably more efficient than ordinary least squares regression, zero-and-one-inflated Beta regression, rescaled Beta regression, and fractional logit while fully capturing nuances in the outcome. I apply the model to a replication of the Aidt and Jensen (2014, European Economic Review 72, 52–75) study of suffrage extensions in Europe. The model can be fit with the R package ordbetareg to facilitate hierarchical, dynamic, and multivariate modeling.

This study examines the variable positioning of a finite adverbial subordinate clause and its main clause with the subordinate clause either preceding or following the main clause in native versus nonnative English. Specifically, we contrast causal, concessive, conditional, and temporal adverbial clauses produced by German and Chinese learners of English with those produced by native speakers. We examined 2,362 attestations from the Chinese and German subsections of the International Corpus of Learner English (Granger, Dagneaux, Meunier, & Paquot, 2009) and from the Louvain Corpus of Native English Essays (Granger, 1998). All instances were annotated for the ordering, the subordinate clause type, the lengths of the main and subordinate clauses, the first language of the speakers, the conjunction used, and the file it originated from (as a proxy for the speaker producing the sentence so as to be able to study individual and lexical variation). The results of a two-step regression modeling protocol suggest that learners behave most nativelike with causal clauses and struggle most with conditional and concessive clauses; in addition, learners make more non-nativelike choices when the main and subordinate clause are of about equal length.

Structural priming is the phenomenon that speakers tend to re-use structures they have recently comprehended or produced themselves. Most studies on this topic are experimental and looked at within-language priming. However, there are now also many observational studies, a development that is inextricably related to new/larger corpora, new statistical methodologies, and new theoretical ideas. Second, there is a growing body of research on cross-linguistic structural priming, though mostly experimental. These developments lead to a new potential research avenue: cross-linguistic priming on the basis of observational data. Here, we will first summarize some fundamental studies of cross-linguistic priming, and then trace the historical development of observational studies of structural priming to showcase how statistical and theoretical developments have shaped research on priming in general and discuss what such observational priming research has offered to within-language priming research. We end with a discussion of how this research can inform cross-linguistic priming.