The European road safety decision support system on risks and measures.

The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs.

Forecasting German crash numbers: The effect of meteorological variables.

At the end of each year, the German Federal Highway Research Institute (BASt) publishes the road safety balance of the closing year. They describe the development of accident and casualty numbers disaggregated by road user types, age groups, type of road and the consequences of the accidents. However, at the time of publishing, these series are only available for the first eight or nine months of the year. To make the balance for the whole year, the last three or four months are forecasted. The objective of this study was to improve the accuracy of these forecasts through structural time-series models that include effects of meteorological conditions. The results show that, compared to the earlier heuristic approach, root mean squared errors are reduced by up to 55% and only two out of the 27 different data series yield a modest rise of prediction errors. With the exception of four data series, prediction accuracies also clearly improve incorporating meteorological data in the analysis. We conclude that our approach provides a valid alternative to provide input to policy makers in Germany.

The word frequency effect in first- and second-language word recognition: a lexical entrenchment account.

We investigate the origin of differences in the word frequency effect between native speakers and second-language speakers. In a large-scale analysis of English word identification times we find that group-level differences are fully accounted for by the individual language proficiency scores. Furthermore, exactly the same quantitative relation between word frequency and proficiency is found for monolinguals and three different bilingual populations (Dutch-English, French-English, and German-English). We conclude that the larger frequency effects for second-language processing than for native-language processing can be explained by within-language characteristics and thus need not be the consequence of "being bilingual" (i.e., a qualitative difference). More specifically, we argue that language proficiency increases lexical entrenchment, which leads to a reduced frequency effect, irrespective of bilingualism, language dominance, and language similarity.

Dealing with zero word frequencies: a review of the existing rules of thumb and a suggestion for an evidence-based choice.

In a critical review of the heuristics used to deal with zero word frequencies, we show that four are suboptimal, one is good, and one may be acceptable. The four suboptimal strategies are discarding words with zero frequencies, giving words with zero frequencies a very low frequency, adding 1 to the frequency per million, and making use of the Good-Turing algorithm. The good algorithm is the Laplace transformation, which consists of adding 1 to each frequency count and increasing the total corpus size by the number of word types observed. A strategy that may be acceptable is to guess the frequency of absent words on the basis of other corpora and then increasing the total corpus size by the estimated summed frequency of the missing words. A comparison with the lexical decision times of the English Lexicon Project and the British Lexicon Project suggests that the Laplace transformation gives the most useful estimates (in addition to being easy to calculate). Therefore, we recommend it to researchers.

How Noisy is Lexical Decision?

Lexical decision is one of the most frequently used tasks in word recognition research. Theoretical conclusions are typically derived from a linear model on the reaction times (RTs) of correct word trials only (e.g., linear regression and ANOVA). Although these models estimate random measurement error for RTs, considering only correct trials implicitly assumes that word/non-word categorizations are without noise: words receive a yes-response because they have been recognized, and they receive a no-response when they are not known. Hence, when participants are presented with the same stimuli on two separate occasions, they are expected to give the same response. We demonstrate that this not true and that responses in a lexical decision task suffer from inconsistency in participants' response choice, meaning that RTs of "correct" word responses include RTs of trials on which participants did not recognize the stimulus. We obtained estimates of this internal noise using established methods from sensory psychophysics (Burgess and Colborne, 1988). The results show similar noise values as in typical psychophysical signal detection experiments when sensitivity and response bias are taken into account (Neri, 2010). These estimates imply that, with an optimal choice model, only 83-91% of the response choices can be explained (i.e., can be used to derive theoretical conclusions). For word responses, word frequencies below 10 per million yield alarmingly low percentages of consistent responses (near 50%). The same analysis can be applied to RTs, yielding noise estimates about three times higher. Correspondingly, the estimated amount of consistent trial-level variance in RTs is only 8%. These figures are especially relevant given the recent popularity of trial-level lexical decision models using the linear mixed-effects approach (e.g., Baayen et al., 2008).

How lingering representations of abandoned context words affect speech production.

Four experiments tested whether and how initially planned but then abandoned speech can influence the production of a subsequent resumption. Participants named initial pictures, which were sometimes suddenly replaced by target pictures that were related in meaning or word form or were unrelated. They then had to stop and resume with the name of the target picture. Target picture naming latencies were measured separately for trials in which the initial speech was skipped, interrupted, or completed. Semantically related initial pictures helped the production of the target word, although the effect dissipated once the utterance of the initial picture name had been completed. In contrast, phonologically related initial pictures hindered the production of the target word, but only for trials in which the name of the initial picture had at least partly been uttered. This semantic facilitation and phonological interference did not depend on the time interval between the initial and target picture, which was either varied between 200 ms and 400 ms (Experiments 1-2) or was kept constant at 300 ms (Experiments 3-4). We discuss the implications of these results for models of speech self-monitoring and for models of problem-free word production.

Further evidence for temporal decay in working memory: reply to Lewandowsky and Oberauer (2009).

The sources of forgetting in working memory (WM) are a matter of intense debate: Is there a time-related decay of memory traces, or is forgetting uniquely due to representation-based interference? In a previous study, we claimed to have provided evidence supporting the temporal decay hypothesis (S. Portrat, P. Barrouillet, & V. Camos, 2008). However, reanalyzing our data, S. Lewandowsky and K. Oberauer (2009) demonstrated that they do not provide compelling evidence for temporal decay and suggested a class of alternative models favoring a representation-based interference account. In this article, we develop from the most recent proposals made by Lewandowsky and Oberauer 2 of the most plausible extensions of these alternative models. We show that neither of these extensions can account for recent findings related to between-domain WM performance and that both lead to predictions that are contradicted by new empirical evidence. Finally, we show that recent studies that have been claimed to rule out the temporal decay hypothesis do not resist close scrutiny. We conclude that the time-based resource-sharing model remains the most parsimonious way to account for forgetting and restoration of memory traces in WM.

Practice effects in large-scale visual word recognition studies: a lexical decision study on 14,000 dutch mono- and disyllabic words and nonwords.

In recent years, psycholinguistics has seen a remarkable growth of research based on the analysis of data from large-scale studies of word recognition, in particular lexical decision and word naming. We present the data of the Dutch Lexicon Project (DLP) in which a group of 39 participants made lexical decisions to 14,000 words and the same number of nonwords. To examine whether the extensive practice precludes comparison with the traditional short experiments, we look at the differences between the first and the last session, compare the results with the English Lexicon Project (ELP) and the French Lexicon Project (FLP), and examine to what extent established findings in Dutch psycholinguistics can be replicated in virtual experiments. Our results show that when good nonwords are used, practice effects are minimal in lexical decision experiments and do not invalidate the behavioral data. For instance, the word frequency curve is the same in DLP as in ELP and FLP. Also, the Dutch-English cognate effect is the same in DLP as in a previously published factorial experiment. This means that large-scale word recognition studies can make use of psychophysical and psychometrical approaches. In addition, our data represent an important collection of very long series of individual reaction times that may be of interest to researchers in other areas.

Semantic transparency and masked morphological priming: the case of prefixed words.

In four lexical decision experiments, we investigated masked morphological priming with Dutch prefixed words. Reliable effects of morphological relatedness were obtained with visual primes and visual targets in the absence of effects due to pure form overlap. In certain conditions, priming effects were significantly greater with semantically transparent prefixed primes (e.g., rename-name) relative to the priming effects obtained with semantically opaque prefixed words (e.g., relate-late), even with very brief (40-msec) prime durations. With visual primes and auditory targets (cross-modal priming), significant facilitation was found in all related prime conditions, independent of whether or not primes were morphologically related to targets. The results are interpreted within a bimodal hierarchical model of word recognition in which morphological effects arise through the interplay of sublexical (morpho-orthographic) and supralexical (morpho-semantic) representations. The word stimuli from this study may be downloaded as supplemental materials from http://mc.psychonomic-journals.org/content/supplemental.

Does bilingualism change native-language reading? Cognate effects in a sentence context.

Becoming a bilingual can change a person's cognitive functioning and language processing in a number of ways. This study focused on how knowledge of a second language influences how people read sentences written in their native language. We used the cognate-facilitation effect as a marker of cross-lingual activations in both languages. Cognates (e.g., Dutch-English schip [ship]) and controls were presented in a sentence context, and eye movements were monitored. Results showed faster reading times for cognates than for controls. Thus, this study shows that one of people's most automated skills, reading in one's native language, is changed by the knowledge of a second language.

The size of the cross-lingual masked phonological priming effect does not depend on second language proficiency.

Using a masked phonological priming paradigm, Brysbaert, Van Dyck, and Van de Poel (1999) showed that Dutch-French bilinguals perform better at identifying tachistoscopically presented L2 words (e.g., oui [yes]) when those words are primed by L1 words or nonwords that are homophonic to the L2 target word according to the L1 grapheme-phoneme conversion rules (e.g., wie [who]). They noted that this priming effect was smaller for balanced bilinguals than for less proficient bilinguals, although the interaction failed to reach significance. Findings of Gollan, Forster, and Frost (1997) suggest that this could be attributed to a greater reliance on phonology in L2 reading, caused by a smaller proficiency in this language. However, in this study we show that the Dutch-French cross-lingual phonological priming effect is equally large for perfectly balanced and less proficient bilinguals. Our findings are in line with more recent work of Van Wijnendaele and Brysbaert (2002).

Masked repetition and phonological priming within and across modalities.

Lexical decision latencies to word targets presented either visually or auditorily were faster when directly preceded by a briefly presented (53-ms) pattern-masked visual prime that was the same word as the target (repetition primes), compared with different word primes. Primes that were pseudohomophones of target words did not significantly influence target processing compared with unrelated primes (Experiments 1-2) but did produce robust priming effects with slightly longer prime exposures (67 ms) in Experiment 3. Like repetition priming, these pseudohomophone priming effects did not interact with target modality. Experiments 4 and 5 replicated this general pattern of effects while introducing a different measure of prime visibility and an orthographic priming condition. Results are interpreted within the framework of a bimodal interactive activation model.