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

The role of form in morphological priming: evidence from bilinguals

This article explores how bilinguals perform automatic morphological decomposition processes, focusing on within- and cross-language masked morphological priming effects. In Experiment 1, unbalanced Spanish (L1) – English (L2) bilingual participants completed a lexical decision task on English targets that could be preceded by morphologically related or unrelated derived masked English and Spanish prime words. The cognate status of the masked Spanish primes was manipulated, in order to explore to what extent form overlap mediates cross-language morphological priming. In Experiment 2, a group of balanced native Basque-Spanish speakers completed a lexical decision task on Spanish targets preceded by morphologically related or unrelated Basque or Spanish masked primes. In this experiment, a large number of items was tested and the cognate status was manipulated according to a continuous measure of orthographic overlap, allowing for a fine-grained analysis of the role of form overlap in cross-language morphological priming. Results demonstrated the existence of between- language masked morphological priming, which was exclusively found for cognate prime-target pairs. Furthermore, the results from balanced and unbalanced bilinguals were highly similar showing that proficiency in the two languages at test does not seem to modulate the pattern of data. These results are correctly accounted for by mechanisms of early morpho-orthographic decomposition that do not necessarily imply an automatic translation of the prime. In contrast, other competing accounts that are based on translation processes do not seem able to capture the present results

Compilation of analyses of risks and measures, deliverable 8.2 of the H2020 project SafetyCube

This deliverable provides information on how the information on road safety risks and measures that has been collected within SafetyCube, is processed, stored and made available to users through the SafetyCube Decision Support System (DSS) [...continues]

SafetyCube: Building a decision support system on risks and measures

The EU research project SafetyCube (Safety CaUsation, Benefits and Efficiency) is developing an innovative road safety Decision Support System (DSS) collecting the available evidence on a broad range of road risks and possible countermeasures. 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 (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

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

Time-series models with meteorological variables to forecast accident figures

Die Bundesanstalt für Straßenwesen (BASt) bringt zum Ende jeden Jahres eine Prognose der Unfall- und Verunglücktenzahlen des noch laufenden Jahres heraus, um so über die Entwicklung der Verkehrssicherheit in Deutschland Bilanz ziehen zu können. Dabei wird das Unfallgeschehen nach dem Schweregrad der Konsequenzen, der Ortslage sowie Alter und Art der Verkehrsbeteiligung der Verunglückten in 27 Zeitreihen unterteilt. Zu diesem Zeitpunkt sind die Daten lediglich für die ersten acht oder neun Monate erhältlich. Um Bilanz zu ziehen, werden die Anzahlen der letzten drei oder vier Monate prognostiziert. Gesamtziel des hier beschriebenen Forschungsvorhabens ist die Optimierung der jährlichen Unfallprognosen durch Anwendung von strukturellen Zeitreihenmodellen, bei denen die Vorhersagen aus dem Trend der vorliegenden Monate, und der Dynamik der vorhergehenden Jahre abgeleitet werden. Um dem Einfluss der Witterungsverhältnisse Rechnung zu tragen, werden dabei meteorologische Variablen in das Vorhersagemodell aufgenommen. Um die Modelle zu testen, werden die endgültigen Daten der letzten 15 Jahre jeweils aus den vorläufigen Daten der ersten Monate vorhergesagt und mit den tatsächlich beobachteten endgültigen Unfall- und Verunglücktenzahlen verglichen. Die Resultate zeigen, dass im Vergleich zu den bisherigen Vorhersagen mithilfe der hier vorgestellten Modelle die Vorhersagen für 25 der 27 Reihen präziser werden. Lediglich zwei Reihen zeigen einen leichten Anstieg des Vorhersagefehlers. Beim Vergleich von Modellen mit und ohne meteorologischen Variablen zeigt sich, dass 23 der 27 Reihen besser vorhergesagt werden können, wenn man das Wetter berücksichtigt. Neben der verbesserten Vorhersage ermöglicht die Aufnahme der Wettervariablen auch eine Einschätzung, wie groß der Einfluss der Witterungsgegebenheiten auf das Unfallgeschehen ist. Es zeigt sich also, dass die Anwendung von strukturellen Zeitreihenmodellen und die Berücksichtigung von meteorologischen Variablen zu einer deutlichen Verbesserung der Vorhersagegenauigkeit führen. Die Verbesserung der Vorhersagen durch die Aufnahme von Wettervariablen bestätigt nochmals den Einfluss der Witterungsumstände auf das Unfallgeschehen.At the end of each year, the German Federal Highway Research Institute (BASt) draws the balance of the road-safety development by forecasting the accident and casualty numbers of the closing year. They describe the development of 27 time-series 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. 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 which derive the forecasts for the remaining months from the trend observed in the first months of the year and the dynamics of the earlier development. To take the weather conditions into account, meteorological variables are included into the forecasting model. To test the models, the final data of the last 15 years were predicted from the preliminary data of the first months for each year. These predictions were compared to the actually observed final numbers of accidents and casualties. The results show that, compared to the earlier heuristic approach, 25 out of the 27 time-series are forecasted more precisely by the models presented. Only two series show a slightly increasing prediction error. When comparing models with and without meteorological variables, 23 out of 27 series were predicted more accurately when taking the weather into account. Apart from increasing the forecasting precision, the inclusion of meteorological variables also allows estimating to what extent changes in the observed numbers of accidents and casualties can be attributed to the specific weather condition in a particular month. We conclude that structural time series modelling and the inclusion of meteorological Variables clearly improves the forecasting precision in the year-end prognosis of the German accident and casualty numbers. The improved prediction due to the inclusion of meteorological variables confirms the dependence of these numbers on the weather condition throughout the year

The Portuguese inflected infinitive: an empirical approach

This paper deals with the seemingly free competition between inflected and uninflected infinitives in Portuguese, a much-debated issue in Portuguese linguistics, which, however, has not been seriously empirically studied before. We specifically focus on Vesterinen’s (2006, 2011) cognitive hypothesis according to which the inflected infinitive is used in cases in which the infinitival subject risks to be less cognitively accessible due to contextual reasons. We investigate this theory by analyzing both corpus and experimental (self-paced reading) data, making use of advanced linear modeling. We show that both types of analysis lead to complementary results: the inflected form primarily eases the processing of sentences with increased complexity. On the basis of these results, we argue that Vesterinen’s accessibility account is but part of the solution for the inflected/non-inflected problem