Stochastic diffusion models (Ratcliff, 1978) can be used to analyze response time data from binary decision tasks. They provide detailed information about cognitive processes underlying the performance in such tasks. Most importantly, different parameters are estimated from the response time distributions of correct responses and errors that map (1) the speed of information uptake, (2) the amount of information used to make a decision, (3) possible decision biases, and (4) the duration of nondecisional processes. Although this kind of model can be applied to many experimental paradigms and provides much more insight than the analysis of mean response times can, it is still rarely used in cognitive psychology. In the present paper, we provide comprehensive information on the theory of the diffusion model, as well as on practical issues that have to be considered for implementing the model.

Diffusion models (Ratcliff, 1978) make it possible to identify and separate different cognitive processes underlying responses in binary decision tasks (e.g., the speed of information accumulation vs. the degree of response conservatism). This becomes possible because of the high degree of information utilization involved. Not only mean response times or error rates are used for the parameter estimation, but also the response time distributions of both correct and error responses. In a series of simulation studies, the efficiency and robustness of parameter recovery were compared for models differing in complexity (i.e., in numbers of free parameters) and trial numbers (ranging from 24 to 5,000) using three different optimization criteria (maximum likelihood, Kolmogorov-Smirnov, and chi-square) that are all implemented in the latest version of fast-dm (Voss, Voss, & Lerche, 2015). The results revealed that maximum likelihood is superior for uncontaminated data, but in the presence of fast contaminants, Kolmogorov-Smirnov outperforms the other two methods. For most conditions, chi-square-based parameter estimations lead to less precise results than the other optimization criteria. The performance of the fast-dm methods was compared to the EZ approach (Wagenmakers, van der Maas, & Grasman, 2007) and to a Bayesian implementation (Wiecki, Sofer, & Frank, 2013). Recommendations for trial numbers are derived from the results for models of different complexities. Interestingly, under certain conditions even small numbers of trials (N < 100) are sufficient for robust parameter estimation.

Why did substantial parts of Europe abandon the institutionalized churches around 1900? Empirical studies using modern data mostly contradict the traditional view that education was a leading source of the seismic social phenomenon of secularization. We construct Valuable comments were kindly provided by the editor, five anonymous referees, Oliver Falck, David Figlio, Jared Rubin, and seminar participants at Stanford, Gothenburg, Hong Kong UST, Modena, the Graduate Institute of International and Development Studies in Geneva, Umeå, the Max Planck Institute for Research on Collective Goods in Bonn, the CAGE/CEPR Conference on "Long-Run Growth: Unified Growth Theory and Economic History" at Warwick, the CAS conference on "The Long Shadow of History" in Munich, the CEPR Economic History Symposium in Perugia, the CESifo Economics of Education area meeting in Munich, the European Economic Association in Gothenburg, the Economic History Society in Warwick, the Association for the Study of Religion, Economics, and Culture at Chapman University, the German Economic Association in Hamburg, the Ammersee workshop "Natural Experiments and Controlled Field Studies", the Education Committee of the German Economic Association in Wuppertal, and the workshop "Political Economy, Economic History, and Religion" at WZB Berlin. We are grateful to Lucian Hölscher for providing the Sacrament Statistics, to Christoph Albert, Laurenz Detsch, and Andreas Ferrara for capable research assistance, and to the Pact for Research and Innovation of the Leibniz Association for partial financial support. a unique panel dataset of advanced-school enrollment and Protestant church attendance in German cities between 1890 and 1930. Our cross-sectional estimates replicate a positive association. By contrast, in panel models where fixed effects account for time-invariant unobserved heterogeneity, education-but not income or urbanization-is negatively related to church attendance. In panel models with lagged explanatory variables, educational expansion precedes reduced church attendance, while the reverse is not true. Dynamic panel models with lagged dependent variables and instrumental-variable models using variation in school supply confirm the results. The pattern of results across school types is most consistent with a mechanism of increased critical thinking in general rather than specific knowledge of natural sciences.

The majority of patients with epilepsy maintain seizure control during pregnancy. The apparently higher risk of seizures among women treated with oxcarbazepine and the more frequent increases in drug load in the oxcarbazepine and lamotrigine cohorts prompts further studies on relationships with pharmacokinetic changes. Risks associated with status epilepticus appear to be lower than previously reported.

BACKGROUND Although polypharmacy is associated with a negative clinical outcome in various settings and commonly observed in patients receiving oral anticoagulation therapy, evidence on the relevance for the clinical outcome of anticoagulated patients is currently limited. The aim of the study was to investigate the effect of polypharmacy on the clinical outcomes among patients taking phenprocoumon. DESIGN Prospective cohort study. SETTING Regular medical care. PARTICIPANTS Information on 2011 individuals receiving vitamin K antagonists was available for analysis from the prospective multicenter thrombEVAL study. MEASUREMENTS Data were obtained from clinical visits, computer‐assisted interviews, and laboratory measurements. Information on clinical outcome was obtained during a 3‐year follow‐up period and subsequently validated via medical records. RESULTS The prevalence of polypharmacy (five drugs or more) was 84.1% (n = 1691). Quality of anticoagulation therapy assessed by time in therapeutic range was lower in individuals on five to eight drugs and nine drugs or more (70.7% and 64.7%, respectively) compared with subjects without polypharmacy (73.4%). In addition, a significantly higher variability of international normalized ratio measurements was found in the presence of polypharmacy. The cumulative incidence of bleeding, hospitalization, and all‐cause mortality, but not for thromboembolic events, increased across groups of medication. In adjusted Cox regression analysis, polypharmacy is an independent risk factor for bleeding (hazard ratio [HR]≥ 9 drugs vs 1‐4 drugs = 1.62; 95% confidence interval [CI] = 1.04‐2.52; p = .033); hospitalization (HR≥ 9 drugs vs 1‐4 drugs = 1.60; 95% CI = 1.26‐2.03; p < .001; and all‐cause mortality (HR≥ 9 drugs vs 1‐4 drugs = 2.16; 95% CI = 1.43‐3.27; p < .001) in a dose‐dependent relationship. Per additional drug, bleeding risk was increased by 4%. CONCLUSIONS Polypharmacy influences the quality of anticoagulation therapy and translates into an elevated risk of adverse events in anticoagulated patients. This suggests that additional medication intake in such patients should be critically reviewed by physicians, and it highlights the importance of initiating investigations aimed at reducing multiple medication intake. J Am Geriatr Soc 67:463–470, 2019.