Liberalization is a perennial topic in politics and political science. We first review a broad scholarly debate, showing that the mainstream theories make rival and contradictory claims regarding the role of political parties in (de)liberalization reforms. We then develop a framework of conditional partisan influence, arguing that and under what conditions parties matter. We test our (and rival) propositions with a new dataset on (de)liberalization reforms in 23 democracies since 1973 covering several policy areas. Methodologically, we argue that existing quantitative studies are problematic: They rely on time-series cross-section models using country-year observations; but governments do not change annually, so that the number of observations is artificially inflated, resulting in incorrect estimates. We propose mixed-effects models instead, with country-year observations nested in cabinets, which are nested in countries and years. The results show under what conditions parties matter for (de)liberalization. More generally, the paper argues that mixed-effects models should become the new standard for studying partisan influences.

Using multiple languages may confer distinct advantages in cognitive control, yet it is unclear whether bilingualism is associated with better implicit statistical learning, a core cognitive ability underlying language. We tested bilingual adults on a challenging task requiring simultaneous learning of two miniature grammars characterized by different statistics. We found that participants learned each grammar significantly better than chance and both grammars equally well. Crucially, a validated continuous measure of bilingual dominance predicted accuracy scores for both artificial grammars in a generalized linear model. The study thus demonstrates the first graded advantage in learning novel statistical relations in adult bilinguals.

Scientific understanding of multitactic weed management systems (MTS) is complicated by (1) the large number of potential combinations among tactics, (2) potentially noisy and complex system behavior because of individually more moderate mortality events, and (3) possible transient system behavior of unknown duration. Therefore, decomposing the relative performance of MTS components is much more difficult than it is for single-tactic strategies (STS). Attempting to accommodate the increased complexity of system behavior while maintaining the generality of results requires analytical methods capable of accomplishing these tasks. We provide two examples of statistical procedures that may help gain understanding of MTS systems using previously published weed demographic time-series data. First, we demonstrate the use of mixed-effects models capable of representing and removing factors contributing uncontrolled variation to system behavior. Model selection criteria are used to highlight the importance of the increased flexibility the mixed-model framework provides. Second, by explicitly modeling the probabilistic process presumed to be generating the data, we demonstrate how different components of the MTS can be compared and how the methodology can facilitate integration of such information into a decision-making application.

We explored the effect of education and occupational complexity on the rate of cognitive decline (as measured by the Mini-Mental State Examination) in 171 patients with a confirmed Alzheimer's disease (AD) diagnosis. Complexity was measured as substantive complexity of work and complexity of work with data, people, and things. Average lifetime occupational complexity was calculated based on years at each occupation. Participants were followed for an average of 2.5 years and 3.7 visits. In multivariate mixed-effects models, high education, high substantive complexity, and high complexity of work with data and people predicted faster rates of cognitive decline, controlling for age, gender, native language, dementia severity, and entry into the analyses at initial versus follow-up testing. These results provide support for the concept of cognitive reserve according to which greater reserve may postpone clinical onset of AD but also accelerate cognitive decline after the onset. (JINS, 2006, 12, 147–152.)