There was no significant difference in the risk of pneumonia in aspirating patients who took thin liquids with safety strategies compared with those who took thickened liquids only. This result, however, is generalizable only for patients with low risk of pneumonia.
Public news can be expected to change market prices but, unlike ''public information,'' there are differing expectations about the impact. Hence trading is necessary for the market to process these divergent views. A surprise announcement of an increase in German interest rates coupled with concurrent transactions data enables us to study in detail dealers' reactions. The patterns observed are consistent with dealers' practice to book targeted profits immediately if possible in the face of uncertainty. Evidence also shows that the speculative activity by traders in initial reaction to the news destabilized the market for the next 2 h.
An important disconnect exists between the current use of formal modeling and applied statistical analysis. In general, a lack of linkage between the two can produce statistically significant parameters of ambiguous origin that, in turn, fail to assist in falsifying theories and hypotheses. To address this scientific challenge, a framework for unification is proposed. Methodological unification leverages the mutually reinforcing properties of formal and applied statistical analysis to produce greater transparency in relating theory to test. This framework for methodological unification, or what has been referred to as the empirical implications of theoretical models (EITM), includes (1) connecting behavioral (formal) and applied statistical concepts, (2) developing behavioral (formal) and applied statistical analogues of these concepts, and (3) linking and evaluating the behavioral (formal) and applied statistical analogues. The elements of this EITM framework are illustrated with examples from voting behavior, macroeconomic policy and outcomes, and political turnout.Empirical observation, in the absence of a theoretical base, is at best descriptive. It tells one what happened, but not why it has the pattern one perceives. Theoretical analysis, in the absence of empirical testing, has a framework more noteworthy for its logical or mathematical elegance than for its utility in generating insights into the real world. The first exercise has been described as "data dredging," the second as building "elegant models of irrelevant universes." My purpose is to try to understand what I believe to be a problem of major importance. This understanding cannot be achieved merely by observation, for their comments and assistance. 1 The discussion focuses on formal analysis and applied statistical analysis. Formal analysis refers to deductive modeling that includes a theorem and proof presentation or computational modeling requiring simulation. Applied statistical analysis involves data analysis using statistical tools. We use the terms analysis and modeling interchangeably.In addition, the linkage of formal and applied statistical analysis-the form of methodological unification described in this articlepossesses important attributes that aid in falsification and, ultimately, scientific cumulation. Formal models, for example, force clarity stract symbols. Real insight can be gained only by their combination.
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