Texas A&M University

About: Texas A&M University is a education organization based out in College Station, Texas, United States. It is known for research contribution in the topics: Population & Finite element method. The organization has 72169 authors who have published 164372 publications receiving 5764236 citations.

Effect Size in Single-Case Research: A Review of Nine Nonoverlap Techniques

Abstract: With rapid advances in the analysis of data from single-case research designs, the various behavior-change indices, that is, effect sizes, can be confusing. To reduce this confusion, nine effect-size indices are described and compared. Each of these indices examines data nonoverlap between phases. Similarities and differences, both conceptual and computational, are highlighted. Seven of the nine indices are applied to a sample of 200 published time series data sets, to examine their distributions. A generic meta-analytic method is presented for combining nonoverlap indices across multiple data series within complex designs.

VEGF upregulates ecNOS message, protein, and NO production in human endothelial cells

Abstract: Vascular endothelial growth factor (VEGF) is an endothelium-specific secreted protein that potently stimulates vasodilation, microvascular hyperpermeability, and angiogenesis. Nitric oxide (NO) is ...

Government Spending Multipliers in Good Times and in Bad: Evidence from U.S. Historical Data

Abstract: This paper investigates whether U.S. government spending multipliers differ according to two potentially important features of the economy: (1) the amount of slack and (2) whether interest rates are near the zero lower bound. We shed light on these questions by analyzing new quarterly historical U.S. data covering multiple large wars and deep recessions. We estimate a state-dependent model in which impulse responses and multipliers depend on the average dynamics of the economy in each state. We find no evidence that multipliers differ by the amount of slack in the economy. These results are robust to many alternative specifications. The results are less clear for the zero lower bound. For the entire sample, there is no evidence of elevated multipliers near the zero lower bound. When World War II is excluded, some point estimates suggest higher multipliers during the zero lower bound state, but they are not statistically different from the normal state. Our results imply that, contrary to recent conjecture, government spending multipliers were not necessarily higher than average during the Great Recession.