THE EMPIRICAL FRAMEWORK: METHODOLOGY, DATA AND COMPUTATION ALGORITHM

Technovation ◽  
1994 ◽  
Vol 14 (5) ◽  
pp. 311-321 ◽  
Author(s):  
Vinod Kumar ◽  
Aditha N.S. Persaud ◽  
Uma Kumar

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110294
Author(s):  
Jayme E Locke ◽  
Rhiannon D Reed ◽  
Richard M Shewchuk ◽  
Katherine L Stegner ◽  
Haiyan Qu

Making up 13.4% of the United States population, African Americans (AAs) account for 28.7% of candidates who are currently waiting for an organ donation. AAs are disproportionately affected by end-organ disease, particularly kidney disease, therefore, the need for transplantation among this population is high, and the high need is also observed for other solid organ transplantation. To this end, we worked with the AA community to derive an empirical framework of organ donation strategies that may facilitate AA decision-making. We used a cognitive mapping approach involving two distinct phases of primary data collection and a sequence of data analytic procedures to elicit and systematically organize strategies for facilitating organ donation. AA adults ( n = 89) sorted 27 strategies identified from nominal group technique meetings in phase 1 based on their perceived similarities. Sorting data were aggregated and analyzed using Multidimensional scaling and hierarchical cluster analyses. Among 89 AA participants, 68.2% were female, 65.5% obtained > high school education, 69.5% reported annual household income ≤ $50,000. The average age was 47.4 years (SD = 14.5). Derived empirical framework consisted of five distinct clusters: fundamental knowledge, psychosocial support, community awareness, community engagement, and system accountability; and two dimensions: Approach, Donor-related Information. The derived empirical framework reflects an organization scheme that may facilitate AA decision-making about organ donation and suggests that targeted dissemination of donor-related information at both the individual-donor and community levels may be critical for increasing donation rates among AAs.


2019 ◽  
Vol 10 (3) ◽  
pp. 1069-1107 ◽  
Author(s):  
Fumio Hayashi ◽  
Junko Koeda

We propose an empirical framework for analyzing the macroeconomic effects of quantitative easing (QE) and apply it to Japan. The framework is a regime‐switching structural vector autoregression in which the monetary policy regime, chosen by the central bank responding to economic conditions, is endogenous and observable. QE is modeled as one of the regimes. The model incorporates an exit condition for terminating QE. We find that higher reserves at the effective lower bound raise inflation and output, and that terminating QE may be contractionary or expansionary, depending on the state of the economy at the point of exit.


RSC Advances ◽  
2015 ◽  
Vol 5 (56) ◽  
pp. 45520-45527 ◽  
Author(s):  
Mengshan Li ◽  
Xingyuan Huang ◽  
Hesheng Liu ◽  
Bingxiang Liu ◽  
Yan Wu ◽  
...  

Excellent prediction modeling of CO2 solubility in polymers using hybrid computation algorithm.


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