886 resultados para Difference-in-Difference


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Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

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Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys. Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone. The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.

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The aim of this paper is to find out if there is a significant difference in using NDVI dataset processed by harmonic analysis method to evaluate its dynamic and response to climate change, compared with the original data.

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It is the author’s position that the framework for WID/GAD, as academic field and practice concerned primarily with developing countries should be broadened so as to incorporate Japan’s own gender and development issues in its scope. Unlike other developed countries, activists and scholars in Japan rarely connected, as was also the case with the fields of women’s/gender studies and WID/GAD. However, this was not due to any lack of interest among Japanese women regarding the lives of women in developing countries. Rather the points of fissure were the notions of ‘difference’ and ‘development’ held by Japanese women. These analytical concepts were narrowly defined, which resulted in limited interaction between discourse on women’s issues in Japan and WID/GAD related to ‘other’ women. By re-examining these notions and looking more deeply into perceived differences in the local context of ‘development’, not only can we strategize on ‘differences’ in such a way that we draw strength from the very fact of being different, but also prevent ‘differences’ from being used as grounds for discrimination. As a whole, we could gain substantially by broadening the field of Gender and Development and, as such, it is imperative that this field be broadened with urgency as development itself changes in this ever-interconnected world

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With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

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Representational difference analysis was used to identify strain-specific differences in the pseudoautosomal region (PAR) of mouse X and Y chromosomes. One second generation (C57BL/6 x Mus spretus) x Mus spretus interspecific backcross male carrying the C57BL/6 (B6) PAR was used for tester DNA. DNA from five backcross males from the same generation that were M. spretus-type for the PAR was pooled for the driver. A cloned probe designated B6-38 was recovered that is B6-specific in Southern analysis. Analysis of genomic DNA from several inbred strains of laboratory mice and diverse Mus species and subspecies identified a characteristic Pst I pattern of fragment sizes that is present only in the C57BL family of strains. Hybridization was observed with sequences in DBA/2J and to a limited extent with Mus musculus (PWK strain) and Mus castaneus DNA. No hybridization was observed in DNA of different Mus species, M. spretus, M. hortulanus, and M. caroli. Genetic analyses of B6-38 was conducted using C57BL congenic males that carry M. spretus alleles for distal X chromosome loci and the PAR and outcrosses of heterozygous congenic females with M. spretus. These analyses demonstrated that the B6-38 sequences were inherited with both the X and Y chromosome. B6-38 sequences were genetically mapped as a locus within the PAR using two interspecific backcrosses. The locus defined by B6-38 is designated DXYRp1. Preliminary analyses of recombination between the distal X chromosome gene amelogenin (Amg) and the PAR loci for either TelXY or sex chromosome association (Sxa) suggest that the locus DXYRp1 maps to the distal portion of the PAR.

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Homozygous deletions have been central to the discovery of several tumor-suppressor genes, but their finding has often been either serendipitous or the result of a directed search. A recently described technique [Lisitsyn, N., Lisitsyn, N. & Wigler, M. (1993) Science 259, 946-951] held out the potential to efficiently discover such events in an unbiased manner. Here we present the application of the representational difference analysis (RDA) to the study of cancer. We cloned two DNA fragments that identified a homozygous deletion in a human pancreatic adenocarcinoma, mapping to a 1-centimorgan region at chromosome 13q12.3 flanked by the markers D13S171 and D13S260. Interestingly, this lies within the 6-centimorgan region recently identified as the BRCA2 locus of heritable breast cancer susceptibility. This suggests that the same gene may be involved in multiple tumor types and that its function is that of a tumor suppressor rather than that of a dominant oncogene.

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From a set of gonioapparent automotive samples from different manufacturers we selected 28 low-chroma color pairs with relatively small color differences predominantly in lightness. These color pairs were visually assessed with a gray scale at six different viewing angles by a panel of 10 observers. Using the Standardized Residual Sum of Squares (STRESS) index, the results of our visual experiment were tested against predictions made by 12 modern color-difference formulas. From a weighted STRESS index accounting for the uncertainty in visual assessments, the best prediction of our whole experiment was achieved using AUDI2000, CAM02-SCD, CAM02-UCS and OSA-GP-Euclidean color-difference formulas, which were no statistically significant different among them. A two-step optimization of the original AUDI2000 color-difference formula resulted in a modified AUDI2000 formula which performed both, significantly better than the original formula and below the experimental inter-observer variability. Nevertheless the proposal of a new revised AUDI2000 color-difference formula requires additional experimental data.

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A driving argument behind recent EU treaty reforms was that more qualified majority voting (QMV) was required to reduce the potential dangers of legislative paralysis caused by enlargement. Whilst existing literature on enlargement mostly focuses on the question of what changed in the legislative process after the 2004 enlargement, the question of why these changes occurred has been given far less attention. Through the use of a single veto player theoretical model, this paper seeks to test and explain whether enlargement reduces the efficiency of the legislative process and alters the type of legislation produced, and whether QMV can compensate for these effects. In doing this, it offers a theoretical explanation as to why institutional changes that alter the level of cohesion between actors in the Council have an influence over both the legislative process and its outcomes.