1,720,974 research outputs found
THREE ESSAYS IN HEALTH SERVICES RESEARCH: IMPACT OF THE AFFORDABLE CARE ACT ON ACCESS TO CARE AND HOSPITALIZATION IN TEXAS
Full text linkThis dissertation presents evaluations of ACA reforms in the state of Texas. In the first essay, I use descriptive analysis to show that after the establishment of the ACA Marketplaces in Texas, the rate of hospital discharges decreased for uninsured patients and increased for privately insured patients. In the second essay, I use the difference-in-difference method to examine if the Marketplace component of the ACA has affected the uninsured discharge rate for acute care services. I find a causal impact of Marketplaces on the ratio of uninsured discharges. In the third essay, I examine the expansion of Medicaid Managed Care (MMC) that required almost all beneficiaries to shift from Medicaid Fee-for-Service to MMC. I examine if this reform has reduced the volume of discharges overall and for potentially preventable conditions in acute care hospitals. I find no impact of MMC on inpatient care use over the time span of study
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Essays on Smoking, Drinking and Obesity: Evidence from a Randomized Experiment
Full text linkThis dissertation consists of three chapters analyzing risky health behaviors utilizing data from the Lung Health Study (LHS), a randomized smoking cessation program. The first two chapters of this dissertation analyze the effects of smoking on alcohol consumption and BMI, respectively. The third chapter studies whether and how much the objective smoking information, which is defined by clinicians, may be misreported.
The first chapter examines the effect of smoking on alcoholic beverage consumption. The epidemiology literature suggests that both behaviors affect similar brain regions and are commonly consumed together. So far, the economics literature has presented inconclusive causal evidence on the relationship. Building on the theory of rational addiction, I estimate the relationship between smoking and alcohol consumption using several different smoking measures. I report four salient findings. First, self-reported and clinically verified smoking variables suggest that quitting smoking lowers alcoholic beverages consumption by 11.5%. Second, cigarette consumption dating back 12 months affects alcohol consumption, and those with the highest past 12 months average cigarette consumption see the largest increase in alcohol consumption. Third, I find that the length of quitting affects future alcohol consumption as well. Continuously abstaining from smoking for 12 months reduces alcoholic beverage consumption by 27.5% per week. Fourth, non-smoking for 12 months also reduces the probability of drinking any alcoholic beverages by 31%.
The second chapter aims to identify the causal effect of smoking on body mass index (BMI). Since nicotine is a metabolic stimulant and appetite suppressant, quitting or reducing smoking could lead to weight gain. Using randomized treatment assignment to instrument for smoking, we estimate that quitting smoking leads to an average long-run weight gain of 1.8-1.9 BMI units, or 11-12 pounds at the average height. These results imply that the drop in smoking in recent decades explains 14% of the concurrent rise in obesity. Semi-parametric models provide evidence of a diminishing marginal effect of smoking on BMI, while subsample regressions show that the impact is largest for younger individuals, females, those with no college degree, and those with healthy baseline BMI levels.
The third chapter analyzes and compares self-reported and clinically verified smoking information. Descriptive statistics show that about 8% of clinically verified smokers self-report that they do not smoke (under-report participation), and that smoking cessation treatment group participants misreport smoking participation 2 to 1 relative to control group participants. In our first methodological approach we regard the objectively verified smoking measure as the gold standard. We estimate linear probability models and find that being male and married increases the probability of misreporting by 10 percentage points. Additionally, older participants are more likely to misreport smoking status, while those using nicotine gum and with a higher BMI are less likely to misreport. However, all variables can only explain a small fraction of the variation that explains misreporting. Our second methodological approach takes an agnostic view on whether the clinically verified smoking information is accurate. We utilize BMI, Carbon Monoxide (CO), and Cotinine level information to inform whether a person is a smoker. We estimate a Bayesian mixture model to account for the heterogeneity in BMI, CO and Cotinine levels after a substantial decrease in post treatment smoking participation. All of our models show that smokers are more likely assigned to the low BMI, high CO and high Cotinine level distributions. Among those classified as misreporters, we find that 30% have a very high probability of being part of the non-smoking distributions. As a result, we believe that objectively- verified smoking measure may not be better than the self-reported measure.Doctor of Philosophy (PhD)Economic
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
