Sample Files Research Articles

Association of State Laws and Healthcare Workers’ Influenza Vaccination Rates

State laws are being used to increase healthcare worker (HCW) influenza vaccine uptake. Approximately 40% of states have enacted such laws but their effectiveness has been infrequently studied. Data sources for this study were the 2000-2011 U.S. National Health Interview Survey Adult Sample File and a summary of U.S. state HCW influenza vaccination laws. Hierarchical linear modeling was used for two time periods: 1) 2000-2005 (before enactment of many state laws) and 2) 2006-2011 (a time of increased enactment of state HCW influenza vaccination legislation). During 2000-2005, two states had HCW influenza vaccination laws and HCW influenza vaccination rates averaged 22.5%. In 2006-2011, 19 states had such laws and vaccination rates averaged 50.9% (p < 0.001). The likelihood of HCW vaccination increased with the scope and breadth, measured by a law score. Although laws varied widely in scope and applicability, states with HCW influenza vaccination laws reported higher HCW vaccination rates.

Detection of Productively Rearranged TcR-α V-J Sequences in TCGA Exome Files: Implications for Tumor Immunoscoring and Recovery of Antitumor T-cells.

Tumor immunoscoring is rapidly becoming a universal parameter of prognosis, and T-cells isolated from tumor masses are used for ex vivo amplification and readministration to patients to facilitate an antitumor immune response. We recently exploited the cancer genome atlas (TCGA) RNASeq data to assess T-cell receptor (TcR) expression and, in particular, discovered strong correlations between major histocompatibility class II (MHCII) and TcR-α constant region expression levels. In this article, we describe the results of searching TCGA exome files for TcR-α V-regions, followed by searching the V-region datasets for TcR-α-J regions. Both primary and metastatic breast cancer sample files contained recombined TcR-α V–J regions, ranging in read counts from 16–39, at the higher level. Among four such V–J rearrangements, three were productive rearrangements. Rearranged TcR-α V–J regions were also detected in TCGA–bladder cancer, –lung cancer, and –ovarian cancer datasets, as well as exome files representing bladder cancer, in Moffitt Cancer Center patients. These results suggest that a direct search of commonly available, conventional exome files for rearranged TcR segments could play a role in more sophisticated immunoscoring or in identifying particular T-cell clones and TcRs directed against tumor antigens.

Extending ELAN into variationist sociolinguistics

Abstract Prior to the implementation of ELAN (tla.mpi.nl/tools/tla-tools/elan, Wittenburg et al. 2006), it was common for sociolinguists to use multiple software applications, and consequently multiple formats, along the route from recording participants to conducting statistical analyses of the data. We present a method which allows for transcription, extracting, coding, preparation for statistical analysis, calculation of some basic frequency statistics, and creation of a concordance all within one program. ELAN is well established as a valuable tool for language documentation. ELAN is frequently used for transcription and multi-tier mark-up illustrating levels of linguistic structure as well as translations and glosses. We hope that this crossover introduction will encourage the efficiency of documentary linguists among sociolinguists and increase the interest in documenting variation among documentarians. After providing an overview of ELAN’s utility, we focus on extracting (or marking) and coding tokens of linguistic variables for quantitative analysis in the variationist sociolinguistic framework. This seamless connection between recording, transcript and coding of dependent and independent variables improves consistency, efficiency, utility, reliability and the accountability of our coding to the original recording. We illustrate a range of benefits and include step-by-step instructions accompanied by downloadable sample files and video clips to illustrate each step of the process (Extending ELAN tutorial files.zip). We also include instructions on importing existing (legacy) transcripts into ELAN.

Association Between Transcatheter Aortic Valve Implantation Volume and Outcomes in the United States

With the rapid advance of transcatheter aortic valve implantation (TAVI), it is important to evaluate the relationship between TAVI volumes and outcomes. The aim of this study was to analyze in-hospital outcomes after TAVI stratified according to hospital volumes. Using the National Inpatient Sample files from 2012, hospitals performing transfemoral (TF)-TAVI and transapical (TA)-TAVI were divided into high-volume and low-volume centers. A total of 7,660 patients underwent TAVI in 256 hospitals in 2012. In the TF-TAVI cohort, multivariate logistic regression analyses demonstrated that low TF-TAVI volume status was an independent predictor of death and bleeding. In the TA-TAVI cohort, low volume status was a predictor of death, myocardial infarction, and need for permanent pacemaker. In addition, hospitals that performed low TA-TAVI volume were associated with significantly higher rate of death after surgical aortic valve replacement in comparison with the hospitals that perform high TA-TAVI volume (3.6% vs 2.3%, p <0.001). In conclusion, centers with lower volume of TAVI had more frequent adverse events compared with higher volume centers.

DIDA: Distributed Indexing Dispatched Alignment.

One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too large, the alignment process becomes computationally challenging. This is usually addressed by preprocessing techniques, where the queries and/or targets are indexed for easy access while searching for matches. When the target is static, such as in an established reference genome, the cost of indexing is amortized by reusing the generated index. However, when the targets are non-static, such as contigs in the intermediate steps of a de novo assembly process, a new index must be computed for each run. To address such scalability problems, we present DIDA, a novel framework that distributes the indexing and alignment tasks into smaller subtasks over a cluster of compute nodes. It provides a workflow beyond the common practice of embarrassingly parallel implementations. DIDA is a cost-effective, scalable and modular framework for the sequence alignment problem in terms of memory usage and runtime. It can be employed in large-scale alignments to draft genomes and intermediate stages of de novo assembly runs. The DIDA source code, sample files and user manual are available through http://www.bcgsc.ca/platform/bioinfo/software/dida. The software is released under the British Columbia Cancer Agency License (BCCA), and is free for academic use.

Costs and In-Hospital Outcomes of Transcatheter Aortic Valve Implantation Versus Surgical Aortic Valve Replacement in Commercial Cases Using a Propensity Score Matched Model

The aim of this study was to compare in-hospital cost and outcomes between transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR). TAVI is an effective treatment option in patients with symptomatic aortic stenosis who are at high risk for traditional SAVR. Several studies using trial data or outside United States registry data have addressed TAVI cost issues, although there is a paucity of cost data involving commercial cases in the United States. Using Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project Nationwide Inpatient Sample files, a propensity score-matched analysis of all commercial TAVI and SAVR cases performed in 2011 was conducted. Overall hospital cost and length of stay, as well as procedural complications, were compared between the 2 matched cohorts: 595 TAVI patients were matched to 1,785 SAVR patients in a 1:3 ratio. There was no difference in mean ($181,912 vs $196,298) or median ($152,993 vs $155,974) hospital cost between TAVI and SAVR (p = 0.60). The TAVI group had significantly shorter lengths of hospital stay than the SAVR group (mean 9.76 vs 12.01 days, p <0.001). There was no difference in postprocedural in-hospital death or stroke, but TAVI patients were more likely to have bleeding complications, to have vascular complications, and to require pacemakers. In conclusion, when analyzing in-hospital cost of commercial TAVI and SAVR cases using the Nationwide Inpatient Sample data set, TAVI is an economically satisfactory alternative to SAVR and results in an approximately 2-day shorter length of stay during the index hospitalization.

Forecasting Financial Performance for Quarries/ Předvídání Hospodářského Výsledku Lomů

Abstract The paper highlights the importance of successful financial performance for companies, and provides for a brief review of foreign expert opinions on the most important factors that influence the financial performance of enterprises. Linear and quadratic discriminate analyses and a logistic regression analysis were applied to a sample file of 233 annual data from 3 countries (Czech Republic, Slovak Republic, Ukraine) for a period of 2008-2012 concerning quarries extracting building materials. These methods provided for distributing the sample file quarries into two classes of profitable and loss-making enterprises. Their financial performance had been known, which enabled to assess the classification accuracy of individual method applications. The average classification accuracy was about 86% and there were no significant differences in the specific method applications. The linear discriminate analysis calculations are the simplest ones in comparison with two other applied methods. The linear discriminate analysis also made possible to identify the most influential discriminators that contributed to the classification into the specific groups. In case of our investigation, prices per production unit, direct variable costs, and ratio of fixed costs to total costs were the most important factors of influence. The factors, if analysed, can provide for prediction of financial performance of quarries in future.

Proteome analysis of stratum corneum from atopic dermatitis patients by hybrid quadrupole-orbitrap mass spectrometer

Proteome analysis of stratum corneum from atopic dermatitis patients by hybrid quadrupole-orbitrap mass spectrometer

Number of people in the United States experiencing ambulatory and independent living difficulties.

Estimating the characteristics of the "disabled" population is necessary for some governments and of interest to health researchers concerned with producing disability prevalence rates. Because generating easy-to-understand estimates of disability in the population is important, this article provides U.S. population estimates for two disability-related measures by using the 2009 to 2011 American Community Survey Public Use Microdata Sample file. The number of people who have "independent living" and "ambulatory" difficulties is calculated from a sample of 9,204,437 (representing >309 million people). The percentage for "disabled" is found to vary by racial and ethnic category, sex, age, citizenship status, educational attainment, and state-level regions divided by weather.

Mexican Americans’ Lucky Few and Baby Boom Cohorts: How Is Relative Cohort Size Related to the Likelihood of Being Out-of-Poverty?

Generational cohorts influence individuals’ economic life chances. Retrospective analysis has found that the “Lucky Few” generation had better life chances than previous generations. We focus on Mexican Americans in the United States and offer a prospective analysis to explore how relative cohort size plays a role in the odds of their being out-of-poverty. Using Public Use Microdata Sample files from 1990, 2000, and 2010, we test the hypothesis by comparing Early Baby Boom (those born between 1946 and 1955) and Late Baby Boom (those born between 1956 and 1965) cohorts to the Lucky Few (born between 1936 and 1945) cohort. Models predicting the odds of being out-of-poverty during the peak wage-earning years indicate that belonging to the Lucky Few cohort affords Mexican Americans no economic advantage. Our findings demonstrate that the relative cohort size hypothesis may not always be generalized to Mexican American minority samples.

Married Once, Twice, and Three or More Times: Data From the American Community Survey

Some people might marry more than once in their lifetime. The demographic characteristics of groups by number of marriages have received little attention. As there is limited knowledge about how demographic profiles differ by number of remarriages, this descriptive report offers detailed tabulations of basic demographic characteristics by number of marriages. The logistic regression predicting the likelihood of having 2 or more marriages in a sample of ever married adults (age > 21) complements the project. By using data from the single-year American Community Survey 2010 Public Use Microdata Sample file, it is found that about 20% of the population reports being married more than once. Regression results indicate that educational attainment, race or ethnic status, age, nativity, disability, and personal income are all associated with the probability of experiencing multiple marriages. Future efforts should continue to provide descriptive characteristics of the population by number of marriages to better understand population-level trends.

Microdata on the Belgian Population for 1961–2001: Documenting and Reconstructing the 1961 Census Sample

This article describes the background and reconstruction of the Belgian 1961 census sample file. Recently, a complete codebook for the sample file has been drawn up, and the representativeness of the sample has been evaluated as accurate, except for the loss of cases that occurred for three Belgian subregions. With the addition of the 1961 census sample, cross-sectional microdata from the five successive population censuses since that year, covering a broad range of topics, are now available to the research community. The reconstruction of the 1961 census sample was part of the activities of the HISSTAT project, which is currently being run by a consortium of research institutions in Belgium to bring together cross-sectional aggregated data since 1800, aggregated longitudinal data since 1880, and cross-sectional microdata since 1961, all covering the entire country.

Choice or necessity: do immigrants and their children choose self-employment for the same reasons?

Using a generational cohort method and the 1981 and 2006 Canadian Census 20 per cent sample files, this study examines whether the effects of three important determinants of self-employment – expected earnings differentials between paid and self-employment, difficulties in the labour market, and ethnic enclave – differ between immigrants and non-immigrants. Unemployment had a stronger push effect on self-employment among immigrant fathers than among Canadian-born fathers. Expected earnings differential had a stronger effect among Canadian-born fathers than among immigrant fathers. Sons of both immigrants and the Canadian-born were more strongly affected by expected earnings differentials than were their fathers, while unemployment was not a significant factor for them. Ethnic enclave was not positively associated with the self-employment rates among both immigrants and their children.

CONTIGUITY PRINCIPLE FOR GEOGRAPHIC UNITS: EVIDENCE ON THE QUANTITY, DEGREE, AND LOCATION OF PUBLIC USE MICRODATA AREA (PUMA) FRAGMENTATION

Social scientists investigating how context varies by geographical location and/or how macro - level phenomenon affects individual outcomes often make use of U.S. Census Bureau Public Use Microdata Sample (PUMS) files where micro - units can only be geographic ally located to Public Use Microdata Area (PUMA) polygons. Most spatial analysis investig a- tions with PUMAs ignore the fact that many of them are multipart polygons — spatially separated polygons that share the same attribute and are stored as a single featu re in a vector file. We briefly discuss the theoretical premises of how ge o- graphical boundaries are created for macro units and investigate the quantity, degree, and location of PUMA fragment a- tion. We argue that the basic contiguity principle (the assumpti on that spatial analysis uses polygon centroids for solid and contiguous geographic units) in spatial dependence analysis is being violated with many PUMAs in the U.S. mainland — where Texas, California, Tennessee, and Illinois merit special attention. Futur e research should outline a method for ha n- dling multipart polygons in spatial and hierarchical analyses.

&lt;b&gt;GENES - a software package for analysis in experimental statistics and quantitative genetics&lt;/b&gt; - doi: 10.4025/actasciagron.v35i3.21251

GENES is a software package used for data analysis and processing with different biometric models and is essential in genetic studies applied to plant and animal breeding. It allows parameter estimation to analyze biological phenomena and is fundamental for the decision-making process and predictions of success and viability of selection strategies. The program can be downloaded from the Internet (http://www.ufv.br/dbg/genes/genes.htm or http://www.ufv.br/dbg/biodata.htm) and is available in Portuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/) and a set of sample files are also provided, making GENES easy to use. The software is integrated into the programs MS Word, MS Excel and Paint, ensuring simplicity and effectiveness in data import and export of results, figures and data. It is also compatible with the free software R and Matlab, through the supply of useful scripts available for complementary analyses in different areas, including genome wide selection, prediction of breeding values and use of neural networks in genetic improvement.

Maximum Entropy Dasymetric Modeling for Demographic Small Area Estimation

This article describes a framework for maximum entropy dasymetric modeling based on spatial allocations of public use microdata sample (PUMS) files provided by the U.S. Census Bureau. The spatial units of the PUMS (PUMAs; public use microdata areas) are too large for fine‐scale geographic analysis of populations because the common expectation is high degrees of variation within one PUMA (containing about 100,000 people). Limited demographic attribution is available at finer spatial resolutions in census summary tables for tracts and block groups. The described method (i.e., the coupling of spatial allocation procedures with dasymetric modeling) extends the literature and implements related variable associations and limiting variable constraints for allocating microdata household records to census tracts, based on sampling weights imputed using maximum entropy models. We present techniques to quantify household‐level uncertainty and to show how this information is useful for guiding the dasymetric modeling and for improving the choice of limiting and related ancillary variables. We demonstrate our methods with a PUMA in Davidson County, Tennessee. Census summary statistics are used as related variables, and land cover‐derived residential areas are included as limiting variables to refine the solution spatially to a subtract level.本文提出了基于美国人口统计局提供的公众微观采样数据（PUMS）的空间布局分析的最大熵密度建模框架。因一个PUMA(包含10万人的统计区)通常被认为有高的变异度，导致其空间单元对于精细尺度的人口地理分析而言过大。在区块组的人口普查表中少有精细尺度的人口属性收。本文所提方法（即基于密度建模的耦合空间配置过程），基于最大熵模型对采样权重进行填充，扩展了现有方法，实现了相关变量的集成以及面向微观住户记录对空间配置的限制变量约束。我们给出了量化住户水平的不确定性量化技术，展示了该信息如何有效指导了密度建模以及增强了限制变量和相关辅助变量的选择。以西安纳西州戴维森的一个PUMA的基础统计作为相关变量，并将土地覆盖‐居民区分布作为限制变量，演示了将结果空间精细化至向亚调查块层次。

Integrated description of agricultural field experiments and production: The ICASA Version 2.0 data standards

Agricultural research increasingly seeks to quantify complex interactions of processes for a wide range of environmental conditions and crop management scenarios, leading to investigation where multiple sets of experimental data are examined using tools such as simulation and regression. The use of standard data formats for documenting experiments and modeling crop growth and development can facilitate exchanges of information and software, allowing researchers to focus on research per se rather than on converting and re-formatting data or trying to estimate or otherwise compensate for missing information. The standards developed by the International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) project and subsequently revised by the International Consortium for Agricultural Systems Applications (ICASA) were of considerable value for describing experiments. However, the resulting ICASA Version 1 standards did not consider important management practices such as tillage and use of mulches, lacked descriptors for certain soil and plant traits (especially related to nutrient levels), and contained minor logical inconsistencies. The ICASA standards have evolved to allow description of additional management practices and traits of soils and plants and to provide greater emphasis on standardizing vocabularies, clarifying relations among variables, and expanding formats beyond the original plain text file format. This paper provides an overview of the ICASA Version 2.0 standards. The foundation of the standards is a master list variables that is organized in a hierarchical arrangement with major separations among descriptions of management practices or treatments, environmental conditions (soil and weather data), and measurements of crop responses. The plain text implementation is described in detail. Implementations in other digital formats (databases, spreadsheets, and data interchange formats) are also reviewed. Areas for further improvement and development are noted, particularly as related to describing pest damage, data quality and appropriate use of datasets. The master variable list and sample files are provided as electronic supplements.

E-Doctor: A Web based Support Vector Machine for Automatic Medical Diagnosis

This paper proposes e-doctor; a web-based application that makes automatic diagnoses about health problems. The whole procedure is based on Support Vector Machines (SVMs), which are supervised learning models that analyze data and proceed to decisions, based on their knowledge. System administrators define specific characteristics for each health problem that can be diagnosed, and educate the SVM by entering sample files of statistical data. After that, medical staff can enter exam information about patients, and e-doctor makes an automatic diagnosis/prediction by means of answering if the patient has (or may have in the future) a specific health problem. The application can be used in cases where statistical information plays a vital role on deciding about a patient's condition. A prototype was developed and the system trained and tested for the case of heart symptoms. The results were satisfactory.

Abstract WP296: Direct Cost Savings Associated with Intensive Systolic Blood Pressure Reduction in Patients with Intracerebral Hemorrhage

INTRODUCTION: The Antihypertensive treatment of Acute Cerebral Hemorrhage (ATACH) II is determining whether intensive systolic blood pressure (SBP) reduction (SBP ≤140mm Hg) using IV nicardipine initiated within 4.5 hours of onset of intracerebral hemorrhage (ICH) reduces the likelihood of death or disability (modified Rankin scale [mRS] score of 4-6) at 3 months by ≥10% compared with standard SBP reduction (SBP ≤180mm Hg). Objective: To determine the direct cost savings by intensive systolic blood pressure reduction if the 10% reduction in death and disability goals are met in patients with ICH. Methods: The dose and duration of IV nicardipine to achieve different SBP goals were derived from ATACH I and the probability of death or disability were obtained from placebo treated ICH patients recruited in recombinant factor VII trials. Total cost associated with acute hospitalization was derived from Nationwide Inpatient Sample files 2010 for none-mild disability (home discharge considered equivalent to mRS 0-1), moderate disability (in-patient rehabilitation=mRS 2-3), severe disability (nursing home=mRS=4-5), and death. The cost of nursing home stay, in-patient and out-patient rehabilitation services, and physician visits were derived from MetLife Market Survey of Nursing Home and Home Care and Medicare re-imbursement policy. Results: The estimated incremental costs for IV nicardipine for intensive SBP reduction was $85,600 for 100 patients treated. The direct cost of death and disability (cost of acute hospitalization, post-hospital care, and physician visits visit for 90 days) was estimated to be $4,377,142 in 100 patients treated with standard SBP reduction. The cost saving was estimated to be $147,570 if 10% of patients with mRS 4-5 changed to mRS 2-3. The cost saving was estimated to be $357,685 if 10% of patients with mRS 4-5 changed to mRS 2-3 (5%) and mRS 0-1 (5%). The net savings in the first and second scenario were $61,970 and $272,085 per 100 patients treated in the first 90 days, respectively. Conclusions: Intensive SBP reduction in patients with ICH appears to result in prominent cost savings if the ATACH II goals of reduction in death and disability are met.

Methodological note: Allocation of disability items in the American Community Survey

BackgroundDetermining the prevalence and correlates of disability requires the use of sample surveys in data analysis. In an effort to generate complete datasets, allocation procedures (i.e., the assignment of values to missing or illogical responses) are frequently used for missing or inconsistent responses. ObjectivesThe goal of this investigation was to explore how six disability-related questions vary in their degree of allocation and how research results may be sensitive to this procedure. This is important because many researchers using large disability information banks are not survey methodologists and may be unaware of how the Census Bureau's editing procedures can influence research findings. MethodsWe use 2010 1-year Public Use Microdata Sample files from the American Community Survey (ACS). We investigated the allocation rates of the following disability items: self-care; hearing; vision; independent living; ambulatory; and cognitive ability. We also asked how allocation rates varied by demographic characteristics and whether the allocated values could influence multivariate results. ResultsDisability item allocation in ACS data have detectable patterns, where the rate of disability allocation is higher for mail surveys, males, older people, groups who speak English not well or not at all, US citizens, Latinos(as), and for people living in or near poverty. Multivariate models may be sensitive to how these allocated values are treated. ConclusionsThe rate of allocations varies as a function of demographic variables because of methodological procedures and survey participation behaviors. Because allocation rates may affect research and policy about the disabled population, more research is required.