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Data Analysis (data + analysis)
Kinds of Data Analysis Terms modified by Data Analysis Selected AbstractsBUILDING A DATA-MINING GRID FOR MULTIPLE HUMAN BRAIN DATA ANALYSISCOMPUTATIONAL INTELLIGENCE, Issue 2 2005Ning Zhong E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision. [source] An Exemplar of the Use of NNN Language in Developing Evidence-Based Practice GuidelinesINTERNATIONAL JOURNAL OF NURSING TERMINOLOGIES AND CLASSIFICATION, Issue 1 2008CRRN-A, Donald D. Kautz PhD PURPOSE. To explore the use of standardized language, NNN, in the development of evidence-based practice (EBP). DATA SOURCES. Published research and texts on family interventions, nursing diagnoses (NANDA-I), nursing interventions (NIC), and nursing outcomes (NOC). DATA ANALYSIS. Research literature was summarized and synthesized to determine levels of evidence for the NIC intervention Family Integrity Promotion. CONCLUSIONS. The authors advocate that a "standards of practice" category of levels of evidence be adopted for interventions not amenable to randomized controlled trials or for which a body of research has not been developed. Priorities for nursing family intervention research are identified. IMPLICATIONS FOR NURSING PRACTICE. The use of NANDA-I nursing diagnoses, NIC interventions, and NOC outcomes (NNN language) as research frameworks will facilitate the development of EBP guidelines and the use of appropriate outcome measures. [source] SENSOMINER: A PACKAGE FOR SENSORY DATA ANALYSISJOURNAL OF SENSORY STUDIES, Issue 1 2008SEBASTIEN LE ABSTRACT We propose a new package for sensory data analysis, named SensoMineR. SensoMineR is implemented in the R programming environment and can be accessed at the following addresses: http://sensominer.free.fr or http://cran.r-project.org. This package produces graphical displays of data that are simple to interpret, and it also provides syntheses of results issuing from various analysis of variance models or from various factor analysis methods accompanied with confidence ellipses. PRACTICAL APPLICATIONS SensoMineR is a free software intended for sensory analysts from both academic and corporate institutions. SensoMineR is an easy and powerful solution that tackles the following problems: characterization of the products, panel performance assessment, links between sensory and instrumental data, consumer's preferences, napping evaluation, optimal designs. SensoMineR is implemented in R and can be used easily with the help of a very intuitive graphical interface. [source] DATA ANALYSIS OF PENETROMETRIC FORCE/DISPLACEMENT CURVES FOR THE CHARACTERIZATION OF WHOLE APPLE FRUITSJOURNAL OF TEXTURE STUDIES, Issue 4 2005C. CAMPS ABSTRACT The objective of the present study was to compare two chemometric approaches for characterizing the rheological properties of fruits from puncture test force/displacement curves. The first approach (parameter approach) computed six texture parameters from the curves, which were supposed to be representative of skin hardness, fruit deformation before skin rupture, flesh firmness and mechanical work needed to penetrate the fruit. The second approach (whole curve approach) used the whole digitized curve (300 data points) in further data processing. Two experimental studies were compared: first, the variability of the rheological parameters of five apple cultivars; second, the rheological variability that was characterized as a function of storage conditions. For both approaches, factorial discriminant analysis was applied to discriminate the fruits based on the measured rheological properties. The qualitative groups in factorial discriminant analysis were either the apple cultivar or the storage conditions (days and temperatures of storage). The tests were carried out using cross-validation procedures, making it possible to compute the number of fruits correctly identified. Thus the percentage of correct identification was 92% and 87% for using the parameter and the whole curve approaches, respectively. The discrimination of storage duration was less accurate for both approaches giving about 50% correct identifications. Comparison of the percentage of correct classifications based on the whole curve and the parameter approaches showed that the six computed parameters gave a good summary of the information present in the curve. The whole curve approach showed that some additional information, not present in the six parameters, may be appropriate for a complete description of the fruit rheology. [source] II. METHOD AND DATA ANALYSISMONOGRAPHS OF THE SOCIETY FOR RESEARCH IN CHILD DEVELOPMENT, Issue 4 2004Article first published online: 6 DEC 200 First page of article [source] ARCHAEOLOGICAL DATA ANALYSIS AND FUZZY CLUSTERINGARCHAEOMETRY, Issue 6 2009M. J. BAXTER Cluster analysis is widely used in archaeological data analysis. Fuzzy clustering is a more modern technique than methods normally used by archaeologists and has not been much exploited. Applications that have been reported are sometimes unsatisfactory and usually do not exploit the ,fuzziness' of the procedure. After a brief review of the more common methods of cluster analysis, fuzzy ideas and fuzzy clustering are discussed. The method is applied to three data sets of different sizes and complexity, to illustrate particular aspects of, and problems in, application. Summarizing results is less easy than for more standard methods, but has the potential to reveal features of the data concealed by other methods. [source] Nonignorable Missingness in Matched Case,Control Data AnalysesBIOMETRICS, Issue 2 2004Myunghee Cho Paik Summary. Matched case,control data analysis is often challenged by a missing covariate problem, the mishandling of which could cause bias or inefficiency. Satten and Carroll (2000, Biometrics56, 384,388) and other authors have proposed methods to handle missing covariates when the probability of missingness depends on the observed data, i.e., when data are missing at random. In this article, we propose a conditional likelihood method to handle the case when the probability of missingness depends on the unobserved covariate, i.e., when data are nonignorably missing. When the missing covariate is binary, the proposed method can be implemented using standard software. Using the Northern Manhattan Stroke Study data, we illustrate the method and discuss how sensitivity analysis can be conducted. [source] Modeling Passing Rates on a Computer-Based Medical Licensing Examination: An Application of Survival Data AnalysisEDUCATIONAL MEASUREMENT: ISSUES AND PRACTICE, Issue 3 2004André F. de Champlain The purpose of this article was to model United States Medical Licensing Examination (USMLE) Step 2 passing rates using the Cox Proportional Hazards Model, best known for its application in analyzing clinical trial data. The number of months it took to pass the computer-based Step 2 examination was treated as the dependent variable in the model. Covariates in the model were: (a) medical school location (U.S. and Canadian or other), (b) primary language (English or other), and (c) gender. Preliminary findings indicate that examinees were nearly 2.7 times more likely to experience the event (pass Step 2) if they were U.S. or Canadian trained. Examinees with English as their primary language were 2.1 times more likely to pass Step 2, but gender had little impact. These findings are discussed more fully in light of past research and broader potential applications of survival analysis in educational measurement. [source] Statistical Analysis of Microarray DataADDICTION BIOLOGY, Issue 1 2005Mark Reimers Microarrays promise dynamic snapshots of cell activity, but microarray results are unfortunately not straightforward to interpret. This article aims to distill the most useful practical results from the vast body of literature availalable on microarray data analysis. Topics covered include: experimental design issues, normalization, quality control, exploratory analysis, and tests for differential expression. Special attention is paid to the peculiarities of low-level analysis of Affymetrix chips, and the multiple testing problem in determining differential expression. The aim of this article is to provide useful answers to the most common practical issues in microarray data analysis. The main topics are pre-processing (normalization), and detecting differential expression. Subsidiary topics include experimental design, and exploratory analysis. Further discussion is found at the author's web page (http://discover.nci.nih.gov, Notes on Microarray Data Analysis). [source] GeoDa: An Introduction to Spatial Data AnalysisGEOGRAPHICAL ANALYSIS, Issue 1 2006Luc Anselin This article presents an overview of GeoDaÔ, a free software program intended to serve as a user-friendly and graphical introduction to spatial analysis for non-geographic information systems (GIS) specialists. It includes functionality ranging from simple mapping to exploratory data analysis, the visualization of global and local spatial autocorrelation, and spatial regression. A key feature of GeoDa is an interactive environment that combines maps with statistical graphics, using the technology of dynamically linked windows. A brief review of the software design is given, as well as some illustrative examples that highlight distinctive features of the program in applications dealing with public health, economic development, real estate analysis, and criminology. [source] Qualitative Data Analysis for Health Services Research: Developing Taxonomy, Themes, and TheoryHEALTH SERVICES RESEARCH, Issue 4 2007Elizabeth H. Bradley Objective. To provide practical strategies for conducting and evaluating analyses of qualitative data applicable for health services researchers. Data Sources and Design. We draw on extant qualitative methodological literature to describe practical approaches to qualitative data analysis. Approaches to data analysis vary by discipline and analytic tradition; however, we focus on qualitative data analysis that has as a goal the generation of taxonomy, themes, and theory germane to health services research. Principle Findings. We describe an approach to qualitative data analysis that applies the principles of inductive reasoning while also employing predetermined code types to guide data analysis and interpretation. These code types (conceptual, relationship, perspective, participant characteristics, and setting codes) define a structure that is appropriate for generation of taxonomy, themes, and theory. Conceptual codes and subcodes facilitate the development of taxonomies. Relationship and perspective codes facilitate the development of themes and theory. Intersectional analyses with data coded for participant characteristics and setting codes can facilitate comparative analyses. Conclusions. Qualitative inquiry can improve the description and explanation of complex, real-world phenomena pertinent to health services research. Greater understanding of the processes of qualitative data analysis can be helpful for health services researchers as they use these methods themselves or collaborate with qualitative researchers from a wide range of disciplines. [source] Cost Convergence between Public and For-Profit Hospitals under Prospective Payment and High Competition in TaiwanHEALTH SERVICES RESEARCH, Issue 6p2 2004Sudha Xirasagar Objective. To test the hypotheses that: (1) average adjusted costs per discharge are higher in high-competition relative to low-competition markets, and (2) increased competition is associated with cost convergence between public and for-profit (FP) hospitals for case payment diagnoses, but not for cost-plus reimbursed diagnoses. Data Sources. Taiwan's National Health Insurance database; 325,851 inpatient claims for cesarean section, vaginal delivery, prostatectomy, and thyroidectomy (all case payment), and bronchial asthma and cholelithiasis (both cost-based payment). Study Design. Retrospective population-based, cross-sectional study. Data Analysis. Diagnosis-wise regression analyses were done to explore associations between cost per discharge and hospital ownership under high and low competition, adjusted for clinical severity and institutional characteristics. Principal Findings. Adjusted costs per discharge are higher for all diagnoses in high-competition markets. For case payment diagnoses, the magnitudes of adjusted cost differences between public and FP hospitals are lower under high competition relative to low competition. This is not so for the cost-based diagnoses. Conclusions. We find that the empirical evidence supports both our hypotheses. [source] Applied Multiway Data Analysis by Pieter M. KroonenbergINTERNATIONAL STATISTICAL REVIEW, Issue 3 2008Kimmo Vehkalahti No abstract is available for this article. [source] Mass Spectrometry Data Analysis in Proteomics.JOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 4 2007Humana Press, New Jersey. (ISBN 978-1-58829-563-7)., Totowa [source] The Menopause Experience: A Woman's PerspectiveJOURNAL OF OBSTETRIC, GYNECOLOGIC & NEONATAL NURSING, Issue 1 2002Sharon A. George PhD Objective: To understand the complexities of the experience of menopause in American women from diverse ethnic and socioeconomic backgrounds. The specific aims of this phenomenologic study were to (a) examine and interpret the reality of the menopausal transition as experienced by American women and (b) identify common elements and themes that occur as a result of the complexities of this experience. Design: Data for this qualitative study were gathered through semistructured interviews with 15 women who experienced natural menopause. Participants: A multiethnic sample of 15 menopausal American women in Massachusetts was selected from a pool of voluntary participants from the Boston area. Data Analysis: The interviews were analyzed to identify themes pertinent to the personal experience of menopause. Those themes, extracted from the similarities and differences described, represent broad aspects of these women's experiences. Results: Three major themes or phases were identified: expectations and realization, sorting things out, and a new life phase. Although some women expressed similar thoughts in particular categories, no two women had the same experience of menopause. Conclusions: The data support the premise that the experience of menopause in American women is unique to each individual and that the meaning or perspective differs among women. The data revealed the complexities of this human experience by explicating personal meanings related to experiences, expectations, attitudes, and beliefs about menopause. [source] Qualitative Data Analysis with NVivoJOURNAL OF PSYCHIATRIC & MENTAL HEALTH NURSING, Issue 10 2008RICHARD LAKEMAN dipnsg bn ba hons pgdip (psychotherapy) [source] Data Analysis and Graphics using R: an Example-based ApproachJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2009Deven D. Patel No abstract is available for this article. [source] Compositional Data Analysis in the Geosciences: from Theory to PracticeJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008R. M. Lark No abstract is available for this article. [source] Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSSJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008Venkata Putcha No abstract is available for this article. [source] Data Analysis of Asymmetric StructuresJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 3 2007Gérard D'Aubigny No abstract is available for this article. [source] Fertile Soil for Structural Funds?A Panel Data Analysis of the Conditional Effectiveness of European Cohesion PolicyKYKLOS INTERNATIONAL REVIEW OF SOCIAL SCIENCES, Issue 1 2006Sjef Ederveen SUMMARY Structural Funds are the most intensively used policy instrument by the European Union to promote economic growth in its member states and to speed up the process of convergence. This paper empirically explores the effectiveness of European Structural Funds by means of a panel data analysis for 13 countries in the European Union. We show that , on average , Structural Funds are ineffective. For countries with a ,proper' institutional framework, however, Structural Funds are effective. The latter result is obtained for a wide range of conditioning variables, such as openness, institutional quality, corruption and indicators for good governance. It is robust to a wide range of robustness tests. [source] Shape and Size Determination by Laser Diffraction: Average Aspect Ratio and Size Distributions by Volume; Feasibility of Data Analysis by Neural NetworksPARTICLE & PARTICLE SYSTEMS CHARACTERIZATION, Issue 1 2005Luc Deriemaeker Abstract A new strategy for the recovery of the average shape factor and the volume weighted size distribution from laser diffraction data using neural networks is presented. The method yields reliable estimates for both the shape factor and the volume weighted size distribution. [source] An Introduction to Categorical Data Analysis (second edition) Alan Agresti (2007) ISBN: 9780471226185; 372 pages; Ł50.30, $94.9, ,66.40 Wiley; http://www.wiley.com/PHARMACEUTICAL STATISTICS: THE JOURNAL OF APPLIED STATISTICS IN THE PHARMACEUTICAL INDUSTRY, Issue 4 2008Alan Ebbutt No abstract is available for this article. [source] Prevalence of cigarette smoking by occupation and industry in the United States,AMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 3 2001Ki Moon Bang PhD Abstract Background This study was undertaken to estimate the most recent prevalence of cigarette smoking by occupation and industry in the US, using the data from the third National Health and Nutrition Examination Survey (NHANES III), 1988,1994. Methods Included in NHANES III are data on the cigarette smoking status, occupation, industry, and other demographic information of US non-institutionalized civilians obtained through household interview surveys. The study population included 20,032 adults aged 17 years and older. To estimate the prevalence of cigarette smoking across occupation and industry groups, we used the Survey Data Analysis (SUDAAN) software. Results The prevalence of cigarette smoking was highest among material moving occupations, construction laborers, and vehicle mechanics and repairers. The lowest smoking prevalence was found among teachers. Among industry groups, the construction industry had the highest prevalence of cigarette smoking. Conclusions These findings provide information useful for targeting education activities focusing on adverse health effects of cigarette smoking and also for indirect adjustments in analysis of morbidity and mortality by occupation. Am. J. Ind. Med. 40:233,239, 2001. Published 2001 Wiley-Liss, Inc. [source] Data Analysis and Citizenship Focus: Analytic Master Keys to Better Governance?PUBLIC ADMINISTRATION REVIEW, Issue 3 2008Christopher Hood No abstract is available for this article. [source] Conditional Lifetime Data Analysis Using the Limited Expected Value FunctionQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2004John Quigley Abstract Much failure, and other event, data are commonly highly censored. Consequently this limits the efficacy of many statistical analysis techniques. The limited expected value (LEV) function presents an alternative way of characterizing lifetime distributions. In essence the LEV provides a means of calculating a truncated mean time to failure (MTTF) (or mean time before failure (MTBF) if appropriate) that is adjusted at each of the censoring times and so appears potentially suitable for dealing with censored data structures. In theory, the LEV has been defined for many standard distributions, however its practical use is not well developed. This paper aims to extend the theory of LEV for typical censoring structures to develop procedures that will assist in model identification as well as parameter estimation. Applications to typical event data will be presented and the use of LEV in comparison with a selection of existing lifetime distributional analysis will be made based on some preliminary research. Copyright © 2004 John Wiley & Sons, Ltd. [source] Finding Some Needles in the Haystack: Textbook Publishing on the Subjects of GIS and Spatial Data AnalysisTHE CANADIAN GEOGRAPHER/LE GEOGRAPHE CANADIEN, Issue 1 2010RON N. BULIUNG First page of article [source] Experimental Design and Data Analysis for BiologistsAUSTRAL ECOLOGY, Issue 5 2003Julian R.W. Reid No abstract is available for this article. [source] FDR Control by the BH Procedure for Two-Sided Correlated Tests with Implications to Gene Expression Data AnalysisBIOMETRICAL JOURNAL, Issue 1 2007Anat Reiner-Benaim Abstract The multiple testing problem attributed to gene expression analysis is challenging not only by its size, but also by possible dependence between the expression levels of different genes resulting from co-regulations of the genes. Furthermore, the measurement errors of these expression levels may be dependent as well since they are subjected to several technical factors. Multiple testing of such data faces the challenge of correlated test statistics. In such a case, the control of the False Discovery Rate (FDR) is not straightforward, and thus demands new approaches and solutions that will address multiplicity while accounting for this dependency. This paper investigates the effects of dependency between bormal test statistics on FDR control in two-sided testing, using the linear step-up procedure (BH) of Benjamini and Hochberg (1995). The case of two multiple hypotheses is examined first. A simulation study offers primary insight into the behavior of the FDR subjected to different levels of correlation and distance between null and alternative means. A theoretical analysis follows in order to obtain explicit upper bounds to the FDR. These results are then extended to more than two multiple tests, thereby offering a better perspective on the effect of the proportion of false null hypotheses, as well as the structure of the test statistics correlation matrix. An example from gene expression data analysis is presented. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Book Review: Statistik , Der Weg zur Datenanalyse (Statistics , The Way to Data Analysis).BIOMETRICAL JOURNAL, Issue 5 2004By L. Fahrmeir, G. Tutz, I. Pigeot, R. Künstler No abstract is available for this article. [source] | |||||||||||||||||||||||||||||||||||||