Mentorship Programs in Radiation Oncology Residency Training Programs: A Critical Unmet Need

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dhami, Gurleen; Gao, Wendy; Gensheimer, Michael F.

Purpose: To conduct a nationwide survey to evaluate the current status of resident mentorship in radiation oncology. Methods and Materials: An anonymous electronic questionnaire was sent to all residents and recent graduates at US Accreditation Council for Graduate Medical Education–accredited radiation oncology residency programs, identified in the member directory of the Association of Residents in Radiation Oncology. Factors predictive of having a mentor and satisfaction with the mentorship experience were identified using univariate and multivariate analyses. Results: The survey response rate was 25%, with 85% of respondents reporting that mentorship plays a critical role in residency training, whereas only 53%more » had a current mentor. Larger programs (≥10 faculty, P=.004; and ≥10 residents, P<.001) were more likely to offer a formal mentorship program, which makes it more likely for residents to have an active mentor (88% vs 44%). Residents in a formal mentoring program reported being more satisfied with the overall mentorship experience (univariate odds ratio 8.77, P<.001; multivariate odds ratio 5, P<.001). On multivariate analysis, women were less likely to be satisfied with the mentorship experience. Conclusions: This is the first survey focusing on the status of residency mentorship in radiation oncology. Our survey highlights the unmet need for mentorship in residency programs.« less

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

PubMed

Zakrzewski, Martha; Proietti, Carla; Ellis, Jonathan J; Hasan, Shihab; Brion, Marie-Jo; Berger, Bernard; Krause, Lutz

2017-03-01

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. l.krause@uq.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Optimal Multicomponent Analysis Using the Generalized Standard Addition Method.

ERIC Educational Resources Information Center

Raymond, Margaret; And Others

1983-01-01

Describes an experiment on the simultaneous determination of chromium and magnesium by spectophotometry modified to include the Generalized Standard Addition Method computer program, a multivariate calibration method that provides optimal multicomponent analysis in the presence of interference and matrix effects. Provides instructions for…

Authentication of Trappist beers by LC-MS fingerprints and multivariate data analysis.

PubMed

Mattarucchi, Elia; Stocchero, Matteo; Moreno-Rojas, José Manuel; Giordano, Giuseppe; Reniero, Fabiano; Guillou, Claude

2010-12-08

The aim of this study was to asses the applicability of LC-MS profiling to authenticate a selected Trappist beer as part of a program on traceability funded by the European Commission. A total of 232 beers were fingerprinted and classified through multivariate data analysis. The selected beer was clearly distinguished from beers of different brands, while only 3 samples (3.5% of the test set) were wrongly classified when compared with other types of beer of the same Trappist brewery. The fingerprints were further analyzed to extract the most discriminating variables, which proved to be sufficient for classification, even using a simplified unsupervised model. This reduced fingerprint allowed us to study the influence of batch-to-batch variability on the classification model. Our results can easily be applied to different matrices and they confirmed the effectiveness of LC-MS profiling in combination with multivariate data analysis for the characterization of food products.

Using video and theater to increase knowledge and change attitudes-Why are gorillas important to the world and to Congo?

PubMed

Breuer, Thomas; Mavinga, Franck Barrel; Evans, Ron; Lukas, Kristen E

2017-10-01

Applying environmental education in primate range countries is an important long-term activity to stimulate pro-conservation behavior. Within captive settings, mega-charismatic species, such as great apes are often used to increase knowledge and positively influence attitudes of visitors. Here, we evaluate the effectiveness of a short-term video and theater program developed for a Western audience and adapted to rural people living in two villages around Nouabalé-Ndoki National Park, Republic of Congo. We assessed the knowledge gain and attitude change using oral evaluation in the local language (N = 111). Overall pre-program knowledge about Western gorillas (Gorilla gorilla) was high. Detailed multivariate analysis of pre-program knowledge revealed differences in knowledge between two villages and people with different jobs while attitudes largely were similar between groups. The short-term education program was successful in raising knowledge, particularly of those people with less pre-program knowledge. We also noted an overall significant attitude improvement. Our data indicate short-term education programs are useful in quickly raising knowledge as well improving attitudes. Furthermore, education messages need to be clearly adapted to the daily livelihood realities of the audience, and multi-variate analysis can help to identify potential target groups for education programs. © 2017 Wiley Periodicals, Inc.

Anticipating Climate Change Impacts on Army Installations

DTIC Science & Technology

2011-10-01

13 3.2 Recent technologically derived ecological characterizations ....................................... 14 3.2.1 USGS Gap Analysis Program... GAP ) ......................................................................................... 14 3.2.2 Hargrove/Hoffman potential multivariate... GAP national land cover map .................................................................................................. 14 5 A Hargrove

Statistical techniques applied to aerial radiometric surveys (STAARS): principal components analysis user's manual. [NURE program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.

1981-01-01

A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From thismore » analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained.« less

Spectroscopic analysis and control

DOEpatents

Tate; , James D.; Reed, Christopher J.; Domke, Christopher H.; Le, Linh; Seasholtz, Mary Beth; Weber, Andy; Lipp, Charles

2017-04-18

Apparatus for spectroscopic analysis which includes a tunable diode laser spectrometer having a digital output signal and a digital computer for receiving the digital output signal from the spectrometer, the digital computer programmed to process the digital output signal using a multivariate regression algorithm. In addition, a spectroscopic method of analysis using such apparatus. Finally, a method for controlling an ethylene cracker hydrogenator.

Multivariate approach in popcorn genotypes using the Ward-MLM strategy: morpho-agronomic analysis and incidence of Fusarium spp.

PubMed

Kurosawa, R N F; do Amaral Junior, A T; Silva, F H L; Dos Santos, A; Vivas, M; Kamphorst, S H; Pena, G F

2017-02-08

The multivariate analyses are useful tools to estimate the genetic variability between accessions. In the breeding programs, the Ward-Modified Location Model (MLM) multivariate method has been a powerful strategy to quantify variability using quantitative and qualitative variables simultaneously. The present study was proposed in view of the dearth of information about popcorn breeding programs under a multivariate approach using the Ward-MLM methodology. The objective of this study was thus to estimate the genetic diversity among 37 genotypes of popcorn aiming to identify divergent groups associated with morpho-agronomic traits and traits related to resistance to Fusarium spp. To this end, 7 qualitative and 17 quantitative variables were analyzed. The experiment was conducted in 2014, at Universidade Estadual do Norte Fluminense, located in Campos dos Goytacazes, RJ, Brazil. The Ward-MLM strategy allowed the identification of four groups as follows: Group I with 10 genotypes, Group II with 11 genotypes, Group III with 9 genotypes, and Group IV with 7 genotypes. Group IV was distant in relation to the other groups, while groups I, II, and III were near. The crosses between genotypes from the other groups with those of group IV allow an exploitation of heterosis. The Ward-MLM strategy provided an appropriate grouping of genotypes; ear weight, ear diameter, and grain yield were the traits that most contributed to the analysis of genetic diversity.

Incentives, Program Configuration, and Employee Uptake of Workplace Wellness Programs.

PubMed

Huang, Haijing; Mattke, Soeren; Batorsky, Benajmin; Miles, Jeremy; Liu, Hangsheng; Taylor, Erin

2016-01-01

The aim of this study was to determine the effect of wellness program configurations and financial incentives on employee participation rate. We analyze a nationally representative survey on workplace wellness programs from 407 employers using cluster analysis and multivariable regression analysis. Employers who offer incentives and provide a comprehensive set of program offerings have higher participation rates. The effect of incentives differs by program configuration, with the strongest effect found for comprehensive and prevention-focused programs. Among intervention-focused programs, incentives are not associated with higher participation. Wellness programs can be grouped into distinct configurations, which have different workplace health focuses. Although monetary incentives can be effective in improving employee participation, the magnitude and significance of the effect is greater for some program configurations than others.

An Examination on the Effect of Prior Knowledge, Personal Goals, and Incentive in an Online Employee Training Program

ERIC Educational Resources Information Center

Zha, Shenghua; Adams, Andrea Harpine; Calcagno-Roach, Jamie Marie; Stringham, David A.

2017-01-01

This study explored factors that predicted learners' transformative learning in an online employee training program in a higher education institution in the U.S. A multivariate multiple regression analysis was conducted with a sample of 74 adult learners on their learning of a new learning management system. Four types of participants' behaviors…

Risk factors for superficial surgical site infection after elective rectal cancer resection: a multivariate analysis of 8880 patients from the American College of Surgeons National Surgical Quality Improvement Program database.

PubMed

Sutton, Elie; Miyagaki, Hiromichi; Bellini, Geoffrey; Shantha Kumara, H M C; Yan, Xiaohong; Howe, Brett; Feigel, Amanda; Whelan, Richard L

2017-01-01

Superficial surgical site infection (sSSI) is one of the most common complications after colorectal resection. The goal of this study was to determine the comorbidities and operative characteristics that place patients at risk for sSSI in patients who underwent rectal cancer resection. The American College of Surgeons National Surgical Quality Improvement Program database was queried (via diagnosis and Current Procedural Terminology codes) for patients with rectal cancer who underwent elective resection between 2005 and 2012. Patients for whom data concerning 27 demographic factors, comorbidities, and operative characteristics were available were eligible. A univariate and multivariate analysis was performed to identify possible risk factors for sSSI. A total of 8880 patients met the entry criteria and were included. sSSIs were diagnosed in 861 (9.7%) patients. Univariate analysis found 14 patients statistically significant risk factors for sSSI. Multivariate analysis revealed the following risk factors: male gender, body mass index (BMI) >30, current smoking, history of chronic obstructive pulmonary disease (COPD), American Society of Anesthesiologists III/IV, abdominoperineal resection (APR), stoma formation, open surgery (versus laparoscopic), and operative time >217 min. The greatest difference in sSSI rates was noted in patients with COPD (18.9 versus 9.5%). Of note, 54.2% of sSSIs was noted after hospital discharge. With regard to the timing of presentation, univariate analysis revealed a statistically significant delay in sSSI presentation in patients with the following factors and/or characteristics: BMI <30, previous radiation therapy (RT), APR, minimally invasive surgery, and stoma formation. Multivariate analysis suggested that only laparoscopic surgery (versus open) and preoperative RT were risk factors for delay. Rectal cancer resections are associated with a high incidence of sSSIs, over half of which are noted after discharge. Nine patient and operative characteristics, including smoking, BMI, COPD, APR, and open surgery were found to be significant risk factors for SSI on multivariate analysis. Furthermore, sSSI presentation in patients who had laparoscopic surgery and those who had preoperative RT is significantly delayed for unclear reasons. Copyright © 2016 Elsevier Inc. All rights reserved.

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

[Quality assurance program for pain management after obstetrical perineal injury].

PubMed

Urion, L; Bayoumeu, F; Jandard, C; Fontaine, B; Bouaziz, H

2004-11-01

A quality insurance program has been set up in order to improve the relief of pain in patients with perineal injury after childbirth. The program has been developed according to the French standards of accreditation. After elaboration of a referential, a first study (103 patients) allowed to evaluate the ongoing practices and to appreciate the pain intensities. After analysis of the results, an action strategy has been elaborated, with a brand new therapeutic standard and a pain-monitoring program for nurses. Six months later, a second study (105 patients) measured the efficiency of the accomplished actions. The statistic analysis used chi2 and Kruskal-Wallis tests and a multivariate analyse (p <0.05). Several indicators led to conclude to the success of this program: analgesics prescribed systematically and earlier, best observance, larger utilisation of the NSAI, decrease of the analgesics requests, improvement of the satisfaction referred to the relief of pain. The multivariate analyse showed a risk twice as little as in the second study to have a 36th hour VAS score superior to four (p =0.03). The apply of this quality insurance program allowed to improve the analgesia after obstetric perineal injuries. A few adaptations are needed, and also more formations of the medical and paramedical staff. The durability of the accomplished actions shall be evaluated in the future.

Outcomes and Pharmacoeconomic Analysis of a Home Intravenous Antibiotic Infusion Program in Veterans.

PubMed

Ruh, Christine A; Parameswaran, Ganapathi I; Wojciechowski, Amy L; Mergenhagen, Kari A

2015-11-01

The use of outpatient parenteral antibiotic therapy (OPAT) programs has become more frequent because of benefits in costs with equivalent clinical outcomes compared with inpatient care. The purpose of this study was to evaluate the outcomes of our program. A modified pharmacoeconomic analysis was performed to compare costs of our program with hospital or rehabilitation facility care. This was a retrospective chart review of 96 courses of OPAT between April 1, 2011, and July 31, 2013. Clinical failures were defined as readmission or death due to worsening infection or readmission secondary to adverse drug event (ADE) to antibiotic therapy. This does not include those patients readmitted for reasons not associated with OPAT therapy, including comorbidities or elective procedures. Baseline characteristics and program-specific data were analyzed. Statistically significant variables were built into a multivariate logistic regression model to determine predictors of failure. A pharmacoeconomic analysis was performed with the use of billing records. Of the total episodes evaluated, 17 (17.71%) clinically failed therapy, and 79 (82.29%) were considered a success. In the multivariate analysis, number of laboratory draws (P = 0.02) and occurrence of drug reaction were significant in the final model, P = 0.02 and P = 0.001, respectively. The presence an adverse drug reaction increases the odds of failure (OR = 10.10; 95% CI, 2.69-44.90). Compared with inpatient or rehabilitation care, the cost savings was $6,932,552.03 or $2,649,870.68, respectively. In our study, patients tolerated OPAT well, with a low number of failures due to ADE. The clinical outcomes and cost savings of our program indicate that OPAT can be a viable alternative to long-term inpatient antimicrobial therapy. Published by Elsevier Inc.

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented.

Assessing the Effectiveness of a School-Based Dental Clinic on the Oral Health of Children Who Lack Access to Dental Care: A Program Evaluation

ERIC Educational Resources Information Center

Carpino, Rachel; Walker, Mary P.; Liu, Ying; Simmer-Beck, Melanie

2017-01-01

This program evaluation examines the effectiveness of a school-based dental clinic. A repeated-measures design was used to longitudinally examine secondary data from participants (N = 293). Encounter intensity was developed to normalize data. Multivariate analysis of variance and Kruskal-Wallis test were used to investigate the effect of encounter…

Applicant Characteristics Associated With Selection for Ranking at Independent Surgery Residency Programs.

PubMed

Dort, Jonathan M; Trickey, Amber W; Kallies, Kara J; Joshi, Amit R T; Sidwell, Richard A; Jarman, Benjamin T

2015-01-01

This study evaluated characteristics of applicants selected for interview and ranked by independent general surgery residency programs and assessed independent program application volumes, interview selection, rank list formation, and match success. Demographic and academic information was analyzed for 2014-2015 applicants. Applicant characteristics were compared by ranking status using univariate and multivariable statistical techniques. Characteristics independently associated with whether or not an applicant was ranked were identified using multivariable logistic regression modeling with backward stepwise variable selection and cluster-correlated robust variance estimates to account for correlations among individuals who applied to multiple programs. The Electronic Residency Application Service was used to obtain applicant data and program match outcomes at 33 independent surgery programs. All applicants selected to interview at 33 participating independent general surgery residency programs were included in the study. Applicants were 60% male with median age of 26 years. Birthplace was well distributed. Most applicants (73%) had ≥1 academic publication. Median United States Medical Licensing Exams (USMLE) Step 1 score was 228 (interquartile range: 218-240), and median USMLE Step 2 clinical knowledge score was 241 (interquartile range: 231-250). Residency programs in some regions more often ranked applicants who attended medical school within the same region. On multivariable analysis, significant predictors of ranking by an independent residency program were: USMLE scores, medical school region, and birth region. Independent programs received an average of 764 applications (range: 307-1704). On average, 12% interviews, and 81% of interviewed applicants were ranked. Most programs (84%) matched at least 1 applicant ranked in their top 10. Participating independent programs attract a large volume of applicants and have high standards in the selection process. This information can be used by surgery residency applicants to gauge their candidacy at independent programs. Independent programs offer a select number of interviews, rank most applicants that they interview, and successfully match competitive applicants. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Viewpoints: A New Computer Program for Interactive Exploration of Large Multivariate Space Science and Astrophysics Data.

NASA Astrophysics Data System (ADS)

Levit, Creon; Gazis, P.

2006-06-01

The graphics processing units (GPUs) built in to all professional desktop and laptop computers currently on the market are capable of transforming, filtering, and rendering hundreds of millions of points per second. We present a prototype open-source cross-platform (windows, linux, Apple OSX) application which leverages some of the power latent in the GPU to enable smooth interactive exploration and analysis of large high-dimensional data using a variety of classical and recent techniques. The targeted application area is the interactive analysis of complex, multivariate space science and astrophysics data sets, with dimensionalities that may surpass 100 and sample sizes that may exceed 10^6-10^8.

A Re-examination of the Black English Copula. Working Papers in Sociolinguistics, No. 66.

ERIC Educational Resources Information Center

Baugh, John

A corpus of Black English (BEV) data is re-examined with exclusive attention to the "is" form of the copula. This analysis differs from previous examinations in that more constraints have been introduced, and the Cedergren/Sankoff computer program for multivariant analysis has been employed. The analytic techniques that are used allow for a finer…

Macro-Econophysics

NASA Astrophysics Data System (ADS)

Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi

2017-07-01

Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.

Multivariate areal analysis of the impact and efficiency of the family planning programme in peninsular Malaysia.

PubMed

Tan Boon Ann

1987-06-01

The findings of the final phase of a 3-phase multivariate areal analysis study undertaken by the Economic and Social Commission for Asia and the Pacific (ESCAP) in 5 countries of the Asian and Pacific Region, including Malaysia, to examine the impact of family planning programs on fertility and reproduction are reported. The study used Malaysia's administrative district as the unit of analysis because the administration and implementation of socioeconomic development activities, as well as the family planning program, depend to a large extent on the decisions of local organizations at the district or state level. In phase 1, existing program and nonprogram data were analyzed using the multivariate technique to separate the impact of the family planning program net of other developmental efforts. The methodology in the 2nd phase consisted of in-depth investigation of selected areas in order to discern the dynamics and determinants of efficiency. The insights gained in phase 2 regarding dynamics of performance were used in phase 3 to refine the input variables of the phase 1 model. Thereafter, the phase 1 analysis was repeated. Insignificant variables and factors were trimmed in order to present a simplified model for studying the impact of environmental, socioeconomic development, family planning programs, and related factors on fertility. The inclusion of a set of family planning program and development variables in phase 3 increased the predictive power of the impact model. THe explained variance for total fertility rate (TFR) of women under 30 years increased from 71% in phase 1 to 79%. It also raised the explained variance of the efficiency model from 34% to 70%. For women age 30 years and older, their TFR was affected directly by the ethnic composition variable (.76), secondary educational status (-.45), and modern nonagricultural occupation (.42), among others. When controlled for other socioeconomic development and environmental indicators, the nonagricultural activities had a positive direct effect on TFR. No direct effects were found to come from other socioeconomic development indicators, once these factors were controlled. The 3 factors that had direct effects on the fertility of women below age 30 were ethnic composition (.33), contraceptive pevalence (-.32), and secondary educational status (-.25). Other family planning program variables (contraceptive knowledge) and socioeconomic development indicators (exposure to modernization as measured by television ownership and health/living conditions as measured by infant mortality rate) affected fertility significantly but indirectly.

Shuttle Data Center File-Processing Tool in Java

NASA Technical Reports Server (NTRS)

Barry, Matthew R.; Miller, Walter H.

2006-01-01

A Java-language computer program has been written to facilitate mining of data in files in the Shuttle Data Center (SDC) archives. This program can be executed on a variety of workstations or via Web-browser programs. This program is partly similar to prior C-language programs used for the same purpose, while differing from those programs in that it exploits the platform-neutrality of Java in implementing several features that are important for analysis of large sets of time-series data. The program supports regular expression queries of SDC archive files, reads the files, interleaves the time-stamped samples according to a chosen output, then transforms the results into that format. A user can choose among a variety of output file formats that are useful for diverse purposes, including plotting, Markov modeling, multivariate density estimation, and wavelet multiresolution analysis, as well as for playback of data in support of simulation and testing.

Comparative Research of Navy Voluntary Education at Operational Commands

DTIC Science & Technology

2017-03-01

return on investment, ROI, logistic regression, multivariate analysis, descriptive statistics, Markov, time-series, linear programming 15. NUMBER...21  B.  DESCRIPTIVE STATISTICS TABLES ...............................................25  C.  PRIVACY CONSIDERATIONS...THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF TABLES Table 1.  Variables and Descriptions . Adapted from NETC (2016). .......................21

Artificial Neural Networks in Policy Research: A Current Assessment.

ERIC Educational Resources Information Center

Woelfel, Joseph

1993-01-01

Suggests that artificial neural networks (ANNs) exhibit properties that promise usefulness for policy researchers. Notes that ANNs have found extensive use in areas once reserved for multivariate statistical programs such as regression and multiple classification analysis and are developing an extensive community of advocates for processing text…

Designing a risk-based surveillance program for Mycobacterium avium ssp. paratuberculosis in Norwegian dairy herds using multivariate statistical process control analysis.

PubMed

Whist, A C; Liland, K H; Jonsson, M E; Sæbø, S; Sviland, S; Østerås, O; Norström, M; Hopp, P

2014-11-01

Surveillance programs for animal diseases are critical to early disease detection and risk estimation and to documenting a population's disease status at a given time. The aim of this study was to describe a risk-based surveillance program for detecting Mycobacterium avium ssp. paratuberculosis (MAP) infection in Norwegian dairy cattle. The included risk factors for detecting MAP were purchase of cattle, combined cattle and goat farming, and location of the cattle farm in counties containing goats with MAP. The risk indicators included production data [culling of animals >3 yr of age, carcass conformation of animals >3 yr of age, milk production decrease in older lactating cows (lactations 3, 4, and 5)], and clinical data (diarrhea, enteritis, or both, in animals >3 yr of age). Except for combined cattle and goat farming and cattle farm location, all data were collected at the cow level and summarized at the herd level. Predefined risk factors and risk indicators were extracted from different national databases and combined in a multivariate statistical process control to obtain a risk assessment for each herd. The ordinary Hotelling's T(2) statistic was applied as a multivariate, standardized measure of difference between the current observed state and the average state of the risk factors for a given herd. To make the analysis more robust and adapt it to the slowly developing nature of MAP, monthly risk calculations were based on data accumulated during a 24-mo period. Monitoring of these variables was performed to identify outliers that may indicate deviance in one or more of the underlying processes. The highest-ranked herds were scattered all over Norway and clustered in high-density dairy cattle farm areas. The resulting rankings of herds are being used in the national surveillance program for MAP in 2014 to increase the sensitivity of the ongoing surveillance program in which 5 fecal samples for bacteriological examination are collected from 25 dairy herds. The use of multivariate statistical process control for selection of herds will be beneficial when a diagnostic test suitable for mass screening is available and validated on the Norwegian cattle population, thus making it possible to increase the number of sampled herds. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

PubMed

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Hanson, Stephen José; Haxby, James V.; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

Households with young children and use of freely distributed bednets in rural Madagascar.

PubMed

Krezanoski, Paul J; Comfort, Alison B; Tsai, Alexander C; Bangsberg, David R

2014-03-01

Malaria infections are the leading cause of death for children in Madagascar. Insecticide-treated bednets offer effective prevention, but it is unclear how well free bednet distribution programs reach young children. We conducted a secondary analysis of a free bednet distribution program in Madagascar from 2007-2008. Interviews were performed at baseline and 6 months. Principal components analysis was used to construct a wealth and malaria knowledge index. Coverage efficiency was calculated as coverage of children per bednet owned. Univariable and multivariable regressions were used to determine predictors of bednet use. Bednet use, among the 560 households in the study, increased from 6 to 91% after 6 months. Coverage efficiency increased from 1.29 to 1.56 children covered per bednet owned. In multivariable analysis, having a child under 5 years of age was the only variable associated with bednet use (OR 9.10; p=0.001), yielding a 99% likelihood of using a bednet (95% CI 96.4 to 99.9%) versus 82% (95% CI 72.2 to 88.4%) in households without young children. This free bednet distribution program achieved high levels of adherence after 6 months. Household presence of children was associated with bednet use, but not household income or education, suggesting that distribution to priority groups may help overcome traditional barriers to adoption in some settings.

A general program to compute the multivariable stability margin for systems with parametric uncertainty

NASA Technical Reports Server (NTRS)

Sanchez Pena, Ricardo S.; Sideris, Athanasios

1988-01-01

A computer program implementing an algorithm for computing the multivariable stability margin to check the robust stability of feedback systems with real parametric uncertainty is proposed. The authors present in some detail important aspects of the program. An example is presented using lateral directional control system.

Controlled Multivariate Evaluation of Open Education: Application of a Critical Model.

ERIC Educational Resources Information Center

Sewell, Alan F.; And Others

This paper continues previous reports of a controlled multivariate evaluation of a junior high school open-education program. A new method of estimating program objectives and implementation is presented, together with the nature and degree of obtained student outcomes. Open-program students were found to approve more highly of their learning…

Dissection of genomic correlation matrices using multivariate factor analysis in dairy and dual-purpose cattle breeds

USDA-ARS?s Scientific Manuscript database

SNP effects estimated in genomic selection programs allow for the prediction of direct genomic values (DGV) both at genome-wide and chromosomal level. As a consequence, genome-wide (G_GW) or chromosomal (G_CHR) correlation matrices between genomic predictions for different traits can be calculated. ...

Farmers as Consumers of Agricultural Education Services: Willingness to Pay and Spend Time

ERIC Educational Resources Information Center

Charatsari, Chrysanthi; Papadaki-Klavdianou, Afroditi; Michailidis, Anastasios

2011-01-01

This study assessed farmers' willingness to pay for and spend time attending an Agricultural Educational Program (AEP). Primary data on the demographic and socio-economic variables of farmers were collected from 355 farmers selected randomly from Northern Greece. Descriptive statistics and multivariate analysis methods were used in order to meet…

A multivariate analysis of sex offender recidivism.

PubMed

Scalora, Mario J; Garbin, Calvin

2003-06-01

Sex offender recidivism risk is a multifaceted phenomenon requiring consideration across multiple risk factor domains. The impact of treatment involvement and subsequent recidivism is given limited attention in comparison to other forensic mental health issues. The present analysis is a retrospective study of sex offenders treated at a secure facility utilizing a cognitive-behavioral program matched with an untreated correctional sample. Variables studied included demographic, criminal history, offense related, and treatment progress. Recidivism was assessed through arrest data. Multivariate analysis suggests that recidivism is significantly related to quality of treatment involvement, offender demographics, offense characteristics, and criminal history. Successfully treated offenders were significantly less likely to subsequently reoffend. Recidivists were also significantly younger, less likely married, had engaged in more victim grooming or less violent offending behavior, and had significantly more prior property charges. The authors discuss the clinical and policy implications of the interrelationship between treatment involvement and recidivism.

Use of chemometrics to compare NIR and HPLC for the simultaneous determination of drug levels in fixed-dose combination tablets employed in tuberculosis treatment.

PubMed

Teixeira, Kelly Sivocy Sampaio; da Cruz Fonseca, Said Gonçalves; de Moura, Luís Carlos Brigido; de Moura, Mario Luís Ribeiro; Borges, Márcia Herminia Pinheiro; Barbosa, Euzébio Guimaraes; De Lima E Moura, Túlio Flávio Accioly

2018-02-05

The World Health Organization recommends that TB treatment be administered using combination therapy. The methodologies for quantifying simultaneously associated drugs are highly complex, being costly, extremely time consuming and producing chemical residues harmful to the environment. The need to seek alternative techniques that minimize these drawbacks is widely discussed in the pharmaceutical industry. Therefore, the objective of this study was to develop and validate a multivariate calibration model in association with the near infrared spectroscopy technique (NIR) for the simultaneous determination of rifampicin, isoniazid, pyrazinamide and ethambutol. These models allow the quality control of these medicines to be optimized using simple, fast, low-cost techniques that produce no chemical waste. In the NIR - PLS method, spectra readings were acquired in the 10,000-4000cm -1 range using an infrared spectrophotometer (IRPrestige - 21 - Shimadzu) with a resolution of 4cm -1 , 20 sweeps, under controlled temperature and humidity. For construction of the model, the central composite experimental design was employed on the program Statistica 13 (StatSoft Inc.). All spectra were treated by computational tools for multivariate analysis using partial least squares regression (PLS) on the software program Pirouette 3.11 (Infometrix, Inc.). Variable selections were performed by the QSAR modeling program. The models developed by NIR in association with multivariate analysis provided good prediction of the APIs for the external samples and were therefore validated. For the tablets, however, the slightly different quantitative compositions of excipients compared to the mixtures prepared for building the models led to results that were not statistically similar, despite having prediction errors considered acceptable in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Natural history definition and a suggested clinical approach to Buerger's disease: a case-control study with survival analysis.

PubMed

Fazeli, Bahare; Ravari, Hassan; Assadi, Reza

2012-08-01

The aim of this study was first to describe the natural history of Buerger's disease (BD) and then to discuss a clinical approach to this disease based on multivariate analysis. One hundred eight patients who corresponded with Shionoya's criteria were selected from 2000 to 2007 for this study. Major amputation was considered the ultimate adverse event. Survival analyses were performed by Kaplan-Meier curves. Independent variables including gender, duration of smoking, number of cigarettes smoked per day, minor amputation events and type of treatments, were determined by multivariate Cox regression analysis. The recorded data demonstrated that BD may present in four forms, including relapsing-remitting (75%), secondary progressive (4.6%), primary progressive (14.2%) and benign BD (6.2%). Most of the amputations occurred due to relapses within the six years after diagnosis of BD. In multivariate analysis, duration of smoking of more than 20 years had a significant relationship with further major amputation among patients with BD. Smoking cessation programs with experienced psychotherapists are strongly recommended for those areas in which Buerger's disease is common. Patients who have smoked for more than 20 years should be encouraged to quit smoking, but should also be recommended for more advanced treatment for limb salvage.

Predictors of workplace sexual health policy at sex work establishments in the Philippines.

PubMed

Withers, M; Dornig, K; Morisky, D E

2007-09-01

Based on the literature, we identified manager and establishment characteristics that we hypothesized are related to workplace policies that support HIV protective behavior. We developed a sexual health policy index consisting of 11 items as our outcome variable. We utilized both bivariate and multivariate analysis of variance. The significant variables in our bivariate analyses (establishment type, number of employees, manager age, and membership in manager association) were entered into a multivariate regression model. The model was significant (p<.01), and predicted 42) of the variability in the development and management of a workplace sexual health policy supportive of condom use. The significant predictors were number of employees and establishment type. In addition to individually-focused CSW interventions, HIV prevention programs should target managers and establishment policies. Future HIV prevention programs may need to focus on helping smaller establishments, in particular those with less employees, to build capacity and develop sexual health policy guidelines.

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

Digital Citizenship and Health Promotion Programs: The Power of Knowing.

PubMed

Hicks, Elaine R

2016-11-03

Patterns of Internet access and use among disadvantaged subgroups of Americans reveal that not all disparities are the same, a distinction crucial for appropriate public policies and health promotion program planning. In their book, Digital Citizenship: The Internet, Society, and Participation, authors Karen Mossberger, Caroline Tolbert, and Ramona McNeal deconstructed national opinion surveys and used multivariate methods of data analysis to demonstrate the impact of exclusion from online society economically, socially, and politically among disadvantaged Americans. © 2016 Society for Public Health Education.

The Michigan Surgical Home and Optimization Program is a scalable model to improve care and reduce costs.

PubMed

Englesbe, Michael J; Grenda, Dane R; Sullivan, June A; Derstine, Brian A; Kenney, Brooke N; Sheetz, Kyle H; Palazzolo, William C; Wang, Nicholas C; Goulson, Rebecca L; Lee, Jay S; Wang, Stewart C

2017-06-01

The Michigan Surgical Home and Optimization Program is a structured, home-based, preoperative training program targeting physical, nutritional, and psychological guidance. The purpose of this study was to determine if participation in this program was associated with reduced hospital duration of stay and health care costs. We conducted a retrospective, single center, cohort study evaluating patients who participated in the Michigan Surgical Home and Optimization Program and subsequently underwent major elective general and thoracic operative care between June 2014 and December 2015. Propensity score matching was used to match program participants to a control group who underwent operative care prior to program implementation. Primary outcome measures were hospital duration of stay and payer costs. Multivariate regression was used to determine the covariate-adjusted effect of program participation. A total of 641 patients participated in the program; 82% were actively engaged in the program, recording physical activity at least 3 times per week for the majority of the program; 182 patients were propensity matched to patients who underwent operative care prior to program implementation. Multivariate analysis demonstrated that participation in the Michigan Surgical Home and Optimization Program was associated with a 31% reduction in hospital duration of stay (P < .001) and 28% lower total costs (P < .001) after adjusting for covariates. A home-based, preoperative training program decreased hospital duration of stay, lowered costs of care, and was well accepted by patients. Further efforts will focus on broader implementation and linking participation to postoperative complications and rigorous patient-reported outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

The influence of worksite and employee variables on employee engagement in telephonic health coaching programs: a retrospective multivariate analysis.

PubMed

Grossmeier, Jessica

2013-01-01

This study assessed 11 determinants of health coaching program participation. A cross-sectional study design used secondary data to assess the role of six employee-level and five worksite-level variables on telephone-based coaching enrollment, active participation, and completion. Data was provided by a national provider of worksite health promotion program services for employers. A random sample of 34,291 employees from 52 companies was selected for inclusion in the study. Survey-based measures included age, gender, job type, health risk status, tobacco risk, social support, financial incentives, comprehensive communications, senior leadership support, cultural support, and comprehensive program design. Gender-stratified multivariate logistic regression models were applied using backwards elimination procedures to yield parsimonious prediction models for each of the dependent variables. Employees were more likely to enroll in coaching programs if they were older, female, and in poorer health, and if they were at worksites with fewer environmental supports for health, clear financial incentives for participation in coaching, more comprehensive communications, and more comprehensive programs. Once employees were enrolled, program completion was greater among those who were older, did not use tobacco, worked at a company with strong communications, and had fewer environmental supports for health. Both worksite-level and employee-level factors have significant influences on health coaching engagement, and there are gender differences in the strength of these predictors.

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.

PubMed

Oliveira, M M; Sousa, L B; Reis, M C; Silva Junior, E G; Cardoso, D B O; Hamawaki, O T; Nogueira, A P O

2017-05-31

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D 2 ), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive genotypes.

Understanding and reaching family forest owners: lessons from social marketing research

Treesearch

Brett J. Butler; Mary Tyrrell; Geoff Feinberg; Scott VanManen; Larry Wiseman; Scott Wallinger

2007-01-01

Social marketing--the use of commercial marketing techniques to effect positive social change--is a promising means by which to develop more effective and efficient outreach, policies, and services for family forest owners. A hierarchical, multivariate analysis based on landowners' attitudes reveals four groups of owners to whom programs can be tailored: woodland...

Multivariate Analysis of Student Loan Defaulters at Prairie View A&M University

ERIC Educational Resources Information Center

Barone, Sandra

2006-01-01

This study examines the default behavior of 3,325 undergraduate student borrowers who attended Prairie View A&M University (PVAMU) and entered repayment on their TG-guaranteed Federal Family Education Loan Program (FFELP) loans between October 1, 2000 and September 30, 2002 (fiscal years 2001-2002). Using the Department of Education's official…

Multivariate Analysis of Student Loan Defaulters at Texas A&M University--Kingsville

ERIC Educational Resources Information Center

Barone, Sandra; Steiner, Matt; Teszler, Natali

2005-01-01

This study examines the default behavior of 5,177 undergraduate student borrowers who attended Texas A&M University--Kingsville (TAMUK) and entered repayment of their TG-guaranteed Federal Family Education Loan Program (FFELP) loans between October 1, 1998 and September 30, 2002 (fiscal years 1999-2002). Using the Department of Education's…

DENBRAN: A basic program for a significance test for multivariate normality of clusters from branching patterns in dendrograms

NASA Astrophysics Data System (ADS)

Sneath, P. H. A.

A BASIC program is presented for significance tests to determine whether a dendrogram is derived from clustering of points that belong to a single multivariate normal distribution. The significance tests are based on statistics of the Kolmogorov—Smirnov type, obtained by comparing the observed cumulative graph of branch levels with a graph for the hypothesis of multivariate normality. The program also permits testing whether the dendrogram could be from a cluster of lower dimensionality due to character correlations. The program makes provision for three similarity coefficients, (1) Euclidean distances, (2) squared Euclidean distances, and (3) Simple Matching Coefficients, and for five cluster methods (1) WPGMA, (2) UPGMA, (3) Single Linkage (or Minimum Spanning Trees), (4) Complete Linkage, and (5) Ward's Increase in Sums of Squares. The program is entitled DENBRAN.

Earth resources data analysis program, phase 2

NASA Technical Reports Server (NTRS)

1974-01-01

The efforts and findings of the Earth Resources Data Analysis Program are summarized. Results of a detailed study of the needs of EOD with respect to an applications development system (ADS) for the analysis of remotely sensed data, including an evaluation of four existing systems with respect to these needs are described. Recommendations as to possible courses for EOD to follow to obtain a viable ADS are presented. Algorithmic development comprised of several subtasks is discussed. These subtasks include the following: (1) two algorithms for multivariate density estimation; (2) a data smoothing algorithm; (3) a method for optimally estimating prior probabilities of unclassified data; and (4) further applications of the modified Cholesky decomposition in various calculations. Little effort was expended on task 3, however, two reports were reviewed.

The impact of family planning clinic programs on adolescent pregnancy.

PubMed

Forrest, J D; Hermalin, A I; Henshaw, S K

1981-01-01

During the 1970s, there was a decline in adolescent childbearing in the United States and, among teenagers who were sexually active, there was a decline in pregnancy rates as well. To what extent was increased enrollment by teenagers in federally funded family planning clinics responsible for these declines? Areal multivariate analysis reveals that adolescent birthrates were reduced between 1970 and 1975 as the result of enrollment by teenagers in family planning clinics, independent of the effects of other factors also affecting fertility, such as poverty status, education and urbanization. Using a model which controls for differences in adolescent sexual activity in different areas in 1970 and 1975, the analysis found that for every 10 teenage patients enrolled in family planning clinics in 1975, about one birth was averted in 1976. Other multivariate models, which did not control for differences in sexual activity, showed changes in the same direction, though of smaller dimension. Since the family planning program averts not only births but also pregnancies that result in abortions and miscarriages, an estimate was made of the total number of pregnancies averted by the program. Based on the proportion of unintended pregnancies among adolescents that resulted in live births in 1976 (36 percent), it was estimated that for every 10 teen patients enrolled in 1975, almost three pregnancies were averted in the following year. Over the 1970s, an estimated 2.6 million unintended adolescent pregnancies were averted by the program--944,000 births, 1,376,000 abortions and 326,000 miscarriages. In 1979 alone, an estimated 417,000 unintended pregnancies were prevented by the program.

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

NASA Technical Reports Server (NTRS)

Christenson, D.; Gordon, M.; Kistler, R.; Kriegler, F.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1977-01-01

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation.

Analysis of National Trends in Hospital Acquired Conditions Following Major Urological Surgery Before and After Implementation of the Hospital Acquired Condition Reduction Program,,✰✰✰.

PubMed

Rude, Tope L; Donin, Nicholas M; Cohn, Matthew R; Meeks, William; Gulig, Scott; Patel, Samir N; Wysock, James S; Makarov, Danil V; Bjurlin, Marc A

2018-06-07

To define the rates of common Hospital Acquired Conditions (HACs) in patients undergoing major urological surgery over a period of time encompassing the implementation of the Hospital Acquired Condition Reduction program, and to evaluate whether implementation of the HAC reimbursement penalties in 2008 was associated with a change in the rate of HACs. Using American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data, we determined rates of HACs in patients undergoing major inpatient urological surgery from 2005 to 2012. Rates were stratified by procedure type and approach (open vs. laparoscopic/robotic). Multivariable logistic regression was used to determine the association between year of surgery and HACs. We identified 39,257 patients undergoing major urological surgery, of whom 2300 (5.9%) had at least one hospital acquired condition. Urinary tract infection (UTI, 2.6%) was the most common, followed by surgical site infection (SSI, 2.5%) and venous thrombotic events (VTE, 0.7%). Multivariable logistic regression analysis demonstrated that open surgical approach, diabetes, congestive heart failure, chronic obstructive pulmonary disease, weight loss, and ASA class were among the variables associated with higher likelihood of HAC. We observed a non-significant secular trend of decreasing rates of HAC from 7.4% to 5.8% HACs during the study period, which encompassed the implementation of the Hospital Acquired Condition Reduction Program. HACs occurred at a rate of 5.9% after major urological surgery, and are significantly affected by procedure type and patient health status. The rate of HAC appeared unaffected by national reduction program in this cohort. Better understanding of the factors associated with HACs is critical in developing effective reduction programs. Copyright © 2018. Published by Elsevier Inc.

Development and implementation of a low cost micro computer system for LANDSAT analysis and geographic data base applications

NASA Technical Reports Server (NTRS)

Faust, N.; Jordon, L.

1981-01-01

Since the implementation of the GRID and IMGRID computer programs for multivariate spatial analysis in the early 1970's, geographic data analysis subsequently moved from large computers to minicomputers and now to microcomputers with radical reduction in the costs associated with planning analyses. Programs designed to process LANDSAT data to be used as one element in a geographic data base were used once NIMGRID (new IMGRID), a raster oriented geographic information system, was implemented on the microcomputer. Programs for training field selection, supervised and unsupervised classification, and image enhancement were added. Enhancements to the color graphics capabilities of the microsystem allow display of three channels of LANDSAT data in color infrared format. The basic microcomputer hardware needed to perform NIMGRID and most LANDSAT analyses is listed as well as the software available for LANDSAT processing.

Effect of microwave radiation on Jayadhar cotton fibers: WAXS studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niranjana, A. R., E-mail: arnphysics@gmail.com; Mahesh, S. S., E-mail: arnphysics@gmail.com; Divakara, S., E-mail: arnphysics@gmail.com

Thermal effect in the form of micro wave energy on Jayadhar cotton fiber has been investigated. Microstructural parameters have been estimated using wide angle x-ray scattering (WAXS) data and line profile analysis program developed by us. Physical properties like tensile strength are correlated with X-ray results. We observe that the microwave radiation do affect significantly many parameters and we have suggested a multivariate analysis of these parameters to arrive at a significant result.

Exercising at work: barriers to women's participation.

PubMed

Verhoef, M J; Hamm, R D; Love, E J

1993-06-01

Only a minority of women in an urban random sample have the opportunity to exercise at work, and even fewer women use these opportunities. Lack of time and inconvenient times are the major reasons for not participating in exercise programs at work. Exercise programs at work are used by women who are already physically active, suggesting that workplace exercise programs do not serve the needs of women who may need exercise programs most. Multivariate analysis shows that age, having children, lack of energy, and lack of support are significant barriers to women's exercise participation at work. The results of this study suggest a leadership opportunity for on site occupational health nurses in addressing these barriers to workplace exercise.

Challenging a dogma: five-year survival does not equal cure in all colorectal cancer patients.

PubMed

Abdel-Rahman, Omar

2018-02-01

The current study tried to evaluate the factors affecting 10- to 20- years' survival among long term survivors (>5 years) of colorectal cancer (CRC). Surveillance, Epidemiology and End Results (SEER) database (1988-2008) was queried through SEER*Stat program.Univariate probability of overall and cancer-specific survival was determined and the difference between groups was examined. Multivariate analysis for factors affecting overall and cancer-specific survival was also conducted. Among node positive patients (Dukes C), 34% of the deaths beyond 5 years can be attributed to CRC; while among M1 patients, 63% of the deaths beyond 5 years can be attributed to CRC. The following factors were predictors of better overall survival in multivariate analysis: younger age, white race (versus black race), female gender, Right colon location (versus rectal location), earlier stage and surgery (P <0.0001 for all parameters). Similarly, the following factors were predictors of better cancer-specific survival in multivariate analysis: younger age, white race (versus black race), female gender, Right colon location (versus left colon and rectal locations), earlier stage and surgery (P <0.0001 for all parameters). Among node positive long-term CRC survivors, more than one third of all deaths can be attributed to CRC.

An Analysis of Officer Accession Programs and the Career Development of U.S. Marine Corps Officers

DTIC Science & Technology

2003-03-01

Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY 2...requirements for the degree of MASTER OF SCIENCE IN MANAGEMENT from the NAVAL POSTGRADUATE SCHOOL March 2003...137 APPENDIX D. TBS ACADEMIC, LEADESHIP AND MILITARY CLASS RANK MULTIVARIATE

Implementation of Motivational Interviewing in Substance Use Disorder Treatment: Research Network Participation and Organizational Compatibility.

PubMed

Rieckmann, Traci R; Abraham, Amanda J; Bride, Brian E

Despite considerable empirical evidence that psychosocial interventions improve addiction treatment outcomes across populations, implementation remains problematic. A small body of research points to the importance of research network participation as a facilitator of implementation; however, studies examined limited numbers of evidence-based practices. To address this gap, the present study examined factors impacting implementation of motivational interviewing (MI). This study used data from a national sample of privately funded treatment programs (n = 345) and programs participating in the National Drug Abuse Treatment Clinical Trials Network (CTN) (n = 156). Data were collected via face-to-face interviews with program administrators and clinical directors (2007-2009). Analysis included bivariate t tests and chi-square tests to compare private and CTN programs, and multivariable logistic regression of MI implementation. A majority (68.0%) of treatment programs reported use of MI. Treatment programs participating in the CTN (88.9%) were significantly more likely to report use of MI compared with non-CTN programs (58.5%; P < 0.01). CTN programs (82.1%) also were more likely to use trainers from the Motivational Interviewing Network of Trainers as compared with private programs (56.1%; P < 0.05). Multivariable logistic regression models reveal that CTN-affiliated programs and programs with a psychiatrist on staff were more likely to use MI. Programs that used the Stages of Change Readiness and Treatment Eagerness Scale assessment tool were more likely to use MI, whereas programs placing greater emphasis on confrontational group therapy were less likely to use MI. Findings suggest the critical role of research network participation, access to psychiatrists, and organizational compatibility in adoption and sustained use of MI.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

SOCR Motion Charts: An Efficient, Open-Source, Interactive and Dynamic Applet for Visualizing Longitudinal Multivariate Data

PubMed Central

Al-Aziz, Jameel; Christou, Nicolas; Dinov, Ivo D.

2011-01-01

The amount, complexity and provenance of data have dramatically increased in the past five years. Visualization of observed and simulated data is a critical component of any social, environmental, biomedical or scientific quest. Dynamic, exploratory and interactive visualization of multivariate data, without preprocessing by dimensionality reduction, remains a nearly insurmountable challenge. The Statistics Online Computational Resource (www.SOCR.ucla.edu) provides portable online aids for probability and statistics education, technology-based instruction and statistical computing. We have developed a new Java-based infrastructure, SOCR Motion Charts, for discovery-based exploratory analysis of multivariate data. This interactive data visualization tool enables the visualization of high-dimensional longitudinal data. SOCR Motion Charts allows mapping of ordinal, nominal and quantitative variables onto time, 2D axes, size, colors, glyphs and appearance characteristics, which facilitates the interactive display of multidimensional data. We validated this new visualization paradigm using several publicly available multivariate datasets including Ice-Thickness, Housing Prices, Consumer Price Index, and California Ozone Data. SOCR Motion Charts is designed using object-oriented programming, implemented as a Java Web-applet and is available to the entire community on the web at www.socr.ucla.edu/SOCR_MotionCharts. It can be used as an instructional tool for rendering and interrogating high-dimensional data in the classroom, as well as a research tool for exploratory data analysis. PMID:21479108

Impact of Gender on 30-Day Complications After Primary Total Joint Arthroplasty.

PubMed

Robinson, Jonathan; Shin, John I; Dowdell, James E; Moucha, Calin S; Chen, Darwin D

2017-08-01

Impact of gender on 30-day complications has been investigated in other surgical procedures but has not yet been studied in total hip arthroplasty (THA) or total knee arthroplasty (TKA). Patients who received THA or TKA from 2012 to 2014 were identified in the National Surgical Quality Improvement Program database. Patients were divided into 2 groups based on gender. Bivariate and multivariate analyses were performed to assess associations between gender and patient factors and complications after THA or TKA and to assess whether gender was an independent risk factor. THA patients consisted of 45.1% male and 54.9% female. In a multivariate analysis, female gender was found to be a protective factor for mortality, sepsis, cardiovascular complications, unplanned reintubation, and renal complications and as an independent risk factor for urinary tract infection, blood transfusion, and nonhome discharge after THA. TKA patients consisted of 36.7% male and 62.3% female. Multivariate analysis revealed female gender as a protective factor for sepsis, cardiovascular complications, and renal complications and as an independent risk factor for urinary tract infection, blood transfusion, and nonhome discharge after TKA. There are discrepancies in the THA or TKA complications based on gender, and the multivariate analyses confirmed gender as an independent risk factor for certain complications. Physicians should be mindful of patient's gender for better risk stratification and informed consent. Copyright © 2017 Elsevier Inc. All rights reserved.

Enhancing Student Writing and Computer Programming with LATEX and MATLAB in Multivariable Calculus

ERIC Educational Resources Information Center

Sullivan, Eric; Melvin, Timothy

2016-01-01

Written communication and computer programming are foundational components of an undergraduate degree in the mathematical sciences. All lower-division mathematics courses at our institution are paired with computer-based writing, coding, and problem-solving activities. In multivariable calculus we utilize MATLAB and LATEX to have students explore…

Insurance Coverage for Rehabilitation Therapies and Association with Social Participation Outcomes among Low-Income Children.

PubMed

Mirza, Mansha; Kim, Yoonsang

2016-01-01

(1) To profile children's health insurance coverage rates for specific rehabilitation therapies; (2) to determine whether coverage for rehabilitation therapies is associated with social participation outcomes after adjusting for child and household characteristics; (3) to assess whether rehabilitation insurance differentially affects social participation of children with and without disabilities. We conducted a cross-sectional analysis of secondary survey data on 756 children (ages 3-17) from 370 households living in low-income neighborhoods in a Midwestern U.S. city. Multivariate mixed effects logistic regression models were estimated. Significantly higher proportions of children with disabilities had coverage for physical therapy, occupational therapy, and speech and language pathology, yet gaps in coverage were noted. Multivariate analysis indicated that rehabilitation insurance coverage was significantly associated with social participation (OR = 1.67, 95% CI: 1.013-2.75). This trend was sustained in subgroup analysis. Findings support the need for comprehensive coverage of all essential services under children's health insurance programs.

Control Charts When the Observations Are Correlated.

DTIC Science & Technology

1987-05-01

l7 D-AiB6 388 CONTROL CHARTS WHEN THE OBSERVATIONS ARE CORRELATED(J) i/iPITTSBURGH UNIV PA CENTER FOR KULTIVARIATE ANALYSIS P R KRISHNAIAH ET AL MAY... Krishnaiah and B. Q. Miao F-49620-85-C-0008 S. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK AREA II WORK UNIT NUMBERS... Krishnaiah and B.Q. Miao Center for Multivariate Analysis University of Pittsburgh N DTIC E L 1Zk-, -I- OCT0 11987 Play 1987 Technical Report No. 87-09

Association between proportion of US medical graduates and program characteristics in gastroenterology fellowships.

PubMed

Atsawarungruangkit, Amporn

2017-01-01

Gastroenterology is one of the most competitive internal medicine fellowship. However, factors that associated with program competitiveness have not been documented. The objective of this study was to evaluate associations between characteristics of gastroenterology fellowship programs and their competitiveness through the proportion of US medical graduates for the academic year 2016/17. This study used a retrospective, cross-sectional design with data obtained from the American Medical Association. The proportion of US medical graduates in gastroenterology fellowships was used as an indicator of program competitiveness. Using both univariate and multivariate linear regression analyses, we analyzed the association between the proportion of medical graduates in each program and 27 program characteristics based on a significance level of 0.05. In total, 153 out of 171 gastroenterology fellowship programs satisfied the inclusion criteria. A multivariate analysis revealed that a higher proportion of US medical graduates was significantly associated with five program characteristics: that it was a university-based program (p < 0.001), the ratio of full-time paid faculty to fellow positions (p < 0.001), the proportion of females in the program (p = 0.002), location in the Pacific region (p = 0.039), and a non-smoker hiring policy (p = 0.042). Among the five significant factors, being university based, located in the Pacific, and having a non-smoker hiring policy were likely to remain unchanged over a long period. However, program directors and candidates should pay attention to equivalence between full-time paid faculty and fellowship positions, and the proportion of women in the program. The former indicates the level of supervision while the latter has become increasingly important owing to the higher proportion of women in medicine.

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

Anima: Modular Workflow System for Comprehensive Image Data Analysis

PubMed Central

Rantanen, Ville; Valori, Miko; Hautaniemi, Sampsa

2014-01-01

Modern microscopes produce vast amounts of image data, and computational methods are needed to analyze and interpret these data. Furthermore, a single image analysis project may require tens or hundreds of analysis steps starting from data import and pre-processing to segmentation and statistical analysis; and ending with visualization and reporting. To manage such large-scale image data analysis projects, we present here a modular workflow system called Anima. Anima is designed for comprehensive and efficient image data analysis development, and it contains several features that are crucial in high-throughput image data analysis: programing language independence, batch processing, easily customized data processing, interoperability with other software via application programing interfaces, and advanced multivariate statistical analysis. The utility of Anima is shown with two case studies focusing on testing different algorithms developed in different imaging platforms and an automated prediction of alive/dead C. elegans worms by integrating several analysis environments. Anima is a fully open source and available with documentation at www.anduril.org/anima. PMID:25126541

General surgery vs fellowship: the role of the Independent Academic Medical Center.

PubMed

Adra, Souheil W; Trickey, Amber W; Crosby, Moira E; Kurtzman, Scott H; Friedell, Mark L; Reines, H David

2012-01-01

To compare career choices of residency graduates from Independent Academic Medical Center (IAMC) and University Academic Medical Center (UAMC) programs and evaluate program directors' perceptions of residents' motivations for pursuing general surgery or fellowships. From May to August 2011, an electronic survey collected information on program characteristics, graduates' career pursuits, and career motivations. Fisher's exact tests were calculated to compare responses by program type. Multivariate logistic regression was used to identify independent program characteristics associated with graduates pursuing general surgery. Data were collected on graduates over 3 years (2009-2011). Surgery residency program directors. Seventy-four program directors completed the survey; 42% represented IAMCs. IAMCs reported more graduates choosing general surgery. Over one-quarter of graduates pursued general surgery from 52% of IAMC vs 37% of UAMC programs (p = 0.243). Career choices varied significantly by region: over one-quarter of graduates pursue general surgery from 78% of Western, 60% of Midwestern, 40% of Southern, and 24% of Northeastern programs (p = 0.018). On multivariate analysis, IAMC programs were independently associated with more graduates choosing general surgery (p = 0.017), after adjustment for other program characteristics. Seventy-five percent of UAMC programs reported over three-fourths of graduates receive first choice fellowship, compared with only 52% of IAMC programs (p = 0.067). Fellowships were comparable among IAMC and UAMC programs, most commonly MIS/Bariatric (16%), Critical Care/Trauma (16%), and Vascular (14%). IAMC and UAMC program directors cite similar reasons for graduate career choices. Most general surgery residents undergo fellowship training. Graduates from IAMC and UAMC programs pursue similar specialties, but UAMC programs report more first choice acceptance. IAMC programs may graduate proportionately more general surgeons. Further studies directly evaluating surgical residents' career choices are warranted to understand the influence of independent and university programs in shaping these choices and to develop strategies for reducing the general surgeon shortage. Copyright © 2012 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Associations between quality indicators of internal medicine residency training programs

PubMed Central

2011-01-01

Background Several residency program characteristics have been suggested as measures of program quality, but associations between these measures are unknown. We set out to determine associations between these potential measures of program quality. Methods Survey of internal medicine residency programs that shared an online ambulatory curriculum on hospital type, faculty size, number of trainees, proportion of international medical graduate (IMG) trainees, Internal Medicine In-Training Examination (IM-ITE) scores, three-year American Board of Internal Medicine Certifying Examination (ABIM-CE) first-try pass rates, Residency Review Committee-Internal Medicine (RRC-IM) certification length, program director clinical duties, and use of pharmaceutical funding to support education. Associations assessed using Chi-square, Spearman rank correlation, univariate and multivariable linear regression. Results Fifty one of 67 programs responded (response rate 76.1%), including 29 (56.9%) community teaching and 17 (33.3%) university hospitals, with a mean of 68 trainees and 101 faculty. Forty four percent of trainees were IMGs. The average post-graduate year (PGY)-2 IM-ITE raw score was 63.1, which was 66.8 for PGY3s. Average 3-year ABIM-CE pass rate was 95.8%; average RRC-IM certification was 4.3 years. ABIM-CE results, IM-ITE results, and length of RRC-IM certification were strongly associated with each other (p < 0.05). PGY3 IM-ITE scores were higher in programs with more IMGs and in programs that accepted pharmaceutical support (p < 0.05). RRC-IM certification was shorter in programs with higher numbers of IMGs. In multivariable analysis, a higher proportion of IMGs was associated with 1.17 years shorter RRC accreditation. Conclusions Associations between quality indicators are complex, but suggest that the presence of IMGs is associated with better performance on standardized tests but decreased duration of RRC-IM certification. PMID:21651768

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Assessing Principal Component Regression Prediction of Neurochemicals Detected with Fast-Scan Cyclic Voltammetry

PubMed Central

2011-01-01

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook’s distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards. PMID:21966586

Assessing principal component regression prediction of neurochemicals detected with fast-scan cyclic voltammetry.

PubMed

Keithley, Richard B; Wightman, R Mark

2011-06-07

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook's distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards.

Motivations and Predictors of Cheating in Pharmacy School

PubMed Central

Nguyen, Kathy; Shah, Bijal M.; Doroudgar, Shadi; Bidwal, Monica K.

2016-01-01

Objective. To assess the prevalence, methods, and motivations for didactic cheating among pharmacy students and to determine predictive factors for cheating in pharmacy colleges and schools. Methods. A 45-item cross-sectional survey was conducted at all four doctor of pharmacy programs in Northern California. For data analysis, t test, Fisher exact test, and logistic regression were used. Results. Overall, 11.8% of students admitted to cheating in pharmacy school. Primary motivations for cheating included fear of failure, procrastination, and stress. In multivariate analysis, the only predictor for cheating in pharmacy school was a history of cheating in undergraduate studies. Conclusion. Cheating occurs in pharmacy schools and is motivated by fear of failure, procrastination, and stress. A history of past cheating predicts pharmacy school cheating. The information presented may help programs better understand their student population and lead to a reassessment of ethical culture, testing procedures, and prevention programs. PMID:27899829

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Newly Graduated Nurses' Competence and Individual and Organizational Factors: A Multivariate Analysis.

PubMed

Numminen, Olivia; Leino-Kilpi, Helena; Isoaho, Hannu; Meretoja, Riitta

2015-09-01

To study the relationships between newly graduated nurses' (NGNs') perceptions of their professional competence, and individual and organizational work-related factors. A multivariate, quantitative, descriptive, correlation design was applied. Data collection took place in November 2012 with a national convenience sample of 318 NGNs representing all main healthcare settings in Finland. Five instruments measured NGNs' perceptions of their professional competence, occupational commitment, empowerment, practice environment, and its ethical climate, with additional questions on turnover intentions, job satisfaction, and demographics. Descriptive statistics summarized the demographic data, and inferential statistics multivariate path analysis modeling estimated the relationships between the variables. The strongest relationship was found between professional competence and empowerment, competence explaining 20% of the variance of empowerment. The explanatory power of competence regarding practice environment, ethical climate of the work unit, and occupational commitment, and competence's associations with turnover intentions, job satisfaction, and age, were statistically significant but considerably weaker. Higher competence and satisfaction with quality of care were associated with more positive perceptions of practice environment and its ethical climate as well as higher empowerment and occupational commitment. Apart from its association with empowerment, competence seems to be a rather independent factor in relation to the measured work-related factors. Further exploration would deepen the knowledge of this relationship, providing support for planning educational and developmental programs. Research on other individual and organizational factors is warranted to shed light on factors associated with professional competence in providing high-quality and safe care as well as retaining new nurses in the workforce. The study sheds light on the strength and direction of the significantly associated work-related factors. Nursing professional bodies, managers, and supervisors can use the findings in planning orientation programs and other occupational interventions for NGNs. © 2015 Sigma Theta Tau International.

College Graduation Rates for Minority Students in a Selective Technical University: Will Participation in a Summer Bridge Program Contribute to Success?

PubMed

Murphy, Terrence E; Gaughan, Monica; Hume, Robert; Moore, S Gordon

2010-03-01

There are many approaches to solving the problem of underrepresentation of some racial and ethnic groups and women in scientific and technical disciplines. Here, the authors evaluate the association of a summer bridge program with the graduation rate of underrepresented minority (URM) students at a selective technical university. They demonstrate that this 5-week program prior to the fall of the 1st year contains elements reported as vital for successful student retention. Using multivariable survival analysis, they show that for URM students entering as fall-semester freshmen, relative to their nonparticipating peers, participation in this accelerated summer bridge program is associated with higher likelihood of graduation. The longitudinal panel data include more than 2,200 URM students.

College Graduation Rates for Minority Students in a Selective Technical University: Will Participation in a Summer Bridge Program Contribute to Success?

PubMed Central

Murphy, Terrence E.; Gaughan, Monica; Hume, Robert; Moore, S. Gordon

2012-01-01

There are many approaches to solving the problem of underrepresentation of some racial and ethnic groups and women in scientific and technical disciplines. Here, the authors evaluate the association of a summer bridge program with the graduation rate of underrepresented minority (URM) students at a selective technical university. They demonstrate that this 5-week program prior to the fall of the 1st year contains elements reported as vital for successful student retention. Using multivariable survival analysis, they show that for URM students entering as fall-semester freshmen, relative to their nonparticipating peers, participation in this accelerated summer bridge program is associated with higher likelihood of graduation. The longitudinal panel data include more than 2,200 URM students. PMID:23136456

Ophthalmology Residency Match outcomes for 2011.

PubMed

Yousuf, Salman J; Jones, Leslie S

2012-03-01

To determine the match rate and predictors of matching into an ophthalmology residency. Population-based, cross-sectional study. All 746 candidates who submitted an application for the 2011 ophthalmology residency match. The Ophthalmology Residency Matching Program applicant database was reviewed to determine applicant characteristics and match outcomes. For US seniors, multivariate regression analysis was performed to determine predictors of matching. Match rate and predictors of US seniors matching. Rank lists were submitted by 622 applicants, among whom 458 (74%) matched. The match rate was higher for US seniors (83%) than for independent applicants (41%; P < 0.001). US seniors who matched were more likely to be Alpha Omega Alpha medical honor society members (odds ratio [OR], 2.94; 95% confidence interval [CI], 1.16-7.29), to attend medical schools ranked in the top 40 according to National Institutes of Health funding (OR, 2.25; CI, 1.14-4.43), and to have ranked more programs (OR, 1.44; CI, 1.29-1.60). Those ranking 6 to 10 programs had an 80% to 90% chance of matching, and those ranking more than 10 programs had a greater than 90% chance of matching. No clear benefit was observed by ranking additional programs once 11 had already been ranked. Average US Medical Licensing Examination Step 1 scores were 239 ± 14 and 223 ± 18 for applicants who were matched and unmatched, respectively; this difference was significant by univariate analysis (P < 0.001) but not by multivariate regression (P = 0.163). Ophthalmology ranks among the most competitive specialties in medicine. Those most likely to match were US seniors who maintained academic excellence beginning in their preclinical years. A finite relationship exists between ranking a greater number of programs and having a greater chance of matching. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Initiation and Maintenance of Fitness Center Utilization in an Incentive-Based Employer Wellness Program

PubMed Central

Abraham, Jean Marie; Crespin, Daniel; Rothman, Alexander

2015-01-01

Objective Investigate the initiation and maintenance of participation in an employer-based wellness program that provides financial incentives for fitness center utilization. Methods Using multivariate analysis, we investigated how employees’ demographics, health status, exercise-related factors, and lifestyle change preferences affect program participation. Results Forty-two percent of eligible employees participated in the program and 24% earned a $20 incentive at least once by utilizing a gym 8 times or more in a month. On average, participants utilized fitness centers 7.0 months each year and earned credit 4.5 months. Participants’ utilization diminished after their first year in the program. Conclusions Factors associated with initiation and maintenance of fitness center utilization were similar. Declining utilization over time raises concern about the long-run effectiveness of fitness-focused wellness programs. Employers may want to consider additional levers to positively reinforce participation. PMID:26340283

Association between participation and compliance with Continuing Medical Education and care production by physicians: a cross-sectional study

PubMed Central

Carrera, Renato Melli; Cendoroglo, Miguel; Gonçales, Paulo David Scatena; Marques, Flavio Rocha Brito; Sardenberg, Camila; Glezer, Milton; dos Santos, Oscar Fernando Pavão; Rizzo, Luiz Vicente; Lottenberg, Claudio Luiz; Schvartsman, Cláudio

2015-01-01

Objective Physician participation in Continuing Medical Education programs may be influenced by a number of factors. To evaluate the factors associated with compliance with the Continuing Medical Education requirements at a private hospital, we investigated whether physicians’ activity, measured by volumes of admissions and procedures, was associated with obtaining 40 Continuing Medical Education credits (40 hours of activities) in a 12-month cycle. Methods In an exclusive and non-mandatory Continuing Medical Education program, we collected physicians’ numbers of hospital admissions and numbers of surgical procedures performed. We also analyzed data on physicians’ time since graduation, age, and gender. Results A total of 3,809 credentialed, free-standing, private practice physicians were evaluated. Univariate analysis showed that the Continuing Medical Education requirements were more likely to be achieved by male physicians (odds ratio 1.251; p=0.009) and who had a higher number of hospital admissions (odds ratio 1.022; p<0.001). Multivariate analysis showed that age and number of hospital admissions were associated with achievement of the Continuing Medical Education requirements. Each hospital admission increased the chance of achieving the requirements by 0.4%. Among physicians who performed surgical procedures, multivariate analysis showed that male physicians were 1.3 time more likely to achieve the Continuing Medical Education requirements than female physicians. Each surgical procedure performed increased the chance of achieving the requirements by 1.4%. Conclusion The numbers of admissions and number of surgical procedures performed by physicians at our hospital were associated with the likelihood of meeting the Continuing Medical Education requirements. These findings help to shed new light on our Continuing Medical Education program. PMID:25807247

Trainee-Associated Factors and Proficiency at Percutaneous Nephrolithotomy.

PubMed

Aghamir, Seyed Mohammad Kazem; Behtash, Negar; Hamidi, Morteza; Farahmand, Hasan; Salavati, Alborz; Mortaz Hejri, Sara

2017-07-01

Percutaneous nephrolithotomy (PNL) is a complicated procedure for urology trainees. This study was designed to investigate the effect of trainees' ages and previous experience, as well as the number of operated cases, on proficiency at PNL by using patient outcomes. A cross sectional observational study was designed during a five-year period. Trainees in PNL fellowship programs were included. At the end of the program, the trainees' performance in PNL was assessed regarding five competencies and scored 1-5. If the overall score was 4 or above, the trainee was considered as proficient. The trainees' age at the beginning of the program and the years passed from their residency graduation were asked and recorded. Also, the number of PNL cases operated by each trainee was obtained via their logbooks. The age, years passed from graduation, and number of operated cases were compared between two groups of proficient and non-proficient trainees. Univariate and multivariate binary logistic regression analysis was applied to estimate the effect of aforementioned variables on the occurrence of the proficiency. Forty-two trainees were included in the study. The mean and standard deviation for the overall score were 3.40 (out of 5) and 0.67, respectively. Eleven trainees (26.2%) recognized as proficient in performing PNL. Univariate regression analysis indicated that each of three variables (age, years passed from graduation and number of operated cases) had statistically significant effect on proficiency. However, the multivariate regression analysis revealed that just the number of cases had significant effect on achieving proficiency. Although it might be assumed that trainees' age negatively correlates with their scores, in fact, it is their amount of practice that makes a difference. A certain number of cases is required to be operated by a trainee in order to reach the desired competency in PNL.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies

PubMed Central

van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.

2013-01-01

To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524

Influences on parental acceptance of HPV vaccination in demonstration projects in Uganda and Vietnam.

PubMed

Galagan, Sean R; Paul, Proma; Menezes, Lysander; LaMontagne, D Scott

2013-06-26

This study investigates the effect of communication strategies on human papillomavirus (HPV) vaccine uptake in HPV vaccine demonstration projects in Uganda and Vietnam. Secondary analysis was conducted on data from surveys of a representative sample of parents and guardians of girls eligible for HPV vaccine, measuring three-dose coverage achieved in demonstration projects in 2008-2010. Univariate and multivariate logistic regression analysis calculated the unadjusted and adjusted odds of receiving at least one dose of HPV vaccine depending on exposure to community influencers; information, education, and communication (IEC) channels; and demographic factors. This study found that exposure to community influencers was associated with HPV vaccine uptake in a multivariate model controlling for other factors. Exposure to non-interactive IEC channels was only marginally associated with HPV vaccine uptake. These results underscore the need of HPV vaccine programs in low- and middle-income countries to involve and utilize key community influencers and stakeholders to maximize HPV vaccine uptake. Copyright © 2013 Elsevier Ltd. All rights reserved.

Boosting Higgs pair production in the [Formula: see text] final state with multivariate techniques.

PubMed

Behr, J Katharina; Bortoletto, Daniela; Frost, James A; Hartland, Nathan P; Issever, Cigdem; Rojo, Juan

2016-01-01

The measurement of Higgs pair production will be a cornerstone of the LHC program in the coming years. Double Higgs production provides a crucial window upon the mechanism of electroweak symmetry breaking and has a unique sensitivity to the Higgs trilinear coupling. We study the feasibility of a measurement of Higgs pair production in the [Formula: see text] final state at the LHC. Our analysis is based on a combination of traditional cut-based methods with state-of-the-art multivariate techniques. We account for all relevant backgrounds, including the contributions from light and charm jet mis-identification, which are ultimately comparable in size to the irreducible 4 b QCD background. We demonstrate the robustness of our analysis strategy in a high pileup environment. For an integrated luminosity of [Formula: see text] ab[Formula: see text], a signal significance of [Formula: see text] is obtained, indicating that the [Formula: see text] final state alone could allow for the observation of double Higgs production at the High Luminosity LHC.

[Methods of the multivariate statistical analysis of so-called polyetiological diseases using the example of coronary heart disease].

PubMed

Lifshits, A M

1979-01-01

General characteristics of the multivariate statistical analysis (MSA) is given. Methodical premises and criteria for the selection of an adequate MSA method applicable to pathoanatomic investigations of the epidemiology of multicausal diseases are presented. The experience of using MSA with computors and standard computing programs in studies of coronary arteries aterosclerosis on the materials of 2060 autopsies is described. The combined use of 4 MSA methods: sequential, correlational, regressional, and discriminant permitted to quantitate the contribution of each of the 8 examined risk factors in the development of aterosclerosis. The most important factors were found to be the age, arterial hypertension, and heredity. Occupational hypodynamia and increased fatness were more important in men, whereas diabetes melitus--in women. The registration of this combination of risk factors by MSA methods provides for more reliable prognosis of the likelihood of coronary heart disease with a fatal outcome than prognosis of the degree of coronary aterosclerosis.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

F100 multivariable control synthesis program: Evaluation of a multivariable control using a real-time engine simulation

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Soeder, J. F.; Seldner, K.; Cwynar, D. S.

1977-01-01

The design, evaluation, and testing of a practical, multivariable, linear quadratic regulator control for the F100 turbofan engine were accomplished. NASA evaluation of the multivariable control logic and implementation are covered. The evaluation utilized a real time, hybrid computer simulation of the engine. Results of the evaluation are presented, and recommendations concerning future engine testing of the control are made. Results indicated that the engine testing of the control should be conducted as planned.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

LinkWinds: An Approach to Visual Data Analysis

NASA Technical Reports Server (NTRS)

Jacobson, Allan S.

1992-01-01

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration and analysis system resulting from a NASA/JPL program of research into graphical methods for rapidly accessing, displaying and analyzing large multivariate multidisciplinary datasets. It is an integrated multi-application execution environment allowing the dynamic interconnection of multiple windows containing visual displays and/or controls through a data-linking paradigm. This paradigm, which results in a system much like a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but provides a highly intuitive, easy to learn user interface on top of the traditional graphical user interface.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Statistical Development of Flood Frequency and Magnitude Equations for the Cosumnes and Mokelumne River Drainage Basins, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Burns, R. G.; Meyer, R. W.; Cornwell, K.

2003-12-01

In-basin statistical relations allow for development of regional flood frequency and magnitude equations in the Cosumnes River and Mokelumne River drainage basins. Current equations were derived from data collected through 1975, and do not reflect newer data with some significant flooding. Physical basin characteristics (area, mean basin elevation, slope of longest reach, and mean annual precipitation) were correlated against predicted flood discharges for each of the 5, 10, 25, 50, 100, 200, and 500-year recurrence intervals in a multivariate analysis. Predicted maximum instantaneous flood discharges were determined using the PEAKFQ program with default settings, for 24 stream gages within the study area presumed not affected by flow management practices. For numerical comparisons, GIS-based methods using Spatial Analyst and the Arc Hydro Tools extension were applied to derive physical basin characteristics as predictor variables from a 30m digital elevation model (DEM) and a mean annual precipitation raster (PRISM). In a bivariate analysis, examination of Pearson correlation coefficients, F-statistic, and t & p thresholds show good correlation between area and flood discharges. Similar analyses show poor correlation for mean basin elevation, slope and precipitation, with flood discharge. Bivariate analysis suggests slope may not be an appropriate predictor term for use in the multivariate analysis. Precipitation and elevation correlate very well, demonstrating possible orographic effects. From the multivariate analysis, less than 6% of the variability in the correlation is not explained for flood recurrences up to 25 years. Longer term predictions up to 500 years accrue greater uncertainty with as much as 15% of the variability in the correlation left unexplained.

Evaluation of an F100 multivariable control using a real-time engine simulation

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Skira, C.; Soeder, J. F.

1977-01-01

A multivariable control design for the F100 turbofan engine was evaluated, as part of the F100 multivariable control synthesis (MVCS) program. The evaluation utilized a real-time, hybrid computer simulation of the engine and a digital computer implementation of the control. Significant results of the evaluation are presented and recommendations concerning future engine testing of the control are made.

Community-based tobacco cessation program among women in Mumbai, India.

PubMed

Mishra, G A; Kulkarni, S V; Majmudar, P V; Gupta, S D; Shastri, S S

2014-12-01

Globally tobacco epidemic kills nearly six million people annually. Consumption of tobacco products is on the rise in low- and middle-income countries. Tobacco is addictive; hence, tobacco users need support in quitting. Providing tobacco cessation services to women in community enabling them to quit tobacco, identifying factors associated with quitting and documenting the processes involved to establish a replicable "model tobacco cessation program." This is a community based tobacco cessation program of one year duration conducted among women in a low socioeconomic area of Mumbai, India. It involved three interventions conducted at three months interval, comprised of health education, games and counseling sessions and a post intervention follow-up. Uni and multivariate analysis was performed to find out association of various factors with quitting tobacco. The average compliance in three intervention rounds was 95.2%. The mean age at initiation of tobacco was 17.3 years. Tobacco use among family members and in the community was primary reasons for initiation and addiction to tobacco was an important factor for continuation, whereas health education and counseling seemed to be largely responsible for quitting. The quit rate at the end of the programme was 33.5%. Multivariate logistic regression analysis found that women in higher age groups and women consuming tobacco at multiple locations are less likely to quit tobacco. Changing cultural norms associated with smokeless tobacco, strict implementation of antitobacco laws in the community and work places and providing cessation support are important measures in preventing initiation and continuation of tobacco use among women in India.

Kinetic Risk Factors of Running-Related Injuries in Female Recreational Runners.

PubMed

Napier, Christopher; MacLean, Christopher L; Maurer, Jessica; Taunton, Jack E; Hunt, Michael A

2018-05-30

Our objective was to prospectively investigate the association of kinetic variables with running-related injury (RRI) risk. Seventy-four healthy female recreational runners ran on an instrumented treadmill while 3D kinetic and kinematic data were collected. Kinetic outcomes were vertical impact transient, average vertical loading rate, instantaneous vertical loading rate, active peak, vertical impulse, and peak braking force (PBF). Participants followed a 15-week half-marathon training program. Exposure time (hours of running) was calculated from start of program until onset of injury, loss to follow-up, or end of program. After converting kinetic variables from continuous to ordinal variables based on tertiles, Cox proportional hazard models with competing risks were fit for each variable independently, before analysis in a forward stepwise multivariable model. Sixty-five participants were included in the final analysis, with a 33.8% injury rate. PBF was the only kinetic variable that was a significant predictor of RRI. Runners in the highest tertile (PBF <-0.27 BW) were injured at 5.08 times the rate of those in the middle tertile and 7.98 times the rate of those in the lowest tertile. When analyzed in the multivariable model, no kinetic variables made a significant contribution to predicting injury beyond what had already been accounted for by PBF alone. Findings from this study suggest PBF is associated with a significantly higher injury hazard ratio in female recreational runners and should be considered as a target for gait retraining interventions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Application of advanced control techniques to aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1984-01-01

Two programs are described which involve the application of advanced control techniques to the design of engine control algorithms. Multivariable control theory is used in the F100 MVCS (multivariable control synthesis) program to design controls which coordinate the control inputs for improved engine performance. A systematic method for handling a complex control design task is given. Methods of analytical redundancy are aimed at increasing the control system reliability. The F100 DIA (detection, isolation, and accommodation) program, which investigates the uses of software to replace or augment hardware redundancy for certain critical engine sensor, is described.

Predictors of matching in an ophthalmology residency program.

PubMed

Loh, Allison R; Joseph, Damien; Keenan, Jeremy D; Lietman, Thomas M; Naseri, Ayman

2013-04-01

To examine the characteristics of US medical students applying for ophthalmology residency and to determine the predictors of matching. A retrospective case series. A total of 3435 medical students from the United States who applied to an ophthalmology residency program from 2003 to 2008 were included. Matched and unmatched applicants were compared and stratified by predictor variables, including United States Medical Licensing Examination (USMLE) Step 1 score, Alpha Omega Alpha (AOA) status, medical school reputation, and medical school geographic region. Differences in proportions were analyzed using the Fisher exact test. Logistic regression was used to determine the predictors of successful matching. Successful matching to an ophthalmology program. The majority of applicants (72%, 2486/3435) matched in ophthalmology. In multivariate analysis, AOA membership (odds ratio [OR], 2.6, P<0.0001), USMLE score (OR, 1.6; P<0.0001), presence of an ophthalmology residency at medical school (OR, 1.4; P = 0.01), top 25 medical school (OR, 1.4; P<0.03), top 10 medical school (OR, 1.6; P<0.02), and allopathic degree (OR, 4.0; P<0.0001) were statistically significant predictors of matching. Approximately 60% (1442/2486) of applicants matched to the same geographic region as their medical school. Applicants were more likely to match at a program in the same geographic region as their medical school than would be predicted by chance alone (P<0.0001). In multivariate analysis, higher USMLE score (OR, 0.9; P<0.0001) and top 10 medical school (OR, 0.7; P = 0.027) were statistically significant predictors of matching to outside the geographic region as one's medical school. The majority of applicants applying for an ophthalmology residency position match successfully. Higher performance on quantitative metrics seems to confer an advantage for matching. The majority of applicants match at a residency program within the same geographic region as one's medical school. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

Accuracy of remotely sensed data: Sampling and analysis procedures

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Oderwald, R. G.; Mead, R. A.

1982-01-01

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.

Does attending an exercise class with a spouse improve long-term exercise adherence among people aged 65 years and older: a 6-month prospective follow-up study.

PubMed

Osuka, Yosuke; Jung, Songee; Kim, Taeho; Okubo, Yoshiro; Kim, Eunbi; Tanaka, Kiyoji

2017-07-31

Family support can help older adults better adhere to exercise routine, but it remains unclear whether an exercise program targeting older married couples would have stronger effects on exercise adherence than would a program for individuals. The purpose of this study was to determine the effects of an exercise program on the exercise adherence of older married couples over a 24-week follow-up period. Thirty-four older married couples and 59 older adults participated in this study as couple and non-couple groups (CG and NCG, respectively). All participants attended an 8-week supervised program (once a week and a home-based exercise program comprising walking and strength exercises) and then participated in a follow-up measurement (24 weeks after post-intervention measurement). Exercise adherence was prospectively measured via an exercise habituation diary during the follow-up period-specifically, we asked them to record practice rates for walking (≥2 days/week) and strength exercises (≥6 items for 2 days/week). A multivariate logistic regression analysis was conducted to obtain the CG's odds ratios (ORs) and 95% confidence intervals (CIs) for adherence to walking and strength exercise adjusted for potential confounders (with NCG as the reference). Although the adherence rate of walking exercise in the CG was significantly higher than that in the NCG (29.2%; P < 0.001), there was no significant difference in the adherence rate of strength exercise between the two groups (P = 0.199). The multivariate logistic regression analysis showed that CG had significantly higher odds of adherence to walking exercise compared with the NCG (3.68 [1.57-8.60]). However, the odds of adherence to strength exercise did not significantly differ between the two groups (1.30 [0.52-3.26]). These results suggest that an exercise program targeting older married couples may be a useful strategy for maintaining walking adherence, even six months after the supervised program has ceased. A blinded randomized controlled trial will be needed to confirm this conclusion. Retrospectively registered. UMIN Clinical Trials Registry (Registered: 02/11/16) UMIN000024689 .

Emotional intelligence and the relationship to resident performance: a multi-institutional study.

PubMed

Talarico, Joseph F; Varon, Albert J; Banks, Shawn E; Berger, Jeffrey S; Pivalizza, Evan G; Medina-Rivera, Glorimar; Rimal, Jyotsna; Davidson, Melissa; Dai, Feng; Qin, Li; Ball, Ryan D; Loudd, Cheryl; Schoenberg, Catherine; Wetmore, Amy L; Metro, David G

2013-05-01

To test the hypothesis that emotional intelligence, as measured by a BarOn Emotional Quotient Inventory (EQ-i), the 125-item version personal inventory (EQ-i:125), correlates with resident performance. Survey (personal inventory) instrument. Five U.S. academic anesthesiology residency programs. Postgraduate year (PGY) 2, 3, and 4 residents enrolled in university-based anesthesiology residency programs. Residents confidentially completed the BarOn EQ-i:125 personal inventory. The deidentified resident evaluations were sent to the principal investigator of a separate data collection study for data analysis. Data collected from the inventory were correlated with daily evaluations of the residents by residency program faculty. Results of the individual BarOn EQ-i:125 and daily faculty evaluations of the residents were compiled and analyzed. Univariate correlation analysis and multivariate canonical analysis showed that some aspects of the BarOn EQ-i:125 were significantly correlated with, and likely to be predictors of, resident performance. Emotional intelligence, as measured by the BarOn EQ-i personal inventory, has considerable promise as an independent indicator of performance as an anesthesiology resident. Copyright © 2013 Elsevier Inc. All rights reserved.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 1: System description

NASA Technical Reports Server (NTRS)

Kriegler, F. J.

1974-01-01

The MIDAS System is described as a third-generation fast multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turnaround time and significant gains in throughput. The hardware and software are described. The system contains a mini-computer to control the various high-speed processing elements in the data path, and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 200,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation.

Predictors of acceptance of offered care management intervention services in a quality improvement trial for dementia.

PubMed

Kaisey, Marwa; Mittman, Brian; Pearson, Marjorie; Connor, Karen I; Chodosh, Joshua; Vassar, Stefanie D; Nguyen, France T; Vickrey, Barbara G

2012-10-01

Care management approaches have been proven to improve outcomes for patients with dementia and their family caregivers (dyads). However, acceptance of services in these programs is incomplete, impacting effectiveness. Acceptance may be related to dyad as well as healthcare system characteristics, but knowledge about factors associated with program acceptance is lacking. This study investigates patient, caregiver, and healthcare system characteristics associated with acceptance of offered care management services. This study analyzed data from the intervention arm of a cluster randomized controlled trial of a comprehensive dementia care management intervention. There were 408 patient-caregiver dyads enrolled in the study, of which 238 dyads were randomized to the intervention. Caregiver, patient, and health system factors associated with participation in offered care management services were assessed through bivariate and multivariate regression analyses. Out of the 238 dyads, 9 were ineligible for this analysis, leaving data of 229 dyads in this sample. Of these, 185 dyads accepted offered care management services, and 44 dyads did not. Multivariate analyses showed that higher likelihood of acceptance of care management services was uniquely associated with cohabitation of caregiver and patient (p < 0.001), lesser severity of dementia (p = 0.03), and higher patient comorbidity (p = 0.03); it also varied across healthcare organization sites. Understanding factors that influence care management participation could result in increased adoption of successful programs to improve quality of care. Using these factors to revise both program design as well as program promotion may also benefit external validity of future quality improvement research trials. Copyright © 2011 John Wiley & Sons, Ltd.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

[Determinants of participation among primiparous women in a prenatal education program].

PubMed

Martínez Galiano, Juan Miguel; Delgado Rodríguez, Miguel

2013-01-01

To determine the factors associated with participation in a prenatal education program among primiparous mothers. A multicenter observational study was carried out in four Andalusian hospitals (Spain) in primiparous women in 2010. Sociodemographic characteristics, obstetric history, and previous diseases were collected through an interview and from the clinical charts. Crude and adjusted odds ratios were calculated. The study population consisted of 520 women. According to multivariate analysis, the factors associated with participation in the program were educational level (p <0.001), higher income levels (p <0.001), birth in Spain (p <0.001) and viewing the program as useful (p <0.001). After adjusting for these variables, no other variable was related to participation. The main reason given by women for not attending prenatal education was lack of an invitation to attend. Participation in the prenatal education program was favored by a higher educational level and income, birth in Spain, and viewing the program as useful. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Understanding dual enrollees' use of Medicare home health services: the effects of differences in Medicaid home care programs.

PubMed

Kenney, G; Rajan, S

2000-01-01

Both the Medicare and Medicaid programs have experienced considerable growth in spending on home care in recent years. As policymakers adopt measures (such as those legislated in the Balanced Budget Act of 1997) to curb the rate of spending growth on home care services, it is important to understand interactions between the Medicare and Medicaid home care programs in serving the dually enrolled population. This study examines the potential effects of the Medicaid home care program on Medicare home health utilization using multivariate models. The study relied on data from the Health Care Financing Administration's Medicare Current Beneficiary Survey (MCBS), a longitudinal survey of Medicare enrollees. The primary MCBS file used was from Round 1 of the survey, which was fielded between September and December 1991. The unit of analysis was individuals. The authors used descriptive and multivariate methods to explore the relationship between Medicare coverage and state home care program characteristics. Included were variables that have been found to be significant determinants of Medicare home health utilization in other studies as well as variables to indicate the availability and generosity of Medicaid home care services in each state represented in the survey. The findings were consistent with those of previous studies, in that dual enrollees were disproportionate users of Medicare home health services, accounting for only 16% of enrollees but receiving 40% of all visits. In addition, lower levels of Medicare home health use were observed in states with relatively higher Medicaid spending on home health and personal care services, but this relationship appeared to be heavily dominated by the inclusion of enrollees living in New York State. When individuals from New York were excluded from the analysis, we found a negative but statistically significant relationship between Medicaid outlays on home health and personal care services and Medicare home health utilization. Because the Medicare and Medicaid programs are interconnected through the sizable dual enrollee population, changes in one program are likely to have ramifications for the other. This study presents another step in exploring how the two programs interact and emphasizes the fact that costs can be shifted between the two programs as policy changes are made to control the rate of home care spending growth.

Coma and Stroke Following Surgical Treatment of Unruptured Intracranial Aneurysm: An American College of Surgeons National Surgical Quality Improvement Program Study.

PubMed

McCutcheon, Brandon A; Kerezoudis, Panagiotis; Porter, Amanda L; Rinaldo, Lorenzo; Murphy, Meghan; Maloney, Patrick; Shepherd, Daniel; Hirshman, Brian R; Carter, Bob S; Lanzino, Giuseppe; Bydon, Mohamad; Meyer, Fredric

2016-07-01

A large national surgical registry was used to establish national benchmarks and associated predictors of major neurologic complications (i.e., coma and stroke) after surgical clipping of unruptured intracranial aneurysms. The American College of Surgeons National Surgical Quality Improvement Program data set between 2007 and 2013 was used for this retrospective cohort analysis. Demographic, comorbidity, and operative characteristics associated with the development of a major neurologic complication (i.e., coma or stroke) were elucidated using a backward selection stepwise logistic regression analysis. This model was subsequently used to fit a predictive score for major neurologic complications. Inclusion criteria were met by 662 patients. Of these patients, 57 (8.61%) developed a major neurologic complication (i.e., coma or stroke) within the 30-day postoperative period. On multivariable analysis, operative time (log odds 0.004 per minute; 95% confidence interval [CI], 0.002-0.007), age (log odds 0.05 per year; 95% CI, 0.02-0.08), history of chronic obstructive pulmonary disease (log odds 1.26; 95% CI, 0.43-2.08), and diabetes (log odds 1.15; 95% CI, 0.38-1.91) were associated with an increased odds of major neurologic complications. When patients were categorized according to quartile of a predictive score generated from the multivariable analysis, rates of major neurologic complications were 1.8%, 4.3%, 6.7%, and 21.2%. Using a large, national multi-institutional cohort, this study established representative national benchmarks and a predictive scoring system for major neurologic complications following operative management of unruptured intracranial aneurysms. The model may assist with risk stratification and tailoring of decision making in surgical candidates. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

PubMed

Liu, Siwei; Molenaar, Peter C M

2014-12-01

This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

A Multivariate Investigation of Employee Absenteeism.

DTIC Science & Technology

1980-05-01

A MULTIVARIATE INVESTIGATION OF EMPLOYEE ABSENTEEISM.(U) MAY 80 J R TERBORG, G A OAVIS, F J SMITH N00014-78"C-0756 UNCLASSIFIED TR-80-5 NL inuuununn...COMPLEX ORGANIZATIONS PROGRAM IN INDUSTRIAL ORGANIZATIONAL PSYCHOLOG C, DEPARTMENT OF PSYCHOLOGY a- UNIVERSITY OF HOUSTON C HOUSTON, TEXAS T7004 C...a-o I *I-- . ’ 4 , ... ,.I .,.- .S 7Jn .jA A Multivariate Investigation of Employee Absenteeism James R. Terborg & Gregory A. Davis University of

Group training programs and self-reported injury risk in female marathoners.

PubMed

Parker, Daniel T; Weitzenberg, Todd W; Amey, Annette L; Nied, Robert J

2011-11-01

To investigate the association of group training program (GTP) participation and other known risk factors with training and intrarace injury rates in female marathoners. Multivariate analysis of a self-reported questionnaire. Nike Women's Marathon, San Francisco, CA. Three hundred seventy-eight female marathoners. Training and intrarace injury rates, severity of these injuries, and satisfaction rates. Participants of GTPs were 2.36 times more likely to experience intrarace injury than non-GTP participants (P = 0.02). Runners with mild and severe injuries in the past 12 months preceding training were 3.54 and 5.08 times more likely to be injured during training (P < 0.0001 and P < 0.0001), respectively, and those with previous severe injury were 6.43 times more likely to experience severe training injury (P < 0.0001). Similarly, the risk for intrarace marathon injury was 3.79 and 7.09 times greater among those with mild and severe injuries during training (P = 0.003 and P < 0.0001), and the risk of severe intrarace injury was 5.63 times greater for those reporting a severe training injury (P < 0.001). Runners with previous marathon experience had a 0.53 risk of severe training injury compared with inexperienced runners (P = 0.04). Participants of GTPs were more likely to be injured during the marathon in multivariate analysis but were also more satisfied with training in bivariate analysis. Female runners with previous injury had a greater risk of future training and race injury, and severe previous injury was associated with severe training and intrarace injury. Previous marathon experience was protective of severe training injury.

Computer program documentation for the patch subsampling processor

NASA Technical Reports Server (NTRS)

Nieves, M. J.; Obrien, S. O.; Oney, J. K. (Principal Investigator)

1981-01-01

The programs presented are intended to provide a way to extract a sample from a full-frame scene and summarize it in a useful way. The sample in each case was chosen to fill a 512-by-512 pixel (sample-by-line) image since this is the largest image that can be displayed on the Integrated Multivariant Data Analysis and Classification System. This sample size provides one megabyte of data for manipulation and storage and contains about 3% of the full-frame data. A patch image processor computes means for 256 32-by-32 pixel squares which constitute the 512-by-512 pixel image. Thus, 256 measurements are available for 8 vegetation indexes over a 100-mile square.

Predictors of retention in community-based methadone maintenance treatment program in Pearl River Delta, China

PubMed Central

2013-01-01

Background The aims were to identify predictors of treatment retention in methadone maintenance treatment (MMT) clinics in Pearl River Delta, China. Methods Retrospective longitudinal study. Participants: 6 MMT clinics in rural and urban area were selected. Statistical analysis: Stratified random sampling was employed, and the data were analyzed using Kaplan-Meier survival curves and life table method. Protective or risk factors were explored using Cox’s proportional hazards model. Independent variables were enrolled in univariate analysis and among which significant variables were analyzed by multivariate analysis. Results A total of 2728 patients were enrolled. The median of the retention duration was 13.63 months, and the cumulative retention rates at 1,2,3 years were 53.0%, 35.0%, 20.0%, respectively. Multivariate Cox analysis showed: age, relationship with family, live on support from family or friends, income, considering treatment cost suitable, considering treatment open time suitable, addiction severity (daily expense for drug), communication with former drug taking peer, living in rural area, daily treatment dosage, sharing needles, re-admission and history of being arrested were predictors for MMT retention. Conclusions MMT retention rate in Guangdong was low and treatment skills and quality should be improved. Meanwhile, participation of family and society should be encouraged. PMID:23497263

Directly observed treatment is associated with reduced default among foreign tuberculosis patients in Thailand.

PubMed

Kapella, B K; Anuwatnonthakate, A; Komsakorn, S; Moolphate, S; Charusuntonsri, P; Limsomboon, P; Wattanaamornkiat, W; Nateniyom, S; Varma, J K

2009-02-01

Thailand's Tuberculosis (TB) Active Surveillance Network in four provinces in Thailand. As treatment default is common in mobile and foreign populations, we evaluated risk factors for default among non-Thai TB patients in Thailand. Observational cohort study using TB program data. Analysis was restricted to patients with an outcome categorized as cured, completed, failure or default. We used multivariate analysis to identify factors associated with default, including propensity score analysis, to adjust for factors associated with receiving directly observed treatment (DOT). During October 2004-September 2006, we recorded data for 14359 TB patients, of whom 995 (7%) were non-Thais. Of the 791 patients analyzed, 313 (40%) defaulted. In multivariate analysis, age>or=45 years (RR 1.47, 95%CI 1.25-1.74), mobility (RR 2.36, 95%CI 1.77-3.14) and lack of DOT (RR 2.29, 95%CI 1.45-3.61) were found to be significantly associated with default among non-Thais. When controlling for propensity to be assigned DOT, the risk of default remained increased in those not assigned DOT (RR 1.99, 95%CI 1.03-3.85). In non-Thai TB patients, DOT was the only modifiable factor associated with default. Using DOT may help improve TB treatment outcomes in non-Thai TB patients.

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0037: Prognosis-Based Control Reconfiguration for an Aircraft with Faulty Actuator to Enable Performance in a Degraded State

DTIC Science & Technology

2010-12-01

computers in 1953. HIL motion simulators were also built for the dynamic testing of vehicle com- ponents (e.g. suspensions, bodies ) with hydraulic or...complex, comprehensive mechanical systems can be simulated in real-time by parallel computers; examples include multi- body sys- tems, brake systems...hard constraints in a multivariable control framework. And the third aspect is the ability to perform online optimization. These aspects results in

Evaluation of 2 whole-brain radiotherapy schedules and prognostic factors for brain metastases in breast cancer patients.

PubMed

Rades, Dirk; Lohynska, Radka; Veninga, Theo; Stalpers, Lukas J A; Schild, Steven E

2007-12-01

The majority of breast cancer patients with brain metastases receive whole-brain radiotherapy (WBRT) and have a survival of only a few months. A short WBRT regimen would be preferable if it provides survival that is similar to that achieved with longer programs. This retrospective study compared survival and local control within the brain resulting from short-course WBRT with longer programs in 207 breast cancer patients. Sixty-nine patients treated with 5 fractions of 4 grays (Gy) each given within 5 days were compared with 138 patients treated with 10 fractions of 3 Gy each given over 2 weeks or 20 fractions of 2 Gy each given over 4 weeks. Six additional potential prognostic factors were investigated: age, Karnofsky performance score (KPS), number of brain metastases, the presence of extracranial metastases, interval from tumor diagnosis to WBRT, and recursive partitioning analysis (RPA) class. On univariate analysis, the WBRT regimen was not found to be associated with survival (P=.254) or local control (P=.397). Improved survival was associated with a KPS>70 (P<.001), single brain metastasis (P=.023), the absence of extracranial metastases (P<.001), and lower RPA class (P<.001). On multivariate analysis, which was performed without RPA class because this is a confounding variable, KPS (relative risk [RR] of 4.00; P<.001) and the presence of extracranial metastases (RR of 1.54; P=.024) maintained statistical significance. On univariate analysis, local control was associated with KPS (P<.001) and RPA class (P<.001). On multivariate analysis, local control was found to be associated with a KPS>70 (RR of 5.75; P<.001). Short-course WBRT with 5 fractions of 4 Gy each resulted in survival and local control that were similar to longer programs in breast cancer patients with brain metastases. The dose of 5 fractions of 4 Gy each appears preferable for the majority of these patients because it is less time consuming and more convenient. Copyright (c) 2007 American Cancer Society.

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

PubMed

Mathew, Boby; Holand, Anna Marie; Koistinen, Petri; Léon, Jens; Sillanpää, Mikko J

2016-02-01

A novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented. Multi-trait genetic parameter estimation is a relevant topic in animal and plant breeding programs because multi-trait analysis can take into account the genetic correlation between different traits and that significantly improves the accuracy of the genetic parameter estimates. Generally, multi-trait analysis is computationally demanding and requires initial estimates of genetic and residual correlations among the traits, while those are difficult to obtain. In this study, we illustrate how to reparametrize covariance matrices of a multivariate animal model/animal models using modified Cholesky decompositions. This reparametrization-based approach is used in the Integrated Nested Laplace Approximation (INLA) methodology to estimate genetic parameters of multivariate animal model. Immediate benefits are: (1) to avoid difficulties of finding good starting values for analysis which can be a problem, for example in Restricted Maximum Likelihood (REML); (2) Bayesian estimation of (co)variance components using INLA is faster to execute than using Markov Chain Monte Carlo (MCMC) especially when realized relationship matrices are dense. The slight drawback is that priors for covariance matrices are assigned for elements of the Cholesky factor but not directly to the covariance matrix elements as in MCMC. Additionally, we illustrate the concordance of the INLA results with the traditional methods like MCMC and REML approaches. We also present results obtained from simulated data sets with replicates and field data in rice.

Inorganic selenium speciation analysis in Allium and Brassica vegetables by ionic liquid assisted liquid-liquid microextraction with multivariate optimization.

PubMed

Castro Grijalba, Alexander; Martinis, Estefanía M; Wuilloud, Rodolfo G

2017-03-15

A highly sensitive vortex assisted liquid-liquid microextraction (VA-LLME) method was developed for inorganic Se [Se(IV) and Se(VI)] speciation analysis in Allium and Brassica vegetables. Trihexyl(tetradecyl)phosphonium decanoate phosphonium ionic liquid (IL) was applied for the extraction of Se(IV)-ammonium pyrrolidine dithiocarbamate (APDC) complex followed by Se determination with electrothermal atomic absorption spectrometry. A complete optimization of the graphite furnace temperature program was developed for accurate determination of Se in the IL-enriched extracts and multivariate statistical optimization was performed to define the conditions for the highest extraction efficiency. Significant factors of IL-VA-LLME method were sample volume, extraction pH, extraction time and APDC concentration. High extraction efficiency (90%), a 100-fold preconcentration factor and a detection limit of 5.0ng/L were achieved. The high sensitivity obtained with preconcentration and the non-chromatographic separation of inorganic Se species in complex matrix samples such as garlic, onion, leek, broccoli and cauliflower, are the main advantages of IL-VA-LLME. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Referral to internal medicine for alcoholism: influence on follow-up care].

PubMed

Avila, P; Marcos, M; Avila, J J; Laso, F J

2008-11-01

The problem of high rates of patient drop-out in alcohol treatment programs is frequently reported in the literature. Our aim was to investigate if internal medicine referral could improve abstinence and retention rates in a cohort of alcoholic patients. A retrospective observational study was conducted comparing 200 alcoholic patients attending a psychiatric unit (group 1) with 100 patients attending both this unit and an internal medicine unit (group 2). We collected sociodemographic and clinical variables and analysed differences regarding abstinence and retention rates by means of univariate and multivariate analysis. At 3 and 12 months follow-up, group 2 patients had higher retention and abstinence rates than group 1 patients. Multivariate analysis including potential confounding variables showed that independent predictors of one-year retention were internal medicine referral and being married. Independent predictors of one-year abstinence were being married, age > 44 years and receipt of drug treatment. The higher retention rate found among patients referred to Internal Medicine specialists, a result that has not been previously reported to the best of our knowledge, emphasizes the importance of a multidisciplinary team approach in the treatment of alcoholism.

Genital Tract Infections, Bacterial Vaginosis, HIV, and Reproductive Health Issues among Lima-Based Clandestine Female Sex Workers

PubMed Central

Perla, M. E.; Ghee, Annette E.; Sánchez, Sixto; McClelland, R. Scott; Fitzpatrick, Annette L.; Suárez-Ognio, Luis; Lama, Javier R.; Sánchez, Jorge

2012-01-01

Sociodemographic and behavioral characteristics of 212 Peruvian female sex workers (FSWs) were analyzed. The association between genital tract infections (GTIs) and risk factors by multivariate analysis was evaluated. Eighty-eight percent of FSWs were diagnosed with at least one GTI (HSV-2 80.1%, BV 44.8%, candidiasis 9.9%, syphilis seropositivity 9.4%, Trichomonas vaginalis 2.4%, HIV seropositivity 2.4%). Reported condom use with clients was nearly universal (98.3%), but infrequent with husband/regular partners (7.3%). In multivariate analysis BV was negatively associated with more consistent condom use (PRR = 0.63, 95% CI, 0.42–0.96). Many had not visited a Sexually Transmitted Infection (STI) clinic or been tested for HIV in the past year (40.6%, 47.1%, resp.). Nonclient contraceptive use was low (57%) and induced abortion was common (68%). High GTI burden and abortions suggest that a services-access gap persists among marginalized FSWs. Continued health outreach programs and integrating family planning and reproductive health services into existing STI clinic services are recommended. PMID:22811592

Harm Reduction Agencies as a Potential Site for Buprenorphine Treatment.

PubMed

Fox, Aaron D; Chamberlain, Adam; Frost, Taeko; Cunningham, Chinazo O

2015-01-01

Harm reduction agencies complement addiction treatment by providing diverse services that improve the health of people who use drugs. Buprenorphine maintenance treatment (BMT) is an effective opioid addiction treatment that may be provided from flexible settings, potentially including harm reduction agencies. This study investigated attitudes toward different potential sites for BMT (harm reduction agencies, general medical clinics, and drug treatment programs) among harm reduction clients. Using computer-based interviews, participants indicated preferred potential site for BMT (harm reduction agency, drug treatment program, or general medical clinic), interest in BMT by potential site, motivation for treatment, and barriers to BMT. Multivariable logistic regression was used to determine factors associated with harm reduction agency preference. Of 102 opioid users, the most preferred potential site for BMT was a harm reduction agency (51%), whereas fewer preferred general medical clinics (13%), drug treatment programs (12%), or were not interested in BMT (25%). In multivariable analysis, experiencing ≥1 barrier to BMT was strongly associated with preferring harm reduction agencies (adjusted odds ratio [aOR] = 3.39, 95% confidence interval [CI]: 1.00-11.43). The potential to initiate BMT at harm reduction agencies is highly favorable among harm reduction clients, especially among those experiencing barriers to BMT. Offering BMT at harm reduction agencies could improve access to treatment, but studies are needed to determine safety and efficacy of this approach.

An Integrated Analysis of the Physiological Effects of Space Flight: Executive Summary

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1985-01-01

A large array of models were applied in a unified manner to solve problems in space flight physiology. Mathematical simulation was used as an alternative way of looking at physiological systems and maximizing the yield from previous space flight experiments. A medical data analysis system was created which consist of an automated data base, a computerized biostatistical and data analysis system, and a set of simulation models of physiological systems. Five basic models were employed: (1) a pulsatile cardiovascular model; (2) a respiratory model; (3) a thermoregulatory model; (4) a circulatory, fluid, and electrolyte balance model; and (5) an erythropoiesis regulatory model. Algorithms were provided to perform routine statistical tests, multivariate analysis, nonlinear regression analysis, and autocorrelation analysis. Special purpose programs were prepared for rank correlation, factor analysis, and the integration of the metabolic balance data.

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP. PMID:29312134

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Quality by design case study: an integrated multivariate approach to drug product and process development.

PubMed

Huang, Jun; Kaul, Goldi; Cai, Chunsheng; Chatlapalli, Ramarao; Hernandez-Abad, Pedro; Ghosh, Krishnendu; Nagi, Arwinder

2009-12-01

To facilitate an in-depth process understanding, and offer opportunities for developing control strategies to ensure product quality, a combination of experimental design, optimization and multivariate techniques was integrated into the process development of a drug product. A process DOE was used to evaluate effects of the design factors on manufacturability and final product CQAs, and establish design space to ensure desired CQAs. Two types of analyses were performed to extract maximal information, DOE effect & response surface analysis and multivariate analysis (PCA and PLS). The DOE effect analysis was used to evaluate the interactions and effects of three design factors (water amount, wet massing time and lubrication time), on response variables (blend flow, compressibility and tablet dissolution). The design space was established by the combined use of DOE, optimization and multivariate analysis to ensure desired CQAs. Multivariate analysis of all variables from the DOE batches was conducted to study relationships between the variables and to evaluate the impact of material attributes/process parameters on manufacturability and final product CQAs. The integrated multivariate approach exemplifies application of QbD principles and tools to drug product and process development.

Assessment of benthic changes during 20 years of monitoring the Mexican Salina Cruz Bay.

PubMed

González-Macías, C; Schifter, I; Lluch-Cota, D B; Méndez-Rodríguez, L; Hernández-Vázquez, S

2009-02-01

In this work a non-parametric multivariate analysis was used to assess the impact of metals and organic compounds in the macro infaunal component of the mollusks benthic community using surface sediment data from several monitoring programs collected over 20 years in Salina Cruz Bay, Mexico. The data for benthic mollusks community characteristics (richness, abundance and diversity) were linked to multivariate environmental patterns, using the Alternating Conditional Expectations method to correlate the biological measurements of the mollusk community with the physicochemical properties of water and sediments. Mollusks community variation is related to environmental characteristics as well as lead content. Surface deposit feeders are increasing their relative density, while subsurface deposit feeders are decreasing with respect to time, these last are expected to be more related with sediment and more affected then by its quality. However gastropods with predatory carnivore as well as chemosymbiotic deposit feeder bivalves have maintained their relative densities along time.

Overview of computational control research at UT Austin

NASA Technical Reports Server (NTRS)

Bong, Wie

1989-01-01

An overview of current research activities at UT Austin is presented to discuss certain technical issues in the following areas: (1) Computer-Aided Nonlinear Control Design: In this project, the describing function method is employed for the nonlinear control analysis and design of a flexible spacecraft equipped with pulse modulated reaction jets. INCA program has been enhanced to allow the numerical calculation of describing functions as well as the nonlinear limit cycle analysis capability in the frequency domain; (2) Robust Linear Quadratic Gaussian (LQG) Compensator Synthesis: Robust control design techniques and software tools are developed for flexible space structures with parameter uncertainty. In particular, an interactive, robust multivariable control design capability is being developed for INCA program; and (3) LQR-Based Autonomous Control System for the Space Station: In this project, real time implementation of LQR-based autonomous control system is investigated for the space station with time-varying inertias and with significant multibody dynamic interactions.

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

ERIC Educational Resources Information Center

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

Socioeconomics and Major Disabilities: Characteristics of Working-Age Adults in Rwanda.

PubMed

Kiregu, Joshua; Murindahabi, Nathalie K; Tumusiime, David; Thomson, Dana R; Hedt-Gauthier, Bethany L; Ahayo, Anita

2016-01-01

Disability affects approximately 15% of the world's population, and has adverse socio-economic effects, especially for the poor. In Rwanda, there are a number of government compensation programs that support the poor, but not specifically persons with disability (PWDs). This study investigates the relationship between poverty and government compensation on disability among working-age adults in Rwanda. This was a secondary analysis of 35,114 adults aged 16 to 65 interviewed in the 2010/2011 Rwanda Household Wealth and Living Conditions survey, a national cross-sectional two-stage cluster survey, stratified by district. This study estimated self-reported major disability, and used chi-square tests to estimate associations (p<0.1) with income, government compensation, occupation type, participation in public works programs, and household poverty status. Non-collinear economic variables were included in a multivariate logistic regression, along with socio-demographic confounders that modified the relationship between any economic predictor and the outcome by 10% or more. All analyses adjusted for sampling weights, stratification, and clustering of households. Over 4% of working-age adults reported having a major disability and the most prevalent types of disability in order were physical, mental, and then sensory disability. In bivariate analysis, annual income, occupation type, and poverty status were associated with major disability (p<0.001 for all). Occupation type was dropped because it was collinear with income. Age, education, and urban/rural residence were confounders. In the multivariate analysis, adults in all income groups had about half the odds of disability compared to adults with no income (Rwf1-120,000 OR = 0.57; Rwf120,000-250,000 OR = 0.61; Rwf250,000-1,000,000 OR = 0.59; Rwf1,000,000+ OR = 0.66; p<0.05 for all), and non-poor adults had 0.77 the odds of disability compared to poor adults (p = 0.001). Given that personal income rather than government programming is associated with disability in Rwanda, we recommend deliberately targeted services to those with disability via cash transfers, placements in disability-appropriate employment, and micro-savings programs.

Socioeconomics and Major Disabilities: Characteristics of Working-Age Adults in Rwanda

PubMed Central

Kiregu, Joshua; Murindahabi, Nathalie K.; Tumusiime, David; Thomson, Dana R.; Hedt-Gauthier, Bethany L.; Ahayo, Anita

2016-01-01

Background Disability affects approximately 15% of the world’s population, and has adverse socio-economic effects, especially for the poor. In Rwanda, there are a number of government compensation programs that support the poor, but not specifically persons with disability (PWDs). This study investigates the relationship between poverty and government compensation on disability among working-age adults in Rwanda. Methods This was a secondary analysis of 35,114 adults aged 16 to 65 interviewed in the 2010/2011 Rwanda Household Wealth and Living Conditions survey, a national cross-sectional two-stage cluster survey, stratified by district. This study estimated self-reported major disability, and used chi-square tests to estimate associations (p<0.1) with income, government compensation, occupation type, participation in public works programs, and household poverty status. Non-collinear economic variables were included in a multivariate logistic regression, along with socio-demographic confounders that modified the relationship between any economic predictor and the outcome by 10% or more. All analyses adjusted for sampling weights, stratification, and clustering of households. Results Over 4% of working-age adults reported having a major disability and the most prevalent types of disability in order were physical, mental, and then sensory disability. In bivariate analysis, annual income, occupation type, and poverty status were associated with major disability (p<0.001 for all). Occupation type was dropped because it was collinear with income. Age, education, and urban/rural residence were confounders. In the multivariate analysis, adults in all income groups had about half the odds of disability compared to adults with no income (Rwf1-120,000 OR = 0.57; Rwf120,000–250,000 OR = 0.61; Rwf250,000–1,000,000 OR = 0.59; Rwf1,000,000+ OR = 0.66; p<0.05 for all), and non-poor adults had 0.77 the odds of disability compared to poor adults (p = 0.001). Conclusion Given that personal income rather than government programming is associated with disability in Rwanda, we recommend deliberately targeted services to those with disability via cash transfers, placements in disability-appropriate employment, and micro-savings programs. PMID:27101377

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

Synergism in work site adoption of employee assistance programs and health promotion activities.

PubMed

Blum, T C; Roman, P M; Patrick, L

1990-05-01

As workplaces increasingly adopt proactive programs directed toward employee health issues, the interrelation between different programs becomes an important issue. Of interest here is the "synergy" in patterns of program adoption between employee assistance programs (EAPs) and health promotion activities (HPAs). We utilize the 1985 National Survey of Worksite Health Promotion Activities (N = 1358) for analyses of the dual presence of EAPs and HPAs, and in multivariate analyses we consider factors affecting such dual presence. The data suggest that synergy occurs, with EAP adoption appearing to influence HPA adoption to a greater extent than the reverse. In multivariate analyses, synergy is confirmed by the finding that, among a variety of relevant organizational characteristics, EAP presence and HPA presence are the best predictors of each other's presence. The analyses also indicate that there is minimal commonality in program ingredients across organizations reporting the presence of HPAs. Implications of the data for the future development of these two programming strategies are discussed.

Compensator improvement for multivariable control systems

NASA Technical Reports Server (NTRS)

Mitchell, J. R.; Mcdaniel, W. L., Jr.; Gresham, L. L.

1977-01-01

A theory and the associated numerical technique are developed for an iterative design improvement of the compensation for linear, time-invariant control systems with multiple inputs and multiple outputs. A strict constraint algorithm is used in obtaining a solution of the specified constraints of the control design. The result of the research effort is the multiple input, multiple output Compensator Improvement Program (CIP). The objective of the Compensator Improvement Program is to modify in an iterative manner the free parameters of the dynamic compensation matrix so that the system satisfies frequency domain specifications. In this exposition, the underlying principles of the multivariable CIP algorithm are presented and the practical utility of the program is illustrated with space vehicle related examples.

A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Watts, Stephen R.

1995-01-01

This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.

Men and women show similar survival outcome in stage IV breast cancer.

PubMed

Wu, San-Gang; Zhang, Wen-Wen; Liao, Xu-Lin; Sun, Jia-Yuan; Li, Feng-Yan; Su, Jing-Jun; He, Zhen-Yu

2017-08-01

To evaluate the clinicopathological features, patterns of distant metastases, and survival outcome between stage IV male breast cancer (MBC) and female breast cancer (FBC). Patients diagnosed with stage IV MBC and FBC between 2010 and 2013 were included using the Surveillance, Epidemiology, and End Results program. Univariate and multivariate Cox regression analyses were used to analyze risk factors for overall survival (OS). A total of 4997 patients were identified, including 60 MBC and 4937 FBC. Compared with FBC, patients with MBC were associated with a significantly higher rate of estrogen receptor-positive, progesterone receptor-positive, unmarried, lung metastases, and a lower frequency of liver metastases. Univariate and multivariate analyses showed no significant difference in OS between MBC and FBC. In the propensity score-matched population, there was also no difference in survival between MBC and FBC. Multivariate analysis of MBC showed that OS was longer for patients aged 50-69 years and with estrogen receptor-positive disease. There was no significant difference in survival outcome between stage IV MBC and FBC, but significant differences in clinicopathological features and patterns of metastases between the genders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Factors contributing to attrition behavior in diabetes self-management programs: A mixed method approach

PubMed Central

Gucciardi, Enza; DeMelo, Margaret; Offenheim, Ana; Stewart, Donna E

2008-01-01

Background Diabetes self-management education is a critical component in diabetes care. Despite worldwide efforts to develop efficacious DSME programs, high attrition rates are often reported in clinical practice. The objective of this study was to examine factors that may contribute to attrition behavior in diabetes self-management programs. Methods We conducted telephone interviews with individuals who had Type 2 diabetes (n = 267) and attended a diabetes education centre. Multivariable logistic regression was performed to identify factors associated with attrition behavior. Forty-four percent of participants (n = 118) withdrew prematurely from the program and were asked an open-ended question regarding their discontinuation of services. We used content analysis to code and generate themes, which were then organized under the Behavioral Model of Health Service Utilization. Results Working full and part-time, being over 65 years of age, having a regular primary care physician or fewer diabetes symptoms were contributing factors to attrition behaviour in our multivariable logistic regression. The most common reasons given by participants for attrition from the program were conflict between their work schedules and the centre's hours of operation, patients' confidence in their own knowledge and ability when managing their diabetes, apathy towards diabetes education, distance to the centre, forgetfulness, regular physician consultation, low perceived seriousness of diabetes, and lack of familiarity with the centre and its services. There was considerable overlap between our quantitative and qualitative results. Conclusion Reducing attrition behaviour requires a range of strategies targeted towards delivering convenient and accessible services, familiarizing individuals with these services, increasing communication between centres and their patients, and creating better partnerships between centres and primary care physicians. PMID:18248673

Impact of academic facility type and volume on post-surgical outcomes following diagnosis of glioblastoma.

PubMed

Hauser, Alan; Dutta, Sunil W; Showalter, Timothy N; Sheehan, Jason P; Grover, Surbhi; Trifiletti, Daniel M

2018-01-01

To identify if facility type and/or facility volume impact overall survival (OS) following diagnosis of glioblastoma (GBM). We also sought to compare early post-surgical outcomes based on these factors. The National Cancer Database was queried for patients with GBM diagnosed from 2004 to 2013 with known survival. Patients were grouped based on facility type and facility volume. Multivariable analyses were performed to investigate factors associated OS following diagnosis and Chi-square tests were used to compare early post-surgical outcomes. 89,839 patients met inclusion criteria. Factors associated with improved OS on multivariable analysis included younger patient age, female gender, race, lower comorbidity score, higher performance score, smaller tumor size, unifocal tumors, MGMT hypermethylation, fully resected tumors, radiotherapy, and chemotherapy (each p < .001). Also, OS was improved among patients treated at centers averaging at least 30.2 cases per year (HR 0.948, compared to <7.4 cases/year, p < .001), and patients treated at Academic/Research programs had improved survival compared to those treated at Comprehensive Community Cancer programs (HR 1.069, p < .001) and Integrated Network Cancer programs (HR 1.126, p < .001). Similarly, Academic/Research programs and high volume centers demonstrated improved 30- and 90-day morality as well as 30-day readmission rates (p < .001). This study suggests that patients treated in Academic/Research programs and high patient-volume centers have increased survival and more favorable early-postsurgical outcomes. The extent to which differences in patient populations, socioeconomic factors, and/or provider expertise play into this cause will be areas of future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Location and organizational features: what type of veteran communities participate in health programs?

PubMed

Patterson, Leslie; McGinley, Emily; Ertl, Kristyn; Morzinski, Jeffrey; Fyfe, Robert; Whittle, Jeff

2012-01-01

Research shows that community-based membership organizations are effective partners in health promotion activities; however, most community organizations do not participate in such partnerships. There is little research regarding the geographical and organizational characteristics associated with participation. We examined the factors associated with community-based veterans service organization (VSO) units' decision to participate in a health promotion project. We collected location and organizational characteristics regarding 218 VSO units asked to participate in POWER, a partnership to improve hypertension self-management skills between the Medical College of Wisconsin, the Milwaukee Veterans Affairs Medical Center (VAMC) and Wisconsin branches of the American Legion, Veterans of Foreign Wars (VFW), Vietnam Veterans of America, and National Association of Black Veterans. We tested the association of these characteristics with participation using chi-square and Fisher's exact tests for categorical variables, and analysis of variance and the Kruskal-Wallis test for continuous variables. We used multivariable logistic regression to identify factors independently associated with participation. In bivariable analyses, likelihood of participation was positively associated with increasing membership (p < .001), meeting attendance (p < .001), publication of an organizational newsletter (p < .001), presence of a women's auxiliary (p = .02), and location within 44 miles of the VAMC (p = .047). On multivariable analysis, only meeting attendance and census tract-level educational attainment predicted participation. Greater membership sizes, meeting attendance, and more group resources might be important factors for researchers to consider when initiating community-based health and wellness programs.

Prevalence and Predictors of Mental Health Programming Among U.S. Religious Congregations.

PubMed

Wong, Eunice C; Fulton, Brad R; Derose, Kathryn P

2018-02-01

This study assessed the prevalence of and factors associated with congregation-based programming in support of people with mental illness. To estimate the proportion of congregations that provide mental health programming, this study reports analyses of survey responses from the 2012 National Congregations Study, a nationally representative survey of religious congregations in the United States (N=1,327). The analysis used multivariate logistic regression to identify congregational characteristics associated with the provision of mental health programming. Nearly one in four U.S. congregations (23%) provided some type of programming to support people with mental illness. Approximately 31% of all attendees belonged to a congregation that provided mental health programming. Congregational characteristics associated with providing mental health programming included having more members and having members with higher incomes, employing staff for social service programs, and providing health-focused programs. Other significant predictors included engaging with the surrounding community (that is, conducting community needs assessments and hosting speakers from social service organizations) and being located in a predominantly African-American community. Greater coordination between mental health providers and congregations with programs that support people with mental illness could foster more integrated and holistic care, which in turn may lead to improved recovery outcomes.

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2015-01-01

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Medicare Payment Penalties and Safety Net Hospital Profitability: Minimal Impact on These Vulnerable Hospitals.

PubMed

Bazzoli, Gloria J; Thompson, Michael P; Waters, Teresa M

2018-02-08

To examine relationships between penalties assessed by Medicare's Hospital Readmission Reduction Program and Value-Based Purchasing Program and hospital financial condition. Centers for Medicare and Medicaid Services, American Hospital Association, and Area Health Resource File data for 4,824 hospital-year observations. Bivariate and multivariate analysis of pooled cross-sectional data. Safety net hospitals have significantly higher HRRP/VBP penalties, but, unlike nonsafety net hospitals, increases in their penalty rate did not significantly affect their total margins. Safety net hospitals appear to rely on nonpatient care revenues to offset higher penalties for the years studied. While reassuring, these funding streams are volatile and may not be able to compensate for cumulative losses over time. © Health Research and Educational Trust.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

Individual and socioeconomic factors associated with childhood immunization coverage in Nigeria

PubMed Central

Oleribe, Obinna; Kumar, Vibha; Awosika-Olumo, Adebowale; Taylor-Robinson, Simon David

2017-01-01

Introduction Immunization is the world’s most successful and cost-effective public health intervention as it prevents over 2 million deaths annually. However, over 2 million deaths still occur yearly from Vaccine preventable diseases, the majority of which occur in sub-Saharan Africa. Nigeria is a major contributor of global childhood deaths from VPDs. Till date, Nigeria still has wild polio virus in circulation. The objective of this study was to identify the individual and socioeconomic factors associated with immunization coverage in Nigeria through a secondary dataset analysis of Nigeria Demographic and Health Survey (NDHS), 2013. Methods A quantitative analysis of the 2013 NDHS dataset was performed. Ethical approvals were obtained from Walden University IRB and the National Health Research Ethics Committee of Nigeria. The dataset was downloaded, validated for completeness and analyzed using univariate, bivariate and multivariate statistics. Results Of 27,571 children aged 0 to 59 months, 22.1% had full vaccination, and 29% never received any vaccination. Immunization coverage was significantly associated with childbirth order, delivery place, child number, and presence or absence of a child health card. Maternal age, geographical location, education, religion, literacy, wealth index, marital status, and occupation were significantly associated with immunization coverage. Paternal education, occupation, and age were also significantly associated with coverage. Respondent's age, educational attainment and wealth index remained significantly related to immunization coverage at 95% confidence interval in multivariate analysis. Conclusion The study highlights child, parental and socioeconomic barriers to successful immunization programs in Nigeria. These findings need urgent attention, given the re-emergence of wild poliovirus in Nigeria. An effective, efficient, sustainable, accessible, and acceptable immunization program for children should be designed, developed and undertaken in Nigeria with adequate strategies put in place to implement them. PMID:28690734

Individual and socioeconomic factors associated with childhood immunization coverage in Nigeria.

PubMed

Oleribe, Obinna; Kumar, Vibha; Awosika-Olumo, Adebowale; Taylor-Robinson, Simon David

2017-01-01

Immunization is the world's most successful and cost-effective public health intervention as it prevents over 2 million deaths annually. However, over 2 million deaths still occur yearly from Vaccine preventable diseases, the majority of which occur in sub-Saharan Africa. Nigeria is a major contributor of global childhood deaths from VPDs. Till date, Nigeria still has wild polio virus in circulation. The objective of this study was to identify the individual and socioeconomic factors associated with immunization coverage in Nigeria through a secondary dataset analysis of Nigeria Demographic and Health Survey (NDHS), 2013. A quantitative analysis of the 2013 NDHS dataset was performed. Ethical approvals were obtained from Walden University IRB and the National Health Research Ethics Committee of Nigeria. The dataset was downloaded, validated for completeness and analyzed using univariate, bivariate and multivariate statistics. Of 27,571 children aged 0 to 59 months, 22.1% had full vaccination, and 29% never received any vaccination. Immunization coverage was significantly associated with childbirth order, delivery place, child number, and presence or absence of a child health card. Maternal age, geographical location, education, religion, literacy, wealth index, marital status, and occupation were significantly associated with immunization coverage. Paternal education, occupation, and age were also significantly associated with coverage. Respondent's age, educational attainment and wealth index remained significantly related to immunization coverage at 95% confidence interval in multivariate analysis. The study highlights child, parental and socioeconomic barriers to successful immunization programs in Nigeria. These findings need urgent attention, given the re-emergence of wild poliovirus in Nigeria. An effective, efficient, sustainable, accessible, and acceptable immunization program for children should be designed, developed and undertaken in Nigeria with adequate strategies put in place to implement them.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

Anger Expression Types and Interpersonal Problems in Nurses.

PubMed

Han, Aekyung; Won, Jongsoon; Kim, Oksoo; Lee, Sang E

2015-06-01

The purpose of this study was to investigate the anger expression types in nurses and to analyze the differences between the anger expression types and interpersonal problems. The data were collected from 149 nurses working in general hospitals with 300 beds or more in Seoul or Gyeonggi province, Korea. For anger expression type, the anger expression scale from the Korean State-Trait Anger Expression Inventory was used. For interpersonal problems, the short form of the Korean Inventory of Interpersonal Problems Circumplex Scales was used. Data were analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance, and Duncan's multiple comparisons test. Three anger expression types in nurses were found: low-anger expression, anger-in, and anger-in/control type. From the results of multivariate analysis of variance, there were significant differences between anger expression types and interpersonal problems (Wilks lambda F = 3.52, p < .001). Additionally, anger-in/control type was found to have the most difficulty with interpersonal problems by Duncan's post hoc test (p < .050). Based on this research, the development of an anger expression intervention program for nurses is recommended to establish the means of expressing the suppressed emotions, which would help the nurses experience less interpersonal problems. Copyright © 2015. Published by Elsevier B.V.

Health education programs may be as effective as exercise intervention on improving health-related quality of life among Japanese people over 65 years.

PubMed

Tamari, Kotaro; Kawamura, Kenji; Sato, Mitsuya; Harada, Kazuhiro

2012-09-01

The current study was aimed to examine the short-term effects of a 3-month health education program on health-related quality of life using the Short-Form 36. Twenty-five Japanese older people aged 65 and older in the health education program were compared with two historical control groups (n = 25 each) undertaking group and resistance exercise interventions and matched by age, sex and body mass index. A series of split-design two-way analyses of variance were conducted for data analysis. Significant improvements were observed in general health and vitality subscales of the Short-Form 36 in the educational program group. Multivariate analyses, adjusted for several confounding factors, revealed that the effects of the three programs were comparable. The findings suggest that a structured 3-month educational program may be as effective as exercise interventions in improving general health and vitality in a community-dwelling Japanese older population. © 2011 The Authors. Australasian Journal on Ageing © 2011 ACOTA.

Concomitant Mediastinoscopy Increases the Risk of Postoperative Pneumonia After Pulmonary Lobectomy.

PubMed

Yendamuri, Sai; Battoo, Athar; Attwood, Kris; Dhillon, Samjot Singh; Dy, Grace K; Hennon, Mark; Picone, Anthony; Nwogu, Chukwumere; Demmy, Todd; Dexter, Elisabeth

2018-05-01

Mediastinoscopy is considered the gold standard for preresectional staging of lung cancer. We sought to examine the effect of concomitant mediastinoscopy on postoperative pneumonia (POP) in patients undergoing lobectomy. All patients in our institutional database (2008-2015) undergoing lobectomy who did not receive neoadjuvant therapy were included in our study. The relationship between mediastinoscopy and POP was examined using univariate (Chi square) and multivariate analyses (binary logistic regression). In order to validate our institutional findings, lobectomy data in the National Surgical Quality Improvement Program (NSQIP) from 2005 to 2014 were analyzed for these associations. Of 810 patients who underwent a lobectomy at our institution, 741 (91.5%) surgeries were performed by video-assisted thoracic surgery (VATS) and 487 (60.1%) patients underwent concomitant mediastinoscopy. Univariate analysis demonstrated an association between mediastinoscopy and POP in patients undergoing VATS [odds ratio (OR) 1.80; p = 0.003], but not open lobectomy. Multivariate analysis retained mediastinoscopy as a variable, although the relationship showed only a trend (OR 1.64; p = 0.1). In the NSQIP cohort (N = 12,562), concomitant mediastinoscopy was performed in 9.0% of patients, with 44.5% of all the lobectomies performed by VATS. Mediastinoscopy was associated with POP in patients having both open (OR1.69; p < 0.001) and VATS lobectomy (OR 1.72; p = 0.002). This effect remained in multivariate analysis in both the open and VATS lobectomy groups (OR 1.46, p = 0.003; and 1.53, p = 0.02, respectively). Mediastinoscopy may be associated with an increased risk of POP after pulmonary lobectomy. This observation should be examined in other datasets as it potentially impacts preresectional staging algorithms for patients with lung cancer.

Fast-NPS-A Markov Chain Monte Carlo-based analysis tool to obtain structural information from single-molecule FRET measurements

NASA Astrophysics Data System (ADS)

Eilert, Tobias; Beckers, Maximilian; Drechsler, Florian; Michaelis, Jens

2017-10-01

The analysis tool and software package Fast-NPS can be used to analyse smFRET data to obtain quantitative structural information about macromolecules in their natural environment. In the algorithm a Bayesian model gives rise to a multivariate probability distribution describing the uncertainty of the structure determination. Since Fast-NPS aims to be an easy-to-use general-purpose analysis tool for a large variety of smFRET networks, we established an MCMC based sampling engine that approximates the target distribution and requires no parameter specification by the user at all. For an efficient local exploration we automatically adapt the multivariate proposal kernel according to the shape of the target distribution. In order to handle multimodality, the sampler is equipped with a parallel tempering scheme that is fully adaptive with respect to temperature spacing and number of chains. Since the molecular surrounding of a dye molecule affects its spatial mobility and thus the smFRET efficiency, we introduce dye models which can be selected for every dye molecule individually. These models allow the user to represent the smFRET network in great detail leading to an increased localisation precision. Finally, a tool to validate the chosen model combination is provided. Programme Files doi:http://dx.doi.org/10.17632/7ztzj63r68.1 Licencing provisions: Apache-2.0 Programming language: GUI in MATLAB (The MathWorks) and the core sampling engine in C++ Nature of problem: Sampling of highly diverse multivariate probability distributions in order to solve for macromolecular structures from smFRET data. Solution method: MCMC algorithm with fully adaptive proposal kernel and parallel tempering scheme.

Single Marital Status and Infectious Mortality in Women With Cervical Cancer in the United States.

PubMed

Machida, Hiroko; Eckhardt, Sarah E; Castaneda, Antonio V; Blake, Erin A; Pham, Huyen Q; Roman, Lynda D; Matsuo, Koji

2017-10-01

Unmarried status including single marital status is associated with increased mortality in women bearing malignancy. Infectious disease weights a significant proportion of mortality in patients with malignancy. Here, we examined an association of single marital status and infectious mortality in cervical cancer. This is a retrospective observational study examining 86,555 women with invasive cervical cancer identified in the Surveillance, Epidemiology, and End Results Program between 1973 and 2013. Characteristics of 18,324 single women were compared with 38,713 married women in multivariable binary logistic regression models. Propensity score matching was performed to examine cumulative risk of all-cause and infectious mortality between the 2 groups. Single marital status was significantly associated with young age, black/Hispanic ethnicity, Western US residents, uninsured status, high-grade tumor, squamous histology, and advanced-stage disease on multivariable analysis (all, P < 0.05). In a prematched model, single marital status was significantly associated with increased cumulative risk of all-cause mortality (5-year rate: 32.9% vs 29.7%, P < 0.001) and infectious mortality (0.5% vs 0.3%, P < 0.001) compared with the married status. After propensity score matching, single marital status remained an independent prognostic factor for increased cumulative risk of all-cause mortality (adjusted hazards ratio [HR], 1.15; 95% confidence interval [CI], 1.11-1.20; P < 0.001) and those of infectious mortality on multivariable analysis (adjusted HR, 1.71; 95% CI, 1.27-2.32; P < 0.001). In a sensitivity analysis for stage I disease, single marital status remained significantly increased risk of infectious mortality after propensity score matching (adjusted HR, 2.24; 95% CI, 1.34-3.73; P = 0.002). Single marital status was associated with increased infectious mortality in women with invasive cervical cancer.

Association between thoracic aortic disease and inguinal hernia.

PubMed

Olsson, Christian; Eriksson, Per; Franco-Cereceda, Anders

2014-08-21

The study hypothesis was that thoracic aortic disease (TAD) is associated with a higher-than-expected prevalence of inguinal hernia. Such an association has been reported for abdominal aortic aneurysm (AAA) and hernia. Unlike AAA, TAD is not necessarily detectable with clinical examination or ultrasound, and there are no population-based screening programs for TAD. Therefore, conditions associated with TAD, such as inguinal hernia, are of particular clinical relevance. The prevalence of inguinal hernia in subjects with TAD was determined from nation-wide register data and compared to a non-TAD group (patients with isolated aortic stenosis). Groups were balanced using propensity score matching. Multivariable statistical analysis (logistic regression) was performed to identify variables independently associated with hernia. Hernia prevalence was 110 of 750 (15%) in subjects with TAD versus 29 of 301 (9.6%) in non-TAD, P=0.03. This statistically significant difference remained after propensity score matching: 21 of 159 (13%) in TAD versus 14 of 159 (8.9%) in non-TAD, P<0.001. Variables independently associated with hernia in multivariable analysis were male sex (odds ratio [OR] with 95% confidence interval [95% CI]) 3.4 (2.1 to 5.4), P<0.001; increased age, OR 1.02/year (1.004 to 1.04), P=0.014; and TAD, OR 1.8 (1.1 to 2.8), P=0.015. The prevalence of inguinal hernia (15%) in TAD is higher than expected in a general population and higher in TAD, compared to non-TAD. TAD is independently associated with hernia in multivariable analysis. Presence or history of hernia may be of importance in detecting TAD, and the association warrants further study. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

The Potential of Multivariate Analysis in Assessing Students' Attitude to Curriculum Subjects

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…

Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects.

PubMed

Thulin, M

2016-09-10

Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

Syringe Disposal Among Injection Drug Users in San Francisco

PubMed Central

Martinez, Alexis N.; Carpenter, Lisa; Geckeler, Dara; Colfax, Grant; Kral, Alex H.

2011-01-01

To assess the prevalence of improperly discarded syringes and to examine syringe disposal practices of injection drug users (IDUs) in San Francisco, we visually inspected 1000 random city blocks and conducted a survey of 602 IDUs. We found 20 syringes on the streets we inspected. IDUs reported disposing of 13% of syringes improperly. In multivariate analysis, obtaining syringes from syringe exchange programs was found to be protective against improper disposal, and injecting in public places was predictive of improper disposal. Few syringes posed a public health threat. PMID:20466956

Factors influencing infant/child mortality in Bangladesh: implication for family planning programs and policies.

PubMed

Miah, M M

1993-01-01

"This study examined a host of socio-economic and demographic factors (including their interactions) that determine infant/child mortality of married women at the different parity levels in Bangladesh [using data from] a multivariate analysis of the 1975-76 Bangladesh Fertility Survey.... The major hypothesis of this research is that the higher the level of fertility of a married woman, the higher will be her experience of infant/child mortality. However, a woman's family planning practice may interact with fertility and affect the total infant/child deaths...." excerpt

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sole, Claudio V., E-mail: cvsole@uc.cl; School of Medicine, Complutense University, Madrid; Service of Radiation Oncology, Instituto de Radiomedicina, Santiago

Purpose: To perform a joint analysis of data from 3 contributing centers within the intraoperative electron-beam radiation therapy (IOERT)-Spanish program, to determine the potential of IOERT as an anticipated boost before external beam radiation therapy in the multidisciplinary treatment of pediatric extremity soft-tissue sarcomas. Methods and Materials: From June 1993 to May 2013, 62 patients (aged <21 years) with a histologic diagnosis of primary extremity soft-tissue sarcoma with absence of distant metastases, undergoing limb-sparing grossly resected surgery, external beam radiation therapy (median dose 40 Gy) and IOERT (median dose 10 Gy) were considered eligible for this analysis. Results: After a median follow-up ofmore » 66 months (range, 4-235 months), 10-year local control, disease-free survival, and overall survival was 85%, 76%, and 81%, respectively. In multivariate analysis after adjustment for other covariates, tumor size >5 cm (P=.04) and R1 margin status (P=.04) remained significantly associated with local relapse. In regard to overall survival only margin status (P=.04) retained association on multivariate analysis. Ten patients (16%) reported severe chronic toxicity events (all grade 3). Conclusions: An anticipated IOERT boost allowed for external beam radiation therapy dose reduction, with high local control and acceptably low toxicity rates. The combined radiosurgical approach needs to be tested in a prospective trial to confirm these results.« less

F100 Multivariable Control Synthesis Program. Computer Implementation of the F100 Multivariable Control Algorithm

NASA Technical Reports Server (NTRS)

Soeder, J. F.

1983-01-01

As turbofan engines become more complex, the development of controls necessitate the use of multivariable control techniques. A control developed for the F100-PW-100(3) turbofan engine by using linear quadratic regulator theory and other modern multivariable control synthesis techniques is described. The assembly language implementation of this control on an SEL 810B minicomputer is described. This implementation was then evaluated by using a real-time hybrid simulation of the engine. The control software was modified to run with a real engine. These modifications, in the form of sensor and actuator failure checks and control executive sequencing, are discussed. Finally recommendations for control software implementations are presented.

Effect of simultaneous model observation and self-modeling of volleyball skill acquisition.

PubMed

Barzouka, Karolina; Bergeles, Nikolaos; Hatziharistos, Dimitris

2007-02-01

This study examined the effect of feedback with simultaneous skilled model observation and self-modeling on volleyball skill acquisition. 53 pupils 12 to 15 years old formed two experimental groups and one control group who followed an intervention program with 12 practice sessions for acquisition and retention of how to receive a ball. Groups received different types of feedback before and in the middle of each practice session. Reception performance outcome (score) and technique in every group were assessed before and at the end of the intervention program and during the retention phase. A 3 (Group) x 3 (Measurement Period) multivariate analysis of variance with repeated measures was applied to investigate differences. Results showed equivalent improvement in all three groups at the end of the intervention program. In conclusion, types of augmented feedback from the physical education teacher are effective in acquisition and retention of the skill for reception in volleyball.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

Multivariable control altitude demonstration on the F100 turbofan engine

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Dehoff, R. L.; Hackney, R. D.

1979-01-01

The F100 Multivariable control synthesis (MVCS) program, was aimed at demonstrating the benefits of LGR synthesis theory in the design of a multivariable engine control system for operation throughout the flight envelope. The advantages of such procedures include: (1) enhanced performance from cross-coupled controls, (2) maximum use of engine variable geometry, and (3) a systematic design procedure that can be applied efficiently to new engine systems. The control system designed, under the MVCS program, for the Pratt & Whitney F100 turbofan engine is described. Basic components of the control include: (1) a reference value generator for deriving a desired equilibrium state and an approximate control vector, (2) a transition model to produce compatible reference point trajectories during gross transients, (3) gain schedules for producing feedback terms appropriate to the flight condition, and (4) integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance.

Scientific and Engineering Studies; Spectral Estimation.

DTIC Science & Technology

1977-01-01

Approved for public release; distribution unlimited. TD 5419 FORTRAN PROGRAM FOR MULTIVARIATE LINEAR PREDICTIVE SPECTRAL ANALYSIS, EMPLOYING FORWARD...Time Series Analysis Symposium, Tulsa, Oklahoma, 14-15 May 1976. 1/2 REVERSE BLANK TD 541.9 0. Z o 0 zx .3 z a Z 9-. LU. u ~ .v C3. 4c U -4 :0 z -󈧈...0 XZ a Z a.a- :2n 3 TD 5419 4A 0 -. .4 z LL - LL LA. I-. D z q uiL L" LA.. wa Q W w i0 c x -Al 2 0 w x41 Is -4 x . I. x .f < I It I- - -4 U 4 -41-C4

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Assessing Reliability of Student Ratings of Advisor: A Comparison of Univariate and Multivariate Generalizability Approaches.

ERIC Educational Resources Information Center

Sun, Anji; Valiga, Michael J.

In this study, the reliability of the American College Testing (ACT) Program's "Survey of Academic Advising" (SAA) was examined using both univariate and multivariate generalizability theory approaches. The primary purpose of the study was to compare the results of three generalizability theory models (a random univariate model, a mixed…

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

Medical cost savings for participants and nonparticipants in health risk assessments, lifestyle management, disease management, depression management, and nurseline in a large financial services corporation.

PubMed

Serxner, Seth; Alberti, Angela; Weinberger, Sarah

2012-01-01

To compare changes in medical costs between participants and nonparticipants in five different health and productivity management (HPM) programs. Quasi-experimental pre/post intervention study. A large financial services corporation. A cohort population of employees enrolled in medical plans (n  =  49,723) [corrected]. A comprehensive HPM program, which addressed health risks, acute and chronic conditions, and psychosocial disorders from 2005 to 2007. Incentives were used to encourage health risk assessment participation in years 2 and 3. Program participation and medical claims data were collected for members at the end of each program year to assess the change in total costs from the baseline period. Analysis . Multivariate analyses for participation categories were conducted comparing baseline versus program year cost differences, controlling for demographics. All participation categories yielded a lower cost increase compared to nonparticipation and a positive return on investment (ROI) for years 2 and 3, resulting in a 2.45∶1 ROI for the combined program years. Medical cost savings exceeded program costs in a wide variety of health and productivity management programs by the second year.

Registered Nurse to Bachelor of Science in Nursing: nesting a fast-track to traditional generic program, teachings from nursing education in Burkina Faso.

PubMed

Beogo, Idrissa; Liu, Chieh-Yu; Dlamini, Colile P; Gagnon, Marie-Pierre

2015-01-01

Nursing education has evolved over time to fit societies' increasing care needs. Innovations in nursing education draw thorny debates on potential jeopardy in the quality, safety, and efficacy of nurse graduates. Accelerated nursing education programs have been among landmark strategic changes to address the persistent bedside nurse shortage. Despite the dearth of empirical studies in sub-Saharan Africa (SSA), the National School of Public Health of Burkina Faso has developed a State Diploma Nursing (SDN) fast-track program. With innovative features, the program is nested into the traditional SDN program. This study investigates preliminary outcomes of the implemented policy using the initial cohort that went through the program. Comparison of the traditional generic program and the fast-track one is drawn to inform nursing education policy. The study was conducted in the three campuses delivering the SDN program. Data collected from a representative sample included 255 students from the 2006-2009 cohort, after concluding the program. Surveyed students were assessed according to the program entry status. Outcomes were measured using students' academic performance. Besides descriptive analysis, bivariate t-test, F-test, and multivariate ordinary least square regression (OLSR) were employed to determine the comparative pattern between the traditional generic and the newly nested fast-track program. Students' varied statuses (private pre-registration, state pre-registration, private post-registration, and state post-registration) were kept to better outline the findings trend. A fifth (19.6 %) of surveyed students were enrolled in the fast-track stream from which, one third (33.7 %) consisted of post-registered students. Fast-track students comparatively achieved the best academic performance (mean: 73.68/100, SD: 5.52). Multivariate OLSR confirmed that fast-track students performed better (β: 5.559, p < 0.001), and further informed differences between campuses. Students entry status also displayed significant differences, yet the academic performance of post-registered students from traditional generic versus fast-track was similar (p = 0.409). Findings suggest that fast-track program students performed better than the ones from the traditional generic program. The uniqueness and success of this mixed nursing program experience sheds light for nursing educators engaged in policy making. The study results can serve as a crucial foundation for policymakers to alleviate the nurse shortage in SSA.

Impact of the University of California, Los Angeles/Charles R. Drew University Medical Education Program on medical students' intentions to practice in underserved areas.

PubMed

Ko, Michelle; Edelstein, Ronald A; Heslin, Kevin C; Rajagopalan, Shobita; Wilkerson, Luann; Colburn, Lois; Grumbach, Kevin

2005-09-01

To estimate the impact of a U.S. inner-city medical education program on medical school graduates' intentions to practice in underserved communities. The authors conducted an analysis of secondary data on 1,088 medical students who graduated from either the joint University of California, Los Angeles/Charles R. Drew University Medical Education Program (UCLA/Drew) or the UCLA School of Medicine between 1996 and 2002. Intention to practice in underserved communities was measured using students' responses to questionnaires administered at matriculation and graduation for program improvement by the Association of American Medical Colleges. Multivariate logistic regression analysis was used to compare the odds of intending to practice in underserved communities among UCLA/Drew students with those of their counterparts in the UCLA School of Medicine. Compared with students in the UCLA School of Medicine, UCLA/Drew students had greater adjusted odds of reporting intention to work in underserved communities at graduation, greater odds of maintaining or increasing such intentions between matriculation and graduation, and lower odds of decreased intention to work in underserved communities between matriculation and graduation. Training in the UCLA/Drew program was independently associated with intention to practice medicine in underserved communities, suggesting that a medical education program can have a positive effect on students' goals to practice in underserved areas.

Nursing as a Career Choice by Hispanic/Latino College Students: A Multi-Institutional Study.

PubMed

Stroup, Linda M; Kuk, Linda

2015-09-01

Despite rapid growth in the Hispanic/Latino population, there is significant underrepresentation of Hispanic/Latino individuals in the nursing workforce and nursing programs. This study investigated college students' interest in and self-efficacy for nursing as a career choice, and factors that students believe will impact their success in a nursing program. A nonexperimental, associational research study using a survey instrument was conducted at three comprehensive, public state universities and one community college in the western United States in an area with a significant Hispanic/Latino population. Descriptive and multivariable correlation statistical analysis suggested that college students' interest in and self-efficacy for nursing as a career choice was similar for both Hispanic/Latino and non-Hispanic/Latino students in the sample. Perceived facilitators for success in a nursing program were identified. Findings can be used to develop strategies and programs to enhance the success of Hispanic/Latino students interested in nursing as a career choice. Copyright 2015, SLACK Incorporated.

Retention and Risk Factors for Attrition in a Large Public Health ART Program in Myanmar: A Retrospective Cohort Analysis

PubMed Central

Thida, Aye; Tun, Sai Thein Than; Zaw, Sai Ko Ko; Lover, Andrew A.; Cavailler, Philippe; Chunn, Jennifer; Aye, Mar Mar; Par, Par; Naing, Kyaw Win; Zan, Kaung Nyunt; Shwe, Myint; Kyaw, Thar Tun; Waing, Zaw Htoon; Clevenbergh, Philippe

2014-01-01

Background The outcomes from an antiretroviral treatment (ART) program within the public sector in Myanmar have not been reported. This study documents retention and the risk factors for attrition in a large ART public health program in Myanmar. Methods A retrospective analysis of a cohort of adult patients enrolled in the Integrated HIV Care (IHC) Program between June 2005 and October 2011 and followed up until April 2012 is presented. The primary outcome was attrition (death or loss-follow up); a total of 10,223 patients were included in the 5-year cumulative survival analysis. Overall 5,718 patients were analyzed for the risk factors for attrition using both logistic regression and flexible parametric survival models. Result The mean age was 36 years, 61% of patients were male, and the median follow up was 13.7 months. Overall 8,564 (84%) patients were retained in ART program: 750 (7%) were lost to follow-up and 909 (9%) died. During the 3 years follow-up, 1,542 attritions occurred over 17,524 person years at risk, giving an incidence density of 8.8% per year. The retention rates of participants at 12, 24, 36, 48 and 60 months were 86, 82, 80, 77 and 74% respectively. In multivariate analysis, being male, having high WHO staging, a low CD4 count, being anaemic or having low BMI at baseline were independent risk factors for attrition; tuberculosis (TB) treatment at ART initiation, a prior ART course before program enrollment and literacy were predictors for retention in the program. Conclusion High retention rate of IHC program was documented within the public sector in Myanmar. Early diagnosis of HIV, nutritional support, proper investigation and treatment for patients with low CD4 counts and for those presenting with anaemia are crucial issues towards improvement of HIV program outcomes in resource-limited settings. PMID:25268903

Retention and risk factors for attrition in a large public health ART program in Myanmar: a retrospective cohort analysis.

PubMed

Thida, Aye; Tun, Sai Thein Than; Zaw, Sai Ko Ko; Lover, Andrew A; Cavailler, Philippe; Chunn, Jennifer; Aye, Mar Mar; Par, Par; Naing, Kyaw Win; Zan, Kaung Nyunt; Shwe, Myint; Kyaw, Thar Tun; Waing, Zaw Htoon; Clevenbergh, Philippe

2014-01-01

The outcomes from an antiretroviral treatment (ART) program within the public sector in Myanmar have not been reported. This study documents retention and the risk factors for attrition in a large ART public health program in Myanmar. A retrospective analysis of a cohort of adult patients enrolled in the Integrated HIV Care (IHC) Program between June 2005 and October 2011 and followed up until April 2012 is presented. The primary outcome was attrition (death or loss-follow up); a total of 10,223 patients were included in the 5-year cumulative survival analysis. Overall 5,718 patients were analyzed for the risk factors for attrition using both logistic regression and flexible parametric survival models. The mean age was 36 years, 61% of patients were male, and the median follow up was 13.7 months. Overall 8,564 (84%) patients were retained in ART program: 750 (7%) were lost to follow-up and 909 (9%) died. During the 3 years follow-up, 1,542 attritions occurred over 17,524 person years at risk, giving an incidence density of 8.8% per year. The retention rates of participants at 12, 24, 36, 48 and 60 months were 86, 82, 80, 77 and 74% respectively. In multivariate analysis, being male, having high WHO staging, a low CD4 count, being anaemic or having low BMI at baseline were independent risk factors for attrition; tuberculosis (TB) treatment at ART initiation, a prior ART course before program enrollment and literacy were predictors for retention in the program. High retention rate of IHC program was documented within the public sector in Myanmar. Early diagnosis of HIV, nutritional support, proper investigation and treatment for patients with low CD4 counts and for those presenting with anaemia are crucial issues towards improvement of HIV program outcomes in resource-limited settings.

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…

Characterizing Durations of Heroin Abstinence in the California Civil Addict Program: Results From a 33-Year Observational Cohort Study

PubMed Central

Nosyk, Bohdan; Anglin, M. Douglas; Brecht, Mary-Lynn; Lima, Viviane Dias; Hser, Yih-Ing

2013-01-01

In accordance with the chronic disease model of opioid dependence, cessation is often observed as a longitudinal process rather than a discrete endpoint. We aimed to characterize and identify predictors of periods of heroin abstinence in the natural history of recovery from opioid dependence. Data were collected on participants from California who were enrolled in the Civil Addict Program from 1962 onward by use of a natural history interview. Multivariate regression using proportional hazards frailty models was applied to identify independent predictors and correlates of repeated abstinence episode durations. Among 471 heroin-dependent males, 387 (82.2%) reported 932 abstinence episodes, 60.3% of which lasted at least 1 year. Multivariate analysis revealed several important findings. First, demographic factors such as age and ethnicity did not explain variation in durations of abstinence episodes. However, employment and lower drug use severity predicted longer episodes. Second, abstinence durations were longer following sustained treatment versus incarceration. Third, individuals with multiple abstinence episodes remained abstinent for longer durations in successive episodes. Finally, abstinence episodes initiated >10 and ≤20 years after first use lasted longer than others. Public policy facilitating engagement of opioid-dependent individuals in maintenance-oriented drug treatment and employment is recommended to achieve and sustain opioid abstinence. PMID:23445901

Resistance Training Exercise Program for Intervention to Enhance Gait Function in Elderly Chronically Ill Patients: Multivariate Multiscale Entropy for Center of Pressure Signal Analysis

PubMed Central

Jiang, Bernard C.

2014-01-01

Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI), based on multiscale entropy (MSE) algorithm, has been applied in recent studies to show a person's adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE) was advanced algorithm used to calculate the complexity index (CI) values of the center of pressure (COP) data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56 ± 10.70 years) with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE) algorithm to identify the sense of balance in the elderly. PMID:25295070

Comparing Medical and Recreational Cannabis Users on Socio-Demographic, Substance and Medication Use, and Health and Disability Characteristics.

PubMed

Goulet-Stock, Sybil; Rueda, Sergio; Vafaei, Afshin; Ialomiteanu, Anca; Manthey, Jakob; Rehm, Jürgen; Fischer, Benedikt

2017-01-01

While recreational cannabis use is common, medical cannabis programs have proliferated across North America, including a federal program in Canada. Few comparisons of medical and recreational cannabis users (RCUs) exist; this study compared these groups on key characteristics. Data came from a community-recruited sample of formally approved medical cannabis users (MCUs; n = 53), and a sub-sample of recreational cannabis users (RCUs; n = 169) from a representative adult survey in Ontario (Canada). Samples were telephone-surveyed on identical measures, including select socio-demographic, substance and medication use, and health and disability measures. Based on initial bivariate comparisons, multivariate logistical regression with a progressive adjustment approach was performed to assess independent predictors of group status. In bivariate analyses, older age, lower household income, lower alcohol use, higher cocaine, prescription opioid, depression and anxiety medication use, and lower health and disability status were significantly associated with medical cannabis use. In the multivariate analysis, final model, household income, alcohol use, and disability levels were associated with medical cannabis use. Conclusions/Scientific Significance: Compared to RCUs, medical users appear to be mainly characterized by factors negatively influencing their overall health status. Future studies should investigate the actual impact and net benefits of medical cannabis use on these health problems. © 2017 S. Karger AG, Basel.

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Immigration and leisure-time physical inactivity: a population-based study.

PubMed

Lindström, M; Sundquist, J

2001-05-01

To investigate the relationship between migration status and sedentary leisure-time physical activity status in the city of Malmö, Sweden. The public health survey in 1994 is a cross-sectional study. A total of 5,600 individuals aged 20-80 completed a postal questionnaire. The response rate was 71%. The population was categorized according to country of birth. Multivariate analysis was performed using a logistic regression model to investigate the importance of possible confounders for the differences in sedentary leisure-time physical activity status. The prevalence of a sedentary leisure-time physical activity status was 18.1% among men and 26.7% among women. The odds ratio of a sedentary leisure-time physical activity status was significantly higher among men born in Arabic-speaking countries, in All other countries, and among women born in Yugoslavia, Poland, Arabic-speaking countries, and the category all other countries', compared to the reference group born in Sweden. The multivariate analysis including age, sex, and education did not alter these results. There were significant ethnic differences in leisure-time physical activity status. This is a CVD risk factor that could be affected by intervention programs aimed at specific ethnic subgroups of the population.

Chronic osteomyelitis correlates with increased risk of acute pancreatitis in a case-control study in Taiwan.

PubMed

Lai, Shih-Wei; Lai, Hsueh-Chou; Lin, Cheng-Li; Liao, Kuan-Fu; Tseng, Chun-Hung

2015-07-01

The objective of this study was to examine the relationship between chronic osteomyelitis and acute pancreatitis in Taiwan. This was a population-based case-control study utilizing the database of the Taiwan National Health Insurance Program. We identified 7678 cases aged 20-84 with newly diagnosed acute pancreatitis during the period of 1998 to 2011. From the same database, 30,712 subjects without diagnosis of acute pancreatitis were selected as controls. The cases and controls were matched with sex, age and index year of diagnosing acute pancreatitis. The odds ratio with 95% confidence interval of acute pancreatitis associated with chronic osteomyelitis was examined by the multivariable unconditional logistic regression analysis. After adjustment for multiple confounders, the multivariable analysis showed that the adjusted odds ratio of acute pancreatitis was 1.93 for subjects with chronic osteomyelitis (95% confidence interval 1.01, 3.69), when compared with subjects without chronic osteomyelitis. Chronic osteomyelitis correlates with increased risk of acute pancreatitis. Patients with chronic osteomyelitis should be carefully monitored about the risk of acute pancreatitis. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Malnutrition: prevalence and risk factors among the children younger than five years in a semi-urban area of Abidjan.

PubMed

Sackou Kouakou, J G; Aka, B S; Hounsa, A E; Attia, R; Wilson, R; Ake, O; Oga, S; Houenou, Y; Kouadio, L

2016-08-01

In Côte d'Ivoire, the prevalence of malnutrition among children younger than 5 years exceeded 5% in 2011 and was thus considered serious. This overall prevalence may nonetheless mask differences and specificities between regions and municipalities. This study sought to determine the prevalence and risk factors of malnutrition among children in this age group in a semi-urban area of Abidjan. This exhaustive, descriptive, cross-sectional survey took place from May 6 to July 31, 2010. The children's nutritional status was determined according to the WHO criteria. Univariate and multivariate analysis of factors associated with malnutrition (social and demographic characteristics, immunization status, children's eating practices, and household characteristics) were studied. We visited 668 households and recruited 809 children. The prevalence of malnutrition was 22.5%. Multivariate analysis showed that the introduction of porridge after 6 months halved the risk of malnutrition. Risk tripled for children whose father's occupation did not guarantee a regular income. Among the factors highlighted by this study, dietary practices seem the most amenable to corrective action. For example, the adoption of outreach programs by the Maternal and Child Protection services could improve nutritional practices in households.

Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems

EPA Pesticide Factsheets

VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Stress transgenerationally programs metabolic pathways linked to altered mental health.

PubMed

Kiss, Douglas; Ambeskovic, Mirela; Montina, Tony; Metz, Gerlinde A S

2016-12-01

Stress is among the primary causes of mental health disorders, which are the most common reason for disability worldwide. The ubiquity of these disorders, and the costs associated with them, lends a sense of urgency to the efforts to improve prediction and prevention. Down-stream metabolic changes are highly feasible and accessible indicators of pathophysiological processes underlying mental health disorders. Here, we show that remote and cumulative ancestral stress programs central metabolic pathways linked to mental health disorders. The studies used a rat model consisting of a multigenerational stress lineage (the great-great-grandmother and each subsequent generation experienced stress during pregnancy) and a transgenerational stress lineage (only the great-great-grandmother was stressed during pregnancy). Urine samples were collected from adult male F4 offspring and analyzed using 1 H NMR spectroscopy. The results of variable importance analysis based on random variable combination were used for unsupervised multivariate principal component analysis and hierarchical clustering analysis, as well as metabolite set enrichment analysis (MSEA) and pathway analysis. We identified distinct metabolic profiles associated with the multigenerational and transgenerational stress phenotype, with consistent upregulation of hippurate and downregulation of tyrosine, threonine, and histamine. MSEA and pathway analysis showed that these metabolites are involved in catecholamine biosynthesis, immune responses, and microbial host interactions. The identification of metabolic signatures linked to ancestral programming assists in the discovery of gene targets for future studies of epigenetic regulation in pathogenic processes. Ultimately, this research can lead to biomarker discovery for better prediction and prevention of mental health disorders.

Association between non-fatal opioid overdose and encounters with healthcare and criminal justice systems: Identifying opportunities for intervention.

PubMed

Wagner, Karla D; Liu, Lin; Davidson, Peter J; Cuevas-Mota, Jazmine; Armenta, Richard F; Garfein, Richard S

2015-08-01

Accidental overdose, driven largely by opioids, is a leading cause of death among people who inject drugs (PWIDs). We conducted secondary analysis of data from a cohort of PWIDs to identify venues where high-risk PWID could be targeted by overdose education/naloxone distribution (OEND) programs. 573 PWIDs completed a quantitative survey between June, 2012 and January, 2014, which was analyzed using multivariable logistic regression. The dependent variable was a dichotomous indicator of experiencing a heroin/opioid-related overdose in the past six months. Independent variables included: demographics, drug use behavior, and encounters with two venues - the health care and criminal justice systems - that could serve as potential venues for OEND programs. Almost half (41.5%) reported ever experiencing a heroin/opioid overdose, and 45 (7.9%) reported experiencing at least one heroin/opioid overdose in the past six months. In the final multivariable model, receiving care in a hospital in the past six months (Adjusted Odds Ratio [AdjOR] 4.08, 95% Confidence Interval [C.I.] 2.07, 8.04, p<0.001) and being arrested for drug possession in the past six months (AdjOR 5.17, 95% C.I. 2.37, 11.24, p<0.001) were associated with experiencing an opioid overdose in the past six months. Identifying venues outside of those that traditionally target services to PWIDs (i.e., syringe exchange programs) will be critical to implementing OEND interventions at a scale sufficient to address the growing epidemic of heroin/opioid related deaths. Clinical settings, such as hospitals, and drug-related encounters with law enforcement officers are promising venues for the expansion of OEND programs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Effects of the A Matter of Balance Program on Falls and Physical Risk of Falls, Tampa, Florida, 2013.

PubMed

Chen, Tuo-Yu; Edwards, Jerri D; Janke, Megan C

2015-09-24

This study investigated the effects of the A Matter of Balance (MOB) program on falls and physical risk factors of falling among community-dwelling older adults living in Tampa, Florida, in 2013. A total of 110 adults (52 MOB, 58 comparison) were enrolled in this prospective cohort study. Data on falls, physical risk of falling, and other known risk factors of falling were collected at baseline and at the end of the program. Multivariate analysis of covariance with repeated measures and logistic regressions were used to investigate the effects of this program. Participants in the MOB group were less likely to have had a fall and had significant improvements in their physical risk of falling compared with adults in the comparison group. No significant effects of the MOB program on recurrent falls or the number of falls reported were found. This study contributes to our understanding of the MOB program and its effectiveness in reducing falls and the physical risk of falling among older adults. The findings support extended use of this program to reduce falls and physical risk of falling among older adults.

Concurrent risk-reduction surgery in patients with increased lifetime risk for breast and ovarian cancer: an analysis of the National Surgical Quality Improvement Program (NSQIP) database.

PubMed

Elmi, Maryam; Azin, Arash; Elnahas, Ahmad; McCready, David R; Cil, Tulin D

2018-05-14

Patients with genetic susceptibility to breast and ovarian cancer are eligible for risk-reduction surgery. Surgical morbidity of risk-reduction mastectomy (RRM) with concurrent bilateral salpingo-oophorectomy (BSO) is unknown. Outcomes in these patients were compared to patients undergoing RRM without BSO using a large multi-institutional database. A retrospective cohort analysis was conducted using the American College of Surgeon's National Surgical Quality Improvement Program (NSQIP) 2007-2016 datasets, comparing postoperative morbidity between patients undergoing RRM with patients undergoing RRM with concurrent BSO. Patients with genetic susceptibility to breast/ovarian cancer undergoing risk-reduction surgery were identified. The primary outcome was 30-day postoperative major morbidity. Secondary outcomes included surgical site infections, reoperations, readmissions, length of stay, and venous thromboembolic events. A multivariate analysis was performed to determine predictors of postoperative morbidity and the adjusted effect of concurrent BSO on morbidity. Of the 5470 patients undergoing RRM, 149 (2.7%) underwent concurrent BSO. The overall rate of major morbidity and postoperative infections was 4.5% and 4.6%, respectively. There was no significant difference in the rate of postoperative major morbidity (4.5% vs 4.7%, p = 0.91) or any of the secondary outcomes between patients undergoing RRM without BSO vs. those undergoing RRM with concurrent BSO. Multivariable analysis showed Body Mass Index (OR 1.05; p < 0.001) and smoking (OR 1.78; p = 0.003) to be the only predictors associated with major morbidity. Neither immediate breast reconstruction (OR 1.02; p = 0.93) nor concurrent BSO (OR 0.94; p = 0.89) were associated with increased postoperative major morbidity. This study demonstrated that RRM with concurrent BSO was not associated with significant additional morbidity when compared to RRM without BSO. Therefore, this joint approach may be considered for select patients at risk for both breast and ovarian cancer.

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

Glascock, M. D.; Neff, H.; Vaughn, K. J.

2004-06-01

The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Localization of genes involved in the metabolic syndrome using multivariate linkage analysis.

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

There are no well accepted criteria for the diagnosis of the metabolic syndrome. However, the metabolic syndrome is identified clinically by the presence of three or more of these five variables: larger waist circumference, higher triglyceride levels, lower HDL-cholesterol concentrations, hypertension, and impaired fasting glucose. We use sets of two or three variables, which are available in the Framingham Heart Study data set, to localize genes responsible for this syndrome using multivariate quantitative linkage analysis. This analysis demonstrates the applicability of using multivariate linkage analysis and how its use increases the power to detect linkage when genes are involved in the same disease mechanism.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Health-state utilities in a prisoner population: a cross-sectional survey

PubMed Central

Chong, Christopher AKY; Li, Sicong; Nguyen, Geoffrey C; Sutton, Andrew; Levy, Michael H; Butler, Tony; Krahn, Murray D; Thein, Hla-Hla

2009-01-01

Background Health-state utilities for prisoners have not been described. Methods We used data from a 1996 cross-sectional survey of Australian prisoners (n = 734). Respondent-level SF-36 data was transformed into utility scores by both the SF-6D and Nichol's method. Socio-demographic and clinical predictors of SF-6D utility were assessed in univariate analyses and a multivariate general linear model. Results The overall mean SF-6D utility was 0.725 (SD 0.119). When subdivided by various medical conditions, prisoner SF-6D utilities ranged from 0.620 for angina to 0.764 for those with none/mild depressive symptoms. Utilities derived by the Nichol's method were higher than SF-6D scores, often by more than 0.1. In multivariate analysis, significant independent predictors of worse utility included female gender, increasing age, increasing number of comorbidities and more severe depressive symptoms. Conclusion The utilities presented may prove useful for future economic and decision models evaluating prison-based health programs. PMID:19715571

Healthy Living Behaviors Among Chinese-American Preschool-Aged Children: Results of a Parent Survey.

PubMed

Chomitz, Virginia Rall; Brown, Alison; Lee, Victoria; Must, Aviva; Chui, Kenneth Kwan Ho

2017-07-17

Associations between diet, physical activity, parenting, and acculturation among Chinese-American children are understudied. Parents/caregivers of children attending child-care programs in Boston Chinatown completed a self-administered survey on demographics, child's diet, physical activities, anthropometrics, and parenting practices. Associations were evaluated in multivariable regression analysis, stratified by survey language preference, a proxy for acculturation. Responding Asian families = 132; 86.4% were immigrants; 75.8% completed the Chinese-version survey. Children (mean ± SD: 4.9 ± 1.1 years) did not eat vegetables (31.8%), or play actively outside (45.4%) daily, 64.8% watched television/screens daily; 32.6% were overweight/obese (based on parent report). Parenting practices associated with obesity were apparent. Although healthy-living behavioral outcomes were less prevalent among less acculturated parents; multivariable adjustment attenuated the observed significant differences. Findings suggest opportunities for improvement in study children's diet and healthy-living behaviors, and underscore the need for further research on acculturation, and parenting styles in this population.

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection.

PubMed

Basques, Bryce A; Golinvaux, Nicholas S; Bohl, Daniel D; Yacob, Alem; Toy, Jason O; Varthi, Arya G; Grauer, Jonathan N

2014-10-15

Retrospective database review. To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. The American College of Surgeons National Surgical Quality Improvement Program database, which includes data from more than 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without the use of an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. A total of 23,670 elective spine procedures were identified, of which 2226 (9.4%) used an operating microscope. The average patient age was 55.1±14.4 years. The average operative time (incision to closure) was 125.7±82.0 minutes.Microscope use was associated with minor increases in preoperative room time (+2.9 min, P=0.013), operative time (+13.2 min, P<0.001), and total room time (+18.6 min, P<0.001) on multivariate analysis.A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and nonmicroscope groups for occurrence of any infection, superficial surgical site infection, deep surgical site infection, organ space infection, or sepsis/septic shock, regardless of surgery type. We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. 3.

Use of an operating microscope during spine surgery is associated with minor increases in operating room times and no increased risk of infection

PubMed Central

Basques, Bryce A.; Golinvaux, Nicholas S.; Bohl, Daniel D.; Yacob, Alem; Toy, Jason O.; Varthi, Arya G.; Grauer, Jonathan N.

2014-01-01

Study Design Retrospective database review. Objective To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Summary of Background Data Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, which includes data from over 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. Results A total of 23,670 elective spine procedures were identified, of which 2,226 (9.4%) used an operating microscope. The average patient age was 55.1 ± 14.4 years. The average operative time (incision to closure) was 125.7 ± 82.0 minutes. Microscope use was associated with minor increases in preoperative room time (+2.9 minutes, p=0.013), operative time (+13.2 minutes, p<0.001), and total room time (+18.6 minutes, p<0.001) on multivariate analysis. A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and non-microscope groups for occurrence of any infection, superficial surgical site infection (SSI), deep SSI, organ space infection, or sepsis/septic shock, regardless of surgery type. Conclusions We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. PMID:25188600

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

Multivariate frequency domain analysis (MFDA) is proposed to characterize collective vibrational dynamics of protein obtained by a molecular dynamics (MD) simulation. MFDA performs principal component analysis (PCA) for a bandpass filtered multivariate time series using the multitaper method of spectral estimation. By applying MFDA to MD trajectories of bovine pancreatic trypsin inhibitor, we determined the collective vibrational modes in the frequency domain, which were identified by their vibrational frequencies and eigenvectors. At near zero temperature, the vibrational modes determined by MFDA agreed well with those calculated by normal mode analysis. At 300 K, the vibrational modes exhibited characteristic features that were considerably different from the principal modes of the static distribution given by the standard PCA. The influences of aqueous environments were discussed based on two different sets of vibrational modes, one derived from a MD simulation in water and the other from a simulation in vacuum. Using the varimax rotation, an algorithm of the multivariate statistical analysis, the representative orthogonal set of eigenmodes was determined at each vibrational frequency.

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

Background The primary cell wall of fruits and vegetables is a structure mainly composed of polysaccharides (pectins, hemicelluloses, cellulose). Polysaccharides are assembled into a network and linked together. It is thought that the percentage of components and of plant cell wall has an important influence on mechanical properties of fruits and vegetables. Results In this study the Raman microspectroscopy technique was introduced to the visualization of the distribution of polysaccharides in cell wall of fruit. The methodology of the sample preparation, the measurement using Raman microscope and multivariate image analysis are discussed. Single band imaging (for preliminary analysis) and multivariate image analysis methods (principal component analysis and multivariate curve resolution) were used for the identification and localization of the components in the primary cell wall. Conclusions Raman microspectroscopy supported by multivariate image analysis methods is useful in distinguishing cellulose and pectins in the cell wall in tomatoes. It presents how the localization of biopolymers was possible with minimally prepared samples. PMID:24917885

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Factors underlying the psychological and behavioral characteristics of Office of Strategic Services candidates: the assessment of men data revisited.

PubMed

Lenzenweger, Mark F

2015-01-01

During World War II, the Office of Strategic Services (OSS), the forerunner of the Central Intelligence Agency, sought the assistance of clinical psychologists and psychiatrists to establish an assessment program for evaluating candidates for the OSS. The assessment team developed a novel and rigorous program to evaluate OSS candidates. It is described in Assessment of Men: Selection of Personnel for the Office of Strategic Services (OSS Assessment Staff, 1948). This study examines the sole remaining multivariate data matrix that includes all final ratings for a group of candidates (n = 133) assessed near the end of the assessment program. It applies the modern statistical methods of both exploratory and confirmatory factor analysis to this rich and highly unique data set. An exploratory factor analysis solution suggested 3 factors underlie the OSS assessment staff ratings. Confirmatory factor analysis results of multiple plausible substantive models reveal that a 3-factor model provides the best fit to these data. The 3 factors are emotional/interpersonal factors (social relations, emotional stability, security), intelligence processing (effective IQ, propaganda skills, observing and reporting), and agency/surgency (motivation, energy and initiative, leadership, physical ability). These factors are discussed in terms of their potential utility for personnel selection within the intelligence community.

Effectiveness of a training program to increase the capacity of health care providers to provide HIV/AIDS care and treatment in Swaziland.

PubMed

Kamiru, H N; Ross, M W; Bartholomew, L K; McCurdy, S A; Kline, M W

2009-11-01

Implementation of HIV care and treatment programs in sub-Saharan Africa is a complex undertaking that requires training of health care providers (HCPs). Many sub-Saharan African countries have introduced training programs to build human resources for health. Evaluation of the ongoing trainings is warranted so that programs can be improved. The purpose of this study was to evaluate Baylor International Pediatric AIDS Initiative's (BIPAI) HCP training program in Swaziland. The specific aims were: (1) to assess coverage and delivery of the training program; and (2) to determine the impact of the training program on HCPs' knowledge about HIV and pediatric practices, attitudes toward HIV/AIDS patients, and self-efficacy to provide antiretroviral therapy (ART). The evaluation was a multimethod design with two types of data collection and analysis: (1) one-group pretest-posttest survey with 101 HCPs; and (2) semi-structured in-depth interviews with seven trainers from Baylor College of Medicine and 16 local HCPs in Swaziland. Quantitative data were analyzed using Stata Statistical Software version 8.2 for descriptive and multivariate analysis while factor analysis was done using Statistical Program for Social Sciences version 14. The transcribed interviews were analyzed using a didactic approach. Process evaluation showed that the training had good coverage, was delivered as intended, and improved as the work progressed. The training program led to a significant increase (p=0.0000) in HCPs' knowledge about HIV/AIDS, ART, and relevant clinical pediatrics practices between pretest (mean 68.7% SD 13.7) and post training (mean 84.0% SD 12.0). The training program also increased trainees' self-efficacy to provide ART and their attitudes toward AIDS patients (p=0.0000 and 0.02, respectively). In conclusion, BIPAI training program in Swaziland had good coverage of all health care facilities and HCPs in Swaziland. The training was effective in imparting knowledge and skills to HCPs and in their attitudes toward HIV/AIDS patients.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution.

PubMed

Li, Ning; Liu, Xueqin; Xie, Wei; Wu, Jidong; Zhang, Peng

2013-01-01

New features of natural disasters have been observed over the last several years. The factors that influence the disasters' formation mechanisms, regularity of occurrence and main characteristics have been revealed to be more complicated and diverse in nature than previously thought. As the uncertainty involved increases, the variables need to be examined further. This article discusses the importance and the shortage of multivariate analysis of natural disasters and presents a method to estimate the joint probability of the return periods and perform a risk analysis. Severe dust storms from 1990 to 2008 in Inner Mongolia were used as a case study to test this new methodology, as they are normal and recurring climatic phenomena on Earth. Based on the 79 investigated events and according to the dust storm definition with bivariate, the joint probability distribution of severe dust storms was established using the observed data of maximum wind speed and duration. The joint return periods of severe dust storms were calculated, and the relevant risk was analyzed according to the joint probability. The copula function is able to simulate severe dust storm disasters accurately. The joint return periods generated are closer to those observed in reality than the univariate return periods and thus have more value in severe dust storm disaster mitigation, strategy making, program design, and improvement of risk management. This research may prove useful in risk-based decision making. The exploration of multivariate analysis methods can also lay the foundation for further applications in natural disaster risk analysis. © 2012 Society for Risk Analysis.

Application of the MNA design method to a nonlinear turbofan engine. [multivariable Nyquist array method

NASA Technical Reports Server (NTRS)

Leininger, G. G.

1981-01-01

Using nonlinear digital simulation as a representative model of the dynamic operation of the QCSEE turbofan engine, a feedback control system is designed by variable frequency design techniques. Transfer functions are generated for each of five power level settings covering the range of operation from approach power to full throttle (62.5% to 100% full power). These transfer functions are then used by an interactive control system design synthesis program to provide a closed loop feedback control using the multivariable Nyquist array and extensions to multivariable Bode diagrams and Nichols charts.

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Retention of court-referred youths in residential treatment programs: client characteristics and treatment process effects.

PubMed

Orlando, Maria; Chan, Kitty S; Morral, Andrew R

2003-05-01

The juvenile justice system relies heavily on residential treatment services for adolescents. Because treatment dropout limits the likely effectiveness of these services, in this study we examine the client and program characteristics associated with program retention among a sample of adolescent probationers referred to residential rehabilitation by the Juvenile Court in Los Angeles. Participants in the present study (n = 291) are a subset of those in the Adolescent Outcomes Project, conducted within RAND's Drug Policy Research Center, to examine the outcomes of youths entering treatment at seven residential treatment programs. Three months after a preadmission interview, youths were asked about their perceptions of counselors at the program, other residents, and their feelings of safety in the program. In addition, they were asked whether they needed and had received various services (e.g., job training, legal advice, family counseling). Results of a multivariate survival analysis revealed that pretreatment characteristics including motivation and substance use severity, as well as treatment program factors including safety, and perceived over- and underprovision of services, contribute significantly to the prediction of retention. Pretreatment environmental risk factors and ratings of program counselor and resident support were marginally significant. These results imply that changes in adolescent residential program delivery may serve to increase retention rates, thus improving long-term outcomes.

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

In this work, the effect of temperature on charcoal structure and chemical composition is investigated for four tree species. Wood charcoal carbonized at various temperatures is analyzed by mid infrared spectroscopy coupled with multivariate analysis and by thermogravimetric analysis to characterize the chemical composition during the carbonization process. The...

Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

Factors influencing knowledge on completion of treatment among TB patients under directly observed treatment strategy, in selected health facilities in Embu County, Kenya.

PubMed

Ndwiga, Joshua Muriuki; Kikuvi, Gideon; Omolo, Jared Odhiambo

2016-01-01

The World Health Organization (WHO) promotes the Directly Observed Treatment (DOT) strategy as the standard to increase adherence to Tuberculosis (TB) medication. However, cases of retreatment and Multi Drug Resistant continue to be reported in many parts of Kenya. This study sought to determine the factors influencing the completion of tuberculosis medication among TB patients in Embu County, Kenya. A descriptive cross-sectional study was conducted on a population of tuberculosis patients under DOT attending selected TB treatment clinics in Embu County, in Kenya. One hundred and forty TB patients interviewed within a period of 3 months. Data were analyzed using SPSS version 17.0 and included Bivariate and Multivariate Analysis. The level of significance was p≤ 0.05. The male and female participants were 61.4% and 38.6% respectively. The mean age of the respondents was 35±31.34-39.3 years. For the majority (52%) of the participants, the highest level of education was primary education. The unemployed participants formed the highest number of the respondent in the study (73%). The majorities (91.4%0) of the respondents were under the home-based DOT strategy (91.4%, 95% C.I: 85.5-95.5). Bivariate analysis using Chi-square showed that the level of education (p=0.003), patients feeling uncomfortable during supervision (p=0.01), and knowledge regarding the frequency of taking medication (p=0.004) were all significantly associated with knowledge regarding the importance of completion of medication. However, none of these factors was significant after multivariate analysis. Most participants did not know the importance of completion of medication. TB programs should come up with better ways to educate TB patients on the importance of supervision and treatment completion during the treatment of TB. The education programs should focus on influencing the attitudes of patients and creating awareness about the importance of treatment completion. The TB programs should be designed towards eliminating the factors influencing the completion of TB medication.

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Short-term Outcomes After Open and Laparoscopic Colostomy Creation.

PubMed

Ivatury, Srinivas Joga; Bostock Rosenzweig, Ian C; Holubar, Stefan D

2016-06-01

Colostomy creation is a common procedure performed in colon and rectal surgery. Outcomes by technique have not been well studied. This study evaluated outcomes related to open versus laparoscopic colostomy creation. This was a retrospective review of patients undergoing colostomy creation using univariate and multivariate propensity score analyses. Hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program database were included. Data on patients were obtained from the American College of Surgeons National Surgical Quality Improvement Program 2005-2011 Participant Use Data Files. We measured 30-day mortality, 30-day complications, and predictors of 30-day mortality. A total of 2179 subjects were in the open group and 1132 in the laparoscopic group. The open group had increased age (open, 64 years vs laparoscopic, 60 years), admission from facility (17.0% vs 14.9%), and disseminated cancer (26.1% vs 21.4%). All were statistically significant. The open group had a significantly higher percentage of emergency operations (24.9% vs 7.9%). Operative time was statistically different (81 vs 86 minutes). Thirty-day mortality was significantly higher in the open group (8.7% vs 3.5%), as was any 30-day complication (25.4% vs 17.0%). Propensity-matching analysis on elective patients only revealed that postoperative length of stay and rate of any wound complication were statistically higher in the open group. Multivariate analysis for mortality was performed on the full, elective, and propensity-matched cohorts; age >65 years and dependent functional status were associated with an increased risk of mortality in all of the models. This study has the potential for selection bias and limited generalizability. Colostomy creation at American College of Surgeons National Surgical Quality Improvement Program hospitals is more commonly performed open rather than laparoscopically. Patient age >65 years and dependent functional status are associated with an increased risk of 30-day mortality.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Assessment of preclinical students’ academic motivation before and after a three-day academic affair program

PubMed Central

Aung, Myo Nyein; Somboonwong, Juraiporn; Jaroonvanichkul, Vorapol; Wannakrairot, Pongsak

2015-01-01

Background Medical students’ motivation is an important driving factor for academic performance, and therefore medical teachers and educators are often highly interested in this topic. This study evaluated the impact of an academic affair program upon preclinical year medical students’ motivation to study. Design and methods An intervention study was conducted using a pretest-posttest study design. A total of 296 preclinical year medical students who had just passed their first year and were about to attend their second year at the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, participated in the study. The intervention comprised of dialogues for personality development, pictorial expression in groups, as well as small group lectures delivered by senior students giving information on how to prepare for the forthcoming classes. Students’ academic motivation was measured before and after the intervention program, applying the transculturally translated Academic Motivation Scale (AMS). Cronbach’s alpha of Thai version AMS was 0.8992. The average scores in seven scales of AMS were compared between the pre- and posttest results, using the Wilcoxon signed-rank test. The differences were confirmed by using the multivariate analysis of variance. Results Students’ academic motivation increased after participation in the three-day academic program. There was also a significant increase in introjected extrinsic motivation, which can enhance the students’ self-esteem and feeling of self-worth (P<0.001). Moreover, intrinsic motivation toward accomplishment increased significantly (P<0.001). This is related to the enjoyment of passing academic milestones, and a step ahead of autonomous motivation. Amotivation level declined significantly (P<0.001). The change of academic motivational constructs before and after the intervention was altogether significant (P=0.036, multivariate analysis of variance). Conclusion After experiencing a three-day intervention, the new students’ motivation advanced along the continuum of self-determination toward autonomous motivation. Therefore, it is considered to be worthwhile conducting an academic intervention to catalyze the evolution of preclinical year medical students’ academic motivation. Moreover, educators and faculties should evaluate the impact of interventions in evidence-based approaches to secure both controlled and autonomous types of motivation. PMID:26719719

Assessment of preclinical students' academic motivation before and after a three-day academic affair program.

PubMed

Aung, Myo Nyein; Somboonwong, Juraiporn; Jaroonvanichkul, Vorapol; Wannakrairot, Pongsak

2015-01-01

Medical students' motivation is an important driving factor for academic performance, and therefore medical teachers and educators are often highly interested in this topic. This study evaluated the impact of an academic affair program upon preclinical year medical students' motivation to study. An intervention study was conducted using a pretest-posttest study design. A total of 296 preclinical year medical students who had just passed their first year and were about to attend their second year at the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, participated in the study. The intervention comprised of dialogues for personality development, pictorial expression in groups, as well as small group lectures delivered by senior students giving information on how to prepare for the forthcoming classes. Students' academic motivation was measured before and after the intervention program, applying the transculturally translated Academic Motivation Scale (AMS). Cronbach's alpha of Thai version AMS was 0.8992. The average scores in seven scales of AMS were compared between the pre- and posttest results, using the Wilcoxon signed-rank test. The differences were confirmed by using the multivariate analysis of variance. Students' academic motivation increased after participation in the three-day academic program. There was also a significant increase in introjected extrinsic motivation, which can enhance the students' self-esteem and feeling of self-worth (P<0.001). Moreover, intrinsic motivation toward accomplishment increased significantly (P<0.001). This is related to the enjoyment of passing academic milestones, and a step ahead of autonomous motivation. Amotivation level declined significantly (P<0.001). The change of academic motivational constructs before and after the intervention was altogether significant (P=0.036, multivariate analysis of variance). After experiencing a three-day intervention, the new students' motivation advanced along the continuum of self-determination toward autonomous motivation. Therefore, it is considered to be worthwhile conducting an academic intervention to catalyze the evolution of preclinical year medical students' academic motivation. Moreover, educators and faculties should evaluate the impact of interventions in evidence-based approaches to secure both controlled and autonomous types of motivation.

The Effect of Visual Information on the Manual Approach and Landing

NASA Technical Reports Server (NTRS)

Wewerinke, P. H.

1982-01-01

The effect of visual information in combination with basic display information on the approach performance. A pre-experimental model analysis was performed in terms of the optimal control model. The resulting aircraft approach performance predictions were compared with the results of a moving base simulator program. The results illustrate that the model provides a meaningful description of the visual (scene) perception process involved in the complex (multi-variable, time varying) manual approach task with a useful predictive capability. The theoretical framework was shown to allow a straight-forward investigation of the complex interaction of a variety of task variables.

Influence of caregiver personality on the burden of family caregivers of terminally ill cancer patients.

PubMed

Kim, Ha-Hyun; Kim, Seon-Young; Kim, Jae-Min; Kim, Sung-Wan; Shin, Il-Seon; Shim, Hyun-Jeong; Hwang, Jun-Eul; Chung, Ik-Joo; Yoon, Jin-Sang

2016-02-01

To determine the influence of caregiver personality and other factors on the burden of family caregivers of terminally ill cancer patients. We investigated a wide range of factors related to the patient-family caregiver dyad in a palliative care setting using a cross-sectional design. Caregiver burden was assessed using the seven-item short version of the Zarit Burden Interview (ZBI-7). Caregiver personality was assessed using the 10-item short version of the Big Five Inventory (BFI-10), which measures the following five personality dimensions: extroversion, agreeableness, conscientiousness, neuroticism, and openness. Patient- and caregiver-related sociodemographic and psychological factors were included in the analysis because of their potential association with caregiver burden. Clinical patient data were obtained from medical charts or by using other measures. Multivariate linear regression analysis was performed to identify the independent factors associated with caregiver burden. We analyzed 227 patient-family caregiver dyads. The multivariate analysis revealed that caregiver extroversion was protective against caregiver burden, whereas depressive symptoms in caregivers were related to increased burden. Neuroticism was positively correlated with caregiver burden, but this relationship was nonsignificant following adjustment for depressive symptoms. Patient-related factors were not significantly associated with caregiver burden. Evaluating caregiver personality traits could facilitate identification of individuals at greater risk of high burden. Furthermore, depression screening and treatment programs for caregivers in palliative care settings are required to decrease caregiver burden.

Cross-sectional survey of workload and burnout among Japanese physicians working in stroke care: the nationwide survey of acute stroke care capacity for proper designation of comprehensive stroke center in Japan (J-ASPECT) study.

PubMed

Nishimura, Kunihiro; Nakamura, Fumiaki; Takegami, Misa; Fukuhara, Schunichi; Nakagawara, Jyoji; Ogasawara, Kuniaki; Ono, Junichi; Shiokawa, Yoshiaki; Miyachi, Shigeru; Nagata, Izumi; Toyoda, Kazunori; Matsuda, Shinya; Kataoka, Hiroharu; Miyamoto, Yoshihiro; Kitaoka, Kazuyo; Kada, Akiko; Iihara, Koji

2014-05-01

Burnout is common among physicians and affects the quality of care. We aimed to determine the prevalence of burnout among Japanese physicians working in stroke care and evaluate personal and professional characteristics associated with burnout. A cross-sectional design was used to develop and distribute a survey to 11 211 physicians. Physician burnout was assessed using the Maslach Burnout Inventory General Survey. The predictors of burnout and the relationships among them were identified by multivariable logistic regression analysis. A total of 2724 (25.3%) physicians returned the surveys. After excluding those who were not working in stroke care or did not complete the survey appropriately, 2564 surveys were analyzed. Analysis of the participants' scores revealed that 41.1% were burned out. Multivariable analysis indicated that number of hours worked per week is positively associated with burnout. Hours slept per night, day-offs per week, years of experience, as well as income, are inversely associated with burnout. Short Form 36 mental health subscale was also inversely associated with burnout. The primary risk factors for burnout are heavy workload, short sleep duration, relatively little experience, and low mental quality of life. Prospective research is required to confirm these findings and develop programs for preventing burnout. © 2014 American Heart Association, Inc.

Overall survival with crizotinib and next-generation ALK inhibitors in ALK-positive non-small-cell lung cancer (IFCT-1302 CLINALK): a French nationwide cohort retrospective study.

PubMed

Duruisseaux, Michaël; Besse, Benjamin; Cadranel, Jacques; Pérol, Maurice; Mennecier, Bertrand; Bigay-Game, Laurence; Descourt, Renaud; Dansin, Eric; Audigier-Valette, Clarisse; Moreau, Lionel; Hureaux, José; Veillon, Remi; Otto, Josiane; Madroszyk-Flandin, Anne; Cortot, Alexis; Guichard, François; Boudou-Rouquette, Pascaline; Langlais, Alexandra; Missy, Pascale; Morin, Franck; Moro-Sibilot, Denis

2017-03-28

Overall survival (OS) with the anaplastic lymphoma kinase (ALK) inhibitor (ALKi) crizotinib in a large population of unselected patients with ALK-positive non-small-cell lung cancer (NSCLC) is not documented. We sought to assess OS with crizotinib in unselected ALK-positive NSCLC patients and whether post-progression systemic treatments affect survival outcomes.ALK-positive NSCLC patients receiving crizotinib in French expanded access programs or as approved drug were enrolled. We collected clinical and survival data, RECIST-defined progressive disease (PD) and post-PD systemic treatment efficacy. We performed multivariable analysis of OS from crizotinib initiation and PD under crizotinib.At time of analysis, 209 (65.7%) of the 318 included patients had died. Median OS with crizotinib was 16.6 months. The line of crizotinib therapy did not impact survival outcomes. Of the 263 patients with PD, 105 received best supportive care, 74 subsequent drugs other than next-generation ALKi and 84 next-generation ALKi. Next-generation ALKi treatment correlated with better survival outcomes in multivariate analysis. These patients had a median post-PD survival of 25.0 months and median OS from metastatic disease diagnosis of 89.6 months.Unselected ALK-positive NSCLC patients achieve good survival outcomes with crizotinib therapy. Next-generation ALKi may provide survival improvement after PD under crizotinib.

[Related factors in the elderly's use of municipal institutions: basic study for promoting participation in a care prevention program].

PubMed

Hirai, Hiroshi; Kondo, Katsunori

2008-01-01

This study was performed to examine factors related to the use of municipal institutions with the focus on 'Accessibility'. The data used in this analysis were from the AGES (Aichi Gerontological Evaluation Study) Project, conducted by Nihon Fukushi University located in Aichi Prefecture, Japan. A self-administrated questionnaires was mailed to 5,759 persons aged 65 years and older who were not disabled in 2006, and 2,795 persons responded. A dependent variable in the analysis was the use of municipal institutions (a Public Health Center, Welfare Center for the elderly and City Hall). Independent variables were age, disease, employment status, IADL (instrumental activities of daily living), depression (GDS: geriatric depression scale), self-rated feeling of health and 'Accessibility' (transportation mode and distance from municipal institutions). Multivariate logistic analysis was used to provide adjusted relative risk estimates for the associations between use of municipal institutions and related factors. In multivariate logistic analysis, 'Accessibility' showed a significant relative risk for the use of municipal institutions after controlling for other related factors. Compared with the elderly whose places of residence was located less than 250 meters from the municipal institutions, the relative risk for the elderly who resided more than 1,500 meters from the municipal institutions was around 0.4 (male: RR = 0.358; female: RR = 0.378). 'Accessibility' is significantly related to the use of municipal institutions. To promote use of the municipal institutions, improving elderly access may well be effective.

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study.

PubMed

El-Sayed, Mohamed I; Ali, Amany M; Sayed, Heba A; Zaky, Eman M

2010-12-24

We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS) rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68%) presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered.

Awareness of pharmaceutical cost-assistance programs among inner-city seniors.

PubMed

Federman, Alex D; Safran, Dana Gelb; Keyhani, Salomeh; Cole, Helen; Halm, Ethan A; Siu, Albert L

2009-04-01

Lack of awareness may be a significant barrier to participation by low- and middle-income seniors in pharmaceutical cost-assistance programs. The goal of this study was to determine whether older adults' awareness of 2 major state and federal pharmaceutical cost-assistance programs was associated with the seniors' ability to access and process information about assistance programs. Data were gathered from a cross-sectional study of independently living, English- or Spanish-speaking adults aged > or =60 years. Participants were interviewed in 30 community-based settings (19 apartment complexes and 11 senior centers) in New York, New York. The analysis focused on adults aged > or =65 years who lacked Medicaid coverage. Multivariable logistic regression was used to model program awareness as a function of information access (family/social support, attendance at senior or community centers and places of worship, viewing of live health insurance presentations, instrumental activities of daily living, site of medical care, computer use, and having a proxy decision maker for health insurance matters) and information-processing ability (education level, English proficiency, health literacy, and cognitive function). The main outcome measure was awareness of New York's state pharmaceutical assistance program (Elderly Pharmaceutical Insurance Coverage [EPIC

MULTIVARIATE CURVE RESOLUTION OF NMR SPECTROSCOPY METABONOMIC DATA

EPA Science Inventory

Sandia National Laboratories is working with the EPA to evaluate and develop mathematical tools for analysis of the collected NMR spectroscopy data. Initially, we have focused on the use of Multivariate Curve Resolution (MCR) also known as molecular factor analysis (MFA), a tech...

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Characteristics of Inpatient Units Associated With Sustained Hand Hygiene Compliance.

PubMed

Wolfe, Jonathan D; Domenico, Henry J; Hickson, Gerald B; Wang, Deede; Dubree, Marilyn; Feistritzer, Nancye; Wells, Nancy; Talbot, Thomas R

2018-04-20

Following institution of a hand hygiene (HH) program at an academic medical center, HH compliance increased from 58% to 92% for 3 years. Some inpatient units modeled early, sustained increases, and others exhibited protracted improvement rates. We examined the association between patterns of HH compliance improvement and unit characteristics. Adult inpatient units (N = 35) were categorized into the following three tiers based on their pattern of HH compliance: early adopters, nonsustained and late adopters, and laggards. Unit-based culture measures were collected, including nursing practice environment scores (National Database of Nursing Quality Indicators [NDNQI]), patient rated quality and teamwork (Hospital Consumer Assessment of Healthcare Provider and Systems), patient complaint rates, case mix index, staff turnover rates, and patient volume. Associations between variables and the binary outcome of laggard (n = 18) versus nonlaggard (n = 17) were tested using a Mann-Whitney U test. Multivariate analysis was performed using an ordinal regression model. In direct comparison, laggard units had clinically relevant differences in NDNQI scores, Hospital Consumer Assessment of Healthcare Provider and Systems scores, case mix index, patient complaints, patient volume, and staff turnover. The results were not statistically significant. In the multivariate model, the predictor variables explained a significant proportion of the variability associated with laggard status, (R = 0.35, P = 0.0481) and identified NDNQI scores and patient complaints as statistically significant. Uptake of an HH program was associated with factors related to a unit's safety culture. In particular, NDNQI scores and patient complaint rates might be used to assist in identifying units that may require additional attention during implementation of an HH quality improvement program.

MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics.

PubMed

Tsugawa, Hiroshi; Arita, Masanori; Kanazawa, Mitsuhiro; Ogiwara, Atsushi; Bamba, Takeshi; Fukusaki, Eiichiro

2013-05-21

We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.

Expanding school-district/university partnerships to advance health promoting schools implementation and efficacy in Taiwan.

PubMed

Liu, Chieh-Hsing; Chang, Fong-Ching; Liao, Li-Ling; Niu, Yu-Zhen; Cheng, Chi-Chia; Shih, Shu-Fang; Chang, Tzu-Chau; Chou, Hsin-Pei

2015-08-01

In 2011, the Taiwan government expanded its support of school-district/university partnership programs that promote the implementation of the evidenced-based Health Promoting Schools (HPS) program. This study examined whether expanding the support for this initiative was effective in advancing HPS implementation, perceived HPS impact and perceived HPS efficacy in Taiwan. In 2011 and 2013, a total of 647 and 1195 schools, respectively, complemented the questionnaire. Univariate analysis results indicated that the HPS implementation levels for six components were significantly increased from 2011 to 2013. These components included school health policies, physical environment, social environment, teaching activities and school-community relationships. Participant teachers also reported significantly greater levels of perceived HPS impact and HPS efficacy after the expansion of support for school-district/university partnership programs. Multivariate analysis results indicated that after controlling for school level, HPS funding and HPS action research approach variables, the expansion had a positive impact on increasing the levels of HPS implementation, perceived HPS impact and perceived HPS efficacy. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Multivariate data analysis methods for the interpretation of microbial flow cytometric data.

PubMed

Davey, Hazel M; Davey, Christopher L

2011-01-01

Flow cytometry is an important technique in cell biology and immunology and has been applied by many groups to the analysis of microorganisms. This has been made possible by developments in hardware that is now sensitive enough to be used routinely for analysis of microbes. However, in contrast to advances in the technology that underpin flow cytometry, there has not been concomitant progress in the software tools required to analyse, display and disseminate the data and manual analysis, of individual samples remains a limiting aspect of the technology. We present two new data sets that illustrate common applications of flow cytometry in microbiology and demonstrate the application of manual data analysis, automated visualisation (including the first description of a new piece of software we are developing to facilitate this), genetic programming, principal components analysis and artificial neural nets to these data. The data analysis methods described here are equally applicable to flow cytometric applications with other cell types.

Measurement Quality of the Chinese Early Childhood Program Rating Scale: An Investigation Using Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Chen, Dezhi; Hu, Bi Ying; Fan, Xitao; Li, Kejian

2014-01-01

Adapted from the Early Childhood Environment Rating Scale-Revised, the Chinese Early Childhood Program Rating Scale (CECPRS) is a culturally comparable measure for assessing the quality of early childhood education and care programs in the Chinese cultural/social contexts. In this study, 176 kindergarten classrooms were rated with CECPRS on eight…

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Moving beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis

ERIC Educational Resources Information Center

Barton, Mitch; Yeatts, Paul E.; Henson, Robin K.; Martin, Scott B.

2016-01-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Multivariate statistical analysis of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Caramelo, Liliana; Pereira, Mário

2013-04-01

Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Assessment of the influence of test characteristics on the clinical and cost impacts of methicillin-resistant Staphylococcus aureus screening programs in US hospitals.

PubMed

Olchanski, Natalia; Mathews, Charles; Fusfeld, Lauren; Jarvis, William

2011-03-01

To compare the impacts of different methicillin-resistant Staphylococcus aureus (MRSA) screening test options (eg, polymerase chain reaction [PCR], rapid culture) and program characteristics on the clinical outcomes and budget of a typical US hospital. We developed an Excel-based decision-analytic model, using published literature to calculate and compare hospital costs and MRSA infection rates for PCR- or culture-based MRSA screening and then used multivariate sensitivity analysis to evaluate key variables. Same-day PCR testing for a representative 370-bed teaching hospital in the United States was assessed in different populations (high-risk patients, intensive care unit [ICU] patients, or all patients) and compared with other test options. Different screening program populations (all patients, high-risk patients, ICU patients, or patients with previous MRSA colonization or infection only) represented a potential savings of $12,158-$76,624 per month over no program ($188,618). Analysis of multiple test options in high-risk population screening indicated that same-day PCR testing of high-risk patients resulted in fewer infections over 1,720 patient-days (2.9, compared with 3.5 for culture on selective media and 3.8 for culture on nonselective media) and the lowest total cost ($112,012). The costs of other testing approaches ranged from $113,742 to $123,065. Sensitivity analysis revealed that variations in transmission rate, conversion to infection, prevalence increases, and hospital size are important to determine program impact. Among test characteristics, turnaround time is highly influential. All screening options showed reductions in infection rates and cost impact improvement over no screening program. Among the options, same-day PCR testing for high-risk patients slightly edges out the others in terms of fewest infections and greatest potential cost savings.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Factors associated with no or delayed linkage to care in newly diagnosed human immunodeficiency virus (HIV)-1-infected patients identified by emergency department-based rapid HIV screening programs in two urban EDs.

PubMed

Rothman, Richard E; Kelen, Gabor D; Harvey, Leah; Shahan, Judy B; Hairston, Heather; Burah, Avanthi; Moring-Parris, Daniel; Hsieh, Yu-Hsiang

2012-05-01

The objective was to describe the proportions of successful linkage to care (LTC) and identify factors associated with LTC among newly diagnosed human immunodeficiency virus (HIV)-positive patients, from two urban emergency department (ED) rapid HIV screening programs. This was a retrospective analysis of programmatic data from two established urban ED rapid HIV screening programs between November 2005 and October 2009. Trained HIV program assistants interviewed all patients tested to gather risk behavior data using a structured data collection instrument. Reactive results were confirmed by Western blot testing. Patients were provided with scheduled appointments at HIV specialty clinics at the institutions where they tested positive within 30 days of their ED visit. "Successful" LTC was defined as attendance at the HIV outpatient clinic within 30 days after HIV diagnosis, in accordance with the ED National HIV Testing Consortium metric. "Any" LTC was defined as attendance at the outpatient HIV clinic within 1 year of initial HIV diagnosis. Multivariate logistic regression was performed to determine factors associated with any LTC or successful LTC. Of the 15,640 tests administered, 108 (0.7%) were newly identified HIV-positive cases. Nearly half (47.2%) of the patients had been previously tested for HIV. Successful LTC occurred in 54% of cases; any LTC occurred in 83% of cases. In multivariate analysis, having public medical insurance and being self-pay were negatively associated with successful LTC (odds ratio [OR] = 0.33, 95% confidence interval [CI] = 0.12 to 0.96; OR = 0.34, 95% CI = 0.13 to 0.89, respectively); being female and having previously tested for HIV was negatively associated with any LTC (OR = 0.30, 95% CI = 0.10 to 0.93; OR = 0.23, 95% CI = 0.07 to 0.77, respectively). In spite of dedicated resources for arranging LTC in the ED HIV testing programs, nearly 50% of patients did not have successful LTC (i.e., LTC occurred at >30 days), although >80% of patients were LTC within 1 year of initial diagnosis. Further evaluation of the barriers associated with successful LTC for those with public insurance and self-pay is warranted. © 2012 by the Society for Academic Emergency Medicine.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Racial and Ethnic Differences in Patient Navigation: Results from the Patient Navigation Research Program

PubMed Central

Ko, Naomi Y; Snyder, Frederick R; Raich, Peter C; Paskett, Electra D.; Dudley, Donald; Lee, Ji-Hyun; Levine, Paul H.; Freund, Karen M

2016-01-01

Purpose Patient navigation was developed to address barriers to timely care and reduce cancer disparities. This study explores navigation and racial and ethnic differences in time to diagnostic resolution of a cancer screening abnormality. Patients and Methods We conducted an analysis of the multi-site Patient Navigation Research Program. Participants with an abnormal cancer screening test were allocated to either navigation or control. Unadjusted median time to resolution was calculated for each racial and ethnic group by navigation and control. Multivariable Cox proportional hazards models were fit, adjusting for sex, age, cancer abnormality type, and health insurance, stratifying by center of care. Results Among a sample of 7,514 participants, 29% were Non-Hispanic White, 43% Hispanic, and 28% Black. In the control group Blacks had a longer median time to diagnostic resolution (108 days) than Non-Hispanic Whites (65 days) or Hispanics (68 days) (p< .0001). In the navigated groups, Blacks had a reduction in median time to diagnostic resolution (97 days) (p <.0001). In the multivariable models, among controls, Black race was associated with increased delay to diagnostic resolution (HR=0.77; 95% CI: 0.69, 0.84) compared to the Non-Hispanic Whites, which was reduced in the navigated arm (HR=0.85; 95% CI: 0.77, 0.94). Conclusion Patient navigation had its greatest impact for Black patients who had the greatest delays in care. PMID:27227342

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

of Likelihood Criteria for I)fferent Hypotheses," in P. A. Krishnaiah (Ed.), Multivariate Analysis-Il, New York: Academic Press. [5] Fisher, R. A...Methods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), rultivariate Analysis-Il, New York: Academic Press. [8) Kendall, M. G. (1966...1982), Applied Multivariate Statisti- cal-Analysis, Englewood Cliffs: Prentice-Mall, Inc. [1U] Krishnaiah , P. R. (1969), "Simultaneous Test

Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis

NASA Astrophysics Data System (ADS)

Almerico, Anna Maria; Tutone, Marco; Lauria, Antonino

2008-05-01

In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.

SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

EPA Science Inventory

Recent work in factor analysis of multivariate data sets has shown that variables with little signal should not be included in the factor analysis. Work also shows that rotational ambiguity is reduced if sources impacting a receptor have both large and small contributions. Thes...

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

The Perseus computational platform for comprehensive analysis of (prote)omics data.

PubMed

Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

2016-09-01

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Workforce Characteristics and Attitudes Regarding Participation in Worksite Wellness Programs.

PubMed

Hall, Jennifer L; Kelly, Kevin M; Burmeister, Leon F; Merchant, James A

2017-09-01

To estimate workforce participation characteristics and employees' attitudes regarding participation in workplace wellness programs. Data from a statewide stratified random sample were used to compare small (<50 employees) and larger (50+ employees) workplaces to estimate participation in screening programs and likelihood of participation in workplace wellness programs. A telephone survey of employed Iowans registered to vote. Surveyed were 1171 employed Iowans registered to vote, ages 18 to 65. Among questionnaire survey modules were items from the Wellness Council of America Employee Needs and Interest Survey, the U.S. Census Bureau for employment documentation, and the World Health Organization Health and Work Performance Questionnaire for assessment of sickness absenteeism and presenteeism. Prevalence of participation in screening and wellness programs was analyzed by employment size and levels of likeliness to participate, and multivariable analyses of employee baseline characteristics regarding participation in screening programs and likelihood of participation in wellness programs was presented as top and bottom quartiles. Those employed in smaller workplaces participated less often in screening programs. Multivariable models identified male gender and those with an abnormal body mass index were associated with nonparticipation, while having a primary care physician was associated with participation. Very few items showed significant statistical difference in willingness to participate. Workforce characteristics and access to health care may influence participation in screening and wellness programs. Employment size is not a determining factor for willingness to participate in wellness programs.

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The multivariate approach and physical interpretation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loveday, D.L.; Craggs, C.

Box-Jenkins-based multivariate stochastic modeling is carried out using data recorded from a domestic heating system. The system comprises an air-source heat pump sited in the roof space of a house, solar assistance being provided by the conventional tile roof acting as a radiation absorber. Multivariate models are presented which illustrate the time-dependent relationships between three air temperatures - at external ambient, at entry to, and at exit from, the heat pump evaporator. Using a deterministic modeling approach, physical interpretations are placed on the results of the multivariate technique. It is concluded that the multivariate Box-Jenkins approach is a suitable techniquemore » for building thermal analysis. Application to multivariate Box-Jenkins approach is a suitable technique for building thermal analysis. Application to multivariate model-based control is discussed, with particular reference to building energy management systems. It is further concluded that stochastic modeling of data drawn from a short monitoring period offers a means of retrofitting an advanced model-based control system in existing buildings, which could be used to optimize energy savings. An approach to system simulation is suggested.« less

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

The cost-effectiveness of treating male trichomoniasis to avert HIV transmission in men seeking sexually transmitted disease care in Malawi.

PubMed

Price, Matthew A; Stewart, Scott R; Miller, William C; Behets, Frieda; Dow, William H; Martinson, Francis E A; Chilongozi, David; Cohen, Myron S

2006-10-01

Allocation of funds to program areas where they may have an impact is critical to the success of any HIV control program. We examined the cost-effectiveness of providing first-line treatment for male trichomoniasis in Malawi, a condition not commonly considered in syndromic management throughout sub-Saharan Africa. We used decision tree analysis to assess program costs and outcomes among a 1-year population of male sexually transmitted disease (STD) clinic attendees estimated at 10,000 in Lilongwe. Our main outcomes were program costs from the government perspective and HIV infections averted. We conducted univariate and multivariate sensitivity analyses on selected parameters. In our study population of male STD clinic attendees with an HIV prevalence of 44% and a Trichomonas vaginalis prevalence of 20%, including universal metronidazole as a first-line treatment for trichomoniasis at $0.05 per dose would increase program costs by $277 (year 2000 US dollars) and avert 23 cases of HIV. The incremental cost-effectiveness ratio (ICER) over the current STD management guidelines was $15.42 per case of HIV averted. The number of HIV infections averted under sensitivity analysis ranged from 2 to 52, with attendant ICERs varying from cost savings to $162.92. Consideration of wider social benefits, such as the costs of HIV infections to the individual or the government, would further enhance the cost-effectiveness of this program. As part of a larger program to control STDs, incorporating metronidazole to treat male trichomoniasis could represent a cost-effective means to reduce HIV transmission in this high-risk group.

Exploring Girls' Science Affinities Through an Informal Science Education Program

NASA Astrophysics Data System (ADS)

Todd, Brandy; Zvoch, Keith

2017-10-01

This study examines science interests, efficacy, attitudes, and identity—referred to as affinities, in the context of an informal science outreach program for girls. A mixed methods design was used to explore girls' science affinities before, during, and after participation in a cohort-based summer science camp. Multivariate analysis of survey data revealed that girls' science affinities varied as a function of the joint relationship between family background and number of years in the program, with girls from more affluent families predicted to increase affinities over time and girls from lower income families to experience initial gains in affinities that diminish over time. Qualitative examination of girls' perspectives on gender and science efficacy, attitudes toward science, and elements of science identities revealed a complex interplay of gendered stereotypes of science and girls' personal desires to prove themselves knowledgeable and competent scientists. Implications for the best practice in fostering science engagement and identities in middle school-aged girls are discussed.

Relationship of breastfeeding self-efficacy with quality of life in Iranian breastfeeding mothers.

PubMed

Mirghafourvand, Mojgan; Kamalifard, Mahin; Ranjbar, Fatemeh; Gordani, Nasrin

2017-07-20

Due to the importance of breastfeeding, we decided to conduct a study to examine the relationship between breastfeeding self-efficacy and quality of life. This study was a cross-sectional study, which was carried out on 547 breastfeeding mothers that had 2-6 months old infants. The participants were selected randomly, and the sociodemographic characteristics questionnaire, Dennis' breastfeeding self-efficacy scale, and WHO's Quality of Life (WHOQOL) questionnaire were completed through interview. The multivariate linear regression model was used for data analysis. The means (standard deviations) of breastfeeding self-efficacy score and quality of life score were 134.5 (13.3) and 67.7 (13.7), respectively. Quality of life and all of its dimensions were directly and significantly related to breastfeeding self-efficacy. According to the results of multivariate linear regression analysis, there was a relationship between breastfeeding self-efficacy and the following variables: environmental dimension of quality of life, education, spouse's age, spouse's job, average duration of previous breastfeeding period and receiving breastfeeding training. Findings showed that there is direct and significant relationship between breastfeeding self-efficacy and quality of life. Moreover, it seems that the development of appropriate training programs is necessary for improving the quality of life of pregnant women, as it consequently enhances breastfeeding self-efficacy.

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

PubMed Central

Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto

2013-01-01

Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341

Reasons for job separations in a cohort of workers with psychiatric disabilities.

PubMed

Cook, Judith A; Burke-Miller, Jane K

2015-01-01

We explored the relative effects of adverse working conditions, job satisfaction, wages, worker characteristics, and local labor markets in explaining voluntary job separations (quits) among employed workers with psychiatric disabilities. Data come from the Employment Intervention Demonstration Program in which 2,086 jobs were ended by 892 workers during a 24 mo observation period. Stepped multivariable logistic regression analysis examined the effect of variables on the likelihood of quitting. Over half (59%) of all job separations were voluntary while 41% were involuntary, including firings (17%), temporary job endings (14%), and layoffs (10%). In multivariable analysis, workers were more likely to quit positions at which they were employed for 20 h/wk or less, those with which they were dissatisfied, low-wage jobs, non-temporary positions, and jobs in the structural (construction) occupations. Voluntary separation was less likely for older workers, members of racial and ethnic minority groups, and those residing in regions with lower unemployment rates. Patterns of job separations for workers with psychiatric disabilities mirrored some findings regarding job leaving in the general labor force but contradicted others. Job separation antecedents reflect the concentration of jobs for workers with psychiatric disabilities in the secondary labor market, characterized by low-salaried, temporary, and part-time employment.

The Impact of Metastatic Spinal Tumor Location on 30-Day Perioperative Mortality and Morbidity After Surgical Decompression.

PubMed

Hussain, Awais K; Vig, Khushdeep S; Cheung, Zoe B; Phan, Kevin; Lima, Mauricio C; Kim, Jun S; Kaji, Deepak A; Arvind, Varun; Cho, Samuel Kang-Wook

2018-06-01

A retrospective cohort study from 2011 to 2014 was performed using the American College of Surgeons National Surgical Quality Improvement Program database. The purpose of this study was to assess the impact of tumor location in the cervical, thoracic, or lumbosacral spine on 30-day perioperative mortality and morbidity after surgical decompression of metastatic extradural spinal tumors. Operative treatment of metastatic spinal tumors involves extensive procedures that are associated with significant complication rates and healthcare costs. Past studies have examined various risk factors for poor clinical outcomes after surgical decompression procedures for spinal tumors, but few studies have specifically investigated the impact of tumor location on perioperative mortality and morbidity. We identified 2238 patients in the American College of Surgeons National Surgical Quality Improvement Program database who underwent laminectomy for excision of metastatic extradural tumors in the cervical, thoracic, or lumbosacral spine. Baseline patient characteristics were collected from the database. Univariate and multivariate regression analyses were performed to examine the association between spinal tumor location and 30-day perioperative mortality and morbidity. On univariate analysis, cervical spinal tumors were associated with the highest rate of pulmonary complications. Multivariate regression analysis demonstrated that cervical spinal tumors had the highest odds of multiple perioperative complications. However, thoracic spinal tumors were associated with the highest risk of intra- or postoperative blood transfusion. In contrast, patients with metastatic tumors in the lumbosacral spine had lower odds of perioperative mortality, pulmonary complications, and sepsis. Tumor location is an independent risk factor for perioperative mortality and morbidity after surgical decompression of metastatic spinal tumors. The addition of tumor location to existing prognostic scoring systems may help to improve their predictive accuracy. 3.

Factors predictive of increased influenza and pneumococcal vaccination coverage in long-term care facilities: the CMS-CDC standing orders program Project.

PubMed

Bardenheier, Barbara H; Shefer, Abigail; McKibben, Linda; Roberts, Henry; Rhew, David; Bratzler, Dale

2005-01-01

Between 1999 and 2002, a multistate demonstration project was conducted in long-term care facilities (LTCFs) to encourage implementation of standing orders programs (SOP) as evidence-based vaccine delivery strategies to increase influenza and pneumococcal vaccination coverage in LTCFs. Examine predictors of increase in influenza and pneumococcal vaccination coverage in LTCFs. Intervention study. Self-administered surveys of LTCFs merged with data from OSCAR (On-line Survey Certification and Reporting System) and immunization coverage was abstracted from residents' medical charts in LTCFs. Twenty LTCFs were sampled from 9 intervention and 5 control states in the 2000 to 2001 influenza season for baseline and during the 2001 to 2002 influenza season for postintervention. Each state's quality improvement organization (QIO) promoted the use of standing orders for immunizations as well as other strategies to increase immunization coverage among LTCF residents. Multivariate analysis included Poisson regression to determine independent predictors of at least a 10 percentage-point increase in facility influenza and pneumococcal vaccination coverage. Forty-two (20%) and 59 (28%) of the facilities had at least a 10 percentage-point increase in influenza and pneumococcal immunizations, respectively. In the multivariate analysis, predictors associated with increase in influenza vaccination coverage included adoption of requirement in written immunization protocol to document refusals, less-demanding consent requirements, lower baseline influenza coverage, and small facility size. Factors associated with increase in pneumococcal vaccination coverage included adoption of recording pneumococcal immunizations in a consistent place, affiliation with a multifacility chain, and provision of resource materials. To improve the health of LTCF residents, strategies should be considered that increase immunization coverage, including written protocol for immunizations and documentation of refusals, documenting vaccination status in a consistent place in medical records, and minimal consent requirements for vaccinations.

Sexual attitudes, pattern of communication, and sexual behavior among unmarried out-of-school youth in China.

PubMed

Wang, Bo; Li, Xiaoming; Stanton, Bonita; Kamali, Vafa; Naar-King, Sylvie; Shah, Iqbal; Thomas, Ronald

2007-07-31

In recent years, more adolescents are engaging in premarital sex in China. However, only a limited number of studies have explored out-of-school youth's sexual attitudes and behaviors, critical for prevention intervention development. Using data from the baseline survey of a comprehensive sex education program that was conducted in a suburb of Shanghai in 2000-2002, this study describes sexual attitudes, patterns of communication on sexual matters, and premarital sexual behavior among 1,304 out-of-school youth. Multivariate logistic regression analysis was conducted to examine the factors associated with youth's premarital sexual intercourse. The majority (60%) of out-of-school youth held favorable attitudes towards premarital sex. Males were more likely to have favorable attitudes compared with females. Male youth generally did not communicate with either parent about sex, while one-third of female youth talked to their mothers about sexual matters. Both males and females chose their friends as the person with whom they were most likely to talk about sexual matters. About 18% of the youth reported having engaged in sexual intercourse. One-fifth of sexually active youth had always used a contraceptive method, and one-quarter had been pregnant (or had impregnated a partner). There were no gender differences in rate of premarital sex or frequency of contraceptive use. Multivariate analysis revealed that age, education, family structure, parent's discipline, attitudes towards premarital sex, pattern of communication and dating were significantly associated with youth premarital sex. A substantial proportion of out-of-school youth engage in risky sexual behaviors. Prevention programs that empower communication and sexual negotiation skills, and promote condom use should be implemented for this vulnerable group.

Sexual attitudes, pattern of communication, and sexual behavior among unmarried out-of-school youth in China

PubMed Central

Wang, Bo; Li, Xiaoming; Stanton, Bonita; Kamali, Vafa; Naar-King, Sylvie; Shah, Iqbal; Thomas, Ronald

2007-01-01

Background In recent years, more adolescents are engaging in premarital sex in China. However, only a limited number of studies have explored out-of-school youth's sexual attitudes and behaviors, critical for prevention intervention development. Methods Using data from the baseline survey of a comprehensive sex education program that was conducted in a suburb of Shanghai in 2000–2002, this study describes sexual attitudes, patterns of communication on sexual matters, and premarital sexual behavior among 1,304 out-of-school youth. Multivariate logistic regression analysis was conducted to examine the factors associated with youth's premarital sexual intercourse. Results The majority (60%) of out-of-school youth held favorable attitudes towards premarital sex. Males were more likely to have favorable attitudes compared with females. Male youth generally did not communicate with either parent about sex, while one-third of female youth talked to their mothers about sexual matters. Both males and females chose their friends as the person with whom they were most likely to talk about sexual matters. About 18% of the youth reported having engaged in sexual intercourse. One-fifth of sexually active youth had always used a contraceptive method, and one-quarter had been pregnant (or had impregnated a partner). There were no gender differences in rate of premarital sex or frequency of contraceptive use. Multivariate analysis revealed that age, education, family structure, parent's discipline, attitudes towards premarital sex, pattern of communication and dating were significantly associated with youth premarital sex. Conclusion A substantial proportion of out-of-school youth engage in risky sexual behaviors. Prevention programs that empower communication and sexual negotiation skills, and promote condom use should be implemented for this vulnerable group. PMID:17672903

Has the Pattern of Practice in the Prescription of Radiotherapy for the Palliation of Thoracic Symptoms Changed Between 1999 and 2006 at the Rapid Response Radiotherapy Program?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fairchild, Alysa; Goh, Philiz; Sinclair, Emily

2008-03-01

Purpose: Eleven randomized controlled trials (RCT) comparing various radiotherapy (RT) schedules for locally advanced lung cancer published since 1991 found no difference in palliation of intrathoracic symptoms. The most commonly prescribed schedule by Canadian Radiation Oncologists (RO) (20 Gy in five fractions [20 Gy/5]), when first evaluated versus 10 Gy/1 in a 2002 RCT, showed a significant survival benefit. A subsequent RCT assessing 20 Gy/5 found worse survival versus 16 Gy/2. This study examines whether the RT prescription for lung cancer palliation in the Rapid Response Radiotherapy Program (RRRP) has changed over time. Methods and Materials: Chart review was conductedmore » for patients treated with palliative thoracic RT across three periods (1999-2006). Patient demographics, tumor, treatment, and organizational factors were analyzed descriptively. Chi-square test was used to detect differences in proportions between unordered categorical variables. Continuous variables were tested using analysis of variance. Multivariate logistic regression was used to identify independent predictors of RT schedule prescribed. Results: A total of 117 patients received 121 courses of palliative thoracic RT. The most common dose (20 Gy/5) comprised 65% of courses in 1999, 68% in 2003, and 60% in 2005-2006 (p = 0.76). The next most common dose was 30 Gy/10 (13%). Overall, the median survival was 14.9 months, independent of RT schedule (p = 0.68). Multivariate analysis indicated palliative chemotherapy and certification year of RO were significant predictors of prescription of 20 Gy/5. Conclusion: RT schedule for palliation of intrathoracic symptoms did not mirror the results of sequential, conflicting RCTs, suggesting that factors other than the literature influenced practice patterns in palliative thoracic RT.« less

An Evaluation of h-Index as a Measure of Research Productivity Among Canadian Academic Plastic Surgeons.

PubMed

Hu, Jiayi; Gholami, Arian; Stone, Nicholas; Bartoszko, Justyna; Thoma, Achilleas

2018-02-01

Evaluation of research productivity among plastic surgeons can be complex. The Hirsch index (h-index) was recently introduced to evaluate both the quality and quantity of one's research activity. It has been proposed to be valuable in assessing promotions and grant funding within academic medicine, including plastic surgery. Our objective is to evaluate research productivity among Canadian academic plastic surgeons using the h-index. A list of Canadian academic plastic surgeons was obtained from websites of academic training programs. The h-index was retrieved using the Scopus database. Relevant demographic and academic factors were collected and their effects on the h-index were analyzed using the t test and Wilcoxon Mann-Whitney U test. Nominal and categorical variables were analyzed using χ 2 test and 1-way analysis of variance. Univariate and multivariate models were built a priori. All P values were 2 sided, and P < .05 was considered to be significant. Our study on Canadian plastic surgeons involved 175 surgeons with an average h-index of 7.6. Over 80% of the surgeons were male. Both univariable and multivariable analysis showed that graduate degree ( P < .0001), academic rank ( P = .03), and years in practice ( P < .0001) were positively correlated with h-index. Limitations of the study include that the Scopus database and the websites of training programs were not always up-to-date. The h-index is a novel tool for evaluating research productivity in academic medicine, and this study shows that the h-index can also serve as a useful metric for measuring research productivity in the Canadian plastic surgery community. Plastic surgeons would be wise to familiarize themselves with the h-index concept and should consider using it as an adjunct to existing metrics such as total publication number.

Headspace-programmed temperature vaporization-mass spectrometry for the rapid determination of possible volatile biomarkers of lung cancer in urine.

PubMed

Pérez Antón, Ana; Ramos, Álvaro García; Del Nogal Sánchez, Miguel; Pavón, José Luis Pérez; Cordero, Bernardo Moreno; Pozas, Ángel Pedro Crisolino

2016-07-01

We propose a new method for the rapid determination of five volatile compounds described in the literature as possible biomarkers of lung cancer in urine samples. The method is based on the coupling of a headspace sampler, a programmed temperature vaporizer in solvent-vent injection mode, and a mass spectrometer (HS-PTV-MS). This configuration is known as an electronic nose based on mass spectrometry. Once the method was developed, it was used for the analysis of urine samples from lung cancer patients and healthy individuals. Multivariate calibration models were employed to quantify the biomarker concentrations in the samples. The detection limits ranged between 0.16 and 21 μg/L. For the assignment of the samples to the patient group or the healthy individuals, the Wilcoxon signed-rank test was used, comparing the concentrations obtained with the median of a reference set of healthy individuals. To date, this is the first time that multivariate calibration and non-parametric methods have been combined to classify biological samples from profile signals obtained with an electronic nose. When significant differences in the concentration of one or more biomarkers were found with respect to the reference set, the sample is considered as a positive one and a new analysis was performed using a chromatographic method (HS-PTV-GC/MS) to confirm the result. The main advantage of the proposed HS-PTV-MS methodology is that no prior chromatographic separation and no sample manipulation are required, which allows an increase of the number of samples analyzed per hour and restricts the use of time-consuming techniques to only when necessary. Graphical abstract Schematic diagram of the developed methodology.

The effect of a diabetes collaborative care management program on clinical and economic outcomes in patients with type 2 diabetes.

PubMed

McAdam-Marx, Carrie; Dahal, Arati; Jennings, Brandon; Singhal, Mukul; Gunning, Karen

2015-06-01

Clinical pharmacy services (CPS) in the primary care setting have been shown to help patients attain treatment goals and improve outcomes. However, the availability of CPS in community-based primary care is not widespread. One reason is that current fee-for-service models offer limited reimbursement opportunities for CPS in the community setting. Furthermore, data demonstrating the value of CPS in this setting are limited, making it difficult for providers to determine the feasibility and sustainability of incorporating CPS into primary care practice. To (a) evaluate the association between a pharmacist-led, diabetes collaborative drug therapy management program and patient outcomes, including glycemic control and health care costs, and (b) assess short-term economic outcomes in a primary care setting. A retrospective cohort analysis was conducted using medical record data. This study was conducted using patients with uncontrolled type 2 diabetes (T2DM), defined as HbA1c ≥ 7.0%. Outcomes were compared between patients referred to a diabetes collaborative care management (DCCM) intervention from 2009-2012 and patients who did not participate in the DCCM program. To illustrate the difference in HbA1c between the 2 cohorts over the follow-up period, mean time adjusted HbA1c values were estimated using a panel-type random effects regression model, with results plotted at 90-day intervals from index date through the end of the study period. To help control for confounding by other factors, multivariate regression models were run. A difference-in-difference model was employed to estimate the effect of the program on resource utilization and all-cause charges. A total of 303 DCCM and 394 comparison patients were included. Mean (95% CI) age was 57.4 years (55.963, 58.902) versus 59.9 years (58.613, 61.276; P < 0.001) with 48% and 44% female for DCCM and comparison patients, respectively (P = 0.49). Mean baseline HbA1c was higher for DCCM (10.3%; 10.10, 10.53) than comparison patients (8.4%; 8.26, 8.61; P < 0.001). The greatest reduction in HbA1c was seen for both groups at 9 and 12 months post-index date. At these time points, the mean time adjusted difference in HbA1c between groups was no longer significant. Multivariate modeling identified that the DCCM program was associated with a -0.44% (-0.64, -0.25; P < 0.001) lower HbA1c at follow-up relative to the comparison group controlling for potential confounders, including baseline HbA1c. Change in resource utilization from pre- to post-index date did not differ between groups. However, in the difference-in-difference multivariate analysis the difference in mean all-cause charges from the 12-month pre- to post-index periods DCCM patients experienced a smaller average increase in charges ($250) than comparison patients ($1,341; coefficient = -0.423; 95% CI = -0.779, -0.068). A pharmacist-led diabetes collaborative care management program in a patient-centered primary care setting was associated with significantly better follow-up glycemic control relative to comparison patients. Further, the data suggest that the DCCM program was associated with a less substantial increase in all-cause total costs in patients with uncontrolled T2DM relative to comparison patients, which could translate into reduced costs and improved outcomes to managed care payers.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Nutritional Intervention: A Secondary Analysis of Its Effect on Malnourished Colombian Pre-Schoolers.

ERIC Educational Resources Information Center

Bejar, Isaac I.

1981-01-01

Effects of nutritional supplementation on physical development of malnourished children was analyzed by univariate and multivariate methods for the analysis of repeated measures. Results showed that the nutritional treatment was successful, but it was necessary to resort to the multivariate approach. (Author/GK)

A Multivariate Descriptive Model of Motivation for Orthodontic Treatment.

ERIC Educational Resources Information Center

Hackett, Paul M. W.; And Others

1993-01-01

Motivation for receiving orthodontic treatment was studied among 109 young adults, and a multivariate model of the process is proposed. The combination of smallest scale analysis and Partial Order Scalogram Analysis by base Coordinates (POSAC) illustrates an interesting methodology for health treatment studies and explores motivation for dental…

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Univariate Analysis of Multivariate Outcomes in Educational Psychology.

ERIC Educational Resources Information Center

Hubble, L. M.

1984-01-01

The author examined the prevalence of multiple operational definitions of outcome constructs and an estimate of the incidence of Type I error rates when univariate procedures were applied to multiple variables in educational psychology. Multiple operational definitions of constructs were advocated and wider use of multivariate analysis was…

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Evaluation of Meterorite Amono Acid Analysis Data Using Multivariate Techniques

NASA Technical Reports Server (NTRS)

McDonald, G.; Storrie-Lombardi, M.; Nealson, K.

1999-01-01

The amino acid distributions in the Murchison carbonaceous chondrite, Mars meteorite ALH84001, and ice from the Allan Hills region of Antarctica are shown, using a multivariate technique known as Principal Component Analysis (PCA), to be statistically distinct from the average amino acid compostion of 101 terrestrial protein superfamilies.

MULTIVARIATE ANALYSIS ON LEVELS OF SELECTED METALS, PARTICULATE MATTER, VOC, AND HOUSEHOLD CHARACTERISTICS AND ACTIVITIES FROM THE MIDWESTERN STATES NHEXAS

EPA Science Inventory

Microenvironmental and biological/personal monitoring information were collected during the National Human Exposure Assessment Survey (NHEXAS), conducted in the six states comprising U.S. EPA Region Five. They have been analyzed by multivariate analysis techniques with general ...

Intensive care nurses' knowledge of pressure ulcers: development of an assessment tool and effect of an educational program.

PubMed

Tweed, Carol; Tweed, Mike

2008-07-01

Critically ill patients are at high risk for pressure ulcers. Successful prevention of pressure ulcers requires that caregivers have adequate knowledge of this complication. To assess intensive care nurses' knowledge of pressure ulcers and the impact of an educational program on knowledge levels. A knowledge assessment test was developed. A cohort of registered nurses in a tertiary referral hospital in New Zealand had knowledge assessed 3 times: before an educational program, within 2 weeks after the program, and 20 weeks later. Multivariate analysis was performed to determine if attributes such as length of time since qualifying or level of intensive care unit experience were associated with test scores. The content and results of the assessment test were evaluated. Completion of the educational program resulted in improved levels of knowledge. Mean scores on the assessment test were 84% at baseline and 89% following the educational program. The mean baseline score did not differ significantly from the mean 20-week follow-up score of 85%. No association was detected between demographic data and test scores. Content validity and standard setting were verified by using a variety of methods. Levels of knowledge to prevent and manage pressure ulcers were good initially and improved with an educational program, but soon returned to baseline.

Job satisfaction and retention of community nutrition educators: the importance of perceived value of the program, consultative supervision, and work relationships.

PubMed

Dickin, Katherine L; Dollahite, Jamie S; Habicht, Jean-Pierre

2010-01-01

To investigate how paraprofessional Community Nutrition Educators' (CNEs') perceptions of work context relate to job satisfaction and intention to leave the position. Cross-sectional statewide survey of program personnel. Expanded Food and Nutrition Education Program (EFNEP) sites (n = 32) serving low- income families in New York. CNEs delivering EFNEP (n = 115). CNE job satisfaction and intention to leave. Multivariate regression analysis predicting work attitudes from perceived work context, CNE personality traits, and characteristics of CNEs, supervisors, and programs. Despite low satisfaction with pay, overall job satisfaction was high and intention to leave was low. Satisfaction was positively related to CNEs' perceptions of program value, work relationships, and having a voice in relevant decisions (adjusted R(2) = 0.60). Intention to leave was negatively related to perceptions of program value and supervision and satisfaction with pay (adjusted R(2) = 0.36), but the latter relationship was found only among more educated CNEs. CNEs' satisfaction and intention to leave were strongly associated with perceptions of program value, work relationships, and consultative management. Intrinsically motivating work, often viewed as the domain of professionals, is critical for the morale and retention of paraprofessional nutrition educators. Copyright 2010 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

Stature and jumping height are required in female volleyball, but motor coordination is a key factor for future elite success.

PubMed

Pion, Johan A; Fransen, Job; Deprez, Dieter N; Segers, Veerle I; Vaeyens, Roel; Philippaerts, Renaat M; Lenoir, Matthieu

2015-06-01

It was hypothesized that differences in anthropometry, physical performance, and motor coordination would be found between Belgian elite and sub-elite level female volleyball players using a retrospective analysis of test results gathered over a 5-year period. The test sample in this study consisted of 21 young female volleyball players (15.3 ± 1.5 years) who were selected to train at the Flemish Top Sports Academy for Volleyball in 2008. All players (elite, n = 13; sub-elite, n = 8) were included in the same talent development program, and the elite-level athletes were of a high to very high performance levels according to European competition level in 2013. Five multivariate analyses of variance were used. There was no significant effect of playing level on measures of anthropometry (F = 0.455, p = 0.718, (Equation is included in full-text article.)= 0.07), flexibility (F = 1.861, p = 0.188, (Equation is included in full-text article.)= 0.19), strength (F = 1.218, p = 0.355, (Equation is included in full-text article.)= 0.32); and speed and agility (F = 1.176, p = 0.350, (Equation is included in full-text article.)= 0.18). Multivariate analyses of variance revealed significant multivariate effects between playing levels for motor coordination (F = 3.470, p = 0.036, (Equation is included in full-text article.)= 0.59). A Mann-Whitney U test and a sequential discriminant analysis confirmed these results. Previous research revealed that stature and jump height are prerequisites for talent identification in female volleyball. In addition, the results show that motor coordination is an important factor in determining inclusion into the elite level in female volleyball.

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

Enhanced ID Pit Sizing Using Multivariate Regression Algorithm

NASA Astrophysics Data System (ADS)

Krzywosz, Kenji

2007-03-01

EPRI is funding a program to enhance and improve the reliability of inside diameter (ID) pit sizing for balance-of plant heat exchangers, such as condensers and component cooling water heat exchangers. More traditional approaches to ID pit sizing involve the use of frequency-specific amplitude or phase angles. The enhanced multivariate regression algorithm for ID pit depth sizing incorporates three simultaneous input parameters of frequency, amplitude, and phase angle. A set of calibration data sets consisting of machined pits of various rounded and elongated shapes and depths was acquired in the frequency range of 100 kHz to 1 MHz for stainless steel tubing having nominal wall thickness of 0.028 inch. To add noise to the acquired data set, each test sample was rotated and test data acquired at 3, 6, 9, and 12 o'clock positions. The ID pit depths were estimated using a second order and fourth order regression functions by relying on normalized amplitude and phase angle information from multiple frequencies. Due to unique damage morphology associated with the microbiologically-influenced ID pits, it was necessary to modify the elongated calibration standard-based algorithms by relying on the algorithm developed solely from the destructive sectioning results. This paper presents the use of transformed multivariate regression algorithm to estimate ID pit depths and compare the results with the traditional univariate phase angle analysis. Both estimates were then compared with the destructive sectioning results.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Intelligent peak deconvolution through in-depth study of the data matrix from liquid chromatography coupled with a photo-diode array detector applied to pharmaceutical analysis.

PubMed

Arase, Shuntaro; Horie, Kanta; Kato, Takashi; Noda, Akira; Mito, Yasuhiro; Takahashi, Masatoshi; Yanagisawa, Toshinobu

2016-10-21

Multivariate curve resolution-alternating least squares (MCR-ALS) method was investigated for its potential to accelerate pharmaceutical research and development. The fast and efficient separation of complex mixtures consisting of multiple components, including impurities as well as major drug substances, remains a challenging application for liquid chromatography in the field of pharmaceutical analysis. In this paper we suggest an integrated analysis algorithm functioning on a matrix of data generated from HPLC coupled with photo-diode array detector (HPLC-PDA) and consisting of the mathematical program for the developed multivariate curve resolution method using an expectation maximization (EM) algorithm with a bidirectional exponentially modified Gaussian (BEMG) model function as a constraint for chromatograms and numerous PDA spectra aligned with time axis. The algorithm provided less than ±1.0% error between true and separated peak area values at resolution (R s ) of 0.6 using simulation data for a three-component mixture with an elution order of a/b/c with similarity (a/b)=0.8410, (b/c)=0.9123 and (a/c)=0.9809 of spectra at peak apex. This software concept provides fast and robust separation analysis even when method development efforts fail to achieve complete separation of the target peaks. Additionally, this approach is potentially applicable to peak deconvolution, allowing quantitative analysis of co-eluted compounds having exactly the same molecular weight. This is complementary to the use of LC-MS to perform quantitative analysis on co-eluted compounds using selected ions to differentiate the proportion of response attributable to each compound. Copyright © 2016 Elsevier B.V. All rights reserved.

Seasonal assessment and apportionment of surface water pollution using multivariate statistical methods: Sinos River, southern Brazil.

PubMed

Alves, Darlan Daniel; Riegel, Roberta Plangg; de Quevedo, Daniela Müller; Osório, Daniela Montanari Migliavacca; da Costa, Gustavo Marques; do Nascimento, Carlos Augusto; Telöken, Franko

2018-06-08

Assessment of surface water quality is an issue of currently high importance, especially in polluted rivers which provide water for treatment and distribution as drinking water, as is the case of the Sinos River, southern Brazil. Multivariate statistical techniques allow a better understanding of the seasonal variations in water quality, as well as the source identification and source apportionment of water pollution. In this study, the multivariate statistical techniques of cluster analysis (CA), principal component analysis (PCA), and positive matrix factorization (PMF) were used, along with the Kruskal-Wallis test and Spearman's correlation analysis in order to interpret a water quality data set resulting from a monitoring program conducted over a period of almost two years (May 2013 to April 2015). The water samples were collected from the raw water inlet of the municipal water treatment plant (WTP) operated by the Water and Sewage Services of Novo Hamburgo (COMUSA). CA allowed the data to be grouped into three periods (autumn and summer (AUT-SUM); winter (WIN); spring (SPR)). Through the PCA, it was possible to identify that the most important parameters in contribution to water quality variations are total coliforms (TCOLI) in SUM-AUT, water level (WL), water temperature (WT), and electrical conductivity (EC) in WIN and color (COLOR) and turbidity (TURB) in SPR. PMF was applied to the complete data set and enabled the source apportionment water pollution through three factors, which are related to anthropogenic sources, such as the discharge of domestic sewage (mostly represented by Escherichia coli (ECOLI)), industrial wastewaters, and agriculture runoff. The results provided by this study demonstrate the contribution provided by the use of integrated statistical techniques in the interpretation and understanding of large data sets of water quality, showing also that this approach can be used as an efficient methodology to optimize indicators for water quality assessment.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Associations among school characteristics and foodservice practices in a nationally representative sample of United States schools.

PubMed

Thomson, Jessica L; Tussing-Humphreys, Lisa M; Martin, Corby K; LeBlanc, Monique M; Onufrak, Stephen J

2012-01-01

Determine school characteristics associated with healthy/unhealthy food service offerings or healthy food preparation practices. Secondary analysis of cross-sectional data. Nationally representative sample of public and private elementary, middle, and high schools. Data from the 2006 School Health Policies and Practices Study Food Service School Questionnaire, n = 526 for Healthy and Unhealthy Offerings analysis; n = 520 for Healthy Preparation analysis. Scores for healthy/unhealthy foodservice offerings and healthy food preparation practices. Multivariable regression to determine significant associations among school characteristics and offerings/preparation practices. Public schools and schools participating in the United States Department of Agriculture (USDA) Team Nutrition reported more healthy offerings and preparation than private or nonparticipating schools, respectively. Elementary schools reported fewer unhealthy offerings than middle or high schools; middle schools reported fewer unhealthy offerings than high schools. Schools requiring foodservice managers to have a college education reported more healthy preparation, whereas those requiring completion of a foodservice training program reported fewer unhealthy offerings and more healthy preparation than schools without these requirements. Results suggest the school nutrition environment may be improved by requiring foodservice managers to hold a nutrition-related college degree and/or successfully pass a foodservice training program, and by participating in a school-based nutrition program, such as USDA Team Nutrition. Copyright © 2012 Society for Nutrition Education and Behavior. All rights reserved.

Outcomes and lessons learned from evaluating TRICARE's disease management programs.

PubMed

Dall, Timothy M; Askarinam Wagner, Rachel C; Zhang, Yiduo; Yang, Wenya; Arday, David R; Gantt, Cynthia J

2010-06-01

To share outcomes and lessons learned from an evaluation of disease management (DM) programs for asthma, congestive heart failure (CHF), and diabetes for TRICARE patients. Multiyear evaluation of participants in voluntary, opt-out DM programs. Patient-centered programs, administered by 3 regional contractors, provide phone-based consultations with a care manager, educational materials, and newsletters. The study sample consisted of 23,793 asthma, 4092 CHF, and 29,604 diabetes patients with at least 6 months' tenure in the program. Medical claims were analyzed to quantify program effect on healthcare utilization, medical costs, and clinical outcomes. Multivariate regression analysis with an historical control group was used to predict patient outcomes in the absence of DM. The difference between actual and predicted DM patient outcomes was attributed to the program. A patient survey collected data on program satisfaction and perceived usefulness of program information and services. Modest improvements in patient outcomes included reduced inpatient days and medical costs, and (with few exceptions) increased percentages of patients receiving appropriate medications and tests. Annual per patient reductions in medical costs were $453, $371, and $783 for asthma, CHF, and diabetes program participants, respectively. The estimated return on investment was $1.26 per $1.00 spent on DM services. Findings suggest that the DM programs more than pay for themselves, in addition to improving patient health and quality of life. Lessons learned in program design, implementation, effectiveness, and evaluation may benefit employers contemplating DM, DM providers, and evaluators of DM programs.

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

principle, Applications of Statistics, P. R. Krishnaiah , ed., North-Holland: Amsterdam, 27-41. Anderson, T. W. (1971). The Statistical Analysis of Time Series...E. (1969). Multiple Time Series Modeling, Multivariate Analysis II, edited by P. Krishnaiah , Academic Press: New York, 389-409. Parzen, E. (1981...Newton, H. J. (1980). Multiple Time Series Modeling, II Multivariate Analysis - V, edited by P. Krishnaiah , North Holland: Amsterdam, 181-197. Shibata, R

Genomic Analysis of Complex Microbial Communities in Wounds

DTIC Science & Technology

2012-01-01

thoroughly in the ecology literature. Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no...difference between the bacterial communities found within a single wound compared to those from different patients (α = 0.05). PerMANOVA is a...permutation-based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and

Quantifying Preferences of Farmers and Veterinarians for National Animal Health Programs: The Example of Bovine Mastitis and Antimicrobial Usage in Switzerland

PubMed Central

van den Borne, Bart H. P.; van Soest, Felix J. S.; Reist, Martin; Hogeveen, Henk

2017-01-01

Bovine udder health in Switzerland is of a relatively high level. However, antimicrobial usage (AMU) seems high in comparison to other European countries also. A new udder health and AMU improvement program could improve this situation but it is uncertain whether there is support from the field. This study aimed to quantify preferences of dairy farmers and veterinarians for the start and design characteristics of a new national udder health and AMU improvement program in Switzerland. A total of 478 dairy farmers and 98 veterinarians completed an online questionnaire. Questions on their demographics and their mindset toward AMU were complemented with an adaptive choice-based conjoint interview, a novel conjoint analysis technique to quantify preferences of respondents for characteristics of a product for which multiple trade-off decisions must be made (here a bovine udder health and AMU improvement program). The conjoint analysis was followed by a multivariate multiple regression analysis to identify groups of respondents with different program design preferences. Logistic regression models were used to associate covariates with respondents’ preference to start a new udder health and AMU improvement program. Most farmers (55%) and veterinarians (62%) were in favor of starting a new voluntary udder health and AMU improvement program, but the program design preferences agreed moderately between the two stakeholder groups. Farmers preferred an udder health and AMU improvement program that did not contain a penalty system for high AMU, was voluntary for all dairy herds, and aimed to simultaneously improve udder health and reduce AMU. Veterinarians preferred a program that had the veterinary organization and the government taking the lead in program design decision making, did not contain a penalty system for high AMU, and aimed to simultaneously improve udder health and reduce AMU. Differences between groups of farmers and veterinarians concerning their start preference were identified. Also, the magnitude of various program design preferences changed for farmers with different opinions toward AMU. The information obtained from this study may support the decision-making process and the communication to the field afterward, when discussing national strategies to improve udder health and AMU in Switzerland. PMID:28626750

Estimating family planning program effects on U.S. fertility rates.

PubMed

Cutright, P; Jaffe, F S

1977-08-01

An evaluation was undertaken of the effects on U. S. fertility rates of the national family planning program. 1968-1969 family planning enrollment data were linked to 1970 census data in the same areas to derive an objective measure of the impact of organized clinical family planning programs on the 1969-70 fertility rates of subgroups of women defined by age, race, marital status, economic status, and racial composition of their area. Multivariate modelling was used to control for spurious effects of irrelevant variables. Results of the multivariate modelling show significant reductions of marital fertility among the low socioeconomic groups served by the program; no effects were exhibited by groups not served. Cumulative fertility of all groups, black and white, at all age and socioeconomic levels was affected by the program. A plausible explanation for these results lies in antecedent factors which led to the presence or absence of family planning clinics in any particular area in 1969 and its 1969 enrollment level. Communities more favorably disposed to provision of birth control services would have been more likely than other areas to apply for federal funding of family planning programs when it became available in the middle 1960s. Due to an earlier start, their programs were flourishing by 1969.

New standard measures for clinical voice analysis include high speed films

NASA Astrophysics Data System (ADS)

Pedersen, Mette; Munch, Kasper

2012-02-01

In the clinical work with patients in a medical voice clinic it is important to have a normal updated reference for the data used. Several new parameters have to be correlated to older traditional measures. The older ones are stroboscopy, eventually coordinated with electroglottography (EGG), the Multi- Dimensional-Voice Program and airflow rates. Long Time Averaged Spectrograms (LTAS) and phonetograms (voice profiles) are calculating the range and dynamics of tones of the patients. High-speed films, updated airflow measures as well as area calculations of phonotograms add information to the understanding of the glottis closure in single movements of the vocal cords. A multivariate analysis was made to study the connection between the measures. This information can be used in many connections, also in the otolaryngological clinic.

CAVIAR: a serial ECG processing system for the comparative analysis of VCGs and their interpretation with auto-reference to the patient.

PubMed

Fayn, J; Rubel, P

1988-01-01

The authors present a new computer program for serial ECG analysis that allows a direct comparison of any couple of three-dimensional ECGs and quantitatively assesses the degree of evolution of the spatial loops as well as of their initial, central, or terminal sectors. Loops and sectors are superposed as best as possible, with the aim of overcoming tracing variability of nonpathological origin. As a result, optimal measures of evolution are computed and a tabular summary of measurements is dynamically configured with respect to the patient's history and is then printed. A multivariate classifier assigns each couple of tracings to one of four classes of evolution. Color graphic displays corresponding to several modes of representation may also be plotted.

In situ X-ray diffraction analysis of (CF x) n batteries: signal extraction by multivariate analysis

DOE PAGES

Rodriguez, Mark A.; Keenan, Michael R.; Nagasubramanian, Ganesan

2007-11-10

In this study, (CF x) n cathode reaction during discharge has been investigated using in situ X-ray diffraction (XRD). Mathematical treatment of the in situ XRD data set was performed using multivariate curve resolution with alternating least squares (MCR–ALS), a technique of multivariate analysis. MCR–ALS analysis successfully separated the relatively weak XRD signal intensity due to the chemical reaction from the other inert cell component signals. The resulting dynamic reaction component revealed the loss of (CF x) n cathode signal together with the simultaneous appearance of LiF by-product intensity. Careful examination of the XRD data set revealed an additional dynamicmore » component which may be associated with the formation of an intermediate compound during the discharge process.« less

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Evaluation of objective structured clinical examination for advanced orthodontic education 12 years after introduction.

PubMed

Fields, Henry W; Kim, Do-Gyoon; Jeon, Minjeong; Firestone, Allen R; Sun, Zongyang; Shanker, Shiva; Mercado, Ana M; Deguchi, Toru; Vig, Katherine W L

2017-05-01

Advanced education programs in orthodontics must ensure student competency in clinical skills. An objective structure clinical examination has been used in 1 program for over a decade. The results were analyzed cross-sectionally and longitudinally to provide insights regarding the achievement of competency, student growth, question difficulty, question discrimination, and question predictive ability. In this study, we analyzed 218 (82 first-year, 68 second-year, and 68 third-year classes) scores of each station from 85 orthodontic students. The grades originated from 13 stations and were collected anonymously for 12 consecutive years during the first 2 decades of the 2000s. The stations tested knowledge and skills regarding dental relationships, analyzing a cephalometric tracing, performing a diagnostic skill, identifying cephalometric points, bracket placement, placing first-order and second-order bends, forming a loop, placing accentuated third-order bends, identifying problems and planning mixed dentition treatment, identifying problems and planning adolescent dentition treatment, identifying problems and planning nongrowing skeletal treatment, superimposing cephalometric tracings, and interpreting cephalometric superimpositions. Results were evaluated using multivariate analysis of variance, chi-square tests, and latent growth analysis. The multivariate analysis of variance showed that all stations except 3 (analyzing a cephalometric tracing, forming a loop, and identifying cephalometric points) had significantly lower mean scores for the first-year student class than the second- and third-year classes (P <0.028); scores between the second- and third-year student classes were not significantly different (P >0.108). The chi-square analysis of the distribution of the number of noncompetent item responses decreased from the first to the second years (P <0.0003), from the second to the third years (P <0.0042), and from the first to the third years (P <0.00003). The latent growth analysis showed a wide range of difficulty and discrimination between questions. It also showed continuous growth for some areas and the ability of 6 questions to predict competency at greater than the 80% level. Objective structure clinical examinations can provide a method of evaluating student performance and curriculum impact over time, but cross-sectional and longitudinal analyses of the results may not be complementary. Significant learning appears to occur during all years of a 3-year program. Valuable questions were both easy and difficult, discriminating and not discriminating, and came from all domains: diagnostic, technical, and evaluation/synthesis. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

The association between body mass index and severe biliary infections: a multivariate analysis.

PubMed

Stewart, Lygia; Griffiss, J McLeod; Jarvis, Gary A; Way, Lawrence W

2012-11-01

Obesity has been associated with worse infectious disease outcomes. It is a risk factor for cholesterol gallstones, but little is known about associations between body mass index (BMI) and biliary infections. We studied this using factors associated with biliary infections. A total of 427 patients with gallstones were studied. Gallstones, bile, and blood (as applicable) were cultured. Illness severity was classified as follows: none (no infection or inflammation), systemic inflammatory response syndrome (fever, leukocytosis), severe (abscess, cholangitis, empyema), or multi-organ dysfunction syndrome (bacteremia, hypotension, organ failure). Associations between BMI and biliary bacteria, bacteremia, gallstone type, and illness severity were examined using bivariate and multivariate analysis. BMI inversely correlated with pigment stones, biliary bacteria, bacteremia, and increased illness severity on bivariate and multivariate analysis. Obesity correlated with less severe biliary infections. BMI inversely correlated with pigment stones and biliary bacteria; multivariate analysis showed an independent correlation between lower BMI and illness severity. Most patients with severe biliary infections had a normal BMI, suggesting that obesity may be protective in biliary infections. This study examined the correlation between BMI and biliary infection severity. Published by Elsevier Inc.

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Multivariate Analysis As a Support for Diagnostic Flowcharts in Allergic Bronchopulmonary Aspergillosis: A Proof-of-Concept Study.

PubMed

Vitte, Joana; Ranque, Stéphane; Carsin, Ania; Gomez, Carine; Romain, Thomas; Cassagne, Carole; Gouitaa, Marion; Baravalle-Einaudi, Mélisande; Bel, Nathalie Stremler-Le; Reynaud-Gaubert, Martine; Dubus, Jean-Christophe; Mège, Jean-Louis; Gaudart, Jean

2017-01-01

Molecular-based allergy diagnosis yields multiple biomarker datasets. The classical diagnostic score for allergic bronchopulmonary aspergillosis (ABPA), a severe disease usually occurring in asthmatic patients and people with cystic fibrosis, comprises succinct immunological criteria formulated in 1977: total IgE, anti- Aspergillus fumigatus ( Af ) IgE, anti- Af "precipitins," and anti- Af IgG. Progress achieved over the last four decades led to multiple IgE and IgG(4) Af biomarkers available with quantitative, standardized, molecular-level reports. These newly available biomarkers have not been included in the current diagnostic criteria, either individually or in algorithms, despite persistent underdiagnosis of ABPA. Large numbers of individual biomarkers may hinder their use in clinical practice. Conversely, multivariate analysis using new tools may bring about a better chance of less diagnostic mistakes. We report here a proof-of-concept work consisting of a three-step multivariate analysis of Af IgE, IgG, and IgG4 biomarkers through a combination of principal component analysis, hierarchical ascendant classification, and classification and regression tree multivariate analysis. The resulting diagnostic algorithms might show the way for novel criteria and improved diagnostic efficiency in Af -sensitized patients at risk for ABPA.

An evaluation of the Well at Dell health management program: health risk change and financial return on investment.

PubMed

Musich, Shirley; McCalister, Tre'; Wang, Sara; Hawkins, Kevin

2015-01-01

To investigate the effectiveness of the Well at Dell comprehensive health management program in delivering health care and productivity cost savings relative to program investment (i.e., return on investment). A quasi-experimental design was used to quantify the financial impact of the program and nonexperimental pre-post design to evaluate change in health risks. Ongoing worksite health management program implemented across multiple U.S. locations. Subjects were 24,651 employees with continuous medical enrollment in 2010-2011 who were eligible for 2011 health management programming. Incentive-driven, outcomes-based multicomponent corporate health management program including health risk appraisal (HRA)/wellness, lifestyle management, and disease management coaching programs. Medical, pharmacy, and short-term disability pre/post expenditure trends adjusted for demographics, health status, and baseline costs. Self-reported health risks from repeat HRA completers. Analysis: Propensity score-weighted and multivariate regression-adjusted comparison of baseline to post trends in health care expenditures and productivity costs for program participants and nonparticipants (i.e., difference in difference) relative to programmatic investment. The Well at Dell program achieved an overall return on investment of 2.48 in 2011. Most of the savings were realized from the HRA/wellness component of the program. Cost savings were supported with high participation and significant health risk improvement. An incentive-driven, well-managed comprehensive corporate health management program can continue to achieve significant health improvement while promoting health care and productivity cost savings in an employee population.

Multivariate analysis of longitudinal rates of change.

PubMed

Bryan, Matthew; Heagerty, Patrick J

2016-12-10

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed in the literature. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, 'accelerated time' methods have been developed which assume that covariates rescale time in longitudinal models for disease progression. In this manuscript, we detail an alternative multivariate model formulation that directly structures longitudinal rates of change and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing.

PubMed

Lommen, Arjen

2009-04-15

Hyphenated full-scan MS technology creates large amounts of data. A versatile easy to handle automation tool aiding in the data analysis is very important in handling such a data stream. MetAlign softwareas described in this manuscripthandles a broad range of accurate mass and nominal mass GC/MS and LC/MS data. It is capable of automatic format conversions, accurate mass calculations, baseline corrections, peak-picking, saturation and mass-peak artifact filtering, as well as alignment of up to 1000 data sets. A 100 to 1000-fold data reduction is achieved. MetAlign software output is compatible with most multivariate statistics programs.

Use of hearing protection and perceptions of noise exposure and hearing loss among construction workers.

PubMed

Lusk, S L; Kerr, M J; Kauffman, S A

1998-07-01

The purpose of this study was to describe construction workers' use of hearing protection devices (HPDs) and determine their perceptions of noise exposure and hearing loss. Operating engineers, carpenters, and plumbers/pipe fitters in the Midwest (n = 400) completed a written questionnaire regarding their use of HPDs and their perceptions of noise exposure and hearing loss. Subjects were recruited through their trade union groups. Mean reported use of HPDs and mean perceived noise exposure were compared across trade groups. Bivariate and multivariate analysis techniques were used to assess relationships between use of HPDs and trade category, education, age, years of employment, noise exposure, and hearing loss. Bivariate analyses identified significant differences in mean use of HPDs by age, years of employment, and trade group. Multivariate logistic regression assessing the independent effects of these variables found significant differences only by trade group. Results indicate a need for significant improvement in all three trade groups' use of HPDs, and suggest a need to consider use and exposure levels, demographics, and trade group membership in designing hearing conservation programs.

Multivariable control theory applied to hierarchial attitude control for planetary spacecraft

NASA Technical Reports Server (NTRS)

Boland, J. S., III; Russell, D. W.

1972-01-01

Multivariable control theory is applied to the design of a hierarchial attitude control system for the CARD space vehicle. The system selected uses reaction control jets (RCJ) and control moment gyros (CMG). The RCJ system uses linear signal mixing and a no-fire region similar to that used on the Skylab program; the y-axis and z-axis systems which are coupled use a sum and difference feedback scheme. The CMG system uses the optimum steering law and the same feedback signals as the RCJ system. When both systems are active the design is such that the torques from each system are never in opposition. A state-space analysis was made of the CMG system to determine the general structure of the input matrices (steering law) and feedback matrices that will decouple the axes. It is shown that the optimum steering law and proportional-plus-rate feedback are special cases. A derivation of the disturbing torques on the space vehicle due to the motion of the on-board television camera is presented. A procedure for computing an upper bound on these torques (given the system parameters) is included.

Comparison of pure laparoscopic versus open left hemihepatectomy by multivariate analysis: a retrospective cohort study.

PubMed

Cho, Hwui-Dong; Kim, Ki-Hun; Hwang, Shin; Ahn, Chul-Soo; Moon, Deok-Bog; Ha, Tae-Yong; Song, Gi-Won; Jung, Dong-Hwan; Park, Gil-Chun; Lee, Sung-Gyu

2018-02-01

To compare the outcomes of pure laparoscopic left hemihepatectomy (LLH) versus open left hemihepatectomy (OLH) for benign and malignant conditions using multivariate analysis. All consecutive cases of LLH and OLH between October 2007 and December 2013 in a tertiary referral hospital were enrolled in this retrospective cohort study. All surgical procedures were performed by one surgeon. The LLH and OLH groups were compared in terms of patient demographics, preoperative data, clinical perioperative outcomes, and tumor characteristics in patients with malignancy. Multivariate analysis of the prognostic factors associated with severe complications was then performed. The LLH group (n = 62) had a significantly shorter postoperative hospital stay than the OLH group (n = 118) (9.53 ± 3.30 vs 14.88 ± 11.36 days, p < 0.001). Multivariate analysis revealed that the OLH group had >4 times the risk of the LLH group in terms of developing severe complications (Clavien-Dindo grade ≥III) (odds ratio 4.294, 95% confidence intervals 1.165-15.832, p = 0.029). LLH was a safe and feasible procedure for selected patients. LLH required shorter hospital stay and resulted in less operative blood loss. Multivariate analysis revealed that LLH was associated with a lower risk of severe complications compared to OLH. The authors suggest that LLH could be a reasonable treatment option for selected patients.

Reduced Circumferential Resection Margin Involvement in Rectal Cancer Surgery: Results of the Dutch Surgical Colorectal Audit.

PubMed

Gietelink, Lieke; Wouters, Michel W J M; Tanis, Pieter J; Deken, Marion M; Ten Berge, Martijn G; Tollenaar, Rob A E M; van Krieken, J Han; de Noo, Mirre E

2015-09-01

The circumferential resection margin (CRM) is a significant prognostic factor for local recurrence, distant metastasis, and survival after rectal cancer surgery. Therefore, availability of this parameter is essential. Although the Dutch total mesorectal excision trial raised awareness about CRM in the late 1990s, quality assurance on pathologic reporting was not available until the Dutch Surgical Colorectal Audit (DSCA) started in 2009. The present study describes the rates of CRM reporting and involvement since the start of the DSCA and analyzes whether improvement of these parameters can be attributed to the audit. Data from the DSCA (2009-2013) were analyzed. Reporting of CRM and CRM involvement was plotted for successive years, and variations of these parameters were analyzed in a funnelplot. Predictors of CRM involvement were determined in univariable analysis and the independent influence of year of registration on CRM involvement was analyzed in multivariable analysis. A total of 12,669 patients were included for analysis. The mean percentage of patients with a reported CRM increased from 52.7% to 94.2% (2009-2013) and interhospital variation decreased. The percentage of patients with CRM involvement decreased from 14.2% to 5.6%. In multivariable analysis, the year of DSCA registration remained a significant predictor of CRM involvement. After the introduction of the DSCA, a dramatic improvement in CRM reporting and a major decrease of CRM involvement after rectal cancer surgery have occurred. This study suggests that a national quality assurance program has been the driving force behind these achievements. Copyright © 2015 by the National Comprehensive Cancer Network.

Cancer screening delivery in persistent poverty rural counties.

PubMed

Bennett, Kevin J; Pumkam, Chaiporn; Bellinger, Jessica D; Probst, Janice C

2011-10-01

Rural populations are diagnosed with cancer at different rate and stages than nonrural populations, and race/ethnicity as well as the area-level income exacerbates the differences. The purpose of this analysis was to explore cancer screening rates across persistent poverty rural counties, with emphasis on nonwhite populations. The 2008 Behavioral Risk Factor Surveillance System was used, combined with data from the Area Resource File (analytic n = 309 937 unweighted, 196 344 347 weighted). Unadjusted analysis estimated screening rates for breast, cervical, and colorectal cancer. Multivariate analysis estimated the odds of screening, controlling for individual and county-level effects. Rural residents, particularly those in persistent poverty counties, were less likely to be screened than urban residents. More African Americans in persistent poverty rural counties reported not having mammography screening (18.3%) compared to 15.9% of urban African Americans. Hispanics had low screening rates across all service types. Multivariate analysis continued to find disparities in screening rates, after controlling for individual and county-level factors. African Americans in persistent poverty rural counties were more likely to be screened for both breast cancer (odds ratio, 1.44; 95% confidence interval, 1.12-1.85) and cervical cancer (1.46; 1.07-1.99) when compared with urban whites. Disparities in cancer screening rates exist across not only race/ethnicity but also county type. These disparities cannot be fully explained by either individual or county-level effects. Programs have been successful in improving screening rates for African American women and should be expanded to target other vulnerable women as well as other services such as colorectal cancer screening.

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study

PubMed Central

2010-01-01

Background We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. Methods This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS) rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Results Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68%) presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Conclusion Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered. PMID:21182799

Infection following Anterior Cruciate Ligament Reconstruction: An Analysis of 6,389 Cases.

PubMed

Westermann, Robert; Anthony, Chris A; Duchman, Kyle R; Gao, Yubo; Pugely, Andrew J; Hettrich, Carolyn M; Amendola, Ned; Wolf, Brian R

2017-07-01

Infection following anterior cruciate ligament reconstruction (ACLR) is rare. Previous authors have concluded that diabetes, tobacco use, and previous knee surgery may influence infection rates following ACLR. The purpose of this study was to identify a cohort of patients undergoing ACLR and define (1) the incidence of infection after ACLR from a large multicenter database and (2) the risk factors for infection after ACLR. We identified patients undergoing elective ACLRs in the American College of Surgeons National Surgical Quality Improvement Program database between 2007 and 2013. The primary outcome was any surgical site infection within 30 days of surgery. We performed univariate and multivariate analyses comparing infected and noninfected cases to identify risk factors for infection. In total, 6,398 ACLRs were available for analysis of which 39 (0.61%) were diagnosed with a postoperative infection. Univariate analysis identified preoperative dyspnea, low hematocrit, operative time > 1 hour, and hospital admission following surgery as predictors of postoperative infection. Diabetes, tobacco use, age, and body mass index (BMI) were not associated with infection ( p  > 0.05). After multivariate analysis, the only independent predictor of postoperative infection was hospital admission following surgery (odds ratio, 2.67; 95% confidence interval, 1.02-6.96; p  = 0.04). Hospital admission following surgery was associated with an increased incidence of infection in this large, multicenter cohort. Smoking, elevated BMI, and diabetes did not increase the risk infection in the present study. Surgeons should optimize outpatient operating systems and practices to aid in same-day discharges following ACLR. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence and estimation.

PubMed

Cain, Meghan K; Zhang, Zhiyong; Yuan, Ke-Hai

2017-10-01

Nonnormality of univariate data has been extensively examined previously (Blanca et al., Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(2), 78-84, 2013; Miceeri, Psychological Bulletin, 105(1), 156, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of nonnormality, this study examined 1,567 univariate distriubtions and 254 multivariate distributions collected from authors of articles published in Psychological Science and the American Education Research Journal. We found that 74 % of univariate distributions and 68 % multivariate distributions deviated from normal distributions. In a simulation study using typical values of skewness and kurtosis that we collected, we found that the resulting type I error rates were 17 % in a t-test and 30 % in a factor analysis under some conditions. Hence, we argue that it is time to routinely report skewness and kurtosis along with other summary statistics such as means and variances. To facilitate future report of skewness and kurtosis, we provide a tutorial on how to compute univariate and multivariate skewness and kurtosis by SAS, SPSS, R and a newly developed Web application.

The impact of colorectal screening program on the detection of right-sided colorectal cancer. A 5-year cohort study in the Mantua District.

PubMed

Asteria, Corrado R; Pucciarelli, Salvatore; Gerard, Leonardo; Mantovani, Nicola; Pagani, Mauro; Boccia, Luigi; Ricci, Paolo; Troiano, Luigi; Lucchini, Giuseppe; Pulica, Coriolano

2015-12-01

High rates of advanced colorectal cancer (CRC) are still diagnosed in the right side of the colon. This study aimed to investigate whether screening programs increase CRC detection and whether tumor location is associated with survival outcome. Patients affected by CRC, aged from 50 to 69 years and operated on from 2005 to 2009 were reviewed. Other than patient-, disease-, and treatment-related factors, detection mode and tumor location were recorded. Overall (OS) and disease-free survival (DFS) were investigated, using univariate and multivariate analyses. Mean age of 386 patients included was 62.0 years, 59 % were males. CRC was detected by screening in 17 % of cases, and diagnosis was made from symptoms in 67 % and emergency surgery for 16 %. Screen-detected CRCs were located in the left colon (59 %), then in rectum (25 %) and in proximal colon (16 %) (p = 0.02). Most of CRC patients urgently operated on had cancer located in proximal colon (45 %), then in the left colon (36 %) and in rectum (18 %) (p = 0.001). Right-sided CRC demonstrated higher pTNM stage (p = 0.001), adequate harvest count nodes (p = 0.0001), metastatic nodes (p = 0.02), and poor differentiation grading (p = 0.0001). With multivariate analysis, poor differentiation grade was independently associated with both worse OS (HR 3.6, p = 0.05) and worse DFS (HR 8.1, p = 0.0001), while distant recurrence was associated with worse OS (HR 20.1, p = 0.0001). Low rates of right-sided CRC are diagnosed following screening program. Proximal CRC demonstrates aggressive behavior without impact on outcome. These findings prompt concern about population awareness for CRC screening.

Demographic and Financial Characteristics of School Districts with Low and High À La Carte Sales in Rural Kansas Public Schools

PubMed Central

Nollen, Nicole L.; Kimminau, Kim; Nazir, Niaman

2013-01-01

Reducing à la carte (ALC) items in schools – i.e., foods and beverages sold outside the reimbursable meals program -- may have important implications for childhood obesity. However, schools are reluctant to reduce ALC offerings because of the impact these changes could have on revenue. Some food service programs operate with limited ALC sales, but little is known about these programs. This secondary data analysis compared rural and urban/suburban school districts with low and high ALC sales. Food service financial records (2007–2008) were obtained from the Kansas State Department of Education (KSDE) for all public K-12 school districts (n=302). Chi-square and t-tests were used to examine the independent association of variables to ALC sales. A multivariate model was then constructed of the factors most strongly associated with low ALC sales. In rural districts with low ALC sales, lunch prices and participation were higher; lunch costs and ALC quality were lower; and fewer free/reduced price lunches were served compared to rural districts with high ALC sales. Lunch price (OR=1.2, 95% CI = 1.1–1.4) and free/reduced price lunch participation (OR=3.0, 95% CI=1.0–9.8) remained in the multivariate model predicting low ALC sales. No differences were found between urban/suburban districts with low and high ALC sales. Findings highlight important factors to maintaining low ALC sales. Schools should consider raising lunch prices and increasing meal participation rates as two potential strategies for reducing the sale of ALC items without compromising food service revenue. PMID:21616201

Prognostic impact of programmed cell death 1 ligand 1 expression in human leukocyte antigen class I-positive hepatocellular carcinoma after curative hepatectomy.

PubMed

Umemoto, Yuichiroh; Okano, Shinji; Matsumoto, Yoshihiro; Nakagawara, Hidekazu; Matono, Rumi; Yoshiya, Shohei; Yamashita, Yo-Ichi; Yoshizumi, Tomoharu; Ikegami, Toru; Soejima, Yuji; Harada, Mamoru; Aishima, Shinichi; Oda, Yoshinao; Shirabe, Ken; Maehara, Yoshihiko

2015-01-01

Hepatocellular carcinoma (HCC) is one of the most common solid tumors worldwide. Surgery is potentially curative, but high recurrence rates worsen patient prognosis. The interaction between the proteins programmed cell death 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1) is an important immune checkpoint. The significance of PD-L1 expression and human leukocyte antigen class I (HLA class I), recognized by CD8 T cells, in the prognosis of patients with HCC remains to be determined. We assessed the levels of PD-L1 and HLA class I expression on HCC samples from 80 patients who had undergone hepatectomy at our institution, and evaluated the correlations between PD-L1 and HLA class I expression and patient prognosis. High HLA class I expression was correlated with significantly better recurrence-free survival (RFS), but not overall survival (OS). Multivariate analysis showed that high HLA class I expression was an independent predictor of improved RFS. Low expression of PD-L1 on HCC tended to predict better OS, but the difference was not statistically significant. PD-L1 expression on HCC correlated with the number of CD163-positive macrophages and HLA class I expression with CD3-positive cell infiltration. Univariable and multivariable analyses showed that combined PD-L1 low/HLA class I high expression on HCCs was prognostic for improved OS and RFS. PD-L1 status may be a good predictor of prognosis in HCC patients with high HLA class I expression. Novel therapies targeting the PD-L1/PD-1 pathway may improve the prognosis of patients with HCC.

Factors associated with intern noncompliance with the 2003 Accreditation Council for Graduate Medical Education’s 30-hour duty period requirement

PubMed Central

2012-01-01

Background In 2003 the Accreditation Council for Graduate Medical Education mandated work hour restrictions. Violations can results in a residency program being cited or placed on probation. Recurrent violations could results in loss of accreditation. We wanted to determine specific intern and workload factors associated with violation of a specific mandate, the 30-hour duty period requirement. Methods Retrospective review of interns’ performance against the 30-hour duty period requirement during inpatient ward rotations at a pediatric residency program between June 24, 2008 and June 23, 2009. The analytical plan included both univariate and multivariable logistic regression analyses. Results Twenty of the 26 (77%) interns had 80 self-reported episodes of continuous work hours greater than 30 hours. In multivariable analysis, noncompliance was inversely associated with the number of prior inpatient rotations (odds ratio: 0.49, 95% confidence interval (0.38, 0.64) per rotation) but directly associated with the total number of patients (odds ratio: 1.30 (1.10, 1.53) per additional patient). The number of admissions on-call, number of admissions after midnight and number of discharges post-call were not significantly associated with noncompliance. The level of noncompliance also varied significantly between interns after accounting for intern experience and workload factors. Subject to limitations in statistical power, we were unable to identify specific intern characteristics, such as demographic variables or examination scores, which account for the variation in noncompliance between interns. Conclusions Both intern and workload factors were associated with pediatric intern noncompliance with the 30-hour duty period requirement during inpatient ward rotations. Residency programs must develop information systems to understand the individual and experience factors associated with noncompliance and implement appropriate interventions to ensure compliance with the duty hour regulations. PMID:22621439

Multiple barriers delay care among women with abnormal cancer screening despite patient navigation.

PubMed

Ramachandran, Ambili; Freund, Karen M; Bak, Sharon M; Heeren, Timothy C; Chen, Clara A; Battaglia, Tracy A

2015-01-01

While there is widespread dissemination of patient navigation programs in an effort to reduce delays in cancer care, little is known about the impact of barriers to care on timely outcomes. We conducted a secondary analysis of the Boston Patient Navigation Research Program (PNRP) to examine the effect that the presence of barriers had on time to diagnostic resolution of abnormal breast or cervical cancer screening tests. We used multivariable Cox proportional hazards regression with time to diagnostic resolution as the outcome to examine the effect of the number of barriers, controlling for demographic covariates and clustered by patients' primary navigator. There were 1481 women who received navigation; mean age was 39 years; 32% were White, 27% Black, and 31% Hispanic; 28% had private health insurance; and 38% did not speak English. Overall, half (n=745, 50%) had documentation of one or more barriers to care. Women with barriers were more likely to be older, non-White, non-English language speakers, and on public or no health insurance compared with women without barriers. In multivariable analyses, we found less timely diagnostic resolution as the number of barriers increased (one barrier, adjusted hazard ratio [aHR] 0.81 [95% CI 0.56-1.17], p=0.26; two barriers, aHR 0.55 [95% CI 0.37-0.81], p=0.0025; three or more barriers, aHR 0.31 [95% CI 0.21-0.46], p<0.0001)]. Within a patient navigation program proven to reduce delays in care, we found that navigated patients with documented barriers to care experience less timely resolution of abnormal cancer screening tests.

Factors associated with intern noncompliance with the 2003 Accreditation Council for Graduate Medical Education's 30-hour duty period requirement.

PubMed

Maloney, Christopher G; Antommaria, Armand H Matheny; Bale, James F; Ying, Jian; Greene, Tom; Srivastava, Rajendu

2012-07-13

In 2003 the Accreditation Council for Graduate Medical Education mandated work hour restrictions. Violations can results in a residency program being cited or placed on probation. Recurrent violations could results in loss of accreditation. We wanted to determine specific intern and workload factors associated with violation of a specific mandate, the 30-hour duty period requirement. Retrospective review of interns' performance against the 30-hour duty period requirement during inpatient ward rotations at a pediatric residency program between June 24, 2008 and June 23, 2009. The analytical plan included both univariate and multivariable logistic regression analyses. Twenty of the 26 (77%) interns had 80 self-reported episodes of continuous work hours greater than 30 hours. In multivariable analysis, noncompliance was inversely associated with the number of prior inpatient rotations (odds ratio: 0.49, 95% confidence interval (0.38, 0.64) per rotation) but directly associated with the total number of patients (odds ratio: 1.30 (1.10, 1.53) per additional patient). The number of admissions on-call, number of admissions after midnight and number of discharges post-call were not significantly associated with noncompliance. The level of noncompliance also varied significantly between interns after accounting for intern experience and workload factors. Subject to limitations in statistical power, we were unable to identify specific intern characteristics, such as demographic variables or examination scores, which account for the variation in noncompliance between interns. Both intern and workload factors were associated with pediatric intern noncompliance with the 30-hour duty period requirement during inpatient ward rotations. Residency programs must develop information systems to understand the individual and experience factors associated with noncompliance and implement appropriate interventions to ensure compliance with the duty hour regulations.

Magnitude and Correlates of Anemia in Elderly Women of a Resettlement Colony of Delhi.

PubMed

Singh, Tulika; Nagesh, S; Ray, T K

2018-01-01

Anemia of any degree contributes significantly to morbidity and mortality and has a significant effect on the quality of life of elderly women. Despite its clinical importance, anemia in the elderly women is underrecognized. The objective of this study was to assess the magnitude and correlates of anemia in elderly women of a resettlement colony of Delhi. A community-based, cross-sectional study for the duration of 1 year was conducted among 512 geriatric women (≥60 years). Demographic characteristics, dietary assessment, and behavioral risk factors were determined by interview, and the participants underwent physical examination followed by hemoglobin estimation by HemoCue. Anemia was defined using the WHO criteria of hemoglobin <12 g/dl. Chi-square test was employed to study the association between sociodemographic factors and anemia followed by multivariate regression analysis. The prevalence of anemia was 79.9% according to the WHO criteria of hemoglobin <12 g/dl in females. Age, education, marital status, financial dependence, diagnosed chronic disease, diet, calorie intake, history of worm infestation, and body mass index (BMI) were significantly associated with anemia on univariate analysis. In multivariate analysis, age, marital status, financial dependence, diagnosed chronic disease, diet, calorie intake, and BMI were significant explanatory variables for anemia. Our study points out high prevalence of and some of the major factors associated with anemia in elderly women. The need of the hour is to include our elderly women under the gamut of National Anemia Prophylaxis Program.

Potential predictors of risk sexual behavior among private college students in Mekelle City, North Ethiopia.

PubMed

Gebresllasie, Fanna; Tsadik, Mache; Berhane, Eyoel

2017-01-01

Risk sexual practice among students from public universities/colleges is common in Ethiopia. However, little has been known about risk sexual behavior of students in private colleges where more students are potentially enrolled. Therefore, this study aimed to assess the magnitude of risky sexual behaviors and predictors among students of Private Colleges in Mekelle City. A mixed design of both quantitative and qualitative methods was used among 627 randomly selected students of private colleges from February to march 2013. Self administered questionnaire and focus group discussion was used to collect data. A thematic content analysis was used for the qualitative part. For the quantitative study, Univariate, Bivariate and multivariable analysis was made using SPSS version 16 statistical package and p value less than 0.05 was used as cut off point for a statistical significance. Among the total 590 respondents, 151 (29.1%) have ever had sex. Among the sexually active students, 30.5% reported having had multiple sexual partners and consistent condom use was nearly 39%. In multivariable logistic regression analysis, variables such as sex, age group, sex last twelve months and condom use last twelve months was found significantly associated with risky sexual behavior. The findings of qualitative and quantitative study showed consistency in presence of risk factors. Finding of this study showed sexual risk behaviors is high among private colleges such as multiple sexual partners and substance use. So that colleges should emphasis on promoting healthy sexual and reproductive health programs.

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

Is Heart Rate Variability Better Than Routine Vital Signs for Prehospital Identification of Major Hemorrhage

DTIC Science & Technology

2015-01-01

different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and routine vital signs to test the hypothesis that...study sponsors did not have any role in the study design, data collection, analysis and interpretation of data, report writing, or the decision to...primary outcome was hemorrhagic injury plus different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and

Multivariate optimum interpolation of surface pressure and winds over oceans

NASA Technical Reports Server (NTRS)

Bloom, S. C.

1984-01-01

The observations of surface pressure are quite sparse over oceanic areas. An effort to improve the analysis of surface pressure over oceans through the development of a multivariate surface analysis scheme which makes use of surface pressure and wind data is discussed. Although the present research used ship winds, future versions of this analysis scheme could utilize winds from additional sources, such as satellite scatterometer data.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

A computer program to find the kernel of a polynomial operator

NASA Technical Reports Server (NTRS)

Gejji, R. R.

1976-01-01

This paper presents a FORTRAN program written to solve for the kernel of a matrix of polynomials with real coefficients. It is an implementation of Sain's free modular algorithm for solving the minimal design problem of linear multivariable systems. The structure of the program is discussed, together with some features as they relate to questions of implementing the above method. An example of the use of the program to solve a design problem is included.

Analysis and assessment on heavy metal sources in the coastal soils developed from alluvial deposits using multivariate statistical methods.

PubMed

Li, Jinling; He, Ming; Han, Wei; Gu, Yifan

2009-05-30

An investigation on heavy metal sources, i.e., Cu, Zn, Ni, Pb, Cr, and Cd in the coastal soils of Shanghai, China, was conducted using multivariate statistical methods (principal component analysis, clustering analysis, and correlation analysis). All the results of the multivariate analysis showed that: (i) Cu, Ni, Pb, and Cd had anthropogenic sources (e.g., overuse of chemical fertilizers and pesticides, industrial and municipal discharges, animal wastes, sewage irrigation, etc.); (ii) Zn and Cr were associated with parent materials and therefore had natural sources (e.g., the weathering process of parent materials and subsequent pedo-genesis due to the alluvial deposits). The effect of heavy metals in the soils was greatly affected by soil formation, atmospheric deposition, and human activities. These findings provided essential information on the possible sources of heavy metals, which would contribute to the monitoring and assessment process of agricultural soils in worldwide regions.

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

PubMed

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

Adulthood depression, anxiety, and trauma symptoms: a comparison of women with nonabusive, abusive, and absent father figures in childhood.

PubMed

Downs, William R; Rindels, Barb

2004-12-01

We collected data from 447 women (aged 18 or higher) from seven domestic violence programs and five substance use disorder treatment programs in a midwestern state. Women who reported a nonabusive natural/adoptive father or stepfather (N=185), abusive natural/adoptive father or stepfather (N=200), or absent father figure (N=40) were compared on a series of mental health measures with multivariate analysis of variance and pairwise post hoc comparisons using the Bonferroni test. Women with absent father figures were found to have significantly lower mean scores on the Beck Anxiety Inventory, Beck Depression Inventory, and Trauma Symptom Checklist-40 (TSC-40) than women with abusive fathers. There were no significant differences between women with absent father figures and women with nonabusive father figures on the Beck Anxiety Inventory, Beck Depression Inventory, and TSC-40. Implications for research, practice, and policy are discussed.

A project management system for the X-29A flight test program

NASA Technical Reports Server (NTRS)

Stewart, J. F.; Bauer, C. A.

1983-01-01

The project-management system developed for NASA's participation in the X-29A aircraft development program is characterized from a theoretical perspective, as an example of a system appropriate to advanced, highly integrated technology projects. System-control theory is applied to the analysis of classical project-management techniques and structures, which are found to be of closed-loop multivariable type; and the effects of increasing project complexity and integration are evaluated. The importance of information flow, sampling frequency, information holding, and delays is stressed. The X-29A system is developed in four stages: establishment of overall objectives and requirements, determination of information processes (block diagrams) definition of personnel functional roles and relationships, and development of a detailed work-breakdown structure. The resulting system is shown to require a greater information flow to management than conventional methods. Sample block diagrams are provided.

The Future of Health Care Reform: What Is Driving Enrollment?

PubMed

Callaghan, Timothy H; Jacobs, Lawrence R

2017-04-01

Against a backdrop of ongoing operational challenges, insurance market turbulence, and the ever present pull of partisanship, enrollment in the ACA's programs has soared and significant variations have developed across states in terms of their pace of coverage expansion. Our article explores why ACA enrollment has varied so dramatically across states. We explore the potential influence of party control, presidential cueing, administrative capacity, the reverberating effects of ACA policy decisions, affluence, and unemployment on enrollment. Our multivariate analysis finds that party control dominated early state decision making, but that relative enrollment in insurance exchanges and the Medicaid expansion are driven by a changing mix of political and administrative factors. Health politics is entering a new era as Republicans replace the ACA and devolve significant discretion to states to administer Medicaid and other programs. Our findings offer insights into future directions in health reform and in learning and diffusion. Copyright © 2017 by Duke University Press.

Recent application of quantification II in Japanese medical research.

PubMed Central

Suzuki, T; Kudo, A

1979-01-01

Hayashi's Quantification II is a method of multivariate discrimination analysis to manipulate attribute data as predictor variables. It is very useful in the medical research field for estimation, diagnosis, prognosis, evaluation of epidemiological factors, and other problems based on multiplicity of attribute data. In Japan, this method is so well known that most of the computer program packages include the Hayashi Quantification, but it seems to be yet unfamiliar with the method for researchers outside Japan. In view of this situation, we introduced 19 selected articles of recent applications of the Quantification II in Japanese medical research. In reviewing these papers, special mention is made to clarify how the researchers were satisfied with findings provided by the method. At the same time, some recommendations are made about terminology and program packages. Also a brief discussion of the background of the quantification methods is given with special reference to the Behaviormetric Society of Japan. PMID:540587

Diet and the role of lipoproteins, lipases, and thyroid hormones in coronary lesion growth

NASA Technical Reports Server (NTRS)

Barth, Jacques D.; Jansen, Hans; Reiber, Johan H. C.; Birkenhager, Jan C.; Kromhout, Daan

1987-01-01

The relationships between the coronary lesion growth and the blood contents of lipoprotein fractions, thyroic hormones, and the lipoprotein lipase activity were investigated in male patients with severe coronary atherosclerosis, who participated in a lipid-lowering dietary intervention program. A quantitative computer-assisted image-processing technique was used to assess the severity of coronary obstructions at the beginning of the program and at its termination two years later. Based on absolute coronary scores, patients were divided into a no-lesion growth group (14 patients) and a progression group (21 paients). At the end of the trial, the very-low-density lipoprotein cholesterol and triglycerides were found to be significantly higher, while the high-density lipoprotein cholesterol and hepatic lipase (HL) were lower in the progression group. Multivariate regression analysis showed HL to be the most important determinant of changes in coronary atherosclerotic lesions.

Change in health-related quality of life amongst participants in a 4-month pedometer-based workplace health program.

PubMed

Harding, Jessica; Freak-Poli, Rosanne Laura Armida; Backholer, Kathryn; Peeters, Anna

2013-05-01

Regular physical activity (PA) is associated with a reduced risk for chronic health conditions and improved health-related quality of life (HRQoL). Efforts to increase PA have included workplace health promotion. Currently, little is known about the effect of these programs on overall HRQoL. To evaluate whether participation in a pedometer-based PA program in the workplace was associated with changes in HRQoL. 487 voluntary employees enrolled in a health program completed the SF-12 Health Survey at baseline and 4 months. Change in Physical and Mental component summary scores (PCS; MCS) was assessed with multivariable regression analysis, adjusting for covariates. Participation in the program was associated with an increase of 1.5 MCS units (95% CI: 0.76, -2.09). Greater improvements in MCS were observed in those reporting an increased level of PA during the program [1.9 (CI: 0.78, 2.92) versus 0.9 (CI: -0.12, 2.03)] and a lower baseline MCS score [6.3 (CI: 4.80, 7.62) versus -1.5 (CI: -2.21, -0.80)]. No change in PCS was observed. Participation in this workplace PA program was associated with improvements in the mental component of HRQoL. We recommend the use of a broad perspective of health be used in both the implementation and evaluation of workplace PA programs.

PYCHEM: a multivariate analysis package for python.

PubMed

Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston

2006-10-15

We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Multivariate longitudinal data analysis with censored and intermittent missing responses.

PubMed

Lin, Tsung-I; Lachos, Victor H; Wang, Wan-Lun

2018-05-08

The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach. Copyright © 2018 John Wiley & Sons, Ltd.

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

A framework for multivariate data-based at-site flood frequency analysis: Essentiality of the conjugal application of parametric and nonparametric approaches

NASA Astrophysics Data System (ADS)

Vittal, H.; Singh, Jitendra; Kumar, Pankaj; Karmakar, Subhankar

2015-06-01

In watershed management, flood frequency analysis (FFA) is performed to quantify the risk of flooding at different spatial locations and also to provide guidelines for determining the design periods of flood control structures. The traditional FFA was extensively performed by considering univariate scenario for both at-site and regional estimation of return periods. However, due to inherent mutual dependence of the flood variables or characteristics [i.e., peak flow (P), flood volume (V) and flood duration (D), which are random in nature], analysis has been further extended to multivariate scenario, with some restrictive assumptions. To overcome the assumption of same family of marginal density function for all flood variables, the concept of copula has been introduced. Although, the advancement from univariate to multivariate analyses drew formidable attention to the FFA research community, the basic limitation was that the analyses were performed with the implementation of only parametric family of distributions. The aim of the current study is to emphasize the importance of nonparametric approaches in the field of multivariate FFA; however, the nonparametric distribution may not always be a good-fit and capable of replacing well-implemented multivariate parametric and multivariate copula-based applications. Nevertheless, the potential of obtaining best-fit using nonparametric distributions might be improved because such distributions reproduce the sample's characteristics, resulting in more accurate estimations of the multivariate return period. Hence, the current study shows the importance of conjugating multivariate nonparametric approach with multivariate parametric and copula-based approaches, thereby results in a comprehensive framework for complete at-site FFA. Although the proposed framework is designed for at-site FFA, this approach can also be applied to regional FFA because regional estimations ideally include at-site estimations. The framework is based on the following steps: (i) comprehensive trend analysis to assess nonstationarity in the observed data; (ii) selection of the best-fit univariate marginal distribution with a comprehensive set of parametric and nonparametric distributions for the flood variables; (iii) multivariate frequency analyses with parametric, copula-based and nonparametric approaches; and (iv) estimation of joint and various conditional return periods. The proposed framework for frequency analysis is demonstrated using 110 years of observed data from Allegheny River at Salamanca, New York, USA. The results show that for both univariate and multivariate cases, the nonparametric Gaussian kernel provides the best estimate. Further, we perform FFA for twenty major rivers over continental USA, which shows for seven rivers, all the flood variables followed nonparametric Gaussian kernel; whereas for other rivers, parametric distributions provide the best-fit either for one or two flood variables. Thus the summary of results shows that the nonparametric method cannot substitute the parametric and copula-based approaches, but should be considered during any at-site FFA to provide the broadest choices for best estimation of the flood return periods.

[Primary Prevention in General Medical Practice: A Survey].

PubMed

Holmberg, C; Muckelbauer, R; Sarganas, G; Braun, V; Heintze, C; Dini, L; Müller-Nordhorn, J

2016-09-16

Aim of the study: According to the German social insurance code §20 Sec. 1, statutory health insurance companies can reimburse up to 80% of costs incurred by primary prevention programs in physical activity, nutrition, stress management and drug consumption. Whether and how many general practitioners (GPs) provide their patients with information on such programs as part of their own practice is unknown. In this study, we investigate to which primary prevention programs primary care physicians refer their patients and whether they take into account reimbursability of programs. Methods: Between November 2010 and February 2011, all GPs with a practice in Berlin (n=1 168) received a questionnaire that assessed if patients were referred to prevention programs and the type of programs they were referred to, if they ensured they are reimbursable and if they themselves offered prevention programs. Descriptive statistics and multivariate logistic regression was used for analysis. Results: Of 474 respondents (response rate: 41%), 67% were female. Of the respondents, 22% offered reimbursable prevention programs and 42% at out-of-pocket expense. Patients were referred to reimbursable programs by 63%. GPs younger than 50 were twice as likely to offer reimbursable programs in their practice compared to those older than 50 (OR=1.7; 95% KI 1.1-2,8; p-value 0.025). Conclusion: A successful implementation of the new German prevention law needs awareness among GPs about reimbursable prevention programs, which may be lacking in some groups. © Georg Thieme Verlag KG Stuttgart · New York.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Multivariate geometry as an approach to algal community analysis

USGS Publications Warehouse

Allen, T.F.H.; Skagen, S.

1973-01-01

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.

Clinical correlates and prognostic value of different metastatic sites in patients with malignant melanoma of the skin: a SEER database analysis.

PubMed

Abdel-Rahman, Omar

2018-03-01

Population-based data on the clinical correlates and prognostic value of the pattern of metastases among patients with cutaneous melanoma are needed. Surveillance, Epidemiology and End Results (SEER) database (2010-2013) has been explored through SEER*Stat program. For each of six distant metastatic sites (bone, brain, liver, lung, distant lymph nodes, and skin/subcutaneous), relevant correlation with baseline characteristics were reported. Survival analysis has been conducted through Kaplan-Meier analysis, and multivariate analysis has been conducted through a Cox proportional hazard model. A total of 2691 patients with metastatic cutaneous melanoma were identified in the period from 2010 to 2013. Patients with isolated skin/subcutaneous metastases have the best overall and melanoma-specific survival (MSS) followed by patients with isolated distant lymph node metastases followed by patients with isolated lung metastases. Patients with isolated liver, bone, or brain metastases have the worst overall and MSS (p < .0001 for both end points). Multivariate analysis revealed that age more than 70 at diagnosis (p = .012); multiple sites of metastases (p <.0001), no surgery to the primary tumor (p <.0001), and no surgery to the metastatic disease (p < .0001) were associated with worse overall survival (OS). For MSS, nodal positivity (p = .038), multiple sites of metastases (p < .0001), no surgery to the primary tumor (p < .0001), and no surgery to the metastatic disease (p < .0001) were associated with worse survival. The prognosis of metastatic cutaneous melanoma patients differs considerably according to the site of distant metastases. Further prospective studies are required to evaluate the role of local treatment in the management of metastatic disease.

Linking Spatial Variations in Water Quality with Water and Land Management using Multivariate Techniques.

PubMed

Wan, Yongshan; Qian, Yun; Migliaccio, Kati White; Li, Yuncong; Conrad, Cecilia

2014-03-01

Most studies using multivariate techniques for pollution source evaluation are conducted in free-flowing rivers with distinct point and nonpoint sources. This study expanded on previous research to a managed "canal" system discharging into the Indian River Lagoon, Florida, where water and land management is the single most important anthropogenic factor influencing water quality. Hydrometric and land use data of four drainage basins were uniquely integrated into the analysis of 25 yr of monthly water quality data collected at seven stations to determine the impact of water and land management on the spatial variability of water quality. Cluster analysis (CA) classified seven monitoring stations into four groups (CA groups). All water quality parameters identified by discriminant analysis showed distinct spatial patterns among the four CA groups. Two-step principal component analysis/factor analysis (PCA/FA) was conducted with (i) water quality data alone and (ii) water quality data in conjunction with rainfall, flow, and land use data. The results indicated that PCA/FA of water quality data alone was unable to identify factors associated with management activities. The addition of hydrometric and land use data into PCA/FA revealed close associations of nutrients and color with land management and storm-water retention in pasture and citrus lands; total suspended solids, turbidity, and NO + NO with flow and Lake Okeechobee releases; specific conductivity with supplemental irrigation supply; and dissolved O with wetland preservation. The practical implication emphasizes the importance of basin-specific land and water management for ongoing pollutant loading reduction and ecosystem restoration programs. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Relationship Between Preoperative Anemia and In-Hospital Mortality in Children Undergoing Noncardiac Surgery.

PubMed

Faraoni, David; DiNardo, James A; Goobie, Susan M

2016-12-01

The relationship between preoperative anemia and in-hospital mortality has not been investigated in the pediatric surgical population. We hypothesized that children with preoperative anemia undergoing noncardiac surgery may have an increased risk of in-hospital mortality. We identified all children between 1 and 18 years of age with a recorded preoperative hematocrit (HCT) in the 2012, 2013, and 2014 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) pediatric databases. The endpoint was defined as the incidence of in-hospital mortality. Children with preoperative anemia were identified based on their preoperative HCT. Demographic and surgical characteristics, as well as comorbidities, were considered potential confounding variables in a multivariable logistic regression analysis. A sensitivity analysis was performed using propensity-matched analysis. Among the 183,833 children included in the 2012, 2013, and 2014 ACS NSQIP database, 74,508 had a preoperative HCT recorded (41%). After exclusion of all children <1 year of age (n = 12,063), those with congenital heart disease (n = 8943), and those who received a preoperative red blood cell (RBC) transfusion (n = 1880), 12,551 (24%) children were anemic, and 39,071 (76%) were nonanemic. The median preoperative HCT was 33% (interquartile range, 31-35) in anemic children, and 39% (interquartile range, 37-42) in nonanemic children (P < .001). Using multivariable logistic regression analysis, and after adjustment for RBC transfusion (OR, 2.13; 95% CI, 1.39-3.26; P < .001), we observed that preoperative anemia was associated with higher odds for in-hospital mortality (OR, 2.17; 95% CI, 1.48-3.19; P < .001). After propensity matching, the presence of anemia was also associated with higher odds of in-hospital mortality (OR, 1.75; 95% CI, 1.15-2.65; P = .004). Our study demonstrates that children with preoperative anemia are at increased risk for in-hospital mortality. Further studies are needed to assess whether the correction of preoperative HCT, through the development of a patient blood management program, improves patient outcomes or simply reduces the need for transfusions.

Adherence rates and health care costs in Crohn's disease patients receiving certolizumab pegol with and without home health nurse assistance: results from a retrospective analysis of patient claims and home health nurse data.

PubMed

Wolf, Douglas C; Jaganathan, Srihari; Burudpakdee, Chakkarin; Seetasith, Arpamas; Low, Robert; Lee, Edward; Gucky, Jay; Yassine, Mohamed; Schwartz, David A

2018-01-01

Patient support programs have a positive effect on adherence to therapy. Certolizumab pegol (CZP) is a tumor necrosis factor antagonist for the treatment of Crohn's disease. To assess, using real-world claims data, whether home health nurse assistance had an effect on patients' adherence to CZP and to measure its impact on health care use and costs. A retrospective analysis of medical and pharmacy claims data from the IQVIA Real-World Data Adjudicated Claims Database was conducted using data from January 1, 2007 through September 30, 2015. CZP patients with Crohn's disease were eligible to receive self-administration instructions from a nurse or nurse-administered CZP injections, or both. These services were provided by CIMplicity ® , a home health nurse program sponsored by UCB Pharma. Cohorts were based on patients with and without nurse assistance and were matched based on gender and categorical age. Adherence to CZP was determined using the medication possession ratio (MPR) and proportion of days covered (PDC). A Kaplan-Meier analysis was performed to compare time to discontinuation of CZP between the two cohorts. Multivariate regression analyses were performed, adjusting for additional covariates to compare the effect of CZP with and without nurse assistance on hospitalization and total health care costs. Patients with at least 12 months of continuous enrollment post-index date were evaluated for adherence to CZP (n=276 in each cohort). The mean and median PDC and MPR values were higher with nurse assistance than without. Time to discontinuation was significantly longer in patients who received CZP with nurse assistance than without ( P =0.0004). Results from the multivariate analyses showed a significant reduction in all-cause hospitalization (-55.8%; P =0.0026) and total health care costs (-14.3%; P =0.0045) with nurse assistance. This analysis suggests that home health nurse assistance increases adherence to CZP and reduces health care costs in patients with Crohn's disease.

Association of Preoperative Anemia With Postoperative Mortality in Neonates.

PubMed

Goobie, Susan M; Faraoni, David; Zurakowski, David; DiNardo, James A

2016-09-01

Neonates undergoing noncardiac surgery are at risk for adverse outcomes. Preoperative anemia is a strong independent risk factor for postoperative mortality in adults. To our knowledge, this association has not been investigated in the neonatal population. To assess the association between preoperative anemia and postoperative mortality in neonates undergoing noncardiac surgery in a large sample of US hospitals. Using data from the 2012 and 2013 pediatric databases of the American College of Surgeons National Surgical Quality Improvement Program, we conducted a retrospective study of neonates undergoing noncardiac surgery. Analysis of the data took place between June 2015 and December 2015. All neonates (0-30 days old) with a recorded preoperative hematocrit value were included. Anemia defined as hematocrit level of less than 40%. Receiver operating characteristics analysis was used to assess the association between preoperative hematocrit and mortality, and the Youden J Index was used to determine the specific hematocrit cutoff point to define anemia in the neonatal population. Demographic and postoperative outcomes variables were compared between anemic and nonanemic neonates. Univariate and multivariable logistic regression analyses were used to determine factors associated with postoperative neonatal mortality. An external validation was performed using the 2014 American College of Surgeons National Surgical Quality Improvement Program database. Neonates accounted for 2764 children (6%) in the 2012-2013 American College of Surgeons National Surgical Quality Improvement Program databases. Neonates inlcuded in the study were predominately male (64.5%), white (66.3%), and term (69.9% greater than 36 weeks' gestation) and weighed more than 2 kg (85.0%). Postoperative in-hospital mortality was 3.4% in neonates and 0.6% in all age groups (0-18 years). A preoperative hematocrit level of less than 40% was the optimal cutoff (Youden) to predict in-hospital mortality. Multivariable regression analysis demonstrated that preoperative anemia is an independent risk factor for mortality (OR, 2.62; 95% CI, 1.51-4.57) in neonates. The prevalence of postoperative in-hospital mortality was significantly higher in neonates with a preoperative hematocrit level less than 40%; being 7.5% (95% CI, 1%-10%) vs 1.4% (95% CI, 0%-4%) for preoperative hematocrit levels 40%, or greater. The relationship between anemia and in-hospital mortality was confirmed in our validation cohort (National Surgical Quality Improvement Program 2014). To our knowledge, this is the first study to define the incidence of preoperative anemia in neonates, the incidence of postoperative in-hospital mortality in neonates, and the association between preoperative anemia and postoperative mortality in US hospitals. Timely diagnosis, prevention, and appropriate treatment of preoperative anemia in neonates might improve survival.

The Economic Payoffs to Workplace Literacy. Upjohn Institute Staff Working Paper 93-21.

ERIC Educational Resources Information Center

Hollenbeck, Kevin

Although a substantial literature has addressed workplace literacy programs, only two studies have attempted to evaluate rigorously the economic benefits to workplace education. A multivariate model has been suggested that provides evidence about the productivity impacts of participation in a workplace literacy program. The data used in this paper…

ASCAL: A Microcomputer Program for Estimating Logistic IRT Item Parameters.

ERIC Educational Resources Information Center

Vale, C. David; Gialluca, Kathleen A.

ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to…

Does clinical presentation predict response to a nonsurgical chronic disease management program for endstage hip and knee osteoarthritis?

PubMed

Eyles, Jillian P; Lucas, Barbara R; Patterson, Jillian A; Williams, Matthew J; Weeks, Kate; Fransen, Marlene; Hunter, David J

2014-11-01

To identify baseline characteristics of participants who will respond favorably following 6 months of participation in a chronic disease management program for hip and knee osteoarthritis (OA). This prospective cohort study assessed 559 participants at baseline and following 6 months of participation in the Osteoarthritis Chronic Care Program. Response was defined as the minimal clinically important difference of an 18% and 9-point absolute improvement in the Western Ontario and McMaster Universities Arthritis Index global score. Multivariate logistic regression modeling was used to identify predictors of response. Complete data were available for 308 participants. Those who withdrew within the study period were imputed as nonresponders. Three variables were independently associated with response: signal joint (knee vs hip), sex, and high level of comorbidity. Index joint and sex were significant in the multivariate model, but the model was not a sensitive predictor of response. Strong predictors of response to a chronic disease management program for hip and knee OA were not identified. The significant predictors that were found should be considered in future studies.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1984-01-01

The objective of this investigation is to develop a state-of-the-art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies. A three-dimensional multivariate O/I analysis scheme has been developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

The development of a state of the art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies was investigated. A three dimensional multivariate O/I analysis scheme was developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Associations among School Characteristics and Foodservice Practices in a Nationally Representative Sample of U.S. Schools

PubMed Central

Thomson, Jessica L.; Tussing-Humphreys, Lisa M.; Martin, Corby K.; LeBlanc, Monique M.; Onufrak, Stephen J.

2012-01-01

Objective Determine school characteristics associated with healthy/unhealthy foodservice offerings or healthy food preparation practices. Design Retrospective analysis of cross-sectional data. Setting Nationally representative sample of public and private elementary, middle and high schools. Participants 526 and 520 schools with valid data from the 2006 School Health Policies and Practices Study (SHPPS) Food Service School Questionnaire. Main Outcome Measure(s) Scores for healthy/unhealthy foodservice offerings and healthy food preparation practices. Analysis Multivariable regression to determine significant associations among school characteristics and offerings/preparation practices. Results Public schools and schools participating in USDA Team Nutrition reported more healthy offerings and preparation than private or non-participating schools, respectively. Elementary schools reported less unhealthy offerings than middle or high schools; middle schools reported less unhealthy offerings than high schools. Schools requiring foodservice managers to have a college education reported more healthy preparation while those requiring completion of a foodservice training program reported less unhealthy offerings and more healthy preparation than schools without these requirements. Conclusions and Implications Results suggest the school nutrition environment may be improved by requiring foodservice managers to hold a nutrition-related college degree and/or successfully pass a foodservice training program, and by participating in a school-based nutrition program, such as USDA Team Nutrition. PMID:22963956

Characteristic analysis-1981: Final program and a possible discovery

USGS Publications Warehouse

McCammon, R.B.; Botbol, J.M.; Sinding-Larsen, R.; Bowen, R.W.

1983-01-01

The latest ornewest version of thecharacteristicanalysis (NCHARAN)computer program offers the exploration geologist a wide variety of options for integrating regionalized multivariate data. The options include the selection of regional cells for characterizing deposit models, the selection of variables that constitute the models, and the choice of logical combinations of variables that best represent these models. Moreover, the program provides for the display of results which, in turn, makes possible review, reselection, and refinement of a model. Most important, the performance of the above-mentioned steps in an interactive computing mode can result in a timely and meaningful interpretation of the data available to the exploration geologist. The most recent application of characteristic analysis has resulted in the possible discovery of economic sulfide mineralization in the Grong area in central Norway. Exploration data for 27 geophysical, geological, and geochemical variables were used to construct a mineralized and a lithogeochemical model for an area that contained a known massive sulfide deposit. The models were applied to exploration data collected from the Gjersvik area in the Grong mining district and resulted in the identification of two localities of possible mineralization. Detailed field examination revealed the presence of a sulfide vein system and a partially inverted stratigraphic sequence indicating the possible presence of a massive sulfide deposit at depth. ?? 1983 Plenum Publishing Corporation.

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Functional Path Analysis as a Multivariate Technique in Developing a Theory of Participation in Adult Education.

ERIC Educational Resources Information Center

Martin, James L.

This paper reports on attempts by the author to construct a theoretical framework of adult education participation using a theory development process and the corresponding multivariate statistical techniques. Two problems are identified: the lack of theoretical framework in studying problems, and the limiting of statistical analysis to univariate…

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Web-Based Tools for Modelling and Analysis of Multivariate Data: California Ozone Pollution Activity

ERIC Educational Resources Information Center

Dinov, Ivo D.; Christou, Nicolas

2011-01-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting…

Bias and Precision of Measures of Association for a Fixed-Effect Multivariate Analysis of Variance Model

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

Multivariate analysis of climate along the southern coast of Alaska—some forestry implications.

Treesearch

Wilbur A. Farr; John S. Hard

1987-01-01

A multivariate analysis of climate was used to delineate 10 significantly different groups of climatic stations along the southern coast of Alaska based on latitude, longitude, seasonal temperatures and precipitation, frost-free periods, and total number of growing degree days. The climatic stations were too few to delineate this rugged, mountainous region into...

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

Supplemental Nutrition Assistance Program participation is associated with an increase in household food security in a national evaluation.

PubMed

Mabli, James; Ohls, Jim

2015-02-01

The Supplemental Nutrition Assistance Program (SNAP) provides nutrition assistance benefits to low-income families in an effort to reduce hunger and improve health and well-being. Because 1 in 7 Americans participate in the program each month, policymakers need to know whether the program is meeting these objectives effectively. The objective of this study was to estimate the association between SNAP participation and household food security using recent data from the largest national survey of the food security of SNAP participants to date. The analysis used a survey of nearly 6500 households and a quasi-experimental research design that consisted of 2 sets of comparisons. Using a cross-sectional sample, we compared information collected from SNAP households within days of program entry with information collected from a contemporaneous sample of SNAP households that had participated for ∼6 mo. Next, using a longitudinal sample, we compared baseline information collected from new-entrant SNAP households with information from those same households 6 mo later. Multivariate logistic regression analysis was used to estimate associations between SNAP and household food security. SNAP participation decreased the percentage of SNAP households that were food insecure in both samples by 6-17%. SNAP participation also decreased the percentage of households experiencing severe food insecurity--designated very low food security--by 12-19%. Findings were qualitatively robust to different empirical specifications. SNAP serves a vital role in improving the health and well-being of households by increasing food security. Given recent legislation to reduce program size and limit program eligibility, this study underscores SNAP's continued importance in affecting households' well-being. Future research is needed to determine whether specific groups of households experience differential improvements in food security. © 2015 American Society for Nutrition.

MULTIVARIATE ANALYSES (CONONICAL CORRELATION AND PARTIAL LEAST SQUARE, PLS) TO MODEL AND ASSESS THE ASSOCIATION OF LANDSCAPE METRICS TO SURFACE WATER CHEMICAL AND BIOLOGICAL PROPERTIES USING SAVANNAH RIVER BASIN DATA.

EPA Science Inventory

Many multivariate methods are used in describing and predicting relation; each has its unique usage of categorical and non-categorical data. In multivariate analysis of variance (MANOVA), many response variables (y's) are related to many independent variables that are categorical...

Multivariate Density Estimation and Remote Sensing

NASA Technical Reports Server (NTRS)

Scott, D. W.

1983-01-01

Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Effect of Contact Damage on the Strength of Ceramic Materials.

DTIC Science & Technology

1982-10-01

variables that are important to erosion, and a multivariate , linear regression analysis is used to fit the data to the dimensional analysis. The...of Equations 7 and 8 by a multivariable regression analysis (room tem- perature data) Exponent Regression Standard error Computed coefficient of...1980) 593. WEAVER, Proc. Brit. Ceram. Soc. 22 (1973) 125. 39. P. W. BRIDGMAN, "Dimensional Analaysis ", (Yale 18. R. W. RICE, S. W. FREIMAN and P. F

Producer attitudes and practices related to antimicrobial use in beef cattle in Tennessee.

PubMed

Green, Alice L; Carpenter, L Rand; Edmisson, Darryl E; Lane, Clyde D; Welborn, Matt G; Hopkins, Fred M; Bemis, David A; Dunn, John R

2010-12-01

To evaluate knowledge, attitudes, and management practices involving antimicrobial use among Tennessee beef producers. Mail survey. A population-based, stratified random sample of 3,000 beef producers across the state. Questionnaires were mailed to beef producers. Questions focused on producer practices related to education, biosecurity, veterinary use, and the purchase and use of antimicrobials. Operation types were categorized as either cow-calf only or multiple operation type (MOT). Associations between various factors and antimicrobial use were evaluated by use of multivariable logistic regression, with the outcome variable being any antimicrobial use (injectable or by mouth) in the past year. Of 3,000 questionnaires mailed, 1,042 (34.7%) were returned. A significantly higher proportion of producers with MOTs reported giving antimicrobials by mouth or by injection than did producers with cow-calf only operations. In addition, higher proportions of producers with MOTs than producers with cow-calf only operations reported treating with macrolides, florfenicol, ceftiofur, and aminoglycosides. In the multivariable analysis, herd size>50 cattle, participation in Beef Quality Assurance or master beef producer certification programs, quarantining of newly purchased animals, use of written instructions for treating disease, and observation of withdrawal times were associated with a higher likelihood of antimicrobial use. Results suggested that producers who engaged in more progressive farming practices were also more likely to use antimicrobials. Incorporating training on judicious antimicrobial use into educational programs would likely increase awareness of best management practices regarding antimicrobial use.

Regional cost and experience, not size or hospital inclusion, helps predict ACO success.

PubMed

Schulz, John; DeCamp, Matthew; Berkowitz, Scott A

2017-06-01

The Medicare Shared Savings Program (MSSP) continues to expand and now includes 434 accountable care organizations (ACOs) serving more than 7 million beneficiaries. During 2014, 86 of these ACOs earned over $300 million in shared savings payments by promoting higher-quality patient care at a lower cost.Whether organizational characteristics, regional cost of care, or experience in the MSSP are associated with the ability to achieve shared savings remains uncertain.Using financial results from 2013 and 2014, we examined all 339 MSSP ACOs with a 2012, 2013, or 2014 start-date. We used a cross-sectional analysis to examine all ACOs and used a multivariate logistic model to predict probability of achieving shared savings.Experience, as measured by years in the MSSP program, was associated with success and the ability to earn shared savings varied regionally. This variation was strongly associated with differences in regional Medicare fee-for-service per capita costs: ACOs in high cost regions were more likely to earn savings. In the multivariate model, the number of ACO beneficiaries, inclusion of a hospital or involvement of an academic medical center, was not associated with likelihood of earning shared savings, after accounting for regional baseline cost variation.These results suggest ACOs are learning and improving from their experience. Additionally, the results highlight regional differences in ACO success and the strong association with variation in regional per capita costs, which can inform CMS policy to help promote ACO success nationwide.

A Framework for Establishing Standard Reference Scale of Texture by Multivariate Statistical Analysis Based on Instrumental Measurement and Sensory Evaluation.

PubMed

Zhi, Ruicong; Zhao, Lei; Xie, Nan; Wang, Houyin; Shi, Bolin; Shi, Jingye

2016-01-13

A framework of establishing standard reference scale (texture) is proposed by multivariate statistical analysis according to instrumental measurement and sensory evaluation. Multivariate statistical analysis is conducted to rapidly select typical reference samples with characteristics of universality, representativeness, stability, substitutability, and traceability. The reasonableness of the framework method is verified by establishing standard reference scale of texture attribute (hardness) with Chinese well-known food. More than 100 food products in 16 categories were tested using instrumental measurement (TPA test), and the result was analyzed with clustering analysis, principal component analysis, relative standard deviation, and analysis of variance. As a result, nine kinds of foods were determined to construct the hardness standard reference scale. The results indicate that the regression coefficient between the estimated sensory value and the instrumentally measured value is significant (R(2) = 0.9765), which fits well with Stevens's theory. The research provides reliable a theoretical basis and practical guide for quantitative standard reference scale establishment on food texture characteristics.

A Course in... Multivariable Control Methods.

ERIC Educational Resources Information Center

Deshpande, Pradeep B.

1988-01-01

Describes an engineering course for graduate study in process control. Lists four major topics: interaction analysis, multiloop controller design, decoupling, and multivariable control strategies. Suggests a course outline and gives information about each topic. (MVL)

Analysis of human tissues by total reflection X-ray fluorescence. Application of chemometrics for diagnostic cancer recognition

NASA Astrophysics Data System (ADS)

Benninghoff, L.; von Czarnowski, D.; Denkhaus, E.; Lemke, K.

1997-07-01

For the determination of trace element distributions of more than 20 elements in malignant and normal tissues of the human colon, tissue samples (approx. 400 mg wet weight) were digested with 3 ml of nitric acid (sub-boiled quality) by use of an autoclave system. The accuracy of measurements has been investigated by using certified materials. The analytical results were evaluated by using a spreadsheet program to give an overview of the element distribution in cancerous samples and in normal colon tissues. A further application, cluster analysis of the analytical results, was introduced to demonstrate the possibility of classification for cancer diagnosis. To confirm the results of cluster analysis, multivariate three-way principal component analysis was performed. Additionally, microtome frozen sections (10 μm) were prepared from the same tissue samples to compare the analytical results, i.e. the mass fractions of elements, according to the preparation method and to exclude systematic errors depending on the inhomogeneity of the tissues.

A systematic review of the relationship factor between women and health professionals within the multivariant analysis of maternal satisfaction.

PubMed

Macpherson, Ignacio; Roqué-Sánchez, María V; Legget Bn, Finola O; Fuertes, Ferran; Segarra, Ignacio

2016-10-01

personalised support provided to women by health professionals is one of the prime factors attaining women's satisfaction during pregnancy and childbirth. However the multifactorial nature of 'satisfaction' makes difficult to assess it. Statistical multivariate analysis may be an effective technique to obtain in depth quantitative evidence of the importance of this factor and its interaction with the other factors involved. This technique allows us to estimate the importance of overall satisfaction in its context and suggest actions for healthcare services. systematic review of studies that quantitatively measure the personal relationship between women and healthcare professionals (gynecologists, obstetricians, nurse, midwifes, etc.) regarding maternity care satisfaction. The literature search focused on studies carried out between 1970 and 2014 that used multivariate analyses and included the woman-caregiver relationship as a factor of their analysis. twenty-four studies which applied various multivariate analysis tools to different periods of maternity care (antenatal, perinatal, post partum) were selected. The studies included discrete scale scores and questionnaires from women with low-risk pregnancies. The "personal relationship" factor appeared under various names: care received, personalised treatment, professional support, amongst others. The most common multivariate techniques used to assess the percentage of variance explained and the odds ratio of each factor were principal component analysis and logistic regression. the data, variables and factor analysis suggest that continuous, personalised care provided by the usual midwife and delivered within a family or a specialised setting, generates the highest level of satisfaction. In addition, these factors foster the woman's psychological and physiological recovery, often surpassing clinical action (e.g. medicalization and hospital organization) and/or physiological determinants (e.g. pain, pathologies, etc.). Copyright © 2016 Elsevier Ltd. All rights reserved.

Copula Multivariate analysis of Gross primary production and its hydro-environmental driver; A BIOME-BGC model applied to the Antisana páramos

NASA Astrophysics Data System (ADS)

Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Galarraga, Remigio; Mynett, Arthur

2014-05-01

Simulations of carbon cycling are prone to uncertainties from different sources, which in general are related to input data, parameters and the model representation capacities itself. The gross carbon uptake in the cycle is represented by the gross primary production (GPP), which deals with the spatio-temporal variability of the precipitation and the soil moisture dynamics. This variability associated with uncertainty of the parameters can be modelled by multivariate probabilistic distributions. Our study presents a novel methodology that uses multivariate Copulas analysis to assess the GPP. Multi-species and elevations variables are included in a first scenario of the analysis. Hydro-meteorological conditions that might generate a change in the next 50 or more years are included in a second scenario of this analysis. The biogeochemical model BIOME-BGC was applied in the Ecuadorian Andean region in elevations greater than 4000 masl with the presence of typical vegetation of páramo. The change of GPP over time is crucial for climate scenarios of the carbon cycling in this type of ecosystem. The results help to improve our understanding of the ecosystem function and clarify the dynamics and the relationship with the change of climate variables. Keywords: multivariate analysis, Copula, BIOME-BGC, NPP, páramos

Multivariate analysis of cytokine profiles in pregnancy complications.

PubMed

Azizieh, Fawaz; Dingle, Kamaludin; Raghupathy, Raj; Johnson, Kjell; VanderPlas, Jacob; Ansari, Ali

2018-03-01

The immunoregulation to tolerate the semiallogeneic fetus during pregnancy includes a harmonious dynamic balance between anti- and pro-inflammatory cytokines. Several earlier studies reported significantly different levels and/or ratios of several cytokines in complicated pregnancy as compared to normal pregnancy. However, as cytokines operate in networks with potentially complex interactions, it is also interesting to compare groups with multi-cytokine data sets, with multivariate analysis. Such analysis will further examine how great the differences are, and which cytokines are more different than others. Various multivariate statistical tools, such as Cramer test, classification and regression trees, partial least squares regression figures, 2-dimensional Kolmogorov-Smirmov test, principal component analysis and gap statistic, were used to compare cytokine data of normal vs anomalous groups of different pregnancy complications. Multivariate analysis assisted in examining if the groups were different, how strongly they differed, in what ways they differed and further reported evidence for subgroups in 1 group (pregnancy-induced hypertension), possibly indicating multiple causes for the complication. This work contributes to a better understanding of cytokines interaction and may have important implications on targeting cytokine balance modulation or design of future medications or interventions that best direct management or prevention from an immunological approach. © 2018 The Authors. American Journal of Reproductive Immunology Published by John Wiley & Sons Ltd.

Characterization of Interfacial Chemistry of Adhesive/Dentin Bond Using FTIR Chemical Imaging With Univariate and Multivariate Data Processing

PubMed Central

Wang, Yong; Yao, Xiaomei; Parthasarathy, Ranganathan

2008-01-01

Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. The spectral imaging data collected from both the adhesive/healthy dentin and adhesive/caries-affected dentin specimens were used and compared. The univariate statistical methods such as mapping of intensities of specific functional group do not always accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. The results showed that the multivariate methods gave more satisfactory, interpretable results than univariate methods and were conclusive in showing that they can discriminate and classify differences between healthy dentin and caries-affected dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. PMID:18980198

Multivariate Analysis of Longitudinal Rates of Change

PubMed Central

Bryan, Matthew; Heagerty, Patrick J.

2016-01-01

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed by Roy and Lin [1]; Proust-Lima, Letenneur and Jacqmin-Gadda [2]; and Gray and Brookmeyer [3] among others. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, Gray and Brookmeyer [3] introduce an “accelerated time” method which assumes that covariates rescale time in longitudinal models for disease progression. In this manuscript we detail an alternative multivariate model formulation that directly structures longitudinal rates of change, and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. PMID:27417129

Additive genetic variation and evolvability of a multivariate trait can be increased by epistatic gene action.

PubMed

Griswold, Cortland K

2015-12-21

Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exploring the Structure of Library and Information Science Web Space Based on Multivariate Analysis of Social Tags

ERIC Educational Resources Information Center

Joo, Soohyung; Kipp, Margaret E. I.

2015-01-01

Introduction: This study examines the structure of Web space in the field of library and information science using multivariate analysis of social tags from the Website, Delicious.com. A few studies have examined mathematical modelling of tags, mainly examining tagging in terms of tripartite graphs, pattern tracing and descriptive statistics. This…

Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental and Workflow Protocols

DTIC Science & Technology

2016-06-01

unlimited. v List of Tables Table 1 Single-lap-joint experimental parameters ..............................................7 Table 2 Survey ...Joints: Experimental and Workflow Protocols by Robert E Jensen, Daniel C DeSchepper, and David P Flanagan Approved for...TR-7696 ● JUNE 2016 US Army Research Laboratory Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental

A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

ERIC Educational Resources Information Center

Jackson, Dan; Rollins, Katie; Coughlin, Patrick

2014-01-01

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

Atomic-scale phase composition through multivariate statistical analysis of atom probe tomography data.

PubMed

Keenan, Michael R; Smentkowski, Vincent S; Ulfig, Robert M; Oltman, Edward; Larson, David J; Kelly, Thomas F

2011-06-01

We demonstrate for the first time that multivariate statistical analysis techniques can be applied to atom probe tomography data to estimate the chemical composition of a sample at the full spatial resolution of the atom probe in three dimensions. Whereas the raw atom probe data provide the specific identity of an atom at a precise location, the multivariate results can be interpreted in terms of the probabilities that an atom representing a particular chemical phase is situated there. When aggregated to the size scale of a single atom (∼0.2 nm), atom probe spectral-image datasets are huge and extremely sparse. In fact, the average spectrum will have somewhat less than one total count per spectrum due to imperfect detection efficiency. These conditions, under which the variance in the data is completely dominated by counting noise, test the limits of multivariate analysis, and an extensive discussion of how to extract the chemical information is presented. Efficient numerical approaches to performing principal component analysis (PCA) on these datasets, which may number hundreds of millions of individual spectra, are put forward, and it is shown that PCA can be computed in a few seconds on a typical laptop computer.

Evaluation of the microscopic distribution of florfenicol in feed pellets for salmon by Fourier Transform infrared imaging and multivariate analysis.

PubMed

Bastidas, Camila Y; von Plessing, Carlos; Troncoso, José; Del P Castillo, Rosario

2018-04-15

Fourier Transform infrared imaging and multivariate analysis were used to identify, at the microscopic level, the presence of florfenicol (FF), a heavily-used antibiotic in the salmon industry, supplied to fishes in feed pellets for the treatment of salmonid rickettsial septicemia (SRS). The FF distribution was evaluated using Principal Component Analysis (PCA) and Augmented Multivariate Curve Resolution with Alternating Least Squares (augmented MCR-ALS) on the spectra obtained from images with pixel sizes of 6.25 μm × 6.25 μm and 1.56 μm × 1.56 μm, in different zones of feed pellets. Since the concentration of the drug was 3.44 mg FF/g pellet, this is the first report showing the powerful ability of the used of spectroscopic techniques and multivariate analysis, especially the augmented MCR-ALS, to describe the FF distribution in both the surface and inner parts of feed pellets at low concentration, in a complex matrix and at the microscopic level. The results allow monitoring the incorporation of the drug into the feed pellets. Copyright © 2018 Elsevier B.V. All rights reserved.

Risk factors for incidental durotomy during lumbar surgery: a retrospective study by multivariate analysis.

PubMed

Chen, Zhixiang; Shao, Peng; Sun, Qizhao; Zhao, Dong

2015-03-01

The purpose of the present study was to use a prospectively collected data to evaluate the rate of incidental durotomy (ID) during lumbar surgery and determine the associated risk factors by using univariate and multivariate analysis. We retrospectively reviewed 2184 patients who underwent lumbar surgery from January 1, 2009 to December 31, 2011 at a single hospital. Patients with ID (n=97) were compared with the patients without ID (n=2019). The influences of several potential risk factors that might affect the occurrence of ID were assessed using univariate and multivariate analyses. The overall incidence of ID was 4.62%. Univariate analysis demonstrated that older age, diabetes, lumbar central stenosis, posterior approach, revision surgery, prior lumber surgery and minimal invasive surgery are risk factors for ID during lumbar surgery. However, multivariate analysis identified older age, prior lumber surgery, revision surgery, and minimally invasive surgery as independent risk factors. Older age, prior lumber surgery, revision surgery, and minimal invasive surgery were independent risk factors for ID during lumbar surgery. These findings may guide clinicians making future surgical decisions regarding ID and aid in the patient counseling process to alleviate risks and complications. Copyright © 2015 Elsevier B.V. All rights reserved.

Patient compliance with antihypertensive medication.

PubMed Central

Hershey, J C; Morton, B G; Davis, J B; Reichgott, M J

1980-01-01

Self-reported medication taking compliance behavior of 132 high blood pressure patients was analyzed using an expanded version of the health belief model. Subjects were selected through random sampling procedures from regular hypertension program sessions at a large urban hospital. A questionnaire was constructed to measure the model components, and interviews were conducted with each patient. Bivariate analysis showed that control over health matters, dependence on providers, perceived barriers, duration of treatment, and others' nonconfirming experience were significantly related to compliance (p < .05). Log-linear multivariate analysis revealed that three of these five variables--control over health matters, perceived barriers, and duration of treatment--contributed independently to patient compliance. Self-reported medication taking was significantly related to blood pressure control (p < .02). These data provide the basis for developing interventions for providers to facilitate the medication taking behavior of clinic patients. PMID:7416325

Kidney donation after circulatory death in a country with a high number of brain dead donors: 10-year experience in Belgium.

PubMed

Jochmans, Ina; Darius, Tom; Kuypers, Dirk; Monbaliu, Diethard; Goffin, Eric; Mourad, Michel; Ledinh, Hieu; Weekers, Laurent; Peeters, Patrick; Randon, Caren; Bosmans, Jean-Louis; Roeyen, Geert; Abramowicz, Daniel; Hoang, Anh-Dung; De Pauw, Luc; Rahmel, Axel; Squifflet, Jean-Paul; Pirenne, Jacques

2012-08-01

Worldwide shortage of standard brain dead donors (DBD) has revived the use of kidneys donated after circulatory death (DCD). We reviewed the Belgian DCD kidney transplant (KT) experience since its reintroduction in 2000. Risk factors for delayed graft function (DGF) were identified using multivariate analysis. Five-year patient/graft survival was assessed using Kaplan-Meier curves. The evolution of the kidney donor type and the impact of DCDs on the total KT activity in Belgium were compared with the Netherlands. Between 2000 and 2009, 287 DCD KT were performed. Primary nonfunction occurred in 1% and DGF in 31%. Five-year patient and death-censored graft survival were 93% and 95%, respectively. In multivariate analysis, cold storage (versus machine perfusion), cold ischemic time, and histidine-tryptophan-ketoglutarate solution were independent risk factors for the development of DGF. Despite an increased number of DCD donations and transplantations, the total number of deceased KT did not increase significantly. This could suggest a shift from DBDs to DCDs. To increase KT activity, Belgium should further expand controlled DCD programs while simultaneously improve the identification of all potential DBDs and avoid their referral for donation as DCDs before brain death occurs. Furthermore, living donation remains underused. © 2012 The Authors. Transplant International © 2012 European Society for Organ Transplantation.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

Causal diagrams and multivariate analysis II: precision work.

PubMed

Jupiter, Daniel C

2014-01-01

In this Investigators' Corner, I continue my discussion of when and why we researchers should include variables in multivariate regression. My examination focuses on studies comparing treatment groups and situations for which we can either exclude variables from multivariate analyses or include them for reasons of precision. Copyright © 2014 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Multivariate optimum interpolation of surface pressure and surface wind over oceans

NASA Technical Reports Server (NTRS)

Bloom, S. C.; Baker, W. E.; Nestler, M. S.

1984-01-01

The present multivariate analysis method for surface pressure and winds incorporates ship wind observations into the analysis of surface pressure. For the specific case of 0000 GMT, on February 3, 1979, the additional data resulted in a global rms difference of 0.6 mb; individual maxima as larse as 5 mb occurred over the North Atlantic and East Pacific Oceans. These differences are noted to be smaller than the analysis increments to the first-guess fields.

Effectiveness of a first-aid intervention program applied by undergraduate nursing students to preparatory school children.

PubMed

Wafik, Wagida; Tork, Hanan

2014-03-01

Childhood injuries constitute a major public health problem worldwide. First aid is an effective life-preservation tool at work, school, home, and in public locations. In this study, the effectiveness of a first-aid program delivered by undergraduate nursing students to preparatory school children was examined. This quasi-experimental study was carried out on 100 school children in governmental preparatory schools in Egypt. The researchers designed a program for first-aid training, and this was implemented by trained nursing students. The evaluation involved immediate post-test and follow-up assessment after two months. The results showed generally low levels of satisfactory knowledge and inadequate situational practice among the school students before the intervention. Statistically-significant improvements were shown at the post- and follow-up tests. Multivariate regression analysis identified the intervention and the type of school as the independent predictors of the change in students' knowledge score, while the intervention and the knowledge score were the predictors of the practice score. The study concluded that a first-aid training program delivered by nursing students to preparatory school children is effective in improving their knowledge and practice. © 2013 Wiley Publishing Asia Pty Ltd.

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Attitudes toward Advanced and Multivariate Statistics When Using Computers.

ERIC Educational Resources Information Center

Kennedy, Robert L.; McCallister, Corliss Jean

This study investigated the attitudes toward statistics of graduate students who studied advanced statistics in a course in which the focus of instruction was the use of a computer program in class. The use of the program made it possible to provide an individualized, self-paced, student-centered, and activity-based course. The three sections…

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Oasis: online analysis of small RNA deep sequencing data.

PubMed

Capece, Vincenzo; Garcia Vizcaino, Julio C; Vidal, Ramon; Rahman, Raza-Ur; Pena Centeno, Tonatiuh; Shomroni, Orr; Suberviola, Irantzu; Fischer, Andre; Bonn, Stefan

2015-07-01

Oasis is a web application that allows for the fast and flexible online analysis of small-RNA-seq (sRNA-seq) data. It was designed for the end user in the lab, providing an easy-to-use web frontend including video tutorials, demo data and best practice step-by-step guidelines on how to analyze sRNA-seq data. Oasis' exclusive selling points are a differential expression module that allows for the multivariate analysis of samples, a classification module for robust biomarker detection and an advanced programming interface that supports the batch submission of jobs. Both modules include the analysis of novel miRNAs, miRNA targets and functional analyses including GO and pathway enrichment. Oasis generates downloadable interactive web reports for easy visualization, exploration and analysis of data on a local system. Finally, Oasis' modular workflow enables for the rapid (re-) analysis of data. Oasis is implemented in Python, R, Java, PHP, C++ and JavaScript. It is freely available at http://oasis.dzne.de. stefan.bonn@dzne.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Training at a faith-based institution matters for obstetrics and gynecology residents: results from a regional survey.

PubMed

Guiahi, Maryam; Westhoff, Carolyn L; Summers, Sondra; Kenton, Kimberly

2013-06-01

Prior data suggest that opportunities in family planning training may be limited during obstetrics and gynecology (Ob-Gyn) residency training, particularly at faith-based institutions with moral and ethical constraints, although this aspect of the Ob-Gyn curriculum has not been formally studied to date. We compared Ob-Gyn residents' self-rated competency and intentions to provide family planning procedures at faith-based versus those of residents at non-faith-based programs. We surveyed residents at all 20 Ob-Gyn programs in Illinois, Indiana, Iowa, and Wisconsin from 2008 to 2009. Residents were queried about current skills and future plans to perform family planning procedures. We examined associations based on program and residents' personal characteristics and performed multivariable logistic regression analysis. A total of 232 of 340 residents (68%) from 17 programs (85%) returned surveys. Seven programs were faith-based. Residents from non-faith-based programs were more likely to be completely satisfied with family planning training (odds ratio [OR]  =  3.4, 95% confidence limit [CI], 1.9-6.2) and to report they "understand and can perform on own" most procedures. Most residents, regardless of program type, planned to provide all surveyed family planning services. Despite similar intentions to provide family planning procedures after graduation, residents at faith-based training programs were less satisfied with their family planning training and rate their ability to perform family planning services lower than residents at non-faith-based training programs.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

PubMed

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing

PubMed Central

STAMATE, MIRELA CRISTINA; TODOR, NICOLAE; COSGAREA, MARCEL

2015-01-01

Background and aim The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. Methods The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. Results We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Conclusion Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies. PMID:26733749

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

Clinical Integration and How It Affects Student Retention in Undergraduate Athletic Training Programs

PubMed Central

Young, Allison; Klossner, Joanne; Docherty, Carrie L; Dodge, Thomas M; Mensch, James M

2013-01-01

Context A better understanding of why students leave an undergraduate athletic training education program (ATEP), as well as why they persist, is critical in determining the future membership of our profession. Objective To better understand how clinical experiences affect student retention in undergraduate ATEPs. Design Survey-based research using a quantitative and qualitative mixed-methods approach. Setting Three-year undergraduate ATEPs across District 4 of the National Athletic Trainers' Association. Patients or Other Participants Seventy-one persistent students and 23 students who left the ATEP prematurely. Data Collection and Analysis Data were collected using a modified version of the Athletic Training Education Program Student Retention Questionnaire. Multivariate analysis of variance was performed on the quantitative data, followed by a univariate analysis of variance on any significant findings. The qualitative data were analyzed through inductive content analysis. Results A difference was identified between the persister and dropout groups (Pillai trace = 0.42, F1,92 = 12.95, P = .01). The follow-up analysis of variance revealed that the persister and dropout groups differed on the anticipatory factors (F1,92 = 4.29, P = .04), clinical integration (F1,92 = 6.99, P = .01), and motivation (F1,92 = 43.12, P = .01) scales. Several themes emerged in the qualitative data, including networks of support, authentic experiential learning, role identity, time commitment, and major or career change. Conclusions A perceived difference exists in how athletic training students are integrated into their clinical experiences between those students who leave an ATEP and those who stay. Educators may improve retention by emphasizing authentic experiential learning opportunities rather than hours worked, by allowing students to take on more responsibility, and by facilitating networks of support within clinical education experiences. PMID:23672327

Testing Mean Differences among Groups: Multivariate and Repeated Measures Analysis with Minimal Assumptions

PubMed Central

Bathke, Arne C.; Friedrich, Sarah; Pauly, Markus; Konietschke, Frank; Staffen, Wolfgang; Strobl, Nicolas; Höller, Yvonne

2018-01-01

ABSTRACT To date, there is a lack of satisfactory inferential techniques for the analysis of multivariate data in factorial designs, when only minimal assumptions on the data can be made. Presently available methods are limited to very particular study designs or assume either multivariate normality or equal covariance matrices across groups, or they do not allow for an assessment of the interaction effects across within-subjects and between-subjects variables. We propose and methodologically validate a parametric bootstrap approach that does not suffer from any of the above limitations, and thus provides a rather general and comprehensive methodological route to inference for multivariate and repeated measures data. As an example application, we consider data from two different Alzheimer’s disease (AD) examination modalities that may be used for precise and early diagnosis, namely, single-photon emission computed tomography (SPECT) and electroencephalogram (EEG). These data violate the assumptions of classical multivariate methods, and indeed classical methods would not have yielded the same conclusions with regards to some of the factors involved. PMID:29565679

Development of multivariate exposure and fatal accident involvement rates for 1977

DOT National Transportation Integrated Search

1985-10-01

The need for multivariate accident involvement rates is often encounted in : accident analysis. The FARS (Fatal Accident Reporting System) files contain : records of fatal involvements characterized by many variables while NPTS : (National Personal T...

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

A Novel Approach to Detect Accelerated Aged and Surface-Mediated Degradation in Explosives by UPLC-ESI-MS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beppler, Christina L

2015-12-01

A new approach was created for studying energetic material degradation. This approach involved detecting and tentatively identifying non-volatile chemical species by liquid chromatography-mass spectrometry (LC-MS) with multivariate statistical data analysis that form as the CL-20 energetic material thermally degraded. Multivariate data analysis showed clear separation and clustering of samples based on sample group: either pristine or aged material. Further analysis showed counter-clockwise trends in the principal components analysis (PCA), a type of multivariate data analysis, Scores plots. These trends may indicate that there was a discrete shift in the chemical markers as the went from pristine to aged material, andmore » then again when the aged CL-20 mixed with a potentially incompatible material was thermally aged for 4, 6, or 9 months. This new approach to studying energetic material degradation should provide greater knowledge of potential degradation markers in these materials.« less

Complex numbers in chemometrics: examples from multivariate impedance measurements on lipid monolayers.

PubMed

Geladi, Paul; Nelson, Andrew; Lindholm-Sethson, Britta

2007-07-09

Electrical impedance gives multivariate complex number data as results. Two examples of multivariate electrical impedance data measured on lipid monolayers in different solutions give rise to matrices (16x50 and 38x50) of complex numbers. Multivariate data analysis by principal component analysis (PCA) or singular value decomposition (SVD) can be used for complex data and the necessary equations are given. The scores and loadings obtained are vectors of complex numbers. It is shown that the complex number PCA and SVD are better at concentrating information in a few components than the naïve juxtaposition method and that Argand diagrams can replace score and loading plots. Different concentrations of Magainin and Gramicidin A give different responses and also the role of the electrolyte medium can be studied. An interaction of Gramicidin A in the solution with the monolayer over time can be observed.

A Multivariate Methodological Workflow for the Analysis of FTIR Chemical Mapping Applied on Historic Paint Stratigraphies

PubMed Central

Sciutto, Giorgia; Oliveri, Paolo; Catelli, Emilio; Bonacini, Irene

2017-01-01

In the field of applied researches in heritage science, the use of multivariate approach is still quite limited and often chemometric results obtained are often underinterpreted. Within this scenario, the present paper is aimed at disseminating the use of suitable multivariate methodologies and proposes a procedural workflow applied on a representative group of case studies, of considerable importance for conservation purposes, as a sort of guideline on the processing and on the interpretation of this FTIR data. Initially, principal component analysis (PCA) is performed and the score values are converted into chemical maps. Successively, the brushing approach is applied, demonstrating its usefulness for a deep understanding of the relationships between the multivariate map and PC score space, as well as for the identification of the spectral bands mainly involved in the definition of each area localised within the score maps. PMID:29333162

Risk Factors for Central Serous Chorioretinopathy: Multivariate Approach in a Case-Control Study.

PubMed

Chatziralli, Irini; Kabanarou, Stamatina A; Parikakis, Efstratios; Chatzirallis, Alexandros; Xirou, Tina; Mitropoulos, Panagiotis

2017-07-01

The purpose of this prospective study was to investigate the potential risk factors associated independently with central serous retinopathy (CSR) in a Greek population, using multivariate approach. Participants in the study were 183 consecutive patients diagnosed with CSR and 183 controls, matched for age. All participants underwent complete ophthalmological examination and information regarding their sociodemographic, clinical, medical and ophthalmological history were recorded, so as to assess potential risk factors for CSR. Univariate and multivariate analysis was performed. Univariate analysis showed that male sex, high educational status, high income, alcohol consumption, smoking, hypertension, coronary heart disease, obstructive sleep apnea, autoimmune disorders, H. pylori infection, type A personality and stress, steroid use, pregnancy and hyperopia were associated with CSR, while myopia was found to protect from CSR. In multivariate analysis, alcohol consumption, hypertension, coronary heart disease and autoimmune disorders lost their significance, while the remaining factors were all independently associated with CSR. It is important to take into account the various risk factors for CSR, so as to define vulnerable groups and to shed light into the pathogenesis of the disease.

Interventions aimed at reducing obesity in early childhood: a meta-analysis of programs that involve parents.

PubMed

Yavuz, H Melis; van Ijzendoorn, Marinus H; Mesman, Judi; van der Veek, Shelley

2015-06-01

Obesity is a growing problem even in very young childhood, resulting in high costs for individuals and society. As a response, numerous obesity prevention and intervention programs have been developed. Previous research has shown that early intervention programs are more effective when parents are involved, but the effectiveness of specific aspects of programs with parental involvement has not been investigated. This meta-analysis aims to investigate the features related to the effectiveness of different types of obesity intervention programs involving parents and targeting young children (0-6-year-olds). The Web of Science, PubMed, PsycInfo, CINAHL, and ERIC databases were searched for childhood obesity prevention and intervention programs involving parents. Data were analyzed using the Comprehensive Meta-analysis (CMA) software. Fifty studies with effect sizes measured at short-term follow-up (within 3 months from the end of the intervention) and 26 studies with effect sizes measured at long-term follow-up (all reported in a total of 49 publications) were identified. The combined effect size of interventions was small but significant at short-term follow-up (d = .08, p < .01). The results suggested the presence of a potential publication bias in studies providing results at long-term follow-up, with a nonsignificant adjusted effect size (d = .02), which indicated that obesity interventions were not effective at long-term follow-up. Multivariate meta-regression analyses showed that interventions were more effective when including either interactive sessions or educational materials as opposed to those including both interactive sessions and noninteractive educational materials. No other moderators regarding sample characteristics, study design, or methodological quality were significant. Interventions targeting young children that require parental involvement are effective at short-term follow-up, specifically when interventions include one mode of intervention rather than two. However, results were not retained in the long run. © 2014 Association for Child and Adolescent Mental Health.

Application of multivariate autoregressive spectrum estimation to ULF waves

NASA Technical Reports Server (NTRS)

Ioannidis, G. A.

1975-01-01

The estimation of the power spectrum of a time series by fitting a finite autoregressive model to the data has recently found widespread application in the physical sciences. The extension of this method to the analysis of vector time series is presented here through its application to ULF waves observed in the magnetosphere by the ATS 6 synchronous satellite. Autoregressive spectral estimates of the power and cross-power spectra of these waves are computed with computer programs developed by the author and are compared with the corresponding Blackman-Tukey spectral estimates. The resulting spectral density matrices are then analyzed to determine the direction of propagation and polarization of the observed waves.

Predictors of consistent condom use among Chinese female sex workers: an application of the protection motivation theory.

PubMed

Zhang, Liying; Li, Xiaoming; Zhou, Yuejiao; Lin, Danhua; Su, Shaobing; Zhang, Chen; Stanton, Bonita

2015-01-01

We utilized Protection Motivation Theory to assess predictors of intention and behavior of consistent condom use among Chinese female sex workers (FSWs). A self-administered questionnaire was used in a cross-sectional survey among 700 FSWs in Guangxi, China. Multivariate logistic regression analysis indicated that extrinsic and intrinsic rewards, self-efficacy, and response costs predicted consistent condom use intention and behavior among FSWs. Sexually transmitted infection/ HIV prevention programs need to reduce FSWs' perceptions of positive extrinsic rewards and intrinsic rewards for engaging in consistent condom use, reduce FSWs' perception of response costs for using a condom, and increase condom use self-efficacy among FSWs.

Clinic Design and Continuity in Internal Medicine Resident Clinics: Findings of the Educational Innovations Project Ambulatory Collaborative.

PubMed

Francis, Maureen D; Wieland, Mark L; Drake, Sean; Gwisdalla, Keri Lyn; Julian, Katherine A; Nabors, Christopher; Pereira, Anne; Rosenblum, Michael; Smith, Amy; Sweet, David; Thomas, Kris; Varney, Andrew; Warm, Eric; Wininger, David; Francis, Mark L

2015-03-01

Many internal medicine (IM) programs have reorganized their resident continuity clinics to improve trainees' ambulatory experience. Downstream effects on continuity of care and other clinical and educational metrics are unclear. This multi-institutional, cross-sectional study included 713 IM residents from 12 programs. Continuity was measured using the usual provider of care method (UPC) and the continuity for physician method (PHY). Three clinic models (traditional, block, and combination) were compared using analysis of covariance. Multivariable linear regression analysis was used to analyze the effect of practice metrics and clinic model on continuity. UPC, reflecting continuity from the patient perspective, was significantly different, and was highest in the block model, midrange in combination model, and lowest in the traditional model programs. PHY, reflecting continuity from the perspective of the resident provider, was significantly lower in the block model than in combination and traditional programs. Panel size, ambulatory workload, utilization, number of clinics attended in the study period, and clinic model together accounted for 62% of the variation found in UPC and 26% of the variation found in PHY. Clinic model appeared to have a significant effect on continuity measured from both the patient and resident perspectives. Continuity requires balance between provider availability and demand for services. Optimizing this balance to maximize resident education, and the health of the population served, will require consideration of relevant local factors and priorities in addition to the clinic model.

Clinic Design and Continuity in Internal Medicine Resident Clinics: Findings of the Educational Innovations Project Ambulatory Collaborative

PubMed Central

Francis, Maureen D.; Wieland, Mark L.; Drake, Sean; Gwisdalla, Keri Lyn; Julian, Katherine A.; Nabors, Christopher; Pereira, Anne; Rosenblum, Michael; Smith, Amy; Sweet, David; Thomas, Kris; Varney, Andrew; Warm, Eric; Wininger, David; Francis, Mark L.

2015-01-01

Background Many internal medicine (IM) programs have reorganized their resident continuity clinics to improve trainees' ambulatory experience. Downstream effects on continuity of care and other clinical and educational metrics are unclear. Methods This multi-institutional, cross-sectional study included 713 IM residents from 12 programs. Continuity was measured using the usual provider of care method (UPC) and the continuity for physician method (PHY). Three clinic models (traditional, block, and combination) were compared using analysis of covariance. Multivariable linear regression analysis was used to analyze the effect of practice metrics and clinic model on continuity. Results UPC, reflecting continuity from the patient perspective, was significantly different, and was highest in the block model, midrange in combination model, and lowest in the traditional model programs. PHY, reflecting continuity from the perspective of the resident provider, was significantly lower in the block model than in combination and traditional programs. Panel size, ambulatory workload, utilization, number of clinics attended in the study period, and clinic model together accounted for 62% of the variation found in UPC and 26% of the variation found in PHY. Conclusions Clinic model appeared to have a significant effect on continuity measured from both the patient and resident perspectives. Continuity requires balance between provider availability and demand for services. Optimizing this balance to maximize resident education, and the health of the population served, will require consideration of relevant local factors and priorities in addition to the clinic model. PMID:26217420

Social Cognitive and Planned Behavior Variables Associated with Stages of Change for Physical Activity in Spinal Cord Injury: A Multivariate Analysis

ERIC Educational Resources Information Center

Keegan, John; Ditchman, Nicole; Dutta, Alo; Chiu, Chung-Yi; Muller, Veronica; Chan, Fong; Kundu, Madan

2016-01-01

Purpose: To apply the constructs of social cognitive theory (SCT) and the theory of planned behavior (TPB) to understand the stages of change (SOC) for physical activities among individuals with a spinal cord injury (SCI). Method: Ex post facto design using multivariate analysis of variance (MANOVA). The participants were 144 individuals with SCI…

To See the World in a Grain of Sand: Recognizing the Origin of Sand Specimens by Diffuse Reflectance Infrared Fourier Transform Spectroscopy and Multivariate Exploratory Data Analysis

ERIC Educational Resources Information Center

Pezzolo, Alessandra De Lorenzi

2011-01-01

The diffuse reflectance infrared Fourier transform (DRIFT) spectra of sand samples exhibit features reflecting their composition. Basic multivariate analysis (MVA) can be used to effectively sort subsets of homogeneous specimens collected from nearby locations, as well as pointing out similarities in composition among sands of different origins.…

Testing key predictions of the associative account of mirror neurons in humans using multivariate pattern analysis.

PubMed

Oosterhof, Nikolaas N; Wiggett, Alison J; Cross, Emily S

2014-04-01

Cook et al. overstate the evidence supporting their associative account of mirror neurons in humans: most studies do not address a key property, action-specificity that generalizes across the visual and motor domains. Multivariate pattern analysis (MVPA) of neuroimaging data can address this concern, and we illustrate how MVPA can be used to test key predictions of their account.

Multivariate Quantitative Chemical Analysis

NASA Technical Reports Server (NTRS)

Kinchen, David G.; Capezza, Mary

1995-01-01

Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

PubMed Central

Metsalu, Tauno; Vilo, Jaak

2015-01-01

The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/. PMID:25969447

Clinical Model of Exercise-Related Dyspnea in Adult Patients With Cystic Fibrosis.

PubMed

Stevens, Daniel; Neyedli, Heather F

2018-05-01

Dyspnea is a highly distressing symptom of pulmonary disease that can make performing physical activities challenging. However, little is known regarding the strongest predictors of exercise-related dyspnea in adult cystic fibrosis (CF). Therefore, the purpose of the present study was to determine the best clinical model of exercise-related dyspnea in this patient group. A retrospective analysis of pulmonary function and cardiopulmonary exercise testing data from patients with CF being followed up at the Adult CF Program at St Michael's Hospital, Toronto, Canada, from 2002 to 2008 were used for the analysis. Patients (n = 88) were male 66%; aged 30.4 ± 9.4 years; body mass index (BMI) 23.1 ± 3.3 kg/m; forced expiratory volume in 1 second (FEV1) 70% ± 19% predicted; and peak oxygen uptake 74% ± 20% predicted. A multivariate linear regression model assessing the effects of age, sex, BMI, airway obstruction (FEV1), perceived muscular leg fatigue, and dynamic hyperinflation explained 54% of the variance in dyspnea severity at peak exercise (P < .01). Relative importance analysis showed that the presence of dynamic hyperinflation and perceived muscular leg fatigue were the largest contributors. Pulmonary rehabilitation programs may consider strategies to reduce dynamic hyperinflation and promote muscular function to best improve exercise-related dyspnea in this patient group.

Characterization of selected volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyl compounds at a roadside monitoring station

NASA Astrophysics Data System (ADS)

Ho, K. F.; Lee, S. C.; Chiu, Gloria M. Y.

Volatile organic compounds (VOCs), PAHs and carbonyl compounds are the major toxic components in Hong Kong. Emissions from motor vehicles have been one of the primary pollution sources in the metropolitan areas throughout Hong Kong for a long time. A 1-yr monitoring program for VOCs, PAHs and carbonyl compounds had been performed at a roadside urban station at Hong Kong Polytechnic University in order to determine the variations and correlations of each selected species (VOCs, PAHs and carbonyl compounds). This study is aimed to analyze toxic volatile organic compounds (benzene, toluene, ethylbenzene and xylene), two carbonyl compounds (formaldehyde, acetaldehyde), and selective polycyclic aromatic hydrocarbons. The monitoring program started from 16 April 1999 to 30 March 2000. Ambient VOC concentrations, many of which originate from the same sources as particulate PAHs and carbonyls compounds, show significant quantities of benzene, toluene and xylenes. Correlations and multivariate analysis of selected gaseous and particulate phase organic pollutants were performed. Source identification by principle component analysis and hierarchical cluster analysis allowed the identification of four sources (factors) for the roadside monitoring station. Factor 1 represents the effect of diesel vehicle exhaust. Factor 2 shows the contribution of aromatic compounds. Factor 3 explains photochemical products—formaldehyde and acetaldehyde. Factor 4 explains the effect of gasoline vehicle exhaust.

The Efficacy of an American Indian Culturally-Based Risk Prevention Program for Upper Elementary School Youth Residing on the Northern Plains Reservations.

PubMed

Usera, John J

2017-04-01

Culturally-based risk behavior prevention programs for American Indian elementary school children are sparse. Thus a group of American Indian educators collaborated in the creation of a program that helps children make healthy decisions based on their cultural and traditional value system. In this paper the effectiveness of Lakota Circles of Hope (LCH), an elementary school culturally-based prevention program was studied and evaluated. Three cohorts of fourth and fifth graders participated in a mixed methods quasi-experimental evaluative research design that included focus groups and surveys prior to and following the intervention. Five research questions regarding the program's impact on students' self-esteem and self-efficacy, Lakota identity, communication, conflict resolution and risk behaviors were addressed in this study. Participants were compared to non-participants in three American Indian reservation school sites. Educators completed a survey to record their observations and feedback regarding the implementation of the program within their respective school sites. The study provides preliminary evidence that, when delivered with fidelity, LCH contributes to statistically significant changes in risk behaviors, Lakota identity, respect for others, and adult and parent communication. A two-way multivariate analysis of variance with post hoc analysis of data collected from the LCH participants (N = 1392) were used to substantiate a significant increase in respect for others and a decrease in risk behaviors which included alcohol, tobacco, and substance use at the 0.10 alpha level. Significant positive improvements in parent and adult communication and an increased Lakota identity at the 0.01 alpha level were obtained. There were no significant differences in self-esteem and conflict resolution from pre to post intervention and in comparison with non LCH participating students.

Academic Facility Utilization and Survival Outcomes in Adult Head and Neck Sarcomas: An NCDB Analysis.

PubMed

Cannon, Richard B; Carpenter, Patrick S; Boothe, Dustin; Buchmann, Luke O; Hunt, Jason P; Lloyd, Shane; Hitchcock, Ying J; Houlton, Jeffrey J; Weis, John R; Shepherd, Hailey M; Monroe, Marcus M

2018-04-01

Objectives To investigate clinicopathologic and treatment factors associated with survival in adult head and neck sarcomas in the National Cancer Database (NCDB). To analyze whether treatment settings and therapies received influence survival outcomes and to compare trends in utilization via an aggregated national data set. Study Design Prospectively gathered data. Setting NCDB. Subjects and Methods The study comprised a total of 6944 adult patients treated for a head and neck sarcoma from January 2004 to December 2013. Overall survival (OS) was the primary outcome. Results Increased age and tumor size, nodal involvement, and poorly differentiated histology had significantly reduced OS ( P < .001). Angiosarcoma, malignant nerve sheath tumor, malignant fibrous histiocytoma, osteosarcoma, and rhabdomyosarcoma histologic subtypes had significantly reduced OS, while liposarcoma, chondrosarcoma, and chordoma had improved OS ( P < .001). Utilization of surgical therapy was associated with improved OS, while positive surgical margins were associated with treatment at a community-based cancer program and had reduced OS ( P < .001). On multivariate analysis, treatment with radiation and/or chemotherapy was not significantly associated with OS; however, primary treatment with definitive chemoradiotherapy had significantly reduced OS. Patients treated at academic/research cancer programs (n = 3874) had significantly improved 5- and 10-year OS (65% and 54%, respectively) when compared with patients treated at community-based cancer programs (n = 3027; 49% and 29%; P < .001). The percentage utilization of these programs (56% vs 44%) did not change over the study period. Conclusion For adult head and neck sarcomas, treatment at an academic/research cancer program was associated with improved survival; however, despite increasing medical specialization, the percentage utilization of these programs for this rare tumor remains constant.

Associations Between Peer Counseling and Breastfeeding Initiation and Duration: An Analysis of Minnesota Participants in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).

PubMed

McCoy, Marcia Burton; Geppert, Joni; Dech, Linda; Richardson, Michaela

2018-01-01

Background Peer counseling (PC) has been associated with increased breastfeeding initiation and duration, but few analyses have examined the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) model for peer counseling or the continuation of breastfeeding from birth through 12 months postpartum. Objectives Identify associations between Minnesota WIC Peer Breastfeeding Support Program services and breastfeeding initiation and continuation. Methods Retrospective analysis of observational data from the Minnesota WIC program's administrative database of women who gave birth in 2012 and accepted a PC program referral prenatally (n = 2219). Multivariate logistic regression and Cox regression models examined associations between peer services and breastfeeding initiation and continuation of any breastfeeding. Results Among women who accepted referral into a PC program, odds of initiation were significantly higher among those who received peer services (Odds Ratio (OR): 1.66; 95% CI 1.19-2.32), after adjusting for confounders. Women who received peer services had a significantly lower hazard of breastfeeding discontinuation from birth through 12 months postpartum than women who did not receive services. (Hazard Ratio (HR) month one: 0.45; 95% CI 0.33-0.61; months two through twelve: 0.33; 95% CI 0.18-0.60). The effect of peer counseling did not differ significantly by race and ethnicity, taking into account mother's country of origin. Conclusion for practice Receipt of peer services was positively associated with breastfeeding initiation and continued breastfeeding from birth through 12 months postpartum. Making peer services available to more women, especially in communities with low initiation and duration, could improve maternal and child health in Minnesota.

Quality of pancreatic transplant program assessment using a risk-adjusted cumulative sum chart: experience from a single, small center.

PubMed

Grochowiecki, T; Jakimowicz, T; Grabowska-Derlatka, L; Szmidt, J

2014-10-01

The high rate of complication after pancreas transplantation not only had an impact on recipient quality of life and survival but also had significant financial implications. Thus, monitoring transplant center performance was crucial to indentifying changes in clinical practice that result in quality deterioration. To evaluate retrospectively the quality of the single, small pancreatic transplant program and to establish prospective monitoring of the center using risk-adjusted cumulative sum (CUSUM). From 1988 to 2014, 119 simultaneous pancreas and the kidney transplantations (SPKTx) were performed. The program was divided into 3 eras, based on surgical technique and immunosuppression. Analyses of the 15 fatal outcomes due to complication from pancreatic graft were performed. The risk model was developed using multivariable logistic regression analysis based on retrospective data of 112 SPKTx recipients. The risk-adjusted 1-sided CUSUM chart was plotted for retrospective and prospective events. The upper control limit was set to 2. There were 2 main causes of death: multiorgan failure (73.3%; 11/15) and septic hemorrhage (26.7%; 4/15). Quality analysis using the CUSUM chart revealed that the process was not homogeneous; however, no significant signal of program deterioration was obtained and the performance of the whole program was within the settled control limit. For a single pancreatic transplant center. The risk-adjusted CUSUM chart was a useful tool for quality program assessment. It could support decision making during traditional surgical morbidity and mortality conferences. For small transplant centers, increasing the sensitivity of the CUSUM method by lowering the upper control limit should be considered. However, an individual assessment approach of the for particular centers is recommended.

Multivariate statistical analysis of low-voltage EDS spectrum images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, I.M.

1998-03-01

Whereas energy-dispersive X-ray spectrometry (EDS) has been used for compositional analysis in the scanning electron microscope for 30 years, the benefits of using low operating voltages for such analyses have been explored only during the last few years. This paper couples low-voltage EDS with two other emerging areas of characterization: spectrum imaging and multivariate statistical analysis. The specimen analyzed for this study was a finished Intel Pentium processor, with the polyimide protective coating stripped off to expose the final active layers.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

2017-01-01

High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Efficacy of bendamustine and rituximab as first salvage treatment in chronic lymphocytic leukemia and indirect comparison with ibrutinib: a GIMEMA, ERIC and UK CLL FORUM study.

PubMed

Cuneo, Antonio; Follows, George; Rigolin, Gian Matteo; Piciocchi, Alfonso; Tedeschi, Alessandra; Trentin, Livio; Medina Perez, Angeles; Coscia, Marta; Laurenti, Luca; Musuraca, Gerardo; Farina, Lucia; Rivas Delgado, Alfredo; Orlandi, Ester Maria; Galieni, Piero; Mauro, Francesca Romana; Visco, Carlo; Amendola, Angela; Billio, Atto; Marasca, Roberto; Chiarenza, Annalisa; Meneghini, Vittorio; Ilariucci, Fiorella; Marchetti, Monia; Molica, Stefano; Re, Francesca; Gaidano, Gianluca; Gonzalez, Marcos; Forconi, Francesco; Ciolli, Stefania; Cortelezzi, Agostino; Montillo, Marco; Smolej, Lukas; Schuh, Anna; Eyre, Toby A; Kennedy, Ben; Bowles, Kris M; Vignetti, Marco; de la Serna, Javier; Moreno, Carol; Foà, Robin; Ghia, Paolo

2018-04-19

We performed an observational study on the efficacy of bendamustine and rituximab as first salvage regimen in chronic lymphocytic leukemia. In an intention-to-treat analysis including 237 patients, the median progression free survival was 25 months. The presence of del(17p), unmutated IGHV and advanced stage were associated with a shorter progression free survival at multivariate analysis. The median time-to-next treatment was 31.3 months. Front-line treatment with a chemoimmunotherapy regimen was the only predictive factor for a shorter time to next treatment at multivariate analysis. The median overall survival was 74.5 months. Advanced Binet stage (i.e. III-IV or C) and resistant disease were the only parameters significantly associated with a shorter OS. Grade 3-5 infections were recorded in 6.3% of patients. A matched-adjusted indirect comparison with ibrutinib given second-line within named patient programs in the United Kingdom and in Italy was carried out with overall survival as objective endpoint. When restricting the analysis to patients with intact 17p who had received chemoimmunotherapy in first line, the overall survival did not differ between patients treated with ibrutinib (63% alive at 36 months) and patients treated with BR (74.4% alive at 36 months). BR is an efficacious first salvage regimen in chronic lymphocytic leukemia in a real-life population, including the elderly and unfit patients. BR and ibrutinib may be equally effective in terms of overall survival when used as first salvage treatment in patients without 17p deletion. ClinicalTrials.gov identifier: NCT02491398. Copyright © 2018, Ferrata Storti Foundation.

Multivariate causal attribution and cost-effectiveness of a national mass media campaign in the Philippines.

PubMed

Kincaid, D Lawrence; Do, Mai Phuong

2006-01-01

Cost-effectiveness analysis is based on a simple formula. A dollar estimate of the total cost to conduct a program is divided by the number of people estimated to have been affected by it in terms of some intended outcome. The direct, total costs of most communication campaigns are usually available. Estimating the amount of effect that can be attributed to the communication alone, however is problematical in full-coverage, mass media campaigns where the randomized control group design is not feasible. Single-equation, multiple regression analysis controls for confounding variables but does not adequately address the issue of causal attribution. In this article, multivariate causal attribution (MCA) methods are applied to data from a sample survey of 1,516 married women in the Philippines to obtain a valid measure of the number of new adopters of modern contraceptives that can be causally attributed to a national mass media campaign and to calculate its cost-effectiveness. The MCA analysis uses structural equation modeling to test the causal pathways and to test for endogeneity, biprobit analysis to test for direct effects of the campaign and endogeneity, and propensity score matching to create a statistically equivalent, matched control group that approximates the results that would have been obtained from a randomized control group design. The MCA results support the conclusion that the observed, 6.4 percentage point increase in modern contraceptive use can be attributed to the national mass media campaign and to its indirect effects on attitudes toward contraceptives. This net increase represented 348,695 new adopters in the population of married women at a cost of U.S. $1.57 per new adopter.

Prevalence of cigarette smoking and associated factors among secondary school teachers in Malaysia.

PubMed

Al-Naggar, Redhwan A; Jawad, Ammar A; Bobryshev, Yuri V

2012-01-01

The smoking prevalence in Malaysia is high, especially among men and adolescents. This study aimed to determine the prevalence and associated factors towards cigarette smoking among school teachers in Malaysia. This study was a school-based cross-sectional study conducted among 495 secondary school teachers. The questionnaire used in this study consisted of 29 questions categorized into two sections: socio-demographic characteristics and smoking behaviour. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) program 13.0. ANOVA; t-tests were used in univariate analysis; multiple linear regression was applied for multivariate analysis. The majority of the participants were female (81.6%), in the age group ranged between 30-39 years (44%), Malay (90.1%), married (89.7%), degree holders (85.1%), with monthly income ranged between 3000-3999 Ringgit Malaysia (33.5%), from urban areas (94.7%), their specialty is social studies (33.9%) and with no family history of cancer (83.6%). The prevalence of smoking among school teachers in Malaysia was found to be 7.8%. Regarding reasons to start smoking among school teachers: the major reason was found to be relaxation (33.3%), followed by stress-relief (28.2%). Univariate analysis showed that sex, educational status, monthly income and residency were significantly associated with smoking among school teachers (p<0.001, p=0.004, p=0.031, p=0.010; respectively). Multivariate analysis showed that gender and marital status were significantly associated with smoking among school teachers (p<0.001, p=0.033; respectively). The prevalence of smoking among school teachers in Malaysia was found to be relatively low. Sex, marital status, educational status, monthly income and residency were significantly associated with smoking among school teachers.

Prescribing potentially inappropriate medication (PIM) in Germany's elderly as indicated by the PRISCUS list. An analysis based on regional claims data.

PubMed

Schubert, Ingrid; Küpper-Nybelen, Jutta; Ihle, Peter; Thürmann, Petra

2013-07-01

The aim of this study was to estimate the prevalence of potentially inappropriate medication (PIM) in the elderly as indicated by Germany's recently published list (PRISCUS) and to assess factors independently associated with PIM prescribing, both overall and separately for therapeutic groups. Claims data analysis (Health Insurance Sample AOK Hesse/KV Hesse, 18.75% random sample of insurants from AOK Hesse, Germany) is used in the study. The study population is composed of 73,665 insurants >64 years of age continuously insured in the last quarter of 2009 and either continuously insured or deceased in 2010. Prevalence estimates are standardized to the population of Germany (31 December 2010). The variables age, sex, polypharmacy, hospital stay and nursing care are assessed for their independent association with general PIM prescription and among 11 therapeutic subgroups using multivariate logistic regression analysis. In 2010, 22.0% of the elderly received at least one PIM prescription (men: 18.3%, women: 24.8%). The highest PIM prevalence was observed for antidepressants (6.5%), antihypertensives (3.8%) and antiarrhythmic drugs (3.5%). Amitriptyline, tetrazepam, doxepin, acetyldigoxin, doxazosin and etoricoxib were the most frequently prescribed PIMs. Multivariate analyses indicate that women (OR 1.39; 95% CI: 1.34-1.44) and persons with extreme polypharmacy (≥10 vs. <5 drugs: OR 5.16; 95% CI: 4.87-5.47) were at higher risk for receiving a PRISCUS-PIM. Risk analysis for therapeutic groups shows divergent associations. PRISCUS-PIMs are widely used. Educational programs should focus on drugs with high treatment prevalence and call professionals' attention to those elderly patients who are at special risk for inappropriate medication. Copyright © 2013 John Wiley & Sons, Ltd.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

PubMed

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

High-resolution mass spectrometry to evaluate the influence of cross-breeding segregating populations on the phenolic profile of virgin olive oils.

PubMed

Sánchez de Medina, Verónica; Calderón-Santiago, Mónica; El Riachy, Milad; Priego-Capote, Feliciano; Luque de Castro, María Dolores

2014-12-01

The growing demand for high-quality virgin olive oils (VOOs) has increased the interest in olive breeding programs. Cross-breeding is considered, within these programs, the best strategy to generate new cultivars as an attempt to improve the present cultivars. In this research, the phenolic profile of VOOs from target crosses (Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana) and their corresponding genitors (Arbequina, Arbosana, Koroneiki, Picual and Sikitita) has been evaluated using a targeted metabolomics approach. The phenolic profiles were obtained by liquid chromatographic-hybrid quadrupole time-of-flight mass spectrometric targeted analysis of 37 phenols or compounds involved in the main pathways for their biosynthesis. Statistical multivariate analysis by principal component analysis was applied to study the influence of genotype on phenol composition. Phenolic compounds with the highest contribution to explain the observed variability associated to genotype were identified through fold change algorithms (cut-off > 2.0) and t-test analysis. A total of nine phenols (viz. quercetin, ligstroside aglycon (p-HPEA-EA), demethyl oleuropein aglycon, oleuropein aglycon (3,4-DHPEA-EA), hydroxypinoresinol, hydroxytyrosol and phenolic acids such as p-coumaric acid, ferulic acid and protocatechuic acid) contributed to explain the observed variability with 99% confidence (P<0.01). © 2014 Society of Chemical Industry.

The application of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the stratum corneum.

PubMed

Goh, Choon Fu; Craig, Duncan Q M; Hadgraft, Jonathan; Lane, Majella E

2017-02-01

Drug permeation through the intercellular lipids, which pack around and between corneocytes, may be enhanced by increasing the thermodynamic activity of the active in a formulation. However, this may also result in unwanted drug crystallisation on and in the skin. In this work, we explore the combination of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the skin. Ex vivo permeation studies of saturated solutions of diclofenac sodium (DF Na) in two vehicles, propylene glycol (PG) and dimethyl sulphoxide (DMSO), were carried out in porcine ear skin. Tape stripping and ATR-FTIR spectroscopy were conducted simultaneously to collect spectral data as a function of skin depth. Multivariate data analysis was applied to visualise and categorise the spectral data in the region of interest (1700-1500cm -1 ) containing the carboxylate (COO - ) asymmetric stretching vibrations of DF Na. Spectral data showed the redshifts of the COO - asymmetric stretching vibrations for DF Na in the solution compared with solid drug. Similar shifts were evident following application of saturated solutions of DF Na to porcine skin samples. Multivariate data analysis categorised the spectral data based on the spectral differences and drug crystallisation was found to be confined to the upper layers of the skin. This proof-of-concept study highlights the utility of ATR-FTIR spectroscopy in combination with multivariate data analysis as a simple and rapid approach in the investigation of drug deposition in the skin. The approach described here will be extended to the study of other actives for topical application to the skin. Copyright © 2016 Elsevier B.V. All rights reserved.

Describing the Elephant: Structure and Function in Multivariate Data.

ERIC Educational Resources Information Center

McDonald, Roderick P.

1986-01-01

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family of models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain. (Author)

A comparative analysis of readmission rates after outpatient cosmetic surgery.

PubMed

Mioton, Lauren M; Alghoul, Mohammed S; Kim, John Y S

2014-02-01

Despite the increasing scrutiny of surgical procedures, outpatient cosmetic surgery has an established record of safety and efficacy. A key measure in assessing surgical outcomes is the examination of readmission rates. However, there is a paucity of data on unplanned readmission following cosmetic surgery procedures. The authors studied readmission rates for outpatient cosmetic surgery and compared the data with readmission rates for other surgical procedures. The 2011 National Surgical Quality Improvement Program (NSQIP) data set was queried for all outpatient procedures. Readmission rates were calculated for the 5 surgical specialties with the greatest number of outpatient procedures and for the overall outpatient cosmetic surgery population. Subgroup analysis was performed on the 5 most common cosmetic surgery procedures. Multivariate regression models were used to determine predictors of readmission for cosmetic surgery patients. The 2879 isolated outpatient cosmetic surgery cases had an associated 0.90% unplanned readmission rate. The 5 specialties with the highest number of outpatient surgical procedures were general, orthopedic, gynecologic, urologic, and otolaryngologic surgery; their unplanned readmission rates ranged from 1.21% to 3.73%. The 5 most common outpatient cosmetic surgery procedures and their associated readmission rates were as follows: reduction mammaplasty, 1.30%; mastopexy, 0.31%; liposuction, 1.13%; abdominoplasty, 1.78%; and breast augmentation, 1.20%. Multivariate regression analysis demonstrated that operating time (in hours) was an independent predictor of readmission (odds ratio, 1.40; 95% confidence interval, 1.08-1.81; P=.010). Rates of unplanned readmission with outpatient cosmetic surgery are low and compare favorably to those of other outpatient surgeries.

Temporal performance assessment of wastewater treatment plants by using multivariate statistical analysis.

PubMed

Ebrahimi, Milad; Gerber, Erin L; Rockaway, Thomas D

2017-05-15

For most water treatment plants, a significant number of performance data variables are attained on a time series basis. Due to the interconnectedness of the variables, it is often difficult to assess over-arching trends and quantify operational performance. The objective of this study was to establish simple and reliable predictive models to correlate target variables with specific measured parameters. This study presents a multivariate analysis of the physicochemical parameters of municipal wastewater. Fifteen quality and quantity parameters were analyzed using data recorded from 2010 to 2016. To determine the overall quality condition of raw and treated wastewater, a Wastewater Quality Index (WWQI) was developed. The index summarizes a large amount of measured quality parameters into a single water quality term by considering pre-established quality limitation standards. To identify treatment process performance, the interdependencies between the variables were determined by using Principal Component Analysis (PCA). The five extracted components from the 15 variables accounted for 75.25% of total dataset information and adequately represented the organic, nutrient, oxygen demanding, and ion activity loadings of influent and effluent streams. The study also utilized the model to predict quality parameters such as Biological Oxygen Demand (BOD), Total Phosphorus (TP), and WWQI. High accuracies ranging from 71% to 97% were achieved for fitting the models with the training dataset and relative prediction percentage errors less than 9% were achieved for the testing dataset. The presented techniques and procedures in this paper provide an assessment framework for the wastewater treatment monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Development of a Test for an Experimental Research Program in Creative Problem Solving. Final Report.

ERIC Educational Resources Information Center

Miles, David T.

The purpose of this first phase of a continuing research program was the development of a test of creative problem solving in general design. A design class of 186 members was divided into an experimental and control group; a non-design control group (an educational psychology class) of 45 was also tested. Multivariate interpretation of creative…

Costs and cost-effectiveness of training traditional birth attendants to reduce neonatal mortality in the Lufwanyama Neonatal Survival study (LUNESP).

PubMed

Sabin, Lora L; Knapp, Anna B; MacLeod, William B; Phiri-Mazala, Grace; Kasimba, Joshua; Hamer, Davidson H; Gill, Christopher J

2012-01-01

The Lufwanyama Neonatal Survival Project ("LUNESP") was a cluster randomized, controlled trial that showed that training traditional birth attendants (TBAs) to perform interventions targeting birth asphyxia, hypothermia, and neonatal sepsis reduced all-cause neonatal mortality by 45%. This companion analysis was undertaken to analyze intervention costs and cost-effectiveness, and factors that might improve cost-effectiveness. We calculated LUNESP's financial and economic costs and the economic cost of implementation for a forecasted ten-year program (2011-2020). In each case, we calculated the incremental cost per death avoided and disability-adjusted life years (DALYs) averted in real 2011 US dollars. The forecasted 10-year program analysis included a base case as well as 'conservative' and 'optimistic' scenarios. Uncertainty was characterized using one-way sensitivity analyses and a multivariate probabilistic sensitivity analysis. The estimated financial and economic costs of LUNESP were $118,574 and $127,756, respectively, or $49,469 and $53,550 per year. Fixed costs accounted for nearly 90% of total costs. For the 10-year program, discounted total and annual program costs were $256,455 and $26,834 respectively; for the base case, optimistic, and conservative scenarios, the estimated cost per death avoided was $1,866, $591, and $3,024, and cost per DALY averted was $74, $24, and $120, respectively. Outcomes were robust to variations in local costs, but sensitive to variations in intervention effect size, number of births attended by TBAs, and the extent of foreign consultants' participation. Based on established guidelines, the strategy of using trained TBAs to reduce neonatal mortality was 'highly cost effective'. We strongly recommend consideration of this approach for other remote rural populations with limited access to health care.

Costs and Cost-Effectiveness of Training Traditional Birth Attendants to Reduce Neonatal Mortality in the Lufwanyama Neonatal Survival Study (LUNESP)

PubMed Central

Sabin, Lora L.; Knapp, Anna B.; MacLeod, William B.; Phiri-Mazala, Grace; Kasimba, Joshua; Hamer, Davidson H.; Gill, Christopher J.

2012-01-01

Background The Lufwanyama Neonatal Survival Project (“LUNESP”) was a cluster randomized, controlled trial that showed that training traditional birth attendants (TBAs) to perform interventions targeting birth asphyxia, hypothermia, and neonatal sepsis reduced all-cause neonatal mortality by 45%. This companion analysis was undertaken to analyze intervention costs and cost-effectiveness, and factors that might improve cost-effectiveness. Methods and Findings We calculated LUNESP's financial and economic costs and the economic cost of implementation for a forecasted ten-year program (2011–2020). In each case, we calculated the incremental cost per death avoided and disability-adjusted life years (DALYs) averted in real 2011 US dollars. The forecasted 10-year program analysis included a base case as well as ‘conservative’ and ‘optimistic’ scenarios. Uncertainty was characterized using one-way sensitivity analyses and a multivariate probabilistic sensitivity analysis. The estimated financial and economic costs of LUNESP were $118,574 and $127,756, respectively, or $49,469 and $53,550 per year. Fixed costs accounted for nearly 90% of total costs. For the 10-year program, discounted total and annual program costs were $256,455 and $26,834 respectively; for the base case, optimistic, and conservative scenarios, the estimated cost per death avoided was $1,866, $591, and $3,024, and cost per DALY averted was $74, $24, and $120, respectively. Outcomes were robust to variations in local costs, but sensitive to variations in intervention effect size, number of births attended by TBAs, and the extent of foreign consultants' participation. Conclusions Based on established guidelines, the strategy of using trained TBAs to reduce neonatal mortality was ‘highly cost effective’. We strongly recommend consideration of this approach for other remote rural populations with limited access to health care. PMID:22545117

Integrated Technology Assessment Center (ITAC) Update

NASA Technical Reports Server (NTRS)

Taylor, J. L.; Neely, M. A.; Curran, F. M.; Christensen, E. R.; Escher, D.; Lovell, N.; Morris, Charles (Technical Monitor)

2002-01-01

The Integrated Technology Assessment Center (ITAC) has developed a flexible systems analysis framework to identify long-term technology needs, quantify payoffs for technology investments, and assess the progress of ASTP-sponsored technology programs in the hypersonics area. For this, ITAC has assembled an experienced team representing a broad sector of the aerospace community and developed a systematic assessment process complete with supporting tools. Concepts for transportation systems are selected based on relevance to the ASTP and integrated concept models (ICM) of these concepts are developed. Key technologies of interest are identified and projections are made of their characteristics with respect to their impacts on key aspects of the specific concepts of interest. Both the models and technology projections are then fed into the ITAC's probabilistic systems analysis framework in ModelCenter. This framework permits rapid sensitivity analysis, single point design assessment, and a full probabilistic assessment of each concept with respect to both embedded and enhancing technologies. Probabilistic outputs are weighed against metrics of interest to ASTP using a multivariate decision making process to provide inputs for technology prioritization within the ASTP. ITAC program is currently finishing the assessment of a two-stage-to-orbit (TSTO), rocket-based combined cycle (RBCC) concept and a TSTO turbine-based combined cycle (TBCC) concept developed by the team with inputs from NASA. A baseline all rocket TSTO concept is also being developed for comparison. Boeing has recently submitted a performance model for their Flexible Aerospace System Solution for Tomorrow (FASST) concept and the ISAT program will provide inputs for a single-stage-to-orbit (SSTO) TBCC based concept in the near-term. Both of these latter concepts will be analyzed within the ITAC framework over the summer. This paper provides a status update of the ITAC program.

Permanent pacemaker insertion following isolated aortic valve replacement before and after the introduction of TAVI.

PubMed

Kogan, Alexander; Sternik, Leonid; Beinart, Roy; Shalabi, Amjad; Glikson, Michael; Spiegelstein, Danny; Levin, Shany; Raanani, Ehud

2015-04-01

Permanent pacemaker (PPM) implantation is required in 3-12% of all patients undergoing surgical aortic valve replacement (AVR). Our aim was to evaluate the contemporary incidence and impact of the introduction of transcatheter aortic valve implantation (TAVI) for PPM insertion after isolated AVR. Since 2004, during a 10-year period, a total of 858 patients underwent isolated AVR at our institution. Forty-one patients with PPM before operation were excluded from the study and 817 patients were included in the statistical analysis. Of these, 20 patients (2.45%) developed significant conduction disorders, leading to PPM implantation within 120 days postoperatively. Patients were further divided into two groups. Before (Group I: June 2004 to September 2008) and after (Group II: October 2008 to May 2014) the introduction of the TAVI program. There were 343 patients in Group I and 475 patients in Group II. The incidence of PPM implantation decreased from 3.79% (13 patients) in Group I to 1.47% (seven patients) in Group II (P < 0.001). Risk factors for permanent pacing identified by univariate analysis were: Group I (before introducing TAVI program), pulmonary hypertension, preoperative anemia, age older than 75 years, and previous myocardial infarction. Multivariate analysis identified Group I (before introducing TAVI program; P < 0.005; odds ratio [OR] 15.2, 95% confidence interval [CI] 6.3-19.9) and pulmonary hypertension (P < 0.005; OR 12.5, 95% CI 3.2-18.3) to be significant. Irreversible atrio-ventricular block or symptomatic bradycardia requiring PPM implantation is a relatively rare complication. The incidence of PPM implantation after isolated surgical AVR decreased in a contemporary setting after the introduction of the TAVI program. ©2015 Wiley Periodicals, Inc.

Prognostic factors and relative risk for survival in N1-3 oral squamous cell carcinoma: a multivariate analysis using Cox's hazard model.

PubMed

Noguchi, M; Kido, Y; Kubota, H; Kinjo, H; Kohama, G

1999-12-01

The records of 136 patients with N1-3 oral squamous cell carcinoma treated by surgery were investigated retrospectively, with the aim of finding out which factors were predictive of survival on multivariate analysis. Four independent factors significantly influenced survival in the following order: pN stage; T stage; histological grade; and N stage. The most significant was pN stage, the five-year survival for patients with pN0 being 91% and for patients with pN1-3 41%. A further study was carried out on the 80 patients with pN1-3 to find out their prognostic factors for survival and the independent factors identified by multivariate analysis were T stage and presence or absence of extracapsular spread to metastatic lymph nodes.

DigOut: viewing differential expression genes as outliers.

PubMed

Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

2010-12-01

With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

Immediate versus delayed intramedullary nailing for open fractures of the tibial shaft: a multivariate analysis of factors affecting deep infection and fracture healing.

PubMed

Yokoyama, Kazuhiko; Itoman, Moritoshi; Uchino, Masataka; Fukushima, Kensuke; Nitta, Hiroshi; Kojima, Yoshiaki

2008-10-01

The purpose of this study was to evaluate contributing factors affecting deep infection and fracture healing of open tibia fractures treated with locked intramedullary nailing (IMN) by multivariate analysis. We examined 99 open tibial fractures (98 patients) treated with immediate or delayed locked IMN in static fashion from 1991 to 2002. Multivariate analyses following univariate analyses were derived to determine predictors of deep infection, nonunion, and healing time to union. The following predictive variables of deep infection were selected for analysis: age, sex, Gustilo type, fracture grade by AO type, fracture location, timing or method of IMN, reamed or unreamed nailing, debridement time (< or =6 h or >6 h), method of soft-tissue management, skin closure time (< or =1 week or >1 week), existence of polytrauma (ISS< 18 or ISS> or =18), existence of floating knee injury, and existence of superficial/pin site infection. The predictive variables of nonunion selected for analysis was the same as those for deep infection, with the addition of deep infection for exchange of pin site infection. The predictive variables of union time selected for analysis was the same as those for nonunion, excluding of location, debridement time, and existence of floating knee and superficial infection. Six (6.1%; type II Gustilo n=1, type IIIB Gustilo n=5) of the 99 open tibial fractures developed deep infections. Multivariate analysis revealed that timing or method of IMN, debridement time, method of soft-tissue management, and existence of superficial or pin site infection significantly correlated with the occurrence of deep infection (P< 0.0001). In the immediate nailing group alone, the deep infection rate in type IIIB + IIIC was significantly higher than those in type I + II and IIIA (P = 0.016). Nonunion occurred in 17 fractures (20.3%, 17/84). Multivariate analysis revealed that Gustilo type, skin closure time, and existence of deep infection significantly correlated with occurrence of nonunion (P < 0.05). Gustilo type and existence of deep infection were significantly correlated with healing time to union on multivariate analysis (r(2) = 0.263, P = 0.0001). Multivariate analyses for open tibial fractures treated with IMN showed that IMN after EF (especially in existence of pin site infection) was at high risk of deep infection, and that debridement within 6 h and appropriate soft-tissue managements were also important factor in preventing deep infections. These analyses postulated that both the Gustilo type and the existence of deep infection is related with fracture healing in open fractures treated with IMN. In addition, immediate IMN for type IIIB and IIIC is potentially risky, and canal reaming did not increase the risk of complication for open tibial fractures treated with IMN.

Is a multivariate consensus representation of genetic relationships among populations always meaningful?

PubMed Central

Moazami-Goudarzi, K; Laloë, D

2002-01-01

To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis. PMID:12242255

Application of multivariate analysis to investigate the trace element contamination in top soil of coal mining district in Jorong, South Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Pujiwati, Arie; Nakamura, K.; Watanabe, N.; Komai, T.

2018-02-01

Multivariate analysis is applied to investigate geochemistry of several trace elements in top soils and their relation with the contamination source as the influence of coal mines in Jorong, South Kalimantan. Total concentration of Cd, V, Co, Ni, Cr, Zn, As, Pb, Sb, Cu and Ba was determined in 20 soil samples by the bulk analysis. Pearson correlation is applied to specify the linear correlation among the elements. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to observe the classification of trace elements and contamination sources. The results suggest that contamination loading is contributed by Cr, Cu, Ni, Zn, As, and Pb. The elemental loading mostly affects the non-coal mining area, for instances the area near settlement and agricultural land use. Moreover, the contamination source is classified into the areas that are influenced by the coal mining activity, the agricultural types, and the river mixing zone. Multivariate analysis could elucidate the elemental loading and the contamination sources of trace elements in the vicinity of coal mine area.

The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

NASA Astrophysics Data System (ADS)

Theodorakou, Chrysoula; Farquharson, Michael J.

2009-08-01

The motivation behind this study is to assess whether angular dispersive x-ray diffraction (ADXRD) data, processed using multivariate analysis techniques, can be used for classifying secondary colorectal liver cancer tissue and normal surrounding liver tissue in human liver biopsy samples. The ADXRD profiles from a total of 60 samples of normal liver tissue and colorectal liver metastases were measured using a synchrotron radiation source. The data were analysed for 56 samples using nonlinear peak-fitting software. Four peaks were fitted to all of the ADXRD profiles, and the amplitude, area, amplitude and area ratios for three of the four peaks were calculated and used for the statistical and multivariate analysis. The statistical analysis showed that there are significant differences between all the peak-fitting parameters and ratios between the normal and the diseased tissue groups. The technique of soft independent modelling of class analogy (SIMCA) was used to classify normal liver tissue and colorectal liver metastases resulting in 67% of the normal tissue samples and 60% of the secondary colorectal liver tissue samples being classified correctly. This study has shown that the ADXRD data of normal and secondary colorectal liver cancer are statistically different and x-ray diffraction data analysed using multivariate analysis have the potential to be used as a method of tissue classification.

Multivariate analysis of risk factors for long-term urethroplasty outcome.

PubMed

Breyer, Benjamin N; McAninch, Jack W; Whitson, Jared M; Eisenberg, Michael L; Mehdizadeh, Jennifer F; Myers, Jeremy B; Voelzke, Bryan B

2010-02-01

We studied the patient risk factors that promote urethroplasty failure. Records of patients who underwent urethroplasty at the University of California, San Francisco Medical Center between 1995 and 2004 were reviewed. Cox proportional hazards regression analysis was used to identify multivariate predictors of urethroplasty outcome. Between 1995 and 2004, 443 patients of 495 who underwent urethroplasty had complete comorbidity data and were included in analysis. Median patient age was 41 years (range 18 to 90). Median followup was 5.8 years (range 1 month to 10 years). Stricture recurred in 93 patients (21%). Primary estimated stricture-free survival at 1, 3 and 5 years was 88%, 82% and 79%. After multivariate analysis smoking (HR 1.8, 95% CI 1.0-3.1, p = 0.05), prior direct vision internal urethrotomy (HR 1.7, 95% CI 1.0-3.0, p = 0.04) and prior urethroplasty (HR 1.8, 95% CI 1.1-3.1, p = 0.03) were predictive of treatment failure. On multivariate analysis diabetes mellitus showed a trend toward prediction of urethroplasty failure (HR 2.0, 95% CI 0.8-4.9, p = 0.14). Length of urethral stricture (greater than 4 cm), prior urethroplasty and failed endoscopic therapy are predictive of failure after urethroplasty. Smoking and diabetes mellitus also may predict failure potentially secondary to microvascular damage. Copyright 2010 American Urological Association. Published by Elsevier Inc. All rights reserved.

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Defining critical habitats of threatened and endemic reef fishes with a multivariate approach.

PubMed

Purcell, Steven W; Clarke, K Robert; Rushworth, Kelvin; Dalton, Steven J

2014-12-01

Understanding critical habitats of threatened and endemic animals is essential for mitigating extinction risks, developing recovery plans, and siting reserves, but assessment methods are generally lacking. We evaluated critical habitats of 8 threatened or endemic fish species on coral and rocky reefs of subtropical eastern Australia, by measuring physical and substratum-type variables of habitats at fish sightings. We used nonmetric and metric multidimensional scaling (nMDS, mMDS), Analysis of similarities (ANOSIM), similarity percentages analysis (SIMPER), permutational analysis of multivariate dispersions (PERMDISP), and other multivariate tools to distinguish critical habitats. Niche breadth was widest for 2 endemic wrasses, and reef inclination was important for several species, often found in relatively deep microhabitats. Critical habitats of mainland reef species included small caves or habitat-forming hosts such as gorgonian corals and black coral trees. Hard corals appeared important for reef fishes at Lord Howe Island, and red algae for mainland reef fishes. A wide range of habitat variables are required to assess critical habitats owing to varied affinities of species to different habitat features. We advocate assessments of critical habitats matched to the spatial scale used by the animals and a combination of multivariate methods. Our multivariate approach furnishes a general template for assessing the critical habitats of species, understanding how these vary among species, and determining differences in the degree of habitat specificity. © 2014 Society for Conservation Biology.

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

PubMed

Cichy, Radoslaw Martin; Pantazis, Dimitrios

2017-09-01

Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

Nontargeted, Rapid Screening of Extra Virgin Olive Oil Products for Authenticity Using Near-Infrared Spectroscopy in Combination with Conformity Index and Multivariate Statistical Analyses.

PubMed

Karunathilaka, Sanjeewa R; Kia, Ali-Reza Fardin; Srigley, Cynthia; Chung, Jin Kyu; Mossoba, Magdi M

2016-10-01

A rapid tool for evaluating authenticity was developed and applied to the screening of extra virgin olive oil (EVOO) retail products by using Fourier-transform near infrared (FT-NIR) spectroscopy in combination with univariate and multivariate data analysis methods. Using disposable glass tubes, spectra for 62 reference EVOO, 10 edible oil adulterants, 20 blends consisting of EVOO spiked with adulterants, 88 retail EVOO products and other test samples were rapidly measured in the transmission mode without any sample preparation. The univariate conformity index (CI) and the multivariate supervised soft independent modeling of class analogy (SIMCA) classification tool were used to analyze the various olive oil products which were tested for authenticity against a library of reference EVOO. Better discrimination between the authentic EVOO and some commercial EVOO products was observed with SIMCA than with CI analysis. Approximately 61% of all EVOO commercial products were flagged by SIMCA analysis, suggesting that further analysis be performed to identify quality issues and/or potential adulterants. Due to its simplicity and speed, FT-NIR spectroscopy in combination with multivariate data analysis can be used as a complementary tool to conventional official methods of analysis to rapidly flag EVOO products that may not belong to the class of authentic EVOO. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Metric Selection for Evaluation of Human Supervisory Control Systems

DTIC Science & Technology

2009-12-01

finding a significant effect when there is none becomes more likely. The inflation of type I error due to multiple dependent variables can be handled...with multivariate analysis techniques, such as Multivariate Analysis of Variance (MANOVA) (Johnson & Wichern, 2002). However, it should be noted that...the few significant differences among many insignificant ones. The best way to avoid failure to identify significant differences is to design an

A Civilian/Military Trauma Institute: National Trauma Coordinating Center

DTIC Science & Technology

2015-12-01

zip codes was used in “proximity to violence” analysis. Data were analyzed using SPSS (version 20.0, SPSS Inc., Chicago, IL). Multivariable linear...number of adverse events and serious events was not statistically higher in one group, the incidence of deep venous thrombosis (DVT) was statistically ...subjects the lack of statistical difference on multivariate analysis may be related to an underpowered sample size. It was recommended that the

Exploratory Multivariate Analysis. A Graphical Approach.

DTIC Science & Technology

1981-01-01

Gnanadesikan , 1977) but we feel that these should be used with great caution unless one really has good reason to believe that the data came from such a...are referred to Gnanadesikan (1977). The present author hopes that the convenience of a single summary or significance level will not deter his readers...fit of a harmonic model to meteorological data. (In preparation). Gnanadesikan , R. (1977). Methods for Statistical Data Analysis of Multivariate

Risk Factors for Anthroponotic Cutaneous Leishmaniasis at the Household Level in Kabul, Afghanistan

PubMed Central

Reithinger, Richard; Mohsen, Mohammad; Leslie, Toby

2010-01-01

Background Kabul, Afghanistan, is the largest focus of anthroponotic cutaneous leishmaniasis (ACL) in the world. ACL is a protozoan disease transmitted to humans by the bite of phlebotomine sand flies. Although not fatal, ACL can lead to considerable stigmatization of affected populations. Methods Using data from a standardized survey of 872 households in 4 wards of Kabul, Afghanistan, univariate and multivariate logistic regression analyses tested associations between presence of active ACL and ACL scars with 15 household-level variables. Findings Univariate analyses showed that active ACL was positively associated with household member's age, ACL prevalence, and brick wall type, but negatively associated with household number of rooms, bednet use, and proportion of windows with screens. Multivariate analysis showed a positive association between active ACL and household member's age, ACL prevalence, and brick wall type, and a negative association with household proportion of windows with screens. Conclusion Household-level charateristics were shown to be risk factors for ACL. Monitoring a selected number of household characteristics could assist in rapid assessments of household-level variation in risk of ACL. ACL prevention and control programs should consider improving house construction, including smoothing of walls and screening of windows. PMID:20351787

A Two Year Longitudinal Outcome Study of Addicted Health Care Professionals: An Investigation of the Role of Personality Variables

PubMed Central

Angres, Daniel; Bologeorges, Stephanie; Chou, Jessica

2013-01-01

The co-morbidity of personality disorders (PDs) and other dysregulatory personality patterns with addiction have been well-established, although few studies have examined this interplay on long-term sobriety outcome. In addition, health care professionals suffering from addiction have both a significant public health impact and a unique set of treatment and recovery challenges. The aim of this study was to investigate if personality variables differentiated sobriety outcome in this population over a two year interval. A clinical sample of health care professionals participated in a substance abuse hospital treatment program individually tailored with respect to personality. Participants took the Temperament and Character Inventory and the Millon Clinical Multiaxial Inventory at intake, and were tracked two years post-discharge to determine sobriety status. Univariate analyses showed antisocial personality, female gender, and alcohol dependence were independent predictors of relapse, however a significant relationship between personality and substance use did not exist in multivariate analysis when controlling for demographic variables The lack of multivariate relationships demonstrates the heterogeneity in self-report measures of personality, which suggests the interplay of personality and addiction is complex and individualized. PMID:23531922

Perceived Devaluation and STI Testing Uptake among a Cohort of Street-Involved Youth in a Canadian Setting.

PubMed

Karamouzian, Mohammad; Shoveller, Jean; Dong, Huiru; Gilbert, Mark; Kerr, Thomas; DeBeck, Kora

2017-10-01

Perceived devaluation has been shown to have adverse effects on the mental and physical health outcomes of people who use drugs. However, the impact of perceived devaluation on sexually transmitted infections (STI) testing uptake among street-involved youth, who face multiple and intersecting stigmas due to their association with drug use and risky sexual practices, has not been fully characterized. Data were obtained between December 2013 and November 2014 from a cohort of street-involved youth who use illicit drugs aged 14-26 in Vancouver, British Columbia. Multivariable generalized estimating equations were constructed to assess the independent relationship between perceived devaluation and STI testing uptake. Among 300 street-involved youth, 87.0% reported a high perceived devaluation score at baseline. In the multivariable analysis, high perceived devaluation was negatively associated with STI testing uptake after adjustment for potential confounders (Adjusted Odds Ratio = 0.38, 95% Confidence Interval 0.15-0.98). Perceived devaluation was high among street-involved youth in our sample and appears to have adverse effects on STI testing uptake. HIV prevention and care programs should be examined and improved to better meet the special needs of street-involved youth in non-stigmatizing ways.

The Cedar Project: correlates of attempted suicide among young Aboriginal people who use injection and non-injection drugs in two Canadian cities.

PubMed

Moniruzzaman, Akm; Pearce, Margo E; Patel, Sheetal H; Chavoshi, Negar; Teegee, Mary; Adam, Warner; Christian, Wayne M; Henderson, Earl; Craib, Kevin J P; Schechter, Martin T; Spittal, Patricia M

2009-06-01

Aboriginal leadership and families are deeply concerned about the rate of suicide attempt among their young people. The objectives of this study were to (a) describe the prevalence of suicide attempt and (b) to describe correlates of vulnerability to suicide attempts within a cohort of young Aboriginal people who use drugs in 2 Canadian cities. We aimed to situate the findings within the context of historical and lifetime trauma. Study design. The Cedar Project is a prospective cohort study involving 605 young Aboriginal people aged 14-30 who use drugs in Vancouver and Prince George, British Columbia, Canada. Multivariable logistic regression modelling identified independent predictors of suicide attempts. Estimates of adjusted odds ratios and 95% confidence intervals were calculated. In multivariable analysis, residing in Prince George (Adjusted Odds Ratio [AOR]: 1.80, 95% CI: 1.23, 2.64), ever having been sexually abused (AOR: 2.07, 95% CI: 1.39, 3.08), and ever having overdosed (AOR: 2.29, 95% CI: 1.53, 3.42) independently predicted lifetime attempted suicide. Suicide prevention and intervention programs must address historical and lifetime trauma among Aboriginal young people who struggle with substance dependence.

Impact of “Sick” and “Recovery” Roles on Brain Injury Rehabilitation Outcomes

PubMed Central

Barclay, David A.

2012-01-01

This study utilizes a multivariate, correlational, expost facto research design to examine Parsons' “sick role” as a dynamic, time-sensitive process of “sick role” and “recovery role” and the impact of this process on goal attainment (H1) and psychosocial distress (H2) of adult survivors of acquired brain injury. Measures used include the Brief Symptom Inventory-18, a Goal Attainment Scale, and an original instrument to measure sick role process. 60 survivors of ABI enrolled in community reentry rehabilitation participated. Stepwise regression analyses did not fully support the multivariate hypotheses. Two models emerged from the stepwise analyses. Goal attainment, gender, and postrehab responsibilities accounted for 40% of the shared variance of psychosocial distress. Anxiety and depression accounted for 22% of the shared variance of goal attainment with anxiety contributing to the majority of the explained variance. Bivariate analysis found sick role variables, anxiety, somatization, depression, gender, and goal attainment as significant. The study has implications for ABI rehabilitation in placing greater emphasis on sick role processes, anxiety, gender, and goal attainment in guiding program planning and future research with survivors of ABI. PMID:23119164

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

PubMed

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

The Fourier decomposition method for nonlinear and non-stationary time series analysis

PubMed Central

Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-01-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of ‘Fourier intrinsic band functions’ (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time–frequency–energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms. PMID:28413352