First- and fifth-year medical students' intention for emigration and practice abroad: a case study of Serbia.

PubMed

Santric-Milicevic, Milena M; Terzic-Supic, Zorica J; Matejic, Bojana R; Vasic, Vladimir; Ricketts, Thomas C

2014-11-01

Health worker migration is causing profound health, safety, social, economic and political challenges to countries without special policies for health professionals' mobility. This study describes the prevalence of migration intentions among medical undergraduates, identifies underlying factors related to migration intention and describes subsequent actions in Serbia. Data were captured by survey of 938 medical students from Belgrade University (94% response rate), representing two thirds of matching students in Serbia stated their intentions, reasons and obstacles regarding work abroad. Statistical analyses included descriptive statistics and a sequential multivariate logistic regression. Based on descriptive and inferential statistics we were able to predict the profile of first and fifth year medical students who intend or have plans to work abroad. This study contributes to our understanding of the causes and correlates of intent to migrate and could serve to raise awareness and point to the valuable policy options to manage migration. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Growth status of Korean orphans raised in the affluent West: anthropometric trend, multivariate determinants, and descriptive comparison with their North and South Korean peers.

PubMed

Schwekendiek, Daniel J

2017-04-01

This paper investigates the trend in height among adult Korean orphans who were adopted in early life into affluent Western nations. Final heights of 148 females were analyzed based on a Korean government survey conducted in 2008. Height of the orphans was descriptively compared against final heights of South and North Koreans. Furthermore, statistical determinants of orphan height were investigated in multivariate regressions. Mean height of Korean orphans was 160.44 cm (SD 5.89), which was higher than that of South Koreans at 158.83 cm (SD 5.01). Both Korean orphans and South Koreans were taller than North Koreans at 155.30 cm (SD 4.94). However, height of Korean orphans stagnated at around 160-161 cm while those of North and South Koreans improved over time. In the regression analysis, the socioeconomic status of the adoptive family was statistically significant in all models, while dummies for the adoptive nations and age at adoption were insignificant. This study shows that the mean final height of women experiencing extreme environmental improvements in early-life is capped at 160-161 cm, tentatively suggesting that social stress factors in the host nation or early-life factors in the birth nation might have offset some of the environmental enrichment effects achieved through intercountry adoption.

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

Meteor localization via statistical analysis of spatially temporal fluctuations in image sequences

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Šihlík, Jan; Fliegel, Karel

2015-09-01

Meteor detection is one of the most important procedures in astronomical imaging. Meteor path in Earth's atmosphere is traditionally reconstructed from double station video observation system generating 2D image sequences. However, the atmospheric turbulence and other factors cause spatially-temporal fluctuations of image background, which makes the localization of meteor path more difficult. Our approach is based on nonlinear preprocessing of image intensity using Box-Cox and logarithmic transform as its particular case. The transformed image sequences are then differentiated along discrete coordinates to obtain statistical description of sky background fluctuations, which can be modeled by multivariate normal distribution. After verification and hypothesis testing, we use the statistical model for outlier detection. Meanwhile the isolated outlier points are ignored, the compact cluster of outliers indicates the presence of meteoroids after ignition.

Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia.

PubMed

Mohamed, Ibrahim; Othman, Faridah; Ibrahim, Adriana I N; Alaa-Eldin, M E; Yunus, Rossita M

2015-01-01

This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

High precision mass measurements for wine metabolomics

PubMed Central

Roullier-Gall, Chloé; Witting, Michael; Gougeon, Régis D.; Schmitt-Kopplin, Philippe

2014-01-01

An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS) analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS2. In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (Pinot noir) and white (Chardonnay) wines from various geographic origins in Burgundy. PMID:25431760

High precision mass measurements for wine metabolomics

NASA Astrophysics Data System (ADS)

Roullier-Gall, Chloé; Witting, Michael; Gougeon, Régis; Schmitt-Kopplin, Philippe

2014-11-01

An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS) analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS². In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (Pinot noir) and white (Chardonnay) wines from various geographic origins in Burgundy.

Foot anthropometry and morphology phenomena.

PubMed

Agić, Ante; Nikolić, Vasilije; Mijović, Budimir

2006-12-01

Foot structure description is important for many reasons. The foot anthropometric morphology phenomena are analyzed together with hidden biomechanical functionality in order to fully characterize foot structure and function. For younger Croatian population the scatter data of the individual foot variables were interpolated by multivariate statistics. Foot structure descriptors are influenced by many factors, as a style of life, race, climate, and things of the great importance in human society. Dominant descriptors are determined by principal component analysis. Some practical recommendation and conclusion for medical, sportswear and footwear practice are highlighted.

[Academic performance in first year medical students: an explanatory multivariate model].

PubMed

Urrutia Aguilar, María Esther; Ortiz León, Silvia; Fouilloux Morales, Claudia; Ponce Rosas, Efrén Raúl; Guevara Guzmán, Rosalinda

2014-12-01

Current education is focused in intellectual, affective, and ethical aspects, thus acknowledging their significance in students´ metacognition. Nowadays, it is known that an adequate and motivating environment together with a positive attitude towards studies is fundamental to induce learning. Medical students are under multiple stressful, academic, personal, and vocational situations. To identify psychosocial, vocational, and academic variables of 2010-2011 first year medical students at UNAM that may help predict their academic performance. Academic surveys of psychological and vocational factors were applied; an academic follow-up was carried out to obtain a multivariate model. The data were analyzed considering descriptive, comparative, correlative, and predictive statistics. The main variables that affect students´ academic performance are related to previous knowledge and to psychological variables. The results show the significance of implementing institutional programs to support students throughout their college adaptation.

Exploring effects of therapeutic massage and patient teaching in the practice of diaphragmatic breathing on blood pressure, stress, and anxiety in hypertensive African-American women: an intervention study.

PubMed

Jefferson, Lenetra L

2010-07-01

The problem of hypertension among African-Americans is one of the major areas of health disparities. The American Heart Association (2009) noted that the prevalence of hypertension among African-Americans is perhaps among the highest in the world and this is particularly so among African-American women (44.0%). The purpose of this study was to determine how therapeutic chair massage and patient teaching in diaphragmatic breathing affected African-American women's blood pressure, stress, and anxiety levels over one week or six weeks time periods. A Modified Stress, Coping, and Adaptation Model (Roy, 1976; Lazarus, 1966), Descriptives, T-tests, Pearson Product Moment Correlations, Multivariate analysis of variance (MANOVA), and Multivariate analysis of variance with covariate (MANCOVA) were used. Descriptive statistics indicated a significance for decreased systolic blood pressure levels for the one week post massage intervention measurement with p = .01, diastolic blood pressure level significance for the same group p = .02, significance for this group's State Trait Anxiety Inventory (STAI) Y2 Scale score p = .01, and Roy's Largest Root p = .03.

Effects of alopecia on body image and quality of life of Turkish cancer women with or without headscarf.

PubMed

Erol, Ozgul; Can, Gulbeyaz; Aydıner, Adnan

2012-10-01

The aim of this study was to find out the effects of chemotherapy-related alopecia on body image and quality of life of Turkish women who have cancer with or without headscarves and factors affecting them. This descriptive study was conducted with 204 women who received chemotherapy at the Istanbul University Institute of Oncology, Turkey. The Patient Description Form, Body Image Scale and Nightingale Symptom Assessment Scale were used in data collection. Statistical analyses were performed using descriptive statistics and non-parametric tests. Logistic regression analysis was done to predict the factors affecting body image and quality of life of the patients. No difference was found between women wearing headscarves and those who did not in respect of their body image. However, women who wore headscarves who had no alopecia felt less dissatisfied with their scars, and women not wearing headscarves who had no alopecia have been feeling less self-conscious, less dissatisfied with their appearance. There was difference in terms of quality of life: women wearing headscarves had worse physical, psychological and general well-being than others. Although there were many important factors, multivariate analysis showed that for body image, having alopecia and wearing headscarves; and for quality of life, having alopecia were the variables that had considerable effects.

Role strain among male RNs in the critical care setting: Perceptions of an unfriendly workplace.

PubMed

Carte, Nicholas S; Williams, Collette

2017-12-01

Traditionally, nursing has been a female-dominated profession. Men employed as registered nurses have been in the minority and little is known about the experiences of this demographic. The purpose of this descriptive, quantitative study was to understand the relationship between the variables of demographics and causes of role strain among male nurses in critical care settings. The Sherrod Role Strain Scale assesses role strain within the context of role conflict, role overload, role ambiguity and role incongruity. Data analysis of the results included descriptive and inferential statistics. Inferential statistics involved the use of repeated measures ANOVA testing for significant difference in the causes of role strain between male nurses employed in critical care settings and a post hoc comparison of specific demographic data using multivariate analyses of variance (MANOVAs). Data from 37 male nurses in critical care settings from the northeast of the United States were used to calculate descriptive statistics standard deviation, mean of the data analysis and results of the repeated ANOVA and the post hoc secondary MANOVA analysis. The descriptive data showed that all participants worked full-time. There was an even split from those participants who worked day shift (46%) vs. night shift (43%), most the participants indicated they had 15 years or more experience as an registered nurse (54%). Significant findings of this study include two causes of role strain in male nurses employed in critical care settings which are: role ambiguity and role overload based on ethnicity. Consistent with previous research findings, the results of this study suggest that male registered nurses employed in critical care settings do experience role strain. The two main causes of role strain in male nurses are role ambiguity and role overload. Copyright © 2017. Published by Elsevier Ltd.

Reference values for the CAVIPRES-30 questionnaire, a global questionnaire on the health-related quality of life of patients with prostate cancer.

PubMed

Gómez-Veiga, F; Silmi-Moyano, A; Günthner, S; Puyol-Pallas, M; Cózar-Olmo, J M

2014-06-01

Define and establish the reference values of the CAVIPRES-30 Questionnaire, a health related quality of life questionnaire specific for prostate cancer patients. The CAVIPRES-30 was administered to 2,630 males with prostate cancer included by 238 Urologist belonging to the Spanish National Healthcare System. Descriptive analysis on socio-demographic and clinical data were performed, and multivariate analyses were used to corroborate that stratification variables were statistically significantly and independently associated to the overall score of the questionnaire. The variables Time since diagnosis of the illness, whether the patient had a Stable partner or not, if he was, or not, undergoing Symptomatic treatment were statistically significantly and independently associated (P < .001) to the overall score of the questionnaire. The reference values table of the CAVIPRES-30 questionnaire is made up of different kinds of information of each patient profile: sample size, descriptive statistics with regard to the overall score, Cronbach's alpha value (between .791 and .875) and the questionnaire's values are reported by deciles. The results of this study contribute new proof as to the suitability and usefulness of the CAVIPRES-30 questionnaire as an instrument for assessing individually the quality of life of prostate cancer. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

A multivariate regression model for detection of fumonisins content in maize from near infrared spectra.

PubMed

Giacomo, Della Riccia; Stefania, Del Zotto

2013-12-15

Fumonisins are mycotoxins produced by Fusarium species that commonly live in maize. Whereas fungi damage plants, fumonisins cause disease both to cattle breedings and human beings. Law limits set fumonisins tolerable daily intake with respect to several maize based feed and food. Chemical techniques assure the most reliable and accurate measurements, but they are expensive and time consuming. A method based on Near Infrared spectroscopy and multivariate statistical regression is described as a simpler, cheaper and faster alternative. We apply Partial Least Squares with full cross validation. Two models are described, having high correlation of calibration (0.995, 0.998) and of validation (0.908, 0.909), respectively. Description of observed phenomenon is accurate and overfitting is avoided. Screening of contaminated maize with respect to European legal limit of 4 mg kg(-1) should be assured. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-12-01

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 variables. However, this univariate approach decreases power, increases the risk for Type 1 error, and contradicts the rationale for conducting multivariate tests in the first place. The purpose of this study was to provide a user-friendly primer on conducting descriptive discriminant analysis (DDA), which is a post-hoc strategy to MANOVA that takes into account the complex relationships among multiple dependent variables. A real-world example using the Statistical Package for the Social Sciences syntax and data from 1,095 middle school students on their body composition and body image are provided to explain and interpret the results from DDA. While univariate post hocs increased the risk for Type 1 error to 76%, the DDA identified which dependent variables contributed to group differences and which groups were different from each other. For example, students in the very lean and Healthy Fitness Zone categories for body mass index experienced less pressure to lose weight, more satisfaction with their body, and higher physical self-concept than the Needs Improvement Zone groups. However, perceived pressure to gain weight did not contribute to group differences because it was a suppressor variable. Researchers are encouraged to use DDA when investigating group differences on multiple correlated dependent variables to determine which variables contributed to group differences.

What's in a title? An assessment of whether randomized controlled trial in a title means that it is one.

PubMed

Koletsi, Despina; Pandis, Nikolaos; Polychronopoulou, Argy; Eliades, Theodore

2012-06-01

In this study, we aimed to investigate whether studies published in orthodontic journals and titled as randomized clinical trials are truly randomized clinical trials. A second objective was to explore the association of journal type and other publication characteristics on correct classification. American Journal of Orthodontics and Dentofacial Orthopedics, European Journal of Orthodontics, Angle Orthodontist, Journal of Orthodontics, Orthodontics and Craniofacial Research, World Journal of Orthodontics, Australian Orthodontic Journal, and Journal of Orofacial Orthopedics were hand searched for clinical trials labeled in the title as randomized from 1979 to July 2011. The data were analyzed by using descriptive statistics, and univariable and multivariable examinations of statistical associations via ordinal logistic regression modeling (proportional odds model). One hundred twelve trials were identified. Of the included trials, 33 (29.5%) were randomized clinical trials, 52 (46.4%) had an unclear status, and 27 (24.1%) were not randomized clinical trials. In the multivariable analysis among the included journal types, year of publication, number of authors, multicenter trial, and involvement of statistician were significant predictors of correctly classifying a study as a randomized clinical trial vs unclear and not a randomized clinical trial. From 112 clinical trials in the orthodontic literature labeled as randomized clinical trials, only 29.5% were identified as randomized clinical trials based on clear descriptions of appropriate random number generation and allocation concealment. The type of journal, involvement of a statistician, multicenter trials, greater numbers of authors, and publication year were associated with correct clinical trial classification. This study indicates the need of clear and accurate reporting of clinical trials and the need for educating investigators on randomized clinical trial methodology. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis.

PubMed

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L

2016-01-01

The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n. , Camponotus androy sp. n. , Camponotus bevohitra sp. n. , Camponotus galoko sp. n. , Camponotus matsilo sp. n. , Camponotus mifaka sp. n. , Camponotus orombe sp. n. , Camponotus tafo sp. n. , Camponotus tratra sp. n. , Camponotus varatra sp. n. , and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi . This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases.

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis

PubMed Central

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L.

2016-01-01

Abstract The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n., Camponotus androy sp. n., Camponotus bevohitra sp. n., Camponotus galoko sp. n., Camponotus matsilo sp. n., Camponotus mifaka sp. n., Camponotus orombe sp. n., Camponotus tafo sp. n., Camponotus tratra sp. n., Camponotus varatra sp. n., and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi. This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases. PMID:28050160

Patient experience and process measures of quality of care at home health agencies: Factors associated with high performance.

PubMed

Smith, Laura M; Anderson, Wayne L; Lines, Lisa M; Pronier, Cristalle; Thornburg, Vanessa; Butler, Janelle P; Teichman, Lori; Dean-Whittaker, Debra; Goldstein, Elizabeth

2017-01-01

We examined the effects of provider characteristics on home health agency performance on patient experience of care (Home Health CAHPS) and process (OASIS) measures. Descriptive, multivariate, and factor analyses were used. While agencies score high on both domains, factor analyses showed that the underlying items represent separate constructs. Freestanding and Visiting Nurse Association agencies, higher number of home health aides per 100 episodes, and urban location were statistically significant predictors of lower performance. Lack of variation in composite measures potentially led to counterintuitive results for effects of organizational characteristics. This exploratory study showed the value of having separate quality domains.

Fixed order dynamic compensation for multivariable linear systems

NASA Technical Reports Server (NTRS)

Kramer, F. S.; Calise, A. J.

1986-01-01

This paper considers the design of fixed order dynamic compensators for multivariable time invariant linear systems, minimizing a linear quadratic performance cost functional. Attention is given to robustness issues in terms of multivariable frequency domain specifications. An output feedback formulation is adopted by suitably augmenting the system description to include the compensator states. Either a controller or observer canonical form is imposed on the compensator description to reduce the number of free parameters to its minimal number. The internal structure of the compensator is prespecified by assigning a set of ascending feedback invariant indices, thus forming a Brunovsky structure for the nominal compensator.

Comparative effectiveness of epsilon-aminocaproic acid and tranexamic acid on postoperative bleeding following cardiac surgery during a national medication shortage.

PubMed

Blaine, Kevin P; Press, Christopher; Lau, Ken; Sliwa, Jan; Rao, Vidya K; Hill, Charles

2016-12-01

The aim of this study was to compare the effectiveness of epsilon-aminocaproic acid (εACA) and tranexamic acid (TXA) in contemporary clinical practice during a national medication shortage. A retrospective cohort study. The study was performed in all consecutive cardiac surgery patients (n=128) admitted to the cardiac-surgical intensive care unit after surgery at a single academic center immediately before and during a national medication shortage. Demographic, clinical, and outcomes data were compared by descriptive statistics using χ 2 and t test. Surgical drainage and transfusions were compared by multivariate linear regression for patients receiving εACA before the shortage and TXA during the shortage. In multivariate analysis, no statistical difference was found for surgical drain output (OR 1.10, CI 0.97-1.26, P=.460) or red blood cell transfusion requirement (OR 1.79, CI 0.79-2.73, P=.176). Patients receiving εACA were more likely to receive rescue hemostatic medications (OR 1.62, CI 1.02-2.55, P=.041). Substitution of εACA with TXA during a national medication shortage produced equivalent postoperative bleeding and red cell transfusions, although patients receiving εACA were more likely to require supplemental hemostatic agents. Published by Elsevier Inc.

Rapid differentiation of Chinese hop varieties (Humulus lupulus) using volatile fingerprinting by HS-SPME-GC-MS combined with multivariate statistical analysis.

PubMed

Liu, Zechang; Wang, Liping; Liu, Yumei

2018-01-18

Hops impart flavor to beer, with the volatile components characterizing the various hop varieties and qualities. Fingerprinting, especially flavor fingerprinting, is often used to identify 'flavor products' because inconsistencies in the description of flavor may lead to an incorrect definition of beer quality. Compared to flavor fingerprinting, volatile fingerprinting is simpler and easier. We performed volatile fingerprinting using head space-solid phase micro-extraction gas chromatography-mass spectrometry combined with similarity analysis and principal component analysis (PCA) for evaluating and distinguishing between three major Chinese hops. Eighty-four volatiles were identified, which were classified into seven categories. Volatile fingerprinting based on similarity analysis did not yield any obvious result. By contrast, hop varieties and qualities were identified using volatile fingerprinting based on PCA. The potential variables explained the variance in the three hop varieties. In addition, the dendrogram and principal component score plot described the differences and classifications of hops. Volatile fingerprinting plus multivariate statistical analysis can rapidly differentiate between the different varieties and qualities of the three major Chinese hops. Furthermore, this method can be used as a reference in other fields. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

A huge diversity of metopids (Ciliophora, Armophorea) in soil from the Murray River floodplain, Australia. I. Description of five new species and redescription of Metopus setosus Kahl, 1927.

PubMed

Vďačný, Peter; Foissner, Wilhelm

2017-04-01

Six metopid ciliates from soil of the Murray River floodplain in Australia were studied using live observation, various silver impregnation methods, scanning electron microscopy, and multivariate statistics. One of the species is affiliated with M. setosus while the others represent new taxa. Metopus filum nov. spec. is distinguished from most congeners by the slender body, the absence of cortical granules, and the low number of ciliary rows and adoral polykinetids. Metopus palaeformides nov. spec. most resembles Heterometopus palaeformis (Kahl, 1927) Foissner, 2016b but they can be distinguished by body size, the number of adoral polykinetids, and the oral area pattern. Metopus murrayensis nov. spec. is outstanding in having a globular macronucleus surrounded by innumerable refractive granules and a conspicuously thick preoral dome. Metopus rex nov. spec. and M. magnus nov. spec. are easily distinguished from most congeners by their large body size and the shape of the macronucleus. Moreover, M. rex displays up to 30μm long endosymbiotic bacteria while the micronucleus of M. magnus is uniquely situated in a small macronuclear concavity. Multivariate statistics corroborates the distinctness of these six metopid populations. Copyright © 2016 Elsevier GmbH. All rights reserved.

Nutrition Deficiencies in Children With Intestinal Failure Receiving Chronic Parenteral Nutrition.

PubMed

Namjoshi, Shweta S; Muradian, Sarah; Bechtold, Hannah; Reyen, Laurie; Venick, Robert S; Marcus, Elizabeth A; Vargas, Jorge H; Wozniak, Laura J

2017-02-01

Home parenteral nutrition (PN) is a lifesaving therapy for children with intestinal failure (IF). Our aims were to describe the prevalence of micronutrient deficiencies (vitamin D, zinc, copper, iron, selenium) in a diverse population of children with IF receiving PN and to identify and characterize risk factors associated with micronutrient deficiencies, including hematologic abnormalities. Data were collected on 60 eligible patients through retrospective chart review between May 2012 and February 2015. Descriptive statistics included frequencies, medians, interquartile ranges (IQRs), and odds ratios (ORs). Statistical analyses included χ 2 , Fisher's exact, t tests, and logistic, univariate, and multivariate regressions. Patients were primarily young (median age, 3.3 years; IQR, 0.7-8.4), Latino (62%), and male (56%), with short bowel syndrome (70%). Of 60 study patients, 88% had ≥1 deficiency and 90% were anemic for age. Of 51 patients who had all 5 markers checked, 59% had multiple deficiencies (defined as ≥3). Multivariate analysis shows multiple deficiencies were associated with nonwhite race (OR, 9.4; P = .012) and higher body mass index z score (OR, 2.2; P = .016). Children with severe anemia (hemoglobin <8.5 g/dL) made up 50% of the cohort. Nonwhite race (OR, 6.6; P = .037) and zinc deficiency (OR, 11; P = .003) were multivariate predictors of severe anemia. Micronutrient deficiency and anemia are overwhelmingly prevalent in children with IF using chronic PN. This emphasizes the importance of universal surveillance and supplementation to potentially improve quality of life and developmental outcomes. Future research should investigate how racial disparities might contribute to nutrition outcomes for children using chronic PN.

A multivariate time series approach to modeling and forecasting demand in the emergency department.

PubMed

Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

2009-02-01

The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

Overview of the SAMSI year-long program on Statistical, Mathematical and Computational Methods for Astronomy

NASA Astrophysics Data System (ADS)

Jogesh Babu, G.

2017-01-01

A year-long research (Aug 2016- May 2017) program on `Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ is well under way at Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation research institute in Research Triangle Park, NC. This program has brought together astronomers, computer scientists, applied mathematicians and statisticians. The main aims of this program are: to foster cross-disciplinary activities; to accelerate the adoption of modern statistical and mathematical tools into modern astronomy; and to develop new tools needed for important astronomical research problems. The program provides multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI. The main program is organized around five working groups:i) Uncertainty Quantification and Astrophysical Emulationii) Synoptic Time Domain Surveysiii) Multivariate and Irregularly Sampled Time Seriesiv) Astrophysical Populationsv) Statistics, computation, and modeling in cosmology.A brief description of each of the work under way by these groups will be given. Overlaps among various working groups will also be highlighted. How the wider astronomy community can both participate and benefit from the activities, will be briefly mentioned.

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…

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.

Multivariate analysis of heavy metal contents in soils, sediments and water in the region of Meknes (central Morocco).

PubMed

Tahri, M; Benyaïch, F; Bounakhla, M; Bilal, E; Gruffat, J J; Moutte, J; Garcia, D

2005-03-01

Concentrations of Al, Fe, Cr, Cu, Ni, Pb and Zn in soils, sediments and water samples collected along the Oued Boufekrane river (Meknes, central Morocco) were determined. In soils, a homogeneous distribution of metal concentrations was observed throughout the study area except for Pb, which presents high enrichment at sites located at the vicinity of a main highway. In sediments, high enrichment, with respect to upstream sites, were observed downstream of the city of Meknes for Al, Cr, Fe and Ni and inside the city for Cu, Zn and Pb. In water samples, the metal contents showed to correlate with their homologues in sediments suggesting that the metal contents in water and sediments have identical origins. Descriptive statistics and multivariate analysis (principal factor method, PFM) were used to assist the interpretation of elemental data. This allowed the determination of the correlations between the metals and the identification of three main factor loadings controlling the metal variability in soils and sediments.

Craters on Earth, Moon, and Mars: Multivariate classification and mode of origin

USGS Publications Warehouse

Pike, R.J.

1974-01-01

Testing extraterrestrial craters and candidate terrestrial analogs for morphologic similitude is treated as a problem in numerical taxonomy. According to a principal-components solution and a cluster analysis, 402 representative craters on the Earth, the Moon, and Mars divide into two major classes of contrasting shapes and modes of origin. Craters of net accumulation of material (cratered lunar domes, Martian "calderas," and all terrestrial volcanoes except maars and tuff rings) group apart from craters of excavation (terrestrial meteorite impact and experimental explosion craters, typical Martian craters, and all other lunar craters). Maars and tuff rings belong to neither group but are transitional. The classification criteria are four independent attributes of topographic geometry derived from seven descriptive variables by the principal-components transformation. Morphometric differences between crater bowl and raised rim constitute the strongest of the four components. Although single topographic variables cannot confidently predict the genesis of individual extraterrestrial craters, multivariate statistical models constructed from several variables can distinguish consistently between large impact craters and volcanoes. ?? 1974.

Nurses' attitudes and knowledge regarding organ and tissue donation and transplantation in a provincial hospital: A descriptive and multivariate analysis.

PubMed

Lomero, Maria Del Mar; Jiménez-Herrera, María F; Rasero, Maria José; Sandiumenge, Alberto

2017-09-01

The attitudes and knowledge of nursing personnel regarding organ and tissue donation can influence the decision to donate. This study aimed to determine these two factors among nurses at a district hospital in Barcelona, Spain. A survey was carried out using a 35 item questionnaire. Results were subjected to descriptive and comparative statistical analyses using bivariate and multivariate analyses to examine the relation between demographic data and attitudes toward donation. The completion rate was 68.2%, with 98.6% of those responding stating that they were in favor of organ donation. The respondents were unsure as to whether the criteria for inclusion in transplant waiting lists were appropriate (57.5%), whereas 72.2% agreed that brain death is equivalent to death. The bivariate analysis revealed a significant association between a positive attitude toward donation and working on permanent night shift no religious beliefs. Attitudes toward donation among nurses were generally positive; a negative attitude, although attitudes towards donation among the nurses participating in the study were generally positive, it should be pointed out that when a negative attitude does exist this affects significant aspects such as belief in the diagnosis of brain death or the criteria for inclusion on the waiting list, amongst others, which reflects that specific training in donation focused on nurses continues to be needed. © 2017 John Wiley & Sons Australia, Ltd.

[Acetabular anteversion angle of the hip in the Mexican adult population measured with computed tomography].

PubMed

Rubalcava, J; Gómez-García, F; Ríos-Reina, J L

2012-01-01

Knowledge of the radiogrametric characteristics of a specific skeletal segment in a healthy population is of the utmost clinical importance. The main justification for this study is that there is no published description of the radiogrametric parameter of acetabular anteversion in a healthy Mexican adult population. A prospective, descriptive and cross-sectional study was conducted. Individuals of both genders older than 18 years and orthopedically healthy were included. They underwent a two-dimensional axial tomographic study of both hips to measure the acetabular anteversion angles. The statistical analysis consisted of obtaining central trend and scatter measurements. A multivariate analysis of variance (ANOVA) and statistical significance were performed. 118 individuals were studied, 60 males and 58 females, with a mean age of 47.7 +/- 16.7, and a range of 18-85 years. The anteversion of the entire group was 18.6 degrees + 4.1 degrees. Anteversion in males was 17.3 degrees +/- 3.5 degrees (10 degrees - 25 degrees) and in females 19.8 degrees +/- 4.7 degrees (10 degrees - 31 degrees). There were no statistically significant differences (p < or = 0.05) in right and left anteversion in the entire group. However, there were statistically significant differences (p > or = 0.005) both in the right and left sides when males and females were compared. Our study showed that there are great variations in the anteversion ranges of a healthy population. When our results are compared with those published by other authors the mean of most measurements exceeds 15 degrees. This should be useful to make therapeutic decisions that involve acetabular anteversion.

Problems with Multivariate Normality: Can the Multivariate Bootstrap Help?

ERIC Educational Resources Information Center

Thompson, Bruce

Multivariate normality is required for some statistical tests. This paper explores the implications of violating the assumption of multivariate normality and illustrates a graphical procedure for evaluating multivariate normality. The logic for using the multivariate bootstrap is presented. The multivariate bootstrap can be used when distribution…

Structural analysis and design of multivariable control systems: An algebraic approach

NASA Technical Reports Server (NTRS)

Tsay, Yih Tsong; Shieh, Leang-San; Barnett, Stephen

1988-01-01

The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.

Analyzing Faculty Salaries When Statistics Fail.

ERIC Educational Resources Information Center

Simpson, William A.

The role played by nonstatistical procedures, in contrast to multivariant statistical approaches, in analyzing faculty salaries is discussed. Multivariant statistical methods are usually used to establish or defend against prima facia cases of gender and ethnic discrimination with respect to faculty salaries. These techniques are not applicable,…

Multivariate Relationships between Statistics Anxiety and Motivational Beliefs

ERIC Educational Resources Information Center

Baloglu, Mustafa; Abbassi, Amir; Kesici, Sahin

2017-01-01

In general, anxiety has been found to be associated with motivational beliefs and the current study investigated multivariate relationships between statistics anxiety and motivational beliefs among 305 college students (60.0% women). The Statistical Anxiety Rating Scale, the Motivated Strategies for Learning Questionnaire, and a set of demographic…

Identification of phases, symmetries and defects through local crystallography

DOE PAGES

Belianinov, Alex; He, Qian; Kravchenko, Mikhail; ...

2015-07-20

Here we report that advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions. This level of fidelity is sufficient to correlate the length (and hence energy) of bonds, as well as bond angles to functional properties of materials. Traditionally, this relied on mapping locally measured parameters to macroscopic variables, for example, average unit cell. This description effectively ignores the information contained in the microscopic degrees of freedom available in a high-resolution image. Here we introduce an approach for local analysis of material structure based on statistical analysis of individual atomic neighbourhoods. Clusteringmore » and multivariate algorithms such as principal component analysis explore the connectivity of lattice and bond structure, as well as identify minute structural distortions, thus allowing for chemical description and identification of phases. This analysis lays the framework for building image genomes and structure–property libraries, based on conjoining structural and spectral realms through local atomic behaviour.« less

Differences in game-related statistics of basketball performance by game location for men's winning and losing teams.

PubMed

Gómez, Miguel A; Lorenzo, Alberto; Barakat, Rubén; Ortega, Enrique; Palao, José M

2008-02-01

The aim of the present study was to identify game-related statistics that differentiate winning and losing teams according to game location. The sample included 306 games of the 2004-2005 regular season of the Spanish professional men's league (ACB League). The independent variables were game location (home or away) and game result (win or loss). The game-related statistics registered were free throws (successful and unsuccessful), 2- and 3-point field goals (successful and unsuccessful), offensive and defensive rebounds, blocks, assists, fouls, steals, and turnovers. Descriptive and inferential analyses were done (one-way analysis of variance and discriminate analysis). The multivariate analysis showed that winning teams differ from losing teams in defensive rebounds (SC = .42) and in assists (SC = .38). Similarly, winning teams differ from losing teams when they play at home in defensive rebounds (SC = .40) and in assists (SC = .41). On the other hand, winning teams differ from losing teams when they play away in defensive rebounds (SC = .44), assists (SC = .30), successful 2-point field goals (SC = .31), and unsuccessful 3-point field goals (SC = -.35). Defensive rebounds and assists were the only game-related statistics common to all three analyses.

Quantitative methods used in Australian health promotion research: a review of publications from 1992-2002.

PubMed

Smith, Ben J; Zehle, Katharina; Bauman, Adrian E; Chau, Josephine; Hawkshaw, Barbara; Frost, Steven; Thomas, Margaret

2006-04-01

This study examined the use of quantitative methods in Australian health promotion research in order to identify methodological trends and priorities for strengthening the evidence base for health promotion. Australian health promotion articles were identified by hand searching publications from 1992-2002 in six journals: Health Promotion Journal of Australia, Australian and New Zealand journal of Public Health, Health Promotion International, Health Education Research, Health Education and Behavior and the American Journal of Health Promotion. The study designs and statistical methods used in articles presenting quantitative research were recorded. 591 (57.7%) of the 1,025 articles used quantitative methods. Cross-sectional designs were used in the majority (54.3%) of studies with pre- and post-test (14.6%) and post-test only (9.5%) the next most common designs. Bivariate statistical methods were used in 45.9% of papers, multivariate methods in 27.1% and simple numbers and proportions in 25.4%. Few studies used higher-level statistical techniques. While most studies used quantitative methods, the majority were descriptive in nature. The study designs and statistical methods used provided limited scope for demonstrating intervention effects or understanding the determinants of change.

A novel examination of atypical major depressive disorder based on attachment theory.

PubMed

Levitan, Robert D; Atkinson, Leslie; Pedersen, Rebecca; Buis, Tom; Kennedy, Sidney H; Chopra, Kevin; Leung, Eman M; Segal, Zindel V

2009-06-01

While a large body of descriptive work has thoroughly investigated the clinical correlates of atypical depression, little is known about its fundamental origins. This study examined atypical depression from an attachment theory framework. Our hypothesis was that, compared to adults with melancholic depression, those with atypical depression would report more anxious-ambivalent attachment and less secure attachment. As gender has been an important consideration in prior work on atypical depression, this same hypothesis was further tested in female subjects only. One hundred ninety-nine consecutive adults presenting to a tertiary mood disorders clinic with major depressive disorder with either atypical or melancholic features according to the Structured Clinical Interview for DSM-IV Axis-I Disorders were administered a self-report adult attachment questionnaire to assess the core dimensions of secure, anxious-ambivalent, and avoidant attachment. Attachment scores were compared across the 2 depressed groups defined by atypical and melancholic features using multivariate analysis of variance. The study was conducted between 1999 and 2004. When men and women were considered together, the multivariate test comparing attachment scores by depressive group was statistically significant at p < .05. Between-subjects testing indicated that atypical depression was associated with significantly lower secure attachment scores, with a trend toward higher anxious-ambivalent attachment scores, than was melancholia. When women were analyzed separately, the multivariate test was statistically significant at p < .01, with both secure and anxious-ambivalent attachment scores differing significantly across depressive groups. These preliminary findings suggest that attachment theory, and insecure and anxious-ambivalent attachment in particular, may be a useful framework from which to study the origins, clinical correlates, and treatment of atypical depression. Gender may be an important consideration when considering atypical depression from an attachment perspective. Copyright 2009 Physicians Postgraduate Press, Inc.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

Accurate Identification of MCI Patients via Enriched White-Matter Connectivity Network

NASA Astrophysics Data System (ADS)

Wee, Chong-Yaw; Yap, Pew-Thian; Brownyke, Jeffery N.; Potter, Guy G.; Steffens, David C.; Welsh-Bohmer, Kathleen; Wang, Lihong; Shen, Dinggang

Mild cognitive impairment (MCI), often a prodromal phase of Alzheimer's disease (AD), is frequently considered to be a good target for early diagnosis and therapeutic interventions of AD. Recent emergence of reliable network characterization techniques have made understanding neurological disorders at a whole brain connectivity level possible. Accordingly, we propose a network-based multivariate classification algorithm, using a collection of measures derived from white-matter (WM) connectivity networks, to accurately identify MCI patients from normal controls. An enriched description of WM connections, utilizing six physiological parameters, i.e., fiber penetration count, fractional anisotropy (FA), mean diffusivity (MD), and principal diffusivities (λ 1, λ 2, λ 3), results in six connectivity networks for each subject to account for the connection topology and the biophysical properties of the connections. Upon parcellating the brain into 90 regions-of-interest (ROIs), the average statistics of each ROI in relation to the remaining ROIs are extracted as features for classification. These features are then sieved to select the most discriminant subset of features for building an MCI classifier via support vector machines (SVMs). Cross-validation results indicate better diagnostic power of the proposed enriched WM connection description than simple description with any single physiological parameter.

Perturbative Gaussianizing transforms for cosmological fields

NASA Astrophysics Data System (ADS)

Hall, Alex; Mead, Alexander

2018-01-01

Constraints on cosmological parameters from large-scale structure have traditionally been obtained from two-point statistics. However, non-linear structure formation renders these statistics insufficient in capturing the full information content available, necessitating the measurement of higher order moments to recover information which would otherwise be lost. We construct quantities based on non-linear and non-local transformations of weakly non-Gaussian fields that Gaussianize the full multivariate distribution at a given order in perturbation theory. Our approach does not require a model of the fields themselves and takes as input only the first few polyspectra, which could be modelled or measured from simulations or data, making our method particularly suited to observables lacking a robust perturbative description such as the weak-lensing shear. We apply our method to simulated density fields, finding a significantly reduced bispectrum and an enhanced correlation with the initial field. We demonstrate that our method reconstructs a large proportion of the linear baryon acoustic oscillations, improving the information content over the raw field by 35 per cent. We apply the transform to toy 21 cm intensity maps, showing that our method still performs well in the presence of complications such as redshift-space distortions, beam smoothing, pixel noise and foreground subtraction. We discuss how this method might provide a route to constructing a perturbative model of the fully non-Gaussian multivariate likelihood function.

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.

Sociodemographic Characteristics of Pregnant Women Exposed to Domestic Violence During Pregnancy in an Iranian Setting

PubMed Central

Hajikhani Golchin, Nayereh Azam; Hamzehgardeshi, Zeinab; Hamzehgardeshi, Leila; Shirzad Ahoodashti, Mahboobeh

2014-01-01

Background: Domestic violence refers to any type of physical, sexual, and psychological abuse enforced in the setting of familial relationships. Domestic violence has a significant relationship with poor outcome among pregnant women. Success in resolving this social phenomenon rests on accurate assessment of the society and the factors associated with violence in that specific community. Objectives: The present study was conducted to assess the demographic characteristics of pregnant women exposed to different types of domestic violence during pregnancy in Iranian setting. Patients and Methods: This is a descriptive-analytic, cross-sectional study. Sampling was done with convenience sampling method. in the current study, 301 pregnant women aged 15-45 years of Iranian nationality who were referred to the hospital for delivery or abortion, regardless of the gestational age, were selected as the subjects. Data collection tools consisted of a sociodemographic questionnaire and a violence checklist. Violence was assessed using Revised Conflict Tactics Scale (CTS2). Data were analyzed using descriptive and analytic statistics on SPSS version 16 (SPSS, Chicago, IL, USA) and STATA version 10. The characteristics of the participants were presented as mean ± SD or number and percentage. Differences between variables were determined by the χ2 test, and multivariate logistic regression. P < 0.05 was considered significant. Results: According to the findings, 34.56% of participants had experienced psychological violence, 28.24% physical violence, and 3.65% sexual violence. Multivariate logistic regression revealed a statistically significant relationship only in the case of physical violence and history of penal conviction for partner (Adjusted Odds Ratio (AOR) = 12.60) and a patriarchal household (AOR = 16.75). Conclusions: As domestic violence is greatly influenced by the customs and cultures of each community, no single strategy can be adopted to resolve it universally. Simultaneously, it is necessary to adopt comprehensive measures to control factors associated with domestic violence in the healthcare, judiciary, and the educational systems in order to prevent and curb this social challenge. PMID:24910784

Pupil Size in Outdoor Environments

DTIC Science & Technology

2007-04-06

studies. .........................19 Table 3: Descriptive statistics for pupils measured over luminance range. .........50 Table 4: N in each...strata for all pupil measurements..........................................50 Table 5: Descriptive statistics stratified against eye color...59 Table 6: Descriptive statistics stratified against gender. .....................................64 Table 7: Descriptive

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.

Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials

PubMed Central

Jiang, Xuejun; Guo, Xu; Zhang, Ning; Wang, Bo

2018-01-01

This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials. The tests are built upon robust estimators of distribution locations (medians, Hodges-Lehmann estimators, and an extended U statistic) with both unscaled and scaled versions. The nonparametric tests are robust to outliers and do not assume that the two samples are drawn from multivariate normal distributions. Bootstrap and permutation approaches are introduced for determining the p-values of the proposed test statistics. Simulation studies are conducted and numerical results are reported to examine performance of the proposed statistical tests. The numerical results demonstrate that the robust multivariate nonparametric tests constructed from the Hodges-Lehmann estimators are more efficient than those based on medians and the extended U statistic. The permutation approach can provide a more stringent control of Type I error and is generally more powerful than the bootstrap procedure. The proposed robust nonparametric tests are applied to detect multivariate distributional difference between the intervention and control groups in the Thai Healthy Choices study and examine the intervention effect of a four-session motivational interviewing-based intervention developed in the study to reduce risk behaviors among youth living with HIV. PMID:29672555

A Hierarchical Multivariate Bayesian Approach to Ensemble Model output Statistics in Atmospheric Prediction

DTIC Science & Technology

2017-09-01

efficacy of statistical post-processing methods downstream of these dynamical model components with a hierarchical multivariate Bayesian approach to...Bayesian hierarchical modeling, Markov chain Monte Carlo methods , Metropolis algorithm, machine learning, atmospheric prediction 15. NUMBER OF PAGES...scale processes. However, this dissertation explores the efficacy of statistical post-processing methods downstream of these dynamical model components

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.

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

PROM and Labour Effects on Urinary Metabolome: A Pilot Study

PubMed Central

Meloni, Alessandra; Palmas, Francesco; Mereu, Rossella; Deiana, Sara Francesca; Fais, Maria Francesca; Mussap, Michele; Ragusa, Antonio; Pintus, Roberta; Fanos, Vassilios; Melis, Gian Benedetto

2018-01-01

Since pathologies and complications occurring during pregnancy and/or during labour may cause adverse outcomes for both newborns and mothers, there is a growing interest in metabolomic applications on pregnancy investigation. In fact, metabolomics has proved to be an efficient strategy for the description of several perinatal conditions. In particular, this study focuses on premature rupture of membranes (PROM) in pregnancy at term. For this project, urine samples were collected at three different clinical conditions: out of labour before PROM occurrence (Ph1), out of labour with PROM (Ph2), and during labour with PROM (Ph3). GC-MS analysis, followed by univariate and multivariate statistical analysis, was able to discriminate among the different classes, highlighting the metabolites most involved in the discrimination. PMID:29511388

Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

PubMed

Campos-Filho, N; Franco, E L

1989-02-01

A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

Nurses' foot care activities in home health care.

PubMed

Stolt, Minna; Suhonen, Riitta; Puukka, Pauli; Viitanen, Matti; Voutilainen, Päivi; Leino-Kilpi, Helena

2013-01-01

This study described the basic foot care activities performed by nurses and factors associated with these in the home care of older people. Data were collected from nurses (n=322) working in nine public home care agencies in Finland using the Nurses' Foot Care Activities Questionnaire (NFAQ). Data were analyzed statistically using descriptive statistics and multivariate liner models. Although some of the basic foot care activities of nurses reported using were outdated, the majority of foot care activities were consistent with recommendations in foot care literature. Longer working experience, referring patients with foot problems to a podiatrist and physiotherapist, and patient education in wart and nail care were associated with a high score for adequate foot care activities. Continuing education should focus on updating basic foot care activities and increasing the use of evidence-based foot care methods. Also, geriatric nursing research should focus in intervention research to improve the use of evidence-based basic foot care activities. Copyright © 2013 Mosby, Inc. All rights reserved.

mvMapper: statistical and geographical data exploration and visualization of multivariate analysis of population structure

USDA-ARS?s Scientific Manuscript database

Characterizing population genetic structure across geographic space is a fundamental challenge in population genetics. Multivariate statistical analyses are powerful tools for summarizing genetic variability, but geographic information and accompanying metadata is not always easily integrated into t...

HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1986-01-01

A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant.

PubMed

Zamani, Abbas Ali; Yaftian, Mohammad Reza; Parizanganeh, Abdolhossein

2012-12-17

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

PubMed Central

2012-01-01

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area. PMID:23369182

Multivariate Strategies in Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hansen, Lars Kai

2007-01-01

We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

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

A new test of multivariate nonlinear causality

PubMed Central

Bai, Zhidong; Jiang, Dandan; Lv, Zhihui; Wong, Wing-Keung; Zheng, Shurong

2018-01-01

The multivariate nonlinear Granger causality developed by Bai et al. (2010) (Mathematics and Computers in simulation. 2010; 81: 5-17) plays an important role in detecting the dynamic interrelationships between two groups of variables. Following the idea of Hiemstra-Jones (HJ) test proposed by Hiemstra and Jones (1994) (Journal of Finance. 1994; 49(5): 1639-1664), they attempt to establish a central limit theorem (CLT) of their test statistic by applying the asymptotical property of multivariate U-statistic. However, Bai et al. (2016) (2016; arXiv: 1701.03992) revisit the HJ test and find that the test statistic given by HJ is NOT a function of U-statistics which implies that the CLT neither proposed by Hiemstra and Jones (1994) nor the one extended by Bai et al. (2010) is valid for statistical inference. In this paper, we re-estimate the probabilities and reestablish the CLT of the new test statistic. Numerical simulation shows that our new estimates are consistent and our new test performs decent size and power. PMID:29304085

A new test of multivariate nonlinear causality.

PubMed

Bai, Zhidong; Hui, Yongchang; Jiang, Dandan; Lv, Zhihui; Wong, Wing-Keung; Zheng, Shurong

2018-01-01

The multivariate nonlinear Granger causality developed by Bai et al. (2010) (Mathematics and Computers in simulation. 2010; 81: 5-17) plays an important role in detecting the dynamic interrelationships between two groups of variables. Following the idea of Hiemstra-Jones (HJ) test proposed by Hiemstra and Jones (1994) (Journal of Finance. 1994; 49(5): 1639-1664), they attempt to establish a central limit theorem (CLT) of their test statistic by applying the asymptotical property of multivariate U-statistic. However, Bai et al. (2016) (2016; arXiv: 1701.03992) revisit the HJ test and find that the test statistic given by HJ is NOT a function of U-statistics which implies that the CLT neither proposed by Hiemstra and Jones (1994) nor the one extended by Bai et al. (2010) is valid for statistical inference. In this paper, we re-estimate the probabilities and reestablish the CLT of the new test statistic. Numerical simulation shows that our new estimates are consistent and our new test performs decent size and power.

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…

Psychological well-being and social support in chronic myeloid leukemia patients receiving lifelong targeted therapies.

PubMed

Efficace, Fabio; Breccia, Massimo; Cottone, Francesco; Okumura, Iris; Doro, Maribel; Riccardi, Francesca; Rosti, Gianantonio; Baccarani, Michele

2016-12-01

The main objective of this study was to investigate whether social support is independently associated with psychological well-being in chronic myeloid leukemia (CML) patients. Secondary objectives were to compare the psychological well-being profile of CML patients with that of their peers in general population and to examine possible age- and sex-related differences. Analysis was performed on 417 patients in treatment with lifelong molecularly targeted therapies. Mean age of patients analyzed was 56 years (range 19-87 years) and 247 (59 %) were male and 170 (41 %) were female. Social support was assessed with the Multidimensional Scale of Perceived Social Support and psychological well-being was evaluated with the short version of the Psychological General Well-Being Index. Descriptive statistics and multivariate logistic regression analyses were used. Multivariate logistic regression analysis revealed that a greater social support was independently associated with lower anxiety and depression, as well as with higher positive well-being, self-control, and vitality (p < 0.001). Female patients reported statistically significant worse outcomes in all dimensions of psychological well-being. Age- and sex-adjusted comparisons with population norms revealed that depression (ES = -0.42, p < 0.001) and self-control (ES = -0.48, p < 0.001) were the two main impaired psychological dimensions. This study indicates that social support is a critical factor associated with psychological well-being of CML patients treated with modern lifelong targeted therapies.

Nursing Homes Appeals of Deficiency Citations: The Informal Dispute Resolution Process

PubMed Central

Mukamel, Dana B.; Weimer, David L.; Li, Yue; Bailey, Lauren; Spector, William D.; Harrington, Charlene

2012-01-01

Objective Nursing homes found to be not meeting quality standards are cited for deficiencies. Before 1995, their only recourse was a formal appeal process, which is lengthy and costly. In 1995, the Centers for Medicare & Medicaid Services (CMS) instituted the Informal Dispute Resolution (IDR) process. This study presents for the first time national statistics about the IDR process and an analysis of the factors that influence nursing homes’ decisions to request an IDR. Design Retrospective study including descriptive statistics and multivariate logistic hierarchical models. Setting U.S. nursing homes in 2005 to 2008. Participant 15,916 Medicaid and Medicare certified nursing homes nationally, with 94,188 surveys and 9,388 IDRs. Measures The unit of observation was an annual survey or a complaint survey that generated at least one deficiency. The dependent variable was dichotomous and indicated whether the annual or a complaint survey triggered an IDR request. Independent variables included characteristics of the nursing home, the deficiency, the market, and the state regulatory environment. Results Ten percent of all annual surveys and complaint surveys resulted in IDRs. There was substantial variation across states, which persisted over time. Multivariate results suggest that nursing homes’ decisions to request an IDR depend on their assessment of the probability of success and assessment of the benefits of the submission. Conclusions Nursing homes avail themselves of the IDR process. Their propensity to do so depends on a number of factors, including the state regulatory system and the market environment in which they operate. PMID:22402171

Assessment and statistics of surgically induced astigmatism.

PubMed

Naeser, Kristian

2008-05-01

The aim of the thesis was to develop methods for assessment of surgically induced astigmatism (SIA) in individual eyes, and in groups of eyes. The thesis is based on 12 peer-reviewed publications, published over a period of 16 years. In these publications older and contemporary literature was reviewed(1). A new method (the polar system) for analysis of SIA was developed. Multivariate statistical analysis of refractive data was described(2-4). Clinical validation studies were performed. The description of a cylinder surface with polar values and differential geometry was compared. The main results were: refractive data in the form of sphere, cylinder and axis may define an individual patient or data set, but are unsuited for mathematical and statistical analyses(1). The polar value system converts net astigmatisms to orthonormal components in dioptric space. A polar value is the difference in meridional power between two orthogonal meridians(5,6). Any pair of polar values, separated by an arch of 45 degrees, characterizes a net astigmatism completely(7). The two polar values represent the net curvital and net torsional power over the chosen meridian(8). The spherical component is described by the spherical equivalent power. Several clinical studies demonstrated the efficiency of multivariate statistical analysis of refractive data(4,9-11). Polar values and formal differential geometry describe astigmatic surfaces with similar concepts and mathematical functions(8). Other contemporary methods, such as Long's power matrix, Holladay's and Alpins' methods, Zernike(12) and Fourier analyses(8), are correlated to the polar value system. In conclusion, analysis of SIA should be performed with polar values or other contemporary component systems. The study was supported by Statens Sundhedsvidenskabeligt Forskningsråd, Cykelhandler P. Th. Rasmussen og Hustrus Mindelegat, Hotelejer Carl Larsen og Hustru Nicoline Larsens Mindelegat, Landsforeningen til Vaern om Synet, Forskningsinitiativet for Arhus Amt, Alcon Denmark, and Desirée and Niels Ydes Fond.

Application of multivariate Gaussian detection theory to known non-Gaussian probability density functions

NASA Astrophysics Data System (ADS)

Schwartz, Craig R.; Thelen, Brian J.; Kenton, Arthur C.

1995-06-01

A statistical parametric multispectral sensor performance model was developed by ERIM to support mine field detection studies, multispectral sensor design/performance trade-off studies, and target detection algorithm development. The model assumes target detection algorithms and their performance models which are based on data assumed to obey multivariate Gaussian probability distribution functions (PDFs). The applicability of these algorithms and performance models can be generalized to data having non-Gaussian PDFs through the use of transforms which convert non-Gaussian data to Gaussian (or near-Gaussian) data. An example of one such transform is the Box-Cox power law transform. In practice, such a transform can be applied to non-Gaussian data prior to the introduction of a detection algorithm that is formally based on the assumption of multivariate Gaussian data. This paper presents an extension of these techniques to the case where the joint multivariate probability density function of the non-Gaussian input data is known, and where the joint estimate of the multivariate Gaussian statistics, under the Box-Cox transform, is desired. The jointly estimated multivariate Gaussian statistics can then be used to predict the performance of a target detection algorithm which has an associated Gaussian performance model.

Professional burnout, stress and job satisfaction of nursing staff at a university hospital.

PubMed

Portero de la Cruz, Silvia; Vaquero Abellán, Manuel

2015-01-01

to describe the social and work characteristics of the nursing staff at a tertiary hospital in the Public Health Service of Andalucía, to assess the degree of professional professional burnout and job satisfaction of those professionals and to study the possible relation between the professional burnout variables and the stress and job satisfaction levels on the one hand and social and employment variables on the other. descriptive and cross-sectional study in a sample of 258 baccalaureate and auxiliary nurses. As research instruments, an original and specific questionnaire was used to collect social and employment variables, the Maslach Burnout Inventory, the Nursing Stress Scale and the Font-Roja questionnaire. Descriptive, inferential statistics and multivariate analysis were applied. average scores were found for professional stress and satisfaction, corresponding to 44,23 and 65,46 points, respectively. As regards professional burnout, an average score was found on the emotional exhaustion subscale; a high score for depersonalization and a low score for professional accomplishment. Studies are needed to identify the scores on these subscales in health organizations and to produce knowledge on their interrelations.

Connection between competence, usability, environment and risk of falls in elderly adults.

PubMed

Leiva-Caro, José Alex; Salazar-González, Bertha Cecilia; Gallegos-Cabriales, Esther Carlota; Gómez-Meza, Marco Vinicio; Hunter, Kathleen F

2015-01-01

To determine connections between competence, usability, environment and risk of falls in elderly adults. Correlational descriptive study, 123 elderly adults, both male and female, aged 70 years and older were included. Data was collected via the Tinetti Scale, CESD-7 Scale, Montreal Cognitive Assessment, Usability Questionnaire on Housing and Housing Enabler; and sociodemographic and health background certificate data. For data analysis, descriptive and inferential statistics were used, multivariate linear and logistic regression models were adjusted. 42.0% of the elderly adults had presented with falls, with a higher prevalence in women, and in the group of 70-75 years. The physical environment of the house, gait, and usability were set as risk factors for falls. A negative relationship between usability and depressive symptoms, cognitive health, balance, gait, the social and physical environment was found, p <0.05; and a strong positive correlation between walking and balance, p <0.05. This study helps to better understand the phenomenon of falling, to find a connection between usability with the risk of falls, and other variables.

Connection between competence, usability, environment and risk of falls in elderly adults

PubMed Central

Leiva-Caro, José Alex; Salazar-González, Bertha Cecilia; Gallegos-Cabriales, Esther Carlota; Gómez-Meza, Marco Vinicio; Hunter, Kathleen F.

2015-01-01

Objective: to determine connections between competence, usability, environment and risk of falls in elderly adults. Method: correlational descriptive study, 123 elderly adults, both male and female, aged 70 years and older were included. Data was collected via the Tinetti Scale, CESD-7 Scale, Montreal Cognitive Assessment, Usability Questionnaire on Housing and Housing Enabler; and sociodemographic and health background certificate data. For data analysis, descriptive and inferential statistics were used, multivariate linear and logistic regression models were adjusted. Results: 42.0% of the elderly adults had presented with falls, with a higher prevalence in women, and in the group of 70-75 years. The physical environment of the house, gait, and usability were set as risk factors for falls. A negative relationship between usability and depressive symptoms, cognitive health, balance, gait, the social and physical environment was found, p <0.05; and a strong positive correlation between walking and balance, p <0.05. Conclusion: this study helps to better understand the phenomenon of falling, to find a connection between usability with the risk of falls, and other variables. PMID:26626006

Quality of reporting statistics in two Indian pharmacology journals.

PubMed

Jaykaran; Yadav, Preeti

2011-04-01

To evaluate the reporting of the statistical methods in articles published in two Indian pharmacology journals. All original articles published since 2002 were downloaded from the journals' (Indian Journal of Pharmacology (IJP) and Indian Journal of Physiology and Pharmacology (IJPP)) website. These articles were evaluated on the basis of appropriateness of descriptive statistics and inferential statistics. Descriptive statistics was evaluated on the basis of reporting of method of description and central tendencies. Inferential statistics was evaluated on the basis of fulfilling of assumption of statistical methods and appropriateness of statistical tests. Values are described as frequencies, percentage, and 95% confidence interval (CI) around the percentages. Inappropriate descriptive statistics was observed in 150 (78.1%, 95% CI 71.7-83.3%) articles. Most common reason for this inappropriate descriptive statistics was use of mean ± SEM at the place of "mean (SD)" or "mean ± SD." Most common statistical method used was one-way ANOVA (58.4%). Information regarding checking of assumption of statistical test was mentioned in only two articles. Inappropriate statistical test was observed in 61 (31.7%, 95% CI 25.6-38.6%) articles. Most common reason for inappropriate statistical test was the use of two group test for three or more groups. Articles published in two Indian pharmacology journals are not devoid of statistical errors.

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.

Integration of ecological indices in the multivariate evaluation of an urban inventory of street trees

Treesearch

J. Grabinsky; A. Aldama; A. Chacalo; H. J. Vazquez

2000-01-01

Inventory data of Mexico City's street trees were studied using classical statistical arboricultural and ecological statistical approaches. Multivariate techniques were applied to both. Results did not differ substantially and were complementary. It was possible to reduce inventory data and to group species, boroughs, blocks, and variables.

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…

Descriptions of self-treatment for the middle-aged and elderly in Shanxi, China.

PubMed

Wang, Rui; Ma, Chenjin; Jiang, Kun; Li, Ming; Ma, Shuangge

2018-01-01

Self-treatment is a widespread practice among patients with common symptoms and ailments; it is necessary to explore multiple aspects of it. Notably, there is little research into self-treatment among middle-aged and elderly people, who are more likely to fall ill. Our goals are to provide a comprehensive description of self-treatment and explore associated factors with insurance utilization and expenditures among the middle-aged and elderly populations in China. A survey was conducted in July 2016 in Shanxi, China. A stratified sampling scheme was applied to achieve representativeness. A total of 972 subjects were surveyed. Descriptive statistics, t- and Chi-squared tests, multivariate logistic regression, and multivariate linear regression were utilized. In our study, 772 (79.4%) of the surveyed subjects self-treated during the previous twelve months. Among them, 253 (32.8%) used health insurance. Subjects' characteristics were associated with insurance utilization and expenditures for self-treatment. Total cost was positively associated with insurance utilization. The subjects with a junior high education (p-value < 0.001, aOR = 0.049) and senior high education (p-value = 0.020, aOR = 0.146) had a lower probability of using insurance. For both total costs and out-of-pocket costs, subjects who were 51 to 60 years old had lower costs. The subjects who were seriously sick and had a primary school education, as well as enterprise occupations, had higher costs. Self-treatment times were also positively associated with costs. Finally, it was found that subjects who didn't use insurance had lower total costs. The prevalence of self-treatment was high (79.4%). Some characteristics were associated with insurance utilization and expenditures in self-treatment. Our results may be helpful for policy interventions, which are needed to further improve the effectiveness of health insurance in China.

Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.

PubMed Central

Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P

1999-01-01

Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149

The Effect of the Multivariate Box-Cox Transformation on the Power of MANOVA.

ERIC Educational Resources Information Center

Kirisci, Levent; Hsu, Tse-Chi

Most of the multivariate statistical techniques rely on the assumption of multivariate normality. The effects of non-normality on multivariate tests are assumed to be negligible when variance-covariance matrices and sample sizes are equal. Therefore, in practice, investigators do not usually attempt to remove non-normality. In this simulation…

Workplace stress in nursing workers from an emergency hospital: Job Stress Scale analysis.

PubMed

Urbanetto, Janete de Souza; da Silva, Priscila Costa; Hoffmeister, Eveline; de Negri, Bianca Souza; da Costa, Bartira Ercília Pinheiro; Poli de Figueiredo, Carlos Eduardo

2011-01-01

This study identifies workplace stress according to the Job Stress Scale and associates it with socio-demographic and occupational variables of nursing workers from an emergency hospital. This is a cross-sectional study and data were collected through a questionnaire applied to 388 nursing professionals. Descriptive statistics were applied; univariate and multivariate analyses were performed. The results indicate there is a significant association with being a nursing technician or auxiliary, working in the position for more than 15 years, and having low social support, with 3.84, 2.25 and 4.79 times more chances of being placed in the 'high strain job' quadrant. The study reveals that aspects related to the workplace should be monitored by competent agencies in order to improve the quality of life of nursing workers.

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

Quality of reporting statistics in two Indian pharmacology journals

PubMed Central

Jaykaran; Yadav, Preeti

2011-01-01

Objective: To evaluate the reporting of the statistical methods in articles published in two Indian pharmacology journals. Materials and Methods: All original articles published since 2002 were downloaded from the journals’ (Indian Journal of Pharmacology (IJP) and Indian Journal of Physiology and Pharmacology (IJPP)) website. These articles were evaluated on the basis of appropriateness of descriptive statistics and inferential statistics. Descriptive statistics was evaluated on the basis of reporting of method of description and central tendencies. Inferential statistics was evaluated on the basis of fulfilling of assumption of statistical methods and appropriateness of statistical tests. Values are described as frequencies, percentage, and 95% confidence interval (CI) around the percentages. Results: Inappropriate descriptive statistics was observed in 150 (78.1%, 95% CI 71.7–83.3%) articles. Most common reason for this inappropriate descriptive statistics was use of mean ± SEM at the place of “mean (SD)” or “mean ± SD.” Most common statistical method used was one-way ANOVA (58.4%). Information regarding checking of assumption of statistical test was mentioned in only two articles. Inappropriate statistical test was observed in 61 (31.7%, 95% CI 25.6–38.6%) articles. Most common reason for inappropriate statistical test was the use of two group test for three or more groups. Conclusion: Articles published in two Indian pharmacology journals are not devoid of statistical errors. PMID:21772766

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

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…

Asian American Women in California: A Pooled Analysis of Predictors for Breast and Cervical Cancer Screening

PubMed Central

Breen, Nancy; Liu, Benmei; Lee, Richard; Kagawa-Singer, Marjorie

2015-01-01

Objectives. We examined patterns of cervical and breast cancer screening among Asian American women in California and assessed their screening trends over time. Methods. We pooled weighted data from 5 cycles of the California Health Interview Survey (2001, 2003, 2005, 2007, 2009) to examine breast and cervical cancer screening trends and predictors among 6 Asian nationalities. We calculated descriptive statistics, bivariate associations, multivariate logistic regressions, predictive margins, and 95% confidence intervals. Results. Multivariate analyses indicated that Papanicolaou test rates did not significantly change over time (77.9% in 2001 vs 81.2% in 2007), but mammography receipt increased among Asian American women overall (75.6% in 2001 vs 81.8% in 2009). Length of time in the United States was associated with increased breast and cervical cancer screening among all nationalities. Sociodemographic and health care access factors had varied effects, with education and insurance coverage significantly predicting screening for certain groups. Overall, we observed striking variation by nationality. Conclusions. Our results underscore the need for intervention and policy efforts that are targeted to specific Asian nationalities, recent immigrants, and individuals without health care access to increase screening rates among Asian women in California. PMID:25521898

Descriptive Epidemiology of Factors Associated with HIV Infections Among Men and Transgender Women Who Have Sex with Men in South India.

PubMed

Shaw, Souradet Y; Lorway, Robert; Bhattacharjee, Parinita; Reza-Paul, Sushena; du Plessis, Elsabé; McKinnon, Lyle; Thompson, Laura H; Isac, Shajy; Ramesh, Banadakoppa M; Washington, Reynold; Moses, Stephen; Blanchard, James F

2016-08-01

Men and transgender women who have sex with men (MTWSM) continue to be an at-risk population for human immunodeficiency virus (HIV) infection in India. Identification of risk factors and determinants of HIV infection is urgently needed to inform prevention and intervention programming. Data were collected from cross-sectional biological and behavioral surveys from four districts in Karnataka, India. Multivariable logistic regression models were constructed to examine factors related to HIV infection. Sociodemographic, sexual history, sex work history, condom practices, and substance use covariates were included in regression models. A total of 456 participants were included; HIV prevalence was 12.4%, with the highest prevalence (26%) among MTWSM from Bellary District. In bivariate analyses, district (P = 0.002), lack of a current regular female partner (P = 0.022), and reported consumption of an alcoholic drink in the last month (P = 0.004) were associated with HIV infection. In multivariable models, only alcohol use remained statistically significant (adjusted odds ratios: 2.6, 95% confidence intervals: 1.2-5.8; P = 0.02). The prevalence of HIV continues to be high among MTWSM, with the highest prevalence found in Bellary district.

Employment hardship among older workers: does residential and gender inequality extend into older age?

PubMed

Slack, Tim; Jensen, Leif

2008-01-01

The realities of a rapidly aging society make the employment circumstances of older workers an increasingly important social issue. We examine the prevalence and correlates of underemployment among older Americans, with a special focus on residence and gender, to provide an assessment of the labor market challenges facing older workers. We analyzed data from the March Current Population Surveys for the years 2003, 2004, and 2005. We used descriptive statistics to explore the prevalence of underemployment among older workers and developed multivariate models to assess the impact of age, residence, and gender on the likelihood of underemployment, net of other predictors. We found clear disadvantages for older workers relative to their middle-aged counterparts, and particular disadvantages for older rural residents and women. Multivariate models showed that the disadvantages of older age held net of other predictors. The results also indicated that much of the disadvantage faced by older rural workers and women was explained by factors other than age, particularly education. In an aging society, underemployment among older workers comes at an increasing social cost. Policies aimed at supporting older workers and alleviating employment hardship among them are increasingly in the public interest.

Employment Hardship Among Older Workers: Does Residential and Gender Inequality Extend Into Older Age?

PubMed Central

Slack, Tim; Jensen, Leif

2008-01-01

Objectives. The realities of a rapidly aging society make the employment circumstances of older workers an increasingly important social issue. We examine the prevalence and correlates of underemployment among older Americans, with a special focus on residence and gender, to provide an assessment of the labor market challenges facing older workers. Methods. We analyzed data from the March Current Population Surveys for the years 2003, 2004, and 2005. We used descriptive statistics to explore the prevalence of underemployment among older workers and developed multivariate models to assess the impact of age, residence, and gender on the likelihood of underemployment, net of other predictors. Results. We found clear disadvantages for older workers relative to their middle-aged counterparts, and particular disadvantages for older rural residents and women. Multivariate models showed that the disadvantages of older age held net of other predictors. The results also indicated that much of the disadvantage faced by older rural workers and women was explained by factors other than age, particularly education. Discussion. In an aging society, underemployment among older workers comes at an increasing social cost. Policies aimed at supporting older workers and alleviating employment hardship among them are increasingly in the public interest. PMID:18332197

TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model.

PubMed

Niño, Maria Eugenia; Serrano, Sergio Eduardo; Niño, Daniela Camila; McCosham, Diana Margarita; Cardenas, Maria Eugenia; Villareal, Vivian Poleth; Lopez, Marcos; Pazin-Filho, Antonio; Jaimes, Fabian Alberto; Cunha, Fernando; Schulz, Richard; Torres-Dueñas, Diego

2017-01-01

Matrix metalloproteinases and tissue inhibitors of metalloproteinases could be promising biomarkers for establishing prognosis during the development of sepsis. It is necessary to clarify the relationship between matrix metalloproteinases and their tissue inhibitors. We conducted a cohort study with 563 septic patients, in order to elucidate the biological role and significance of these inflammatory biomarkers and their relationship to the severity and mortality of patients with sepsis. A multicentric prospective cohort was performed. The sample was composed of patients who had sepsis as defined by the International Conference 2001. Serum procalcitonin, creatinine, urea nitrogen, C-Reactive protein, TIMP1, TIMP2, MMP2 and MMP9 were quantified; each patient was followed until death or up to 30 days. A descriptive analysis was performed by calculating the mean and the 95% confidence interval for continuous variables and proportions for categorical variables. A multivariate logistic regression model was constructed by the method of intentional selection of covariates with mortality at 30 days as dependent variable and all the other variables as predictors. Of the 563 patients, 68 patients (12.1%) died within the first 30 days of hospitalization in the ICU. The mean values for TIMP1, TIMP2 and MMP2 were lower in survivors, MMP9 was higher in survivors. Multivariate logistic regression showed that age, SOFA and Charlson scores, along with TIMP1 concentration, were statistically associated with mortality at 30 days of septic patients; serum MMP9 was not statistically associated with mortality of patients, but was a confounder of the TIMP1 variable. It could be argued that plasma levels of TIMP1 should be considered as a promising prognostic biomarker in the setting of sepsis. Additionally, this study, like other studies with large numbers of septic patients does not support the predictive value of TIMP1 / MMP9.

A multivariate model and statistical method for validating tree grade lumber yield equations

Treesearch

Donald W. Seegrist

1975-01-01

Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.

Descriptive data analysis.

PubMed

Thompson, Cheryl Bagley

2009-01-01

This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.

Mapping the Diversity among Runaways: A Descriptive Multivariate Analysis of Selected Social Psychological Background Conditions.

ERIC Educational Resources Information Center

Brennan, Tim

1980-01-01

A review of prior classification systems of runaways is followed by a descriptive taxonomy of runaways developed using cluster-analytic methods. The empirical types illustrate patterns of weakness in bonds between runaways and families, schools, or peer relationships. (Author)

Atrial Electrogram Fractionation Distribution before and after Pulmonary Vein Isolation in Human Persistent Atrial Fibrillation-A Retrospective Multivariate Statistical Analysis.

PubMed

Almeida, Tiago P; Chu, Gavin S; Li, Xin; Dastagir, Nawshin; Tuan, Jiun H; Stafford, Peter J; Schlindwein, Fernando S; Ng, G André

2017-01-01

Purpose: Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigate CFAE distribution before and after PVI in patients with persAF using a multivariate statistical model. Methods: 207 pairs of atrial electrograms (AEGs) were collected before and after PVI respectively, from corresponding LA regions in 18 persAF patients. Twelve attributes were measured from the AEGs, before and after PVI. Statistical models based on multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) have been used to characterize the atrial regions and AEGs. Results: PVI significantly reduced CFAEs in the LA (70 vs. 40%; P < 0.0001). Four types of LA regions were identified, based on the AEGs characteristics: (i) fractionated before PVI that remained fractionated after PVI (31% of the collected points); (ii) fractionated that converted to normal (39%); (iii) normal prior to PVI that became fractionated (9%) and; (iv) normal that remained normal (21%). Individually, the attributes failed to distinguish these LA regions, but multivariate statistical models were effective in their discrimination ( P < 0.0001). Conclusion: Our results have unveiled that there are LA regions resistant to PVI, while others are affected by it. Although, traditional methods were unable to identify these different regions, the proposed multivariate statistical model discriminated LA regions resistant to PVI from those affected by it without prior ablation information.

Application of multivariate statistical techniques in microbial ecology

PubMed Central

Paliy, O.; Shankar, V.

2016-01-01

Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large scale ecological datasets. Especially noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions, and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amounts of data, powerful statistical techniques of multivariate analysis are well suited to analyze and interpret these datasets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular dataset. In this review we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive, and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and dataset structure. PMID:26786791

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.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

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.

Descriptive statistics.

PubMed

Nick, Todd G

2007-01-01

Statistics is defined by the Medical Subject Headings (MeSH) thesaurus as the science and art of collecting, summarizing, and analyzing data that are subject to random variation. The two broad categories of summarizing and analyzing data are referred to as descriptive and inferential statistics. This chapter considers the science and art of summarizing data where descriptive statistics and graphics are used to display data. In this chapter, we discuss the fundamentals of descriptive statistics, including describing qualitative and quantitative variables. For describing quantitative variables, measures of location and spread, for example the standard deviation, are presented along with graphical presentations. We also discuss distributions of statistics, for example the variance, as well as the use of transformations. The concepts in this chapter are useful for uncovering patterns within the data and for effectively presenting the results of a project.

Renewed growth in hospital inpatient cost since 1998: variation across metropolitan areas and leading clinical conditions.

PubMed

Friedman, Bernard S; Wong, Herbert S; Steiner, Claudia A

2006-03-01

To use disaggregated data about metropolitan statistical areas (MSAs) and clinical conditions to better describe the variation in cost increases and explore some of the hypothesized influences. The study uses the state inpatient databases from the Healthcare Cost and Utilization Project, containing all discharges from hospitals in 172 MSAs in 1998 and 2001. The discharge summary information was combined with standardized hospital accounting files, surveys of managed care plans, MSA demographics, and state data pertaining to caps on medical malpractice awards. The analysis used descriptive comparisons and multivariate regressions of admission rate and cost per case in 9 leading disease categories across the MSAs. The increase in hospital input prices and changes in severity of illness were controlled. Metropolitan statistical areas with higher HMO market penetration continued to show lower admission rates, no less so in 2001 than in 1998. A cap on malpractice awards appeared to restrain admissions, but the net effect on hospital cost per adult eroded for those states with the most experience with award caps. Higher admission rates and increase in cost were found in several disease categories.

Live weight, carcass ultrasound images, and visual scores in Angus cattle under feeding regimes in Brazil.

PubMed

Pinto, Luís Fernando Batista; Tarouco, Jaime Urdapilleta; Pedrosa, Victor Breno; de Farias Jucá, Adriana; Leão, André Gustavo; Moita, Antonia Kécya França

2013-08-01

This study aimed to evaluate visual precocity, muscling, conformation, skeletal, and breed scores; live weights at birth, at 205, and at 550 days of age; and, besides, rib eye area and fat thickness between the 12th and 13th ribs obtained by ultrasound. Those traits were evaluated in 1,645 Angus cattle kept in five feeding conditions as follows: supplemented or non-supplemented, grazing native pasture or grazing cultivated pasture, and feedlot. Descriptive statistics, Pearson's correlations, and principal component analysis were carried out. Gender and feeding conditions were fixed effects, while animal's age and mother's weight at weaning were the covariates analyzed. Gender and feeding conditions were very significant for the studied traits, but visual scores were not influenced by gender. Animal's age and mother's weight at weaning influenced many traits and must be appropriately adjusted in the statistical models. An important correlation between visual scores, live weights, and carcass traits obtained by ultrasound was found, which can be analyzed by univariate procedure. However, the multivariate approach revealed some information that cannot be neglected in order to ensure a more detailed assessment.

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.

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…

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.

Impact of structural and economic factors on hospitalization costs, inpatient mortality, and treatment type of traumatic hip fractures in Switzerland.

PubMed

Mehra, Tarun; Moos, Rudolf M; Seifert, Burkhardt; Bopp, Matthias; Senn, Oliver; Simmen, Hans-Peter; Neuhaus, Valentin; Ciritsis, Bernhard

2017-12-01

The assessment of structural and potentially economic factors determining cost, treatment type, and inpatient mortality of traumatic hip fractures are important health policy issues. We showed that insurance status and treatment in university hospitals were significantly associated with treatment type (i.e., primary hip replacement), cost, and lower inpatient mortality respectively. The purpose of this study was to determine the influence of the structural level of hospital care and patient insurance type on treatment, hospitalization cost, and inpatient mortality in cases with traumatic hip fractures in Switzerland. The Swiss national medical statistic 2011-2012 was screened for adults with hip fracture as primary diagnosis. Gender, age, insurance type, year of discharge, hospital infrastructure level, length-of-stay, case weight, reason for discharge, and all coded diagnoses and procedures were extracted. Descriptive statistics and multivariate logistic regression with treatment by primary hip replacement as well as inpatient mortality as dependent variables were performed. We obtained 24,678 inpatient case records from the medical statistic. Hospitalization costs were calculated from a second dataset, the Swiss national cost statistic (7528 cases with hip fractures, discharged in 2012). Average inpatient costs per case were the highest for discharges from university hospitals (US$21,471, SD US$17,015) and the lowest in basic coverage hospitals (US$18,291, SD US$12,635). Controlling for other variables, higher costs for hip fracture treatment at university hospitals were significant in multivariate regression (p < 0.001). University hospitals had a lower inpatient mortality rate than full and basic care providers (2.8% vs. both 4.0%); results confirmed in our multivariate logistic regression analysis (odds ratio (OR) 1.434, 95% CI 1.127-1.824 and OR 1.459, 95% confidence interval (CI) 1.139-1.870 for full and basic coverage hospitals vs. university hospitals respectively). The proportion of privately insured varied between 16.0% in university hospitals and 38.9% in specialized hospitals. Private insurance had an OR of 1.419 (95% CI 1.306-1.542) in predicting treatment of a hip fracture with primary hip replacement. The seeming importance of insurance type on hip fracture treatment and the large inequity in the distribution of privately insured between provider types would be worth a closer look by the regulatory authorities. Better outcomes, i.e., lower mortality rates for hip fracture treatment in hospitals with a higher structural care level advocate centralization of care.

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

A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data.

PubMed

Adams, Dean C

2014-09-01

Phylogenetic signal is the tendency for closely related species to display similar trait values due to their common ancestry. Several methods have been developed for quantifying phylogenetic signal in univariate traits and for sets of traits treated simultaneously, and the statistical properties of these approaches have been extensively studied. However, methods for assessing phylogenetic signal in high-dimensional multivariate traits like shape are less well developed, and their statistical performance is not well characterized. In this article, I describe a generalization of the K statistic of Blomberg et al. that is useful for quantifying and evaluating phylogenetic signal in highly dimensional multivariate data. The method (K(mult)) is found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices. Using computer simulations based on Brownian motion, I demonstrate that the expected value of K(mult) remains at 1.0 as trait variation among species is increased or decreased, and as the number of trait dimensions is increased. By contrast, estimates of phylogenetic signal found with a squared-change parsimony procedure for multivariate data change with increasing trait variation among species and with increasing numbers of trait dimensions, confounding biological interpretations. I also evaluate the statistical performance of hypothesis testing procedures based on K(mult) and find that the method displays appropriate Type I error and high statistical power for detecting phylogenetic signal in high-dimensional data. Statistical properties of K(mult) were consistent for simulations using bifurcating and random phylogenies, for simulations using different numbers of species, for simulations that varied the number of trait dimensions, and for different underlying models of trait covariance structure. Overall these findings demonstrate that K(mult) provides a useful means of evaluating phylogenetic signal in high-dimensional multivariate traits. Finally, I illustrate the utility of the new approach by evaluating the strength of phylogenetic signal for head shape in a lineage of Plethodon salamanders. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Professional burnout, stress and job satisfaction of nursing staff at a university hospital1

PubMed Central

Portero de la Cruz, Silvia; Vaquero Abellán, Manuel

2015-01-01

OBJECTIVES: to describe the social and work characteristics of the nursing staff at a tertiary hospital in the Public Health Service of Andalucía, to assess the degree of professional professional burnout and job satisfaction of those professionals and to study the possible relation between the professional burnout variables and the stress and job satisfaction levels on the one hand and social and employment variables on the other. METHOD: descriptive and cross-sectional study in a sample of 258 baccalaureate and auxiliary nurses. As research instruments, an original and specific questionnaire was used to collect social and employment variables, the Maslach Burnout Inventory, the Nursing Stress Scale and the Font-Roja questionnaire. Descriptive, inferential statistics and multivariate analysis were applied. RESULTS: average scores were found for professional stress and satisfaction, corresponding to 44,23 and 65,46 points, respectively. As regards professional burnout, an average score was found on the emotional exhaustion subscale; a high score for depersonalization and a low score for professional accomplishment. Studies are needed to identify the scores on these subscales in health organizations and to produce knowledge on their interrelations. PMID:26155012

Universal Pressure Ulcer Prevention Bundle With WOC Nurse Support.

PubMed

Anderson, Megan; Finch Guthrie, Patricia; Kraft, Wendy; Reicks, Patty; Skay, Carol; Beal, Alan L

2015-01-01

This study examined the effectiveness of a universal pressure ulcer prevention bundle (UPUPB) applied to intensive care unit (ICU) patients combined with proactive, semiweekly WOC nurse rounds. The UPUBP was compared to a standard guideline with referral-based WOC nurse involvement measuring adherence to 5 evidence-based prevention interventions and incidence of pressure ulcers. The study used a quasi-experimental, pre-, and postintervention design in which each phase included different subjects. Descriptive methods assisted in exploring the content of WOC nurse rounds. One hundred eighty-one pre- and 146 postintervention subjects who met inclusion criteria and were admitted to ICU for more than 24 hours participated in the study. The research setting was 3 ICUs located at North Memorial Medical Center in Minneapolis, Minnesota. Data collection included admission/discharge skin assessments, chart reviews for 5 evidence-based interventions and patient characteristics, and WOC nurse rounding logs. Study subjects with intact skin on admission identified with an initial skin assessment were enrolled in which prephase subjects received standard care and postphase subjects received the UPUPB. Skin assessments on ICU discharge and chart reviews throughout the stay determined the presence of unit-acquired pressure ulcers and skin care received. Analysis included description of WOC nurse rounds, t-tests for guideline adherence, and multivariate analysis for intervention effect on pressure ulcer incidence. Unit assignment, Braden Scale score, and ICU length of stay were covariates for a multivariate model based on bivariate logistic regression screening. The incidence of unit-acquired pressure ulcers decreased from 15.5% to 2.1%. WOC nurses logged 204 rounds over 6 months, focusing primarily on early detection of pressure sources. Data analysis revealed significantly increased adherence to heel elevation (t = -3.905, df = 325, P < .001) and repositioning (t = -2.441, df = 325, P < .015). Multivariate logistic regression modeling showed a significant reduction in unit-acquired pressure ulcers (P < .001). The intervention increased the Nagelkerke R-Square value by 0.099 (P < .001) more than 0.297 (P < .001) when including only covariates, for a final model value of 0.396 (P < .001). The UPUPB with WOC nurse rounds resulted in a statistically significant and clinically relevant reduction in the incidence of pressure ulcers.

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

Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil.

PubMed

Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; Furlan, Larissa Maria; Arrivabene, Hiulana Pereira; Monferrán, Magdalena Victoria; Matsumoto, Silvia Tamie; Milanez, Camilla Rozindo Dias; Wunderlin, Daniel Alberto; Fernandes, Marisa Narciso

2014-08-01

Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. Copyright © 2014 Elsevier Ltd. All rights reserved.

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…

Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

NASA Astrophysics Data System (ADS)

Jin, Seung-Seop; Jung, Hyung-Jo

2014-03-01

It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.

Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)

NASA Astrophysics Data System (ADS)

Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

2015-11-01

The aim of this work is to define reliable susceptibility models for shallow landslides using Logistic Regression and Random Forests multivariate statistical techniques. The study area, located in North-East Sicily, was hit on October 1st 2009 by a severe rainstorm (225 mm of cumulative rainfall in 7 h) which caused flash floods and more than 1000 landslides. Several small villages, such as Giampilieri, were hit with 31 fatalities, 6 missing persons and damage to buildings and transportation infrastructures. Landslides, mainly types such as earth and debris translational slides evolving into debris flows, were triggered on steep slopes and involved colluvium and regolith materials which cover the underlying metamorphic bedrock. The work has been carried out with the following steps: i) realization of a detailed event landslide inventory map through field surveys coupled with observation of high resolution aerial colour orthophoto; ii) identification of landslide source areas; iii) data preparation of landslide controlling factors and descriptive statistics based on a bivariate method (Frequency Ratio) to get an initial overview on existing relationships between causative factors and shallow landslide source areas; iv) choice of criteria for the selection and sizing of the mapping unit; v) implementation of 5 multivariate statistical susceptibility models based on Logistic Regression and Random Forests techniques and focused on landslide source areas; vi) evaluation of the influence of sample size and type of sampling on results and performance of the models; vii) evaluation of the predictive capabilities of the models using ROC curve, AUC and contingency tables; viii) comparison of model results and obtained susceptibility maps; and ix) analysis of temporal variation of landslide susceptibility related to input parameter changes. Models based on Logistic Regression and Random Forests have demonstrated excellent predictive capabilities. Land use and wildfire variables were found to have a strong control on the occurrence of very rapid shallow landslides.

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.

Application of multivariate statistical techniques in microbial ecology.

PubMed

Paliy, O; Shankar, V

2016-03-01

Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large-scale ecological data sets. In particular, noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amount of data, powerful statistical techniques of multivariate analysis are well suited to analyse and interpret these data sets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular data set. In this review, we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and data set structure. © 2016 John Wiley & Sons Ltd.

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications.

PubMed

Spriestersbach, Albert; Röhrig, Bernd; du Prel, Jean-Baptist; Gerhold-Ay, Aslihan; Blettner, Maria

2009-09-01

Descriptive statistics are an essential part of biometric analysis and a prerequisite for the understanding of further statistical evaluations, including the drawing of inferences. When data are well presented, it is usually obvious whether the author has collected and evaluated them correctly and in keeping with accepted practice in the field. Statistical variables in medicine may be of either the metric (continuous, quantitative) or categorical (nominal, ordinal) type. Easily understandable examples are given. Basic techniques for the statistical description of collected data are presented and illustrated with examples. The goal of a scientific study must always be clearly defined. The definition of the target value or clinical endpoint determines the level of measurement of the variables in question. Nearly all variables, whatever their level of measurement, can be usefully presented graphically and numerically. The level of measurement determines what types of diagrams and statistical values are appropriate. There are also different ways of presenting combinations of two independent variables graphically and numerically. The description of collected data is indispensable. If the data are of good quality, valid and important conclusions can already be drawn when they are properly described. Furthermore, data description provides a basis for inferential statistics.

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.

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.

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.

Lumbar subcutaneous edema and degenerative spinal disease in patients with low back pain: a retrospective MRI study.

PubMed

Quattrocchi, C C; Giona, A; Di Martino, A; Gaudino, F; Mallio, C A; Errante, Y; Occhicone, F; Vitali, M A; Zobel, B B; Denaro, V

2015-08-01

This study was designed to determine the association between LSE, spondylolisthesis, facet arthropathy, lumbar canal stenosis, BMI, radiculopathy and bone marrow edema at conventional lumbar spine MR imaging. This is a retrospective radiological study; 441 consecutive patients with low back pain (224 men and 217 women; mean age 57.3 years; mean BMI 26) underwent conventional lumbar MRI using a 1.5-T magnet (Avanto, Siemens). Lumbar MR images were reviewed by consensus for the presence of LSE, spondylolisthesis, facet arthropathy, lumbar canal stenosis, radiculopathy and bone marrow edema. Descriptive statistics and association studies were conducted using STATA software 11.0. Association studies have been performed using linear univariate regression analysis and multivariate regression analysis, considering LSE as response variable. The overall prevalence of LSE was 40%; spondylolisthesis (p = 0.01), facet arthropathy (p < 0.001), BMI (p = 0.008) and lumbar canal stenosis (p < 0.001) were included in the multivariate regression model, whereas bone marrow edema, radiculopathy and age were not. LSE is highly associated with spondylolisthesis, facet arthropathy and BMI, suggesting underestimation of its clinical impact as an integral component in chronic lumbar back pain. Longitudinal simultaneous X-ray/MRI studies should be conducted to test the relationship of LSE with lumbar spinal instability and low back pain.

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.

Distribution of black-tailed jackrabbit habitat determined by GIS in southwestern Idaho

USGS Publications Warehouse

Knick, Steven T.; Dyer, D.L.

1997-01-01

We developed a multivariate description of black-tailed jackrabbit (Lepus californicus) habitat associations from Geographical Information Systems (GIS) signatures surrounding known jackrabbit locations in the Snake River Birds of Prey National Conservation Area (NCA), in southwestern Idaho. Habitat associations were determined for characteristics within a 1-km radius (approx home range size) of jackrabbits sighted on night spotlight surveys conducted from 1987 through 1995. Predictive habitat variables were number of shrub, agriculture, and hydrography cells, mean and standard deviation of shrub patch size, habitat richness, and a measure of spatial heterogeneity. In winter, jackrabbits used smaller and less variable sizes of shrub patches and areas of higher spatial heterogeneity when compared to summer observations (P 0.05), differed significantly between high and low population phase. We used the Mahalanobis distance statistic to rank all 50-m cells in a 440,000-ha region relative to the multivariate mean habitat vector. On verification surveys to test predicted models, we sighted jackrabbits in areas ranked close to the mean habitat vector. Areas burned by large-scale fires between 1980 and 1992 or in an area repeatedly burned by military training activities had greater Mahalanobis distances from the mean habitat vector than unburned areas and were less likely to contain habitats used by jackrabbits.

Patient-provider communication and hormonal therapy side effects in breast cancer survivors.

PubMed

Lin, Jenny J; Chao, Jennifer; Bickell, Nina A; Wisnivesky, Juan P

2017-09-01

Side effects from hormonal therapy (HT) for breast cancer treatment occur frequently and are associated with worse quality of life and HT non-adherence. Whether improved patient-physician communication is associated with patients' reporting of side effects is unknown. We undertook this study to assess factors associated with women's reports of HT side effects. Between December 2012 and April 2013, we conducted a cross-sectional survey of breast cancer patients undergoing HT in an urban medical center. Descriptive statistics, univariate analyses, and multivariate analyses were used to evaluate associations. Of the 100 participants, 67% reported having HT side effects. However, when prompted, an additional 9% reported experiencing specific HT-related symptoms. Despite very high communication scores, one-third of participants reported they had not discussed side effects with providers. Multivariate analysis showed that after controlling for age, education, race, and medication beliefs, women who had difficulty asking providers for more information were more likely to report side effects (odds ratio 8.27, 95% confidence interval 1.01-69.88). Although HT side effects often occur and are bothersome, patient-provider discussions about side effects remain suboptimal. Providers should actively ask patients about medication side effects so that they can be addressed to improve quality of life and potentially, medication adherence.

Biostatistics primer: part I.

PubMed

Overholser, Brian R; Sowinski, Kevin M

2007-12-01

Biostatistics is the application of statistics to biologic data. The field of statistics can be broken down into 2 fundamental parts: descriptive and inferential. Descriptive statistics are commonly used to categorize, display, and summarize data. Inferential statistics can be used to make predictions based on a sample obtained from a population or some large body of information. It is these inferences that are used to test specific research hypotheses. This 2-part review will outline important features of descriptive and inferential statistics as they apply to commonly conducted research studies in the biomedical literature. Part 1 in this issue will discuss fundamental topics of statistics and data analysis. Additionally, some of the most commonly used statistical tests found in the biomedical literature will be reviewed in Part 2 in the February 2008 issue.

Statistical analysis and interpretation of prenatal diagnostic imaging studies, Part 2: descriptive and inferential statistical methods.

PubMed

Tuuli, Methodius G; Odibo, Anthony O

2011-08-01

The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.

Self-Regulated Learning Strategies in Relation with Statistics Anxiety

ERIC Educational Resources Information Center

Kesici, Sahin; Baloglu, Mustafa; Deniz, M. Engin

2011-01-01

Dealing with students' attitudinal problems related to statistics is an important aspect of statistics instruction. Employing the appropriate learning strategies may have a relationship with anxiety during the process of statistics learning. Thus, the present study investigated multivariate relationships between self-regulated learning strategies…

EXTENDING MULTIVARIATE DISTANCE MATRIX REGRESSION WITH AN EFFECT SIZE MEASURE AND THE ASYMPTOTIC NULL DISTRIBUTION OF THE TEST STATISTIC

PubMed Central

McArtor, Daniel B.; Lubke, Gitta H.; Bergeman, C. S.

2017-01-01

Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains. PMID:27738957

Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic.

PubMed

McArtor, Daniel B; Lubke, Gitta H; Bergeman, C S

2017-12-01

Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains.

Occurrence and transport of pesticides and alkylphenols in water samples along the Ebro River Basin

NASA Astrophysics Data System (ADS)

Navarro, Alícia; Tauler, Romà; Lacorte, Sílvia; Barceló, Damià

2010-03-01

SummaryWe report the temporal and geographical variations of a set of 30 pesticides (including triazines, organophosphorus and acetanilides) and industrial compounds in surface waters along the Ebro River during the period 2004-2006. Using descriptive statistics we found that the compounds with industrial origin (tributylphosphate, octylphenol and nonylphenol) appeared in over 60% of the samples analyzed and at very high concentrations, while pesticides had a point source origin in the Ebro delta area and overall low-levels, between 0.005 and 2.575 μg L -1. Correlations among pollutants and their distributions were studied using Principal Component Analysis (PCA), a multivariate exploratory data analysis technique which permitted us to discern between agricultural and industrial source contamination. Over a 3 years period a seasonal trend revealed highest concentrations of pesticides over the spring-summer period following pesticide application.

[Rocky Mountain spotted fever in Mexican children: Clinical and mortality factors].

PubMed

Álvarez-Hernández, Gerardo; Candia-Plata, María Del Carmen; Delgado-de la Mora, Jesús; Acuña-Meléndrez, Natalia Haydeé; Vargas-Ortega, Anabel Patricia; Licona-Enríquez, Jesús David

2016-06-01

Characterize clinical manifestations and predictors of mortality in children hospitalized for spotted fever. Cross-sectional study in 210 subjects with a diagnosis of Rocky Mountain spotted fever (RMSF) in a pediatric hospital in Sonora, from January 1st, 2004 to June 30th, 2015. Data were analyzed using descriptive statistics and multivariate logistic regression. An upward trend was observed in RMSF morbidity and mortality. Fatality rate was 30%.Three predictors were associated with risk of death: delay ≥ 5 days at the start of doxycycline (ORa= 2.95, 95% CI 1.10-7.95), acute renal failure ((ORa= 8.79, 95% CI 3.46-22.33) and severe sepsis (ORa= 3.71, 95% CI 1.44-9.58). RMSF causes high mortality in children, which can be avoided with timely initiation of doxycycline. Acute renal failure and severe sepsis are two independent predictors of death in children with RMSF.

The impact of various work schedules on sleep complaints and minor accidents during work or leisure time: evidence from a national survey.

PubMed

Chiu, Hsiao-Yean; Tsai, Pei-Shan

2013-03-01

To explore the prevalence of insomnia symptoms and excessive daytime sleepiness (EDS) in different work schedules and the impact of shift schedules on the risk of minor accidents during work or leisure time. Using the data from Taiwan Social Development Trend Survey in 2005 (n = 18,794), insomnia symptoms, EDS, and minor accidents were analyzed using descriptive statistics and multivariable logistic regression model. The evening-to-night group had significantly higher prevalence rates of insomnia symptoms. Higher prevalence rate of EDS was presented in both day-to-evening and evening-to-night groups. Adjusting for confounders, the day-to-evening shift had a higher odds ratio of minor accidents as compared with the fixed daytime workers. Extended-shift workers tend to experience insomnia symptoms and EDS and have an increased likelihood of minor accidents.

Risk prediction and impaired tactile sensory perception among cancer patients during chemotherapy.

PubMed

Cardoso, Ana Carolina Lima Ramos; Araújo, Diego Dias de; Chianca, Tânia Couto Machado

2018-01-08

to estimate the prevalence of impaired tactile sensory perception, identify risk factors, and establish a risk prediction model among adult patients receiving antineoplastic chemotherapy. historical cohort study based on information obtained from the medical files of 127 patients cared for in the cancer unit of a private hospital in a city in Minas Gerais, Brazil. Data were analyzed using descriptive and bivariate statistics, with survival and multivariate analysis by Cox regression. 57% of the 127 patients included in the study developed impaired tactile sensory perception. The independent variables that caused significant impact, together with time elapsed from the beginning of treatment up to the onset of the condition, were: bone, hepatic and regional lymph node metastases; alcoholism; palliative chemotherapy; and discomfort in lower limbs. impaired tactile sensory perception was common among adult patients during chemotherapy, indicating the need to implement interventions designed for early identification and treatment of this condition.

Ligophorus pilengas n. sp. (Monogenea: Ancyrocephalidae) from the introduced So-iuy mullet, Mugil soiuy (Teleostei: Mugilidae), in the Sea of Azov and the Black Sea.

PubMed

Sarabeev, Volodimir Leonidovich; Balbuena, Juan Antonio

2004-04-01

The monogenean Ligophorus chabaudi was originally described on the gills of the flathead mullet, Mugil cephalus, and was subsequently reported on the So-iuy mullet, Mugil soiuy. However, the morphology of sclerotized parts and multivariate statistical analyses suggest that the form from the So-iuy mullet represents a new species. This study provides a description of the new species Ligophorus pilengas n. sp. and provides additional morphological data concerning the morphology of the ventral bar that might be useful for the diagnosis of Ligophorus. Ligophorus pilengas n. sp. is the second species of Ligophorus reported on the So-iuy mullet. Zoogeographical records indicate that L. pilengas n. sp. was probably introduced to the Black Sea and the Sea of Azov from the western Pacific Ocean together with its host.

Alcohol and condom use among HIV-positive and HIV-negative female sex workers in Nagaland, India.

PubMed

Nuken, Amenla; Kermode, Michelle; Saggurti, Niranjan; Armstrong, Greg; Medhi, Gajendra Kumar

2013-09-01

This study examines the relationship between alcohol use, HIV status, and condom use among female sex workers in Nagaland, India. We analyzed data from a cross-sectional survey undertaken in 2009, using descriptive and multivariate statistics. Out of 417 female sex workers, one-fifth used alcohol daily and one-tenth were HIV-positive. HIV-positive female sex workers were more likely than HIV-negative female sex workers to consume alcohol daily (30.2% vs. 18.0%). HIV-positive daily alcohol users reported lower condom use at last sex with regular clients compared to HIV-positive non-daily alcohol users (46.2% vs. 79.3%), a relationship not evident among HIV-negative female sex workers. There is a need to promote awareness of synergies between alcohol use and HIV, and to screen for problematic alcohol use among female sex workers in order to reduce the spread of HIV.

Family Caregiver Role and Burden Related to Gender and Family Relationships

PubMed Central

Friedemann, Marie-Luise; Buckwalter, Kathleen C.

2015-01-01

This study described and contrasted family caregivers and explored the effect of gender and family relationship on the caregiver’s role perception, workload, burden, and family help. Home care agencies and community organizations assisted with the recruitment of 533 multicultural, predominantly Latino caregivers who were interviewed at home. The Caregiver Identity Theory guided the study. Survey instruments were standardized tools or were constructed and pretested for this study. Descriptive statistics and t-test analyses assisted in describing the sample and multivariate analyses were used to contrast the caregiver groups. Findings suggested a gendered approach to self-appraisal and coping. Men in this predominantly Latino and Caribbean sample felt less burden and depression than women who believed caregiving is a female duty. Family nurses should pay attention to the most vulnerable groups: older spouses resistant to using family and community resources and hard-working female adult children, and assess each family situation individually. PMID:24777069

Relationships Among Substance Use, Multiple Sexual Partners, and Condomless Sex.

PubMed

Zhao, Yunchuan Lucy; Kim, Heejung; Peltzer, Jill

2017-04-01

Male and female students manifest different behaviors in condomless sex. This cross-sectional, exploratory, correlational study examined the differences in risk factors for condomless sex between male and female high school students, using secondary data from 4,968 sexually active males and females participating in the 2011 National Youth Risk Behavior Survey. Results in descriptive statistics and multivariate binary logistic regressions revealed that condomless sex was reported as 39.70% in general. A greater proportion of females engaged in condomless sex (23.26%) than did males (16.44%). Physical abuse by sex partners was a common reason for failure to use condoms regardless of gender. Lower condom use was found in (1) those experiencing forced sex by a partner in males, (2) female smokers, and (3) female with multiple sex partners. Thus, sexual health education should address the different risk factors and consider gender characteristics to reduce condomless sex.

Epidemiology of Skin Cancer in the German Population: Impact of Socioeconomic and Geographic Factors.

PubMed

Augustin, J; Kis, A; Sorbe, C; Schäfer, I; Augustin, M

2018-04-06

Skin cancer being the most common cancer in Germany has shown increasing incidence in the past decade. Since mostly caused by excessive UV exposure, skin cancer is largely related to behaviour. So far, the impact of regional and sociodemographic factors on the development of skin cancer in Germany is unclear. The current study aimed to investigate the association of potential predictive factors with the prevalence of skin cancers in Germany. Nationwide ambulatory care claims data from persons insured in statutory health insurances (SHI) with malignant melanoma (MM, ICD-10 C43) and non-melanoma skin cancer (NMSC, ICD-10 C44) in the years 2009-2015 were analysed. In addition, sociodemographic population data and satellite based UV and solar radiation data were associated. Descriptive as well as multivariate (spatial) statistical analyses (for example Bayes' Smoothing) were conducted on county level. Data from 70.1 million insured persons were analysed. Age standardized prevalences per 100,000 SHI insured persons for MM and NMSC were 284.7 and 1126.9 in 2009 and 378.5 and 1708.2 in 2015. Marked regional variations were observed with prevalences between 32.9% and 51.6%. Multivariate analysis show statistically significant positive correlations between higher income and education, and MM/NMSC prevalence. Prevalence of MM and NMSC in Germany shows spatio-temporal dynamics. Our results show that regional UV radiation, sunshine hours and sociodemographic factors have significant impact on skin cancer prevalence in Germany. Individual behaviour obviously is a major determinant which should be subject to preventive interventions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Chordee and Penile Shortening Rather Than Voiding Function Are Associated With Patient Dissatisfaction After Urethroplasty.

PubMed

Maciejewski, Conrad C; Haines, Trevor; Rourke, Keith F

2017-05-01

To identify factors that predict patient satisfaction after urethroplasty by prospectively examining patient-reported quality of life scores using 3 validated instruments. A 3-part prospective survey consisting of the International Prostate Symptom Score (IPSS), the International Index of Erectile Function (IIEF) score, and a urethroplasty quality of life survey was completed by patients who underwent urethroplasty preoperatively and at 6 months postoperatively. The quality of life score included questions on genitourinary pain, urinary tract infection (UTI), postvoid dribbling, chordee, shortening, overall satisfaction, and overall health. Data were analyzed using descriptive statistics, paired t test, univariate and multivariate logistic regression analyses, and Wilcoxon signed-rank analysis. Patients were enrolled in the study from February 2011 to December 2014, and a total of 94 patients who underwent a total of 102 urethroplasties completed the study. Patients reported statistically significant improvements in IPSS (P < .001). Ordinal linear regression analysis revealed no association between age, IPSS, or IIEF score and patient satisfaction. Wilcoxon signed-rank analysis revealed significant improvements in pain scores (P = .02), UTI (P < .001), perceived overall health (P = .01), and satisfaction (P < .001). Univariate logistic regression identified a length >4 cm and the absence of UTI, pain, shortening, and chordee as predictors of patient satisfaction. Multivariate analysis of quality of life domain scores identified absence of shortening and absence of chordee as independent predictors of patient satisfaction following urethroplasty (P < .01). Patient voiding function and quality of life improve significantly following urethroplasty, but improvement in voiding function is not associated with patient satisfaction. Chordee status and perceived penile shortening impact patient satisfaction, and should be included in patient-reported outcome measures. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of Professional and Pre-Accession Characteristics and Junior Naval Officer Performance

DTIC Science & Technology

2018-03-01

REVIEW .............................................5 A. NAVY PERFORMANCE EVALUATION SYSTEM ............................5 B. PROFESSIONAL...17 A. DATA DESCRIPTION ...........................................................................17 B. SUMMARY...STATISTICS ......................................................................24 C. DESCRIPTIVE STATISTICS

qFeature

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

2015-09-14

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

Asymptotic Distribution of the Likelihood Ratio Test Statistic for Sphericity of Complex Multivariate Normal Distribution.

DTIC Science & Technology

1981-08-01

RATIO TEST STATISTIC FOR SPHERICITY OF COMPLEX MULTIVARIATE NORMAL DISTRIBUTION* C. Fang P. R. Krishnaiah B. N. Nagarsenker** August 1981 Technical...and their applications in time sEries, the reader is referred to Krishnaiah (1976). Motivated by the applications in the area of inference on multiple...for practical purposes. Here, we note that Krishnaiah , Lee and Chang (1976) approxi- mated the null distribution of certain power of the likeli

Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

NASA Astrophysics Data System (ADS)

Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

2014-12-01

Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

GAISE 2016 Promotes Statistical Literacy

ERIC Educational Resources Information Center

Schield, Milo

2017-01-01

In the 2005 Guidelines for Assessment and Instruction in Statistics Education (GAISE), statistical literacy featured as a primary goal. The 2016 revision eliminated statistical literacy as a stated goal. Although this looks like a rejection, this paper argues that by including multivariate thinking and--more importantly--confounding as recommended…

Descriptive Statistical Techniques for Librarians. 2nd Edition.

ERIC Educational Resources Information Center

Hafner, Arthur W.

A thorough understanding of the uses and applications of statistical techniques is integral in gaining support for library funding or new initiatives. This resource is designed to help practitioners develop and manipulate descriptive statistical information in evaluating library services, tracking and controlling limited resources, and analyzing…

Southeast Atlantic Cloud Properties in a Multivariate Statistical Model - How Relevant is Air Mass History for Local Cloud Properties?

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik

2017-04-01

This study aims at untangling the impacts of external dynamics and local conditions on cloud properties in the Southeast Atlantic (SEA) by combining satellite and reanalysis data using multivariate statistics. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget, and thus prominent in climate-system research. In this study, SEA stratocumulus cloud properties are observed not only as the result of local environmental conditions but also as affected by external dynamics and spatial origins of air masses entering the study area. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a multivariate approach is conducted using satellite observations of aerosol and cloud properties (MODIS, SEVIRI), information on aerosol species composition (MACC) and meteorological context (ERA-Interim reanalysis). To account for the often-neglected but important role of air mass origin, information on air mass history based on HYSPLIT modeling is included in the statistical model. This multivariate approach is intended to lead to a better understanding of the physical processes behind observed stratocumulus cloud properties in the SEA.

Descriptive statistics and spatial distributions of geochemical variables associated with manganese oxide-rich phases in the northern Pacific

USGS Publications Warehouse

Botbol, Joseph Moses; Evenden, Gerald Ian

1989-01-01

Tables, graphs, and maps are used to portray the frequency characteristics and spatial distribution of manganese oxide-rich phase geochemical data, to characterize the northern Pacific in terms of publicly available nodule geochemical data, and to develop data portrayal methods that will facilitate data analysis. Source data are a subset of the Scripps Institute of Oceanography's Sediment Data Bank. The study area is bounded by 0° N., 40° N., 120° E., and 100° W. and is arbitrarily subdivided into 14-20°x20° geographic subregions. Frequency distributions of trace metals characterized in the original raw data are graphed as ogives, and salient parameters are tabulated. All variables are transformed to enrichment values relative to median concentration within their host subregions. Scatter plots of all pairs of original variables and their enrichment transforms are provided as an aid to the interpretation of correlations between variables. Gridded spatial distributions of all variables are portrayed as gray-scale maps. The use of tables and graphs to portray frequency statistics and gray-scale maps to portray spatial distributions is an effective way to prepare for and facilitate multivariate data analysis.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Study of the questionnaire of the Polytechnic University of Valencia (UPV) teaching staff, using students opinion survey. Statistical treatment

NASA Astrophysics Data System (ADS)

Martinez Gomez, Monica

Quality improvement of university institutions represents the most important challenge in the next years, and the potential tool to achieve it is based on the institutional evaluation in general, and specially the evaluation of the teaching performance. The opinion questionnaire from the students is the most generalised tool used to evaluate the teaching performance at Spanish universities. The general objective of this thesis is to develop a statistical methodology suitable to extract, analyse and interpret the information contained in the Questionnaire of Teaching Evaluation from Student Opinion (CEDA) of the UPV, aimed at optimising its practical use. The study is centred in the application of different multivariate techniques and has been structured in three parts: (1) Evaluation of the reliability, validity and dimensionality of the tool. The multivariate method used for this purpose is the Factorial Analysis. (2) Determination of the capacity of the questionnaire to identify different profiles of lecturers based on the quality perceived by students. This target is conducted with different multivariate classification techniques: hierarchical cluster analysis, non-hierarchical and two-stage analysis. Moreover, those items that best discriminate among the teaching typologies obtained are identified in the questionnaire. (3) Identification of the teaching typologies according to different descriptive characteristics referent to the subject and lecturer, with the use of decision trees. Once identified these typologies, a new discriminant analysis is conducted aimed at identifying those items that best characterise each typology. Finally, a study is carried out with the classification method SIMCA (Soft Independent Modelling of Class Analogy) in order to determine the discriminant loading of every item among the identified teaching typologies, allowing the identification of those that best distinguish the different classes obtained. With the combined use of the proposed techniques, it is expected to optimise the use of CEDA as a measuring tool and an indicator of the teaching quality at the university, that would allow the introduction of actions for the continuous improvement in the teaching processes of the UPV.

Resemblance profiles as clustering decision criteria: Estimating statistical power, error, and correspondence for a hypothesis test for multivariate structure.

PubMed

Kilborn, Joshua P; Jones, David L; Peebles, Ernst B; Naar, David F

2017-04-01

Clustering data continues to be a highly active area of data analysis, and resemblance profiles are being incorporated into ecological methodologies as a hypothesis testing-based approach to clustering multivariate data. However, these new clustering techniques have not been rigorously tested to determine the performance variability based on the algorithm's assumptions or any underlying data structures. Here, we use simulation studies to estimate the statistical error rates for the hypothesis test for multivariate structure based on dissimilarity profiles (DISPROF). We concurrently tested a widely used algorithm that employs the unweighted pair group method with arithmetic mean (UPGMA) to estimate the proficiency of clustering with DISPROF as a decision criterion. We simulated unstructured multivariate data from different probability distributions with increasing numbers of objects and descriptors, and grouped data with increasing overlap, overdispersion for ecological data, and correlation among descriptors within groups. Using simulated data, we measured the resolution and correspondence of clustering solutions achieved by DISPROF with UPGMA against the reference grouping partitions used to simulate the structured test datasets. Our results highlight the dynamic interactions between dataset dimensionality, group overlap, and the properties of the descriptors within a group (i.e., overdispersion or correlation structure) that are relevant to resemblance profiles as a clustering criterion for multivariate data. These methods are particularly useful for multivariate ecological datasets that benefit from distance-based statistical analyses. We propose guidelines for using DISPROF as a clustering decision tool that will help future users avoid potential pitfalls during the application of methods and the interpretation of results.

Learning investment indicators through data extension

NASA Astrophysics Data System (ADS)

Dvořák, Marek

2017-07-01

Stock prices in the form of time series were analysed using single and multivariate statistical methods. After simple data preprocessing in the form of logarithmic differences, we augmented this single variate time series to a multivariate representation. This method makes use of sliding windows to calculate several dozen of new variables using simple statistic tools like first and second moments as well as more complicated statistic, like auto-regression coefficients and residual analysis, followed by an optional quadratic transformation that was further used for data extension. These were used as a explanatory variables in a regularized logistic LASSO regression which tried to estimate Buy-Sell Index (BSI) from real stock market data.

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.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.

PubMed

Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

PubMed Central

Timmis, Jon; Qwarnstrom, Eva E.

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414

Fear of crime and its relationship to self-reported health and stress among men.

PubMed

Macassa, Gloria; Winersjö, Rocio; Wijk, Katarina; McGrath, Cormac; Ahmadi, Nader; Soares, Joaquim

2017-12-13

Fear of crime is a growing social and public health problem globally, including in developed countries such as Sweden. This study investigated the impact of fear of crime on self-reported health and stress among men living in Gävleborg County. The study used data collected from 2993 men through a cross sectional survey in the 2014 Health in Equal Terms survey. Descriptive and logistic regression analyses were carried out to study the relationship between fear of crime and self-reported health and stress. There was a statistically significant association between fear of crime and self-reported poor health and stress among men residing in Gävleborg County. In the bivariate analysis, men who reported fear of crime had odds of 1.98 (CI 1.47-2.66) and 2.23 (CI 1.45-3.41) respectively. Adjusting for demographic, social and economic variables in the multivariate analysis only reduced the odds ratio for self-reported poor health to 1.52 (CI 1.05-2.21) but not for self-reported stress with odds of 2.22 (1.27-3.86). Fear of crime among men was statistically significantly associated with self-reported poor health and stress in Gävleborg County. However, the statistically significant relationship remained even after accounting for demographic, social and economic factors, which warrants further research to better understand the role played by other variables.

Quick Overview Scout 2008 Version 1.0

EPA Science Inventory

The Scout 2008 version 1.0 statistical software package has been updated from past DOS and Windows versions to provide classical and robust univariate and multivariate graphical and statistical methods that are not typically available in commercial or freeware statistical softwar...

Fully probabilistic control design in an adaptive critic framework.

PubMed

Herzallah, Randa; Kárný, Miroslav

2011-12-01

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Descriptive and inferential statistical methods used in burns research.

PubMed

Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars

2010-05-01

Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals in the fields of biostatistics and epidemiology when using more advanced statistical techniques. Copyright 2009 Elsevier Ltd and ISBI. All rights reserved.

The Statistical Consulting Center for Astronomy (SCCA)

NASA Technical Reports Server (NTRS)

Akritas, Michael

2001-01-01

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

The use of multivariate statistics in studies of wildlife habitat

Treesearch

David E. Capen

1981-01-01

This report contains edited and reviewed versions of papers presented at a workshop held at the University of Vermont in April 1980. Topics include sampling avian habitats, multivariate methods, applications, examples, and new approaches to analysis and interpretation.

Rejection of Multivariate Outliers.

DTIC Science & Technology

1983-05-01

available in Gnanadesikan (1977). 2 The motivation for the present investigation lies in a recent paper of Schvager and Margolin (1982) who derive a... Gnanadesikan , R. (1977). Methods for Statistical Data Analysis of Multivariate Observations. Wiley, New York. [7] Hawkins, D.M. (1980). Identification of

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 ...

Writing to Learn Statistics in an Advanced Placement Statistics Course

ERIC Educational Resources Information Center

Northrup, Christian Glenn

2012-01-01

This study investigated the use of writing in a statistics classroom to learn if writing provided a rich description of problem-solving processes of students as they solved problems. Through analysis of 329 written samples provided by students, it was determined that writing provided a rich description of problem-solving processes and enabled…

The Greyhound Strike: Using a Labor Dispute to Teach Descriptive Statistics.

ERIC Educational Resources Information Center

Shatz, Mark A.

1985-01-01

A simulation exercise of a labor-management dispute is used to teach psychology students some of the basics of descriptive statistics. Using comparable data sets generated by the instructor, students work in small groups to develop a statistical presentation that supports their particular position in the dispute. (Author/RM)

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.

[Impact of childhood sexual abuse on the sexual and affective relationships of adult women].

PubMed

López, Sílvia; Faro, Concepció; Lopetegui, Lourdes; Pujol-Ribera, Enriqueta; Monteagudo, Mònica; Cobo, Jesús; Fernández, María Isabel

To analyse perceived sexual satisfaction, sexual dysfunction, satisfaction with affective relationships and confidence and communication in existing relationships, related to a past history of childhood sexual abuse (CSA) and type suffered, among women treated as part of the Catalonian Sexual and Reproductive Health Care Programme (PASSIR). Multicentric, descriptive, cross-sectional study. A total of 1,013 women over the age of 18 years, who underwent psychological therapy at any of the 24 PASSIR centres, were enrolled. A structured, anonymised, self-administered Sex History Questionnaire adapted from Wyatt (1985) & Dubé et al. (2005), and the Female Sexual Function Index (Rosen, 2000), were used. Statistical analysis was descriptive, bivariate and multivariate. Women who suffered childhood sexual abuse had a significantly higher prevalence of sexual dysfunction, with lower perceived sexual satisfaction. CSA with penetration or attempted penetration was associated with greater arousal difficulties and greater rejection. Women who experienced CSA were less confident and experienced greater communication difficulties with their partner. It is necessary to identify potential childhood sexual abuse among women who seek therapy due to relationship problems. It is also necessary to continue research into protective factors and therapeutic interventions to alleviate the consequences of CSA in adult life. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Registered nurses' perceptions of rewarding and its significance.

PubMed

Seitovirta, Jaana; Lehtimäki, Aku-Ville; Vehviläinen-Julkunen, Katri; Mitronen, Lasse; Kvist, Tarja

2017-11-07

To examine reward type preferences and their relationships with the significance of rewarding perceived by registered nurses in Finland. Previous studies have found relationships between nurses' rewarding and their motivation at work, job satisfaction and organisational commitment. Data were collected in a cross-sectional, descriptive, questionnaire survey from 402 registered nurses using the Registered Nurses' Perceptions of Rewarding Scale in 2015, and analysed with descriptive and multivariate statistical methods. Registered nurses assigned slightly higher values to several non-financial than to financial rewards. The non-financial reward types appreciation and feedback from work community, worktime arrangements, work content, and opportunity to develop, influence and participate were highly related to the significance of rewarding. We identified various rewards that registered nurses value, and indications that providing an appropriate array of rewards, particularly non-financial rewards, is a highly beneficial element of nursing management. It is important to understand the value of rewards for nursing management. Nurse managers should offer diverse rewards to their registered nurses to promote excellent performance and to help efforts to secure and maintain high-quality, safe patient care. The use of appropriate rewards is especially crucial to improving registered nurses' reward satisfaction and job satisfaction globally in the nursing profession. © 2017 John Wiley & Sons Ltd.

Facial trauma as physical violence markers against elderly Brazilians: A comparative analysis between genders.

PubMed

de Sousa, Rayanne Izabel Maciel; de Macedo Bernardino, Ítalo; Castro, Ricardo Dias; Cavalcanti, Alessandro Leite; Bento, Patricia Meira; d'Ávila, Sérgio

2016-01-01

The aim of this study was to characterize the profile of elderly Brazilians with injuries resulting from physical violence and identify victimization differences. A descriptive and exploratory study was conducted involving the analysis of medico-legal and social records of 259 elderly victims of physical violence treated at an Institute of Forensic Medicine and Dentistry over four years (from January 2008 to December 2011). The forensic service database was evaluated by researchers properly trained and calibrated to perform this function between January and March 2013. Socio-demographic variables of victims, aggression characteristics, aggressor's profile and types of lesions were evaluated. Descriptive and multivariate statistics using Multiple Correspondence Analysis (MCA) were performed. The prevalence of facial trauma was 42.9%. Based on the MCA results, two groups with different victimization profiles were identified: married men aged 70-79 years, victims of community violence at night, suffering facial injuries; and single, widowed or separated women aged 60-69 years, victims of domestic violence during the day, suffering trauma in other areas of the body. The results suggest that there is a high prevalence of facial injuries among elderly Brazilians victims of physical violence and there are important differences related to victimization characteristics according to gender. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rear-End Crashes: Problem Size Assessment And Statistical Description

DOT National Transportation Integrated Search

1993-05-01

KEYWORDS : RESEARCH AND DEVELOPMENT OR R&D, ADVANCED VEHICLE CONTROL & SAFETY SYSTEMS OR AVCSS, INTELLIGENT VEHICLE INITIATIVE OR IVI : THIS DOCUMENT PRESENTS PROBLEM SIZE ASSESSMENTS AND STATISTICAL CRASH DESCRIPTION FOR REAR-END CRASHES, INC...

Effects of reservoir heterogeneity on scaling of effective mass transfer coefficient for solute transport

NASA Astrophysics Data System (ADS)

Leung, Juliana Y.; Srinivasan, Sanjay

2016-09-01

Modeling transport process at large scale requires proper scale-up of subsurface heterogeneity and an understanding of its interaction with the underlying transport mechanisms. A technique based on volume averaging is applied to quantitatively assess the scaling characteristics of effective mass transfer coefficient in heterogeneous reservoir models. The effective mass transfer coefficient represents the combined contribution from diffusion and dispersion to the transport of non-reactive solute particles within a fluid phase. Although treatment of transport problems with the volume averaging technique has been published in the past, application to geological systems exhibiting realistic spatial variability remains a challenge. Previously, the authors developed a new procedure where results from a fine-scale numerical flow simulation reflecting the full physics of the transport process albeit over a sub-volume of the reservoir are integrated with the volume averaging technique to provide effective description of transport properties. The procedure is extended such that spatial averaging is performed at the local-heterogeneity scale. In this paper, the transport of a passive (non-reactive) solute is simulated on multiple reservoir models exhibiting different patterns of heterogeneities, and the scaling behavior of effective mass transfer coefficient (Keff) is examined and compared. One such set of models exhibit power-law (fractal) characteristics, and the variability of dispersion and Keff with scale is in good agreement with analytical expressions described in the literature. This work offers an insight into the impacts of heterogeneity on the scaling of effective transport parameters. A key finding is that spatial heterogeneity models with similar univariate and bivariate statistics may exhibit different scaling characteristics because of the influence of higher order statistics. More mixing is observed in the channelized models with higher-order continuity. It reinforces the notion that the flow response is influenced by the higher-order statistical description of heterogeneity. An important implication is that when scaling-up transport response from lab-scale results to the field scale, it is necessary to account for the scale-up of heterogeneity. Since the characteristics of higher-order multivariate distributions and large-scale heterogeneity are typically not captured in small-scale experiments, a reservoir modeling framework that captures the uncertainty in heterogeneity description should be adopted.

Statistics in the pharmacy literature.

PubMed

Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R

2004-09-01

Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Assessment of trace elements levels in patients with Type 2 diabetes using multivariate statistical analysis.

PubMed

Badran, M; Morsy, R; Soliman, H; Elnimr, T

2016-01-01

The trace elements metabolism has been reported to possess specific roles in the pathogenesis and progress of diabetes mellitus. Due to the continuous increase in the population of patients with Type 2 diabetes (T2D), this study aims to assess the levels and inter-relationships of fast blood glucose (FBG) and serum trace elements in Type 2 diabetic patients. This study was conducted on 40 Egyptian Type 2 diabetic patients and 36 healthy volunteers (Hospital of Tanta University, Tanta, Egypt). The blood serum was digested and then used to determine the levels of 24 trace elements using an inductive coupled plasma mass spectroscopy (ICP-MS). Multivariate statistical analysis depended on correlation coefficient, cluster analysis (CA) and principal component analysis (PCA), were used to analysis the data. The results exhibited significant changes in FBG and eight of trace elements, Zn, Cu, Se, Fe, Mn, Cr, Mg, and As, levels in the blood serum of Type 2 diabetic patients relative to those of healthy controls. The statistical analyses using multivariate statistical techniques were obvious in the reduction of the experimental variables, and grouping the trace elements in patients into three clusters. The application of PCA revealed a distinct difference in associations of trace elements and their clustering patterns in control and patients group in particular for Mg, Fe, Cu, and Zn that appeared to be the most crucial factors which related with Type 2 diabetes. Therefore, on the basis of this study, the contributors of trace elements content in Type 2 diabetic patients can be determine and specify with correlation relationship and multivariate statistical analysis, which confirm that the alteration of some essential trace metals may play a role in the development of diabetes mellitus. Copyright © 2015 Elsevier GmbH. All rights reserved.

A Case Study on Teaching the Topic "Experimental Unit" and How It Is Presented in Advanced Placement Statistics Textbooks

ERIC Educational Resources Information Center

Perrett, Jamis J.

2012-01-01

This article demonstrates how textbooks differ in their description of the term "experimental unit". Advanced Placement Statistics teachers and students are often limited in their statistical knowledge by the information presented in their classroom textbook. Definitions and descriptions differ among textbooks as well as among different…

Accession Medical Standards Analysis and Research Activity (AMSARA) 2014, Annual Report, and four Supplemental Applicants and Accessions Tables for: Army, Air Force, Marine, and Navy

DTIC Science & Technology

2016-02-02

23 Descriptive Statistics for Enlisted Service Applicants and Accessions...33 Summary Statistics for Applicants and Accessions for Enlisted Service ..................................... 36 Applicants and...utilization among Soldiers screened using TAPAS. Section 2 of this report includes the descriptive statistics AMSARA compiles and publishes

Statistical methods used in the public health literature and implications for training of public health professionals

PubMed Central

Hayat, Matthew J.; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L.

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals. PMID:28591190

Statistical methods used in the public health literature and implications for training of public health professionals.

PubMed

Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.

Psychosocial predictors of depression among older African American cancer patients

PubMed Central

Hamilton, Jill B.; Deal, Allison M.; Moore, Angelo D.; Best, Nakia C.; Galbraith, Kayoll V.; Muss, Hyman

2013-01-01

Purpose To determine whether psychosocial factors predict depression among older African American cancer patients. Design/Methods A descriptive correlational study. Setting Outpatient oncology clinic of NCI designated Cancer Center in Southeastern U.S. Sample African American cancer patients aged 50 and over. Methods Fisher’s Exact and Wilcoxon Rank Sum tests were used to evaluate differences between patients who were possibly depressed (Geriatric Depression Scale) or not. Multivariate linear regression statistics were used to identify the psychosocial factors that predicted higher depression scores. Education and gender were included as covariates. Main Variables Religiosity, emotional support, collectivism, perceived stigma and depression. Findings African American cancer patients (n=77) were on average a median age of 58 years (IQR = 55–65), a majority were well-educated, insured, religiously affiliated, and currently in treatment. Participants in the lowest income category, not married, and male gender had higher depression scores. The multivariable model consisting of organized religion, emotional support, collectivism, education, and gender explained 52% (adjusted R2) of the variation in depression scores. Stigma became insignificant in the multivariable model. Conclusions Psychosocial factors are important predictors of depression. For these participants, emotional support and organized religious activities may represent protective factors against depression, while collectivism may increase their risk. Implications Nurses need to be especially aware of the potential psychological strain for patients with collectivist values, experienced stigma, disruptions in church attendance and lack of emotional support. Further, these treatment plans for these patients should ensure that family members are knowledgeable about cancer, its treatment and side effects so they are empowered to meet the needs for support of the African American cancer patient. PMID:23803271

Multivariate Analysis and Prediction of Dioxin-Furan ...

EPA Pesticide Factsheets

Peer Review Draft of Regional Methods Initiative Final Report Dioxins, which are bioaccumulative and environmentally persistent, pose an ongoing risk to human and ecosystem health. Fish constitute a significant source of dioxin exposure for humans and fish-eating wildlife. Current dioxin analytical methods are costly, time-consuming, and produce hazardous by-products. A Danish team developed a novel, multivariate statistical methodology based on the covariance of dioxin-furan congener Toxic Equivalences (TEQs) and fatty acid methyl esters (FAMEs) and applied it to North Atlantic Ocean fishmeal samples. The goal of the current study was to attempt to extend this Danish methodology to 77 whole and composite fish samples from three trophic groups: predator (whole largemouth bass), benthic (whole flathead and channel catfish) and forage fish (composite bluegill, pumpkinseed and green sunfish) from two dioxin contaminated rivers (Pocatalico R. and Kanawha R.) in West Virginia, USA. Multivariate statistical analyses, including, Principal Components Analysis (PCA), Hierarchical Clustering, and Partial Least Squares Regression (PLS), were used to assess the relationship between the FAMEs and TEQs in these dioxin contaminated freshwater fish from the Kanawha and Pocatalico Rivers. These three multivariate statistical methods all confirm that the pattern of Fatty Acid Methyl Esters (FAMEs) in these freshwater fish covaries with and is predictive of the WHO TE

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

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).

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

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

C-statistic fitting routines: User's manual and reference guide

NASA Technical Reports Server (NTRS)

Nousek, John A.; Farwana, Vida

1991-01-01

The computer program is discussed which can read several input files and provide a best set of values for the functions provided by the user, using either C-statistic or the chi(exp 2) statistic method. The program consists of one main routine and several functions and subroutines. Detail descriptions of each function and subroutine is presented. A brief description of the C-statistic and the reason for its application is also presented.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

[What factors help to explain satisfaction with Primary Health care in Spain?].

PubMed

Arrazola-Vacas, M; de Hevia-Payá, J; Rodríguez-Esteban, L

2015-01-01

To find out the factors that determine satisfaction with public primary health care in Spain. The work has considered a wide group of potential determining factors of that satisfaction, which are organised into 3 blocks of variables: Those related to the perceived quality in the care received, socioeconomic, and those relative to the state of health. The micro data of the Barómetro Sanitario (BS) of 2013, which are representative at a national level, were employed. After a prior first descriptive analysis, 2 multivariate models were estimated: One in which satisfaction is considered as being of a cardinal nature (regression model), and another in which it is contemplated as being of an ordinal nature (ordered probit model). There were practically no differences between the results obtained with one or other of the multivariate models. Not all the variables considered were statistically significant. Of the 3 blocks of variables studied, the one related to the perceived quality in the care received in the health centre exerts the greatest relevance in the explanation of satisfaction. The results obtained show that, by means of the management of the variables related to the perception of quality of care in health centres, public administrators and health professionals may have a highly favourable influence on the levels of satisfaction of primary health care patients. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

Perinatal Depression and Associated Factors among Mothers in Southern Ethiopia: Evidence from Arba Minch Zuria Health and Demographic Surveillance Site.

PubMed

Gebremichael, Gebrekiros; Yihune, Manaye; Ajema, Dessalegn; Haftu, Desta; Gedamu, Genet

2018-01-01

Background. Perinatal depression is a serious mental health problem that can negatively affect the lives of women and children. The adverse consequences of perinatal depression in high-income countries also occur in low-income countries. Objective. To assess the perinatal depression and associated factors among mothers in Southern Ethiopia. Methods. A community based cross-sectional study was conducted among selected 728 study participants in Arba Minch Zuria HDSS. A pretested questionnaire was used to collect the data. Data were analyzed using STATA version 12 software. Descriptive statistical methods were used to summarize the characteristics of the mothers. Bivariate and multivariable logistic regression was used for analysis. Results. The prevalence of perinatal depression among the study period was 26.7%. In the final multivariable logistic regression, monthly income AOR (95% C.I): 4.2 (1.9, 9.3), parity [AOR (95% C.I): 0.14 (0.03, 0.65)], pregnancy complications AOR (95% C.I): 5 (2.5, 10.4), husband smoking status [AOR (95% C.I): 4.12 (1.6, 10.6)], history of previous depression AOR (95% C.I): 2.7 (1.54, 4.8), and family history of psychiatric disorders were the independent factors associated with perinatal depression. Conclusion. The study showed a high prevalence of perinatal depression among pregnant mothers and mothers who have less than a one-year-old child.

Risk perception and sexual behavior in HPV-vaccinated and unvaccinated young Colombian women.

PubMed

Ruiz-Sternberg, Angela M; Pinzón-Rondón, Ángela M

2014-09-01

To compare sexual behaviors and risk perception between young women vaccinated for HPV and unvaccinated Colombian women. In a cross-sectional design study, 1436 women (231 adolescents, <18 years; 1205 young women, 18-26 years) completed a self-administered questionnaire between May 2011 and March 2012 in Bogotá, Colombia. Data from vaccinated and unvaccinated women were compared by descriptive statistics and multivariate models. Sexual risk behaviors were not associated with vaccination after adjustment for risk perception, age, educational level, and HPV knowledge. By contrast, vaccination was associated with higher routine Pap smear screening (odds ratio [OR], 2.35; 95% confidence interval [CI], 1.69-3.28), use of modern contraceptives (OR, 2.02; 95% CI, 1.26-3.22), and consistent use of condoms (OR, 1.49; 95% CI, 1.11-2.01). Vaccinated young women were more likely to have had sex (OR, 2.08; 95% CI, 1.56-2.78), but sexual debut among adolescents was not associated with vaccination. In bivariate and multivariate analyses, vaccination status was negatively associated with perceived risk of HPV infection, warts, and cervical cancer. There was no association between vaccination and perceived risk of sexually transmitted infections in any model. No association was found between changes in risk perception after HPV vaccination and sexual risk behaviors. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

NASA Astrophysics Data System (ADS)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

Status quo of German-speaking medical students' attitudes toward and knowledge about central aspects of forensic psychiatry across four European countries.

PubMed

Warnke, Ingeborg; Gamma, Alex; Buadze, Anna; Schleifer, Roman; Canela, Carlos; Rüsch, Nicolas; Rössler, Wulf; Strebel, Bernd; Tényi, Tamás; Liebrenz, Michael

While forensic psychiatry is of increasing importance in mental health care, limited available evidence shows that attitudes toward the discipline are contradictory and that knowledge about it seems to be limited in medical students. We aimed to shed light on this subject by analyzing medical students' central attitudes toward and their association with knowledge about forensic psychiatry as well as with socio-demographic and education-specific predictor variables. We recruited N = 1345 medical students from 45 universities with a German language curriculum across four European countries (Germany, Switzerland, Austria and Hungary) by using an innovative approach, namely snowball sampling via Facebook. Students completed an online questionnaire, and data were analyzed descriptively and multivariably by linear mixed effects models and multinomial regression. The results showed overall neutral to positive attitudes toward forensic psychiatry, with indifferent attitudes toward the treatment of sex offenders, and forensic psychiatrists' expertise in the media. Whereas medical students knew about the term 'forensic psychiatry', they showed a lack of specific medico-legal knowledge. Multivariable models on predictor variables revealed statistically significant findings with, however, small estimates and variance explanation. Therefore, further research is required along with the development of a refined assessment instrument for medical students to explore both attitudes and knowledge in forensic psychiatry. Copyright © 2018 Elsevier Ltd. All rights reserved.

Parental Opinions and Attitudes about Children's Vaccination Safety in Silesian Voivodeship, Poland.

PubMed

Braczkowska, Bogumiła; Kowalska, Małgorzata; Barański, Kamil; Gajda, Maksymilian; Kurowski, Tomasz; Zejda, Jan E

2018-04-15

Despite mandatory vaccinations in Poland, the final decision on vaccination in children is taken by their parents or legal guardians. Understanding parents' attitudes and opinions regarding vaccinations is essential for planning and undertaking extensive and properly targeted educational actions aimed at preventing their hesitancy. In 2016, a cross-sectional study was conducted in the Silesian Voivodeship (Poland) in 11 randomly selected educational institutions. The authors' self-administered questionnaire contained 24 mixed-type questions. It was distributed among 3000 parents or legal guardians of children aged 6-13 years; prior consent of the relevant bioethics committee had been obtained. The response rate was 41.3% ( N = 1239). Data were analysed using descriptive and analytical statistics, and focused on parental opinions regarding the safety of vaccines. Results of simple and multivariable analyses showed that perceived risk of adverse vaccine reaction (AVR), contraindications and perception of the qualification procedure for vaccination as substandard were significant factors associated with the rating of children's vaccination as unsafe ( p < 0.001). Respondents with a lower level of education, compared with those with higher, more often declared vaccinations to be safe ( p = 0.03); however, results of multivariable analysis did not confirm that effect. AVR occurrence, finding of contraindication to vaccinations and perception of qualification procedure for vaccination were found to be the most important factors responsible for influencing general public opinions in the field of vaccination safety.

Symptoms and signs associated with benign and malignant proximal fibular tumors: a clinicopathological analysis of 52 cases.

PubMed

Sun, Tao; Wang, Lingxiang; Guo, Changzhi; Zhang, Guochuan; Hu, Wenhai

2017-05-02

Malignant tumors in the proximal fibula are rare but life-threatening; however, biopsy is not routine due to the high risk of peroneal nerve injury. Our aim was to determine preoperative clinical indicators of malignancy. Between 2004 and 2016, 52 consecutive patients with proximal fibular tumors were retrospectively reviewed. Details of the clinicopathological characteristics including age, gender, location of tumors, the presenting symptoms, the duration of symptoms, and pathological diagnosis were collected. Descriptive statistics were calculated, and univariate and multivariate regression were performed. Of these 52 patients, 84.6% had benign tumors and 15.4% malignant tumors. The most common benign tumors were osteochondromas (46.2%), followed by enchondromas (13.5%) and giant cell tumors (13.5%). The most common malignancy was osteosarcomas (11.5%). The most common presenting symptoms were a palpable mass (52.0%) and pain (46.2%). Pain was the most sensitive (100%) and fourth specific (64%); both high skin temperature and peroneal nerve compression had the highest specificity (98%) and third sensitivity (64%); change in symptoms had the second highest specificity (89%) while 50% sensitivity. Using multivariate regression, palpable pain, high skin temperature, and peroneal nerve compression symptoms were predictors of malignancy. Most tumors in the proximal fibula are benign, and the malignancy is rare. Palpable pain, peroneal nerve compression symptoms, and high skin temperature were specific in predicting malignancy.

Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency

NASA Astrophysics Data System (ADS)

Papalexiou, Simon Michael

2018-05-01

Hydroclimatic processes come in all "shapes and sizes". They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific "parent" Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.

Applying Sociocultural Theory to Teaching Statistics for Doctoral Social Work Students

ERIC Educational Resources Information Center

Mogro-Wilson, Cristina; Reeves, Michael G.; Charter, Mollie Lazar

2015-01-01

This article describes the development of two doctoral-level multivariate statistics courses utilizing sociocultural theory, an integrative pedagogical framework. In the first course, the implementation of sociocultural theory helps to support the students through a rigorous introduction to statistics. The second course involves students…

A review on the multivariate statistical methods for dimensional reduction studies

NASA Astrophysics Data System (ADS)

Aik, Lim Eng; Kiang, Lam Chee; Mohamed, Zulkifley Bin; Hong, Tan Wei

2017-05-01

In this research study we have discussed multivariate statistical methods for dimensional reduction, which has been done by various researchers. The reduction of dimensionality is valuable to accelerate algorithm progression, as well as really may offer assistance with the last grouping/clustering precision. A lot of boisterous or even flawed info information regularly prompts a not exactly alluring algorithm progression. Expelling un-useful or dis-instructive information segments may for sure help the algorithm discover more broad grouping locales and principles and generally speaking accomplish better exhibitions on new data set.

Generating an Empirical Probability Distribution for the Andrews-Pregibon Statistic.

ERIC Educational Resources Information Center

Jarrell, Michele G.

A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used…

Validating Future Force Performance Measures (Army Class): Concluding Analyses

DTIC Science & Technology

2016-06-01

32 Table 3.10. Descriptive Statistics and Intercorrelations for LV Final Predictor Factor Scores...55 Table 4.7. Descriptive Statistics for Analysis Criteria...Soldier attrition and performance: Dependability (Non- Delinquency ), Adjustment, Physical Conditioning, Leadership, Work Orientation, and Agreeableness

[Families of the economic crisis in paediatric Primary Care clinics: descriptive observational study].

PubMed

Martín Martín, R; Sánchez Bayle, M; Gancedo García, C; Teruel de Francisco, M C; Coullaut López, A

2016-04-01

To study the impact of the economic crisis on the families of the children who attend Primary Health Care and its relationship with their socioeconomic status. Observational descriptive study was conducted by analysing the results of 453 questionnaires, given to the parents of children between 1 and 7 years old who attended 4 paediatric clinics in Madrid. The raw data was analysed, and comparisons between groups and multivariate analysis were performed. In the multivariate analysis, the variables related to the non-acquisition of prescribed medication are: lower income level OR=0.118, p<.0001 and lower educational level OR=0.464, p<.001; the variables related to the reduction of food expenditure are: lower income level OR=0.100, p<.0001 and a higher number of family members OR=1.308, p=.045; the variables related to anti-pneumococcal vaccination without public funding are: higher income level OR=2.170, p=.0001, higher educational level OR=1.835, p=.013, and not being an immigrant OR=0.532, p=.037. The presence of health problems from the beginning of the economic crisis is related to unemployment OR=4.079, p=.032, lower educational level R=0.678, p=.042, and income level OR=0.342, p<.0001. In all cases, the models achieved a statistical significance of p<.0001. The economic crisis has greater impact on the group with the lowest income level in all analysed variables. The lower educational level and higher number of family members has an impact on the reduction in food expenditure. The fact of being an immigrant has an impact on not receiving the anti-pneumococcal and rotavirus vaccination. Unemployment leads to an increase in health problems in the family. To sum up, the economic crisis has increased inequalities according to socioeconomic status. Copyright © 2015 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Impact of Body Habitus on Phenytoin Levels Following Fosphenytoin Loading Dose in Pediatric Patients.

PubMed

Messinger, Mindl M; Moffett, Brady S; Wilfong, Angus

2015-12-01

Obesity has been shown to affect the disposition of water-soluble medications in pediatric patients. There are no published data describing serum phenytoin concentrations in obese pediatric patients. A retrospective descriptive study was designed that included patients from 2011 to 2013 between 2 and 19 years of age who received a dose of fosphenytoin with a subsequent serum phenytoin concentration, drawn 2-4 hours postloading dose. Body mass index (BMI) was calculated and patients were categorized by BMI percentiles into underweight (<5th percentile), normal weight (5th-84th percentile), overweight (85th-94th percentile), and obese (≥95th percentile). Descriptive statistical analysis and comparisons between groups occurred to determine differences in serum phenytoin concentrations. Multivariable linear regression analysis was performed to determine the effect of body habitus on serum phenytoin concentrations. One hundred ten patients met study criteria (male 51.8%, mean age: 8.3 ± 4.9 years). Patients were normal weight (47.3%), underweight (20.9%), overweight (14.6%), and obese (17.3%). No significant differences were identified between groups in regard to patient demographics, with the exception of weight (P < 0.05). The mean fosphenytoin dose was 23.4 ± 5.7 mg Phenytoin Equivalents (PE)/kg and the serum phenytoin concentration was 22.4 ± 6.8 mg/L measured at 2.9 ± 0.6 hours after dose, and this did not vary significantly across groups (P > 0.05). Multivariable linear regression identified body habitus as a nonsignificant predictor of serum phenytoin concentrations (P > 0.05). Patients of higher BMI did not require further antiepileptic therapy as compared with patients with lower BMI (P > 0.05). Contrary to the adult population, loading dose adjustments do not seem to be required in pediatric patients. Obesity does not affect serum phenytoin concentrations in pediatric patients after intravenous bolus fosphenytoin administration.

Work Related Musculoskeletal Morbidity among Tailors: A Cross Sectional Study in a Slum of Kolkata.

PubMed

Banerjee, S; Bandyopadhyay, L; Dasgupta, A; Paul, B; Chattopadhyay, O

Background Musculoskeletal disorders comprise the single largest group of work-related illnesses in developing countries. Sedentary working style with wrong posture for long time is considered to be an important risk factor, which is largely modifiable. Objective This study was performed to determine the prevalence and find out the factors associated with Musculoskeletal disorders among the workers involved in tailoring occupation. Method A descriptive community based cross-sectional study was conducted in the urban slums of Chetla, Kolkata on March and April, 2015. One hundred and ten (110) out of 383 resident tailors in the area were chosen by simple random sampling and interviewed by approaching them in their work place. Descriptive statistics and multivariable logistic regression were used Result Using Nordic Musculoskeletal questionnaire, Musculoskeletal disorders was found among 65.45% of tailors. The most commonly affected site was neck (41.8%) followed by lower and upper back. In bivariate analysis, musculo-skeletal disorders was found to be significantly associated with age more than 45 years [OR (95% CI)= 3.35 (1.30- 8.60)], working for > 10 years [OR (95% CI)= 7.01 (2.93-16.79)*], working > 8 hours per day [OR (95% CI)= 2.75 (1.20-6.20)], full time job [OR (95% CI)= 2.41 (1.08-5.39)] and unfavourable workstation ergonomic [OR (95% CI)= 2.40 (1.10-5.40)], whereas in multivariate analysis age, sex, duration in the profession [AOR (95%CI= 4.40 (1.40- 14.30)], working hours per day [AOR (95%CI= 7.20 (1.80-27.80)], and unfavourable workstation ergonomic [AOR (95%CI)= 3.50 (1.26-9.80)] remained significant. Conclusion A multidimensional approach including appropriate technique in terms of operators' posture and ergonomically sound workstation are required to avoid the debilitating effect of Musculoskeletal disorders among the workers.

[Forensic importance of homicide].

PubMed

Novaković, Milan

2009-01-01

This study encompassed the total number of homicides in Bosnia and Herzegovina (B&H) in the period from 1st January 1997 to 31st December 2006 and then analysed homicidal behaviour. The aim is to assess the differences between the people who committed violent and those who committed accidental homicide in Bosnia and Herzegovina. In a multicentric, retrospective study of comparing the groups with equal number of respondents we analysed the individuals who had committed violent (n=135) and accidental homicides (n=135). The homicides were tested by using sociodemographic and psychosocial items. Measurement instruments were: General data list, Eysenck Personality Questionnaire (EPQ), Hamilton Depression Rating Scale (HDRS), Emotions Profile Index (EPI). The descriptive and multivariable logistic analysis was done statistically. In the descriptive analysis the socio-demographically violent murderers were: male gender (chi 2=3.340, P=0.009), more workers than officials (chi 2=7.340, P=0.011), fathers were more often workers/farmers (chi 2=1.430, P=0.046), gambling (chi 2=13.100, P=0.001) and possible recidivism (chi 2=6.770, a P=0.001). The accidental murderers were family people (chi 2=4.100, P=0.041), with more frequent drug abuse (chi 2=3.190, P=0.012) and they would not repeat the delict. In the multivariate analysis the violent murderers were highly discriminated (P=0.001) from accidental ones by: war involvement r=0.1148, OR=2.971 (95%), CI=1.040-7.890; age, father's education, psychoticism (EPQ) r =-0.1085, OR=0.291 (95%), CI=0.110-0870, HDRS-total r=-0.1797, OR=0.830 (95%), CI=0.710-0.930, destructiveness r=0.1270, OR=1.560 (95%), (CI=1.197-2.032, and deprivation in the P. I. E. tests. By the violence of their acts murderers confirm micro-social model of transferring the violence, and transition and heredity confirm the ecological-developmental trans-generation model of violence. Accidental murderers commit homicide in anomy, with intoxications and prolonged psycho-traumatism.

Predictors of outcome after elective endovascular abdominal aortic aneurysm repair and external validation of a risk prediction model.

PubMed

Wisniowski, Brendan; Barnes, Mary; Jenkins, Jason; Boyne, Nicholas; Kruger, Allan; Walker, Philip J

2011-09-01

Endovascular abdominal aortic aneurysm (AAA) repair (EVAR) has been associated with lower operative mortality and morbidity than open surgery but comparable long-term mortality and higher delayed complication and reintervention rates. Attention has therefore been directed to identifying preoperative and operative variables that influence outcomes after EVAR. Risk-prediction models, such as the EVAR Risk Assessment (ERA) model, have also been developed to help surgeons plan EVAR procedures. The aims of this study were (1) to describe outcomes of elective EVAR at the Royal Brisbane and Women's Hospital (RBWH), (2) to identify preoperative and operative variables predictive of outcomes after EVAR, and (3) to externally validate the ERA model. All elective EVAR procedures at the RBWH before July 1, 2009, were reviewed. Descriptive analyses were performed to determine the outcomes. Univariate and multivariate analyses were performed to identify preoperative and operative variables predictive of outcomes after EVAR. Binomial logistic regression analyses were used to externally validate the ERA model. Before July 1, 2009, 197 patients (172 men), who were a mean age of 72.8 years, underwent elective EVAR at the RBWH. Operative mortality was 1.0%. Survival was 81.1% at 3 years and 63.2% at 5 years. Multivariate analysis showed predictors of survival were age (P = .0126), American Society of Anesthesiologists (ASA) score (P = .0180), and chronic obstructive pulmonary disease (P = .0348) at 3 years and age (P = .0103), ASA score (P = .0006), renal failure (P = .0048), and serum creatinine (P = .0022) at 5 years. Aortic branch vessel score was predictive of initial (30-day) type II endoleak (P = .0015). AAA tortuosity was predictive of midterm type I endoleak (P = .0251). Female sex was associated with lower rates of initial clinical success (P = .0406). The ERA model fitted RBWH data well for early death (C statistic = .906), 3-year survival (C statistic = .735), 5-year survival (C statistic = .800), and initial type I endoleak (C statistic = .850). The outcomes of elective EVAR at the RBWH are broadly consistent with those of a nationwide Australian audit and recent randomized trials. Age and ASA score are independent predictors of midterm survival after elective EVAR. The ERA model predicts mortality-related outcomes and initial type I endoleak well for RBWH elective EVAR patients. Copyright © 2011 Society for Vascular Surgery. All rights reserved.

Predicting Subsequent Myopia in Initially Pilot-Qualified USAFA Cadets.

DTIC Science & Technology

1985-12-27

Refraction Measurement 14 Accesion For . 4.0 RESULTS NTIS CRA&I 15 4.1 Descriptive Statistics DTIC TAB 0 15i ~ ~Unannoutwced [ 4.2 Predictive Statistics ...mentioned), and three were missing a status. The data of the subject who was commissionable were dropped from the statistical analyses. Of the 91...relatively equal numbers of participants from all classes will become obvious ’’" - within the results. J 4.1 Descriptive Statistics In the original plan

Evidence-based orthodontics. Current statistical trends in published articles in one journal.

PubMed

Law, Scott V; Chudasama, Dipak N; Rinchuse, Donald J

2010-09-01

To ascertain the number, type, and overall usage of statistics in American Journal of Orthodontics and Dentofacial (AJODO) articles for 2008. These data were then compared to data from three previous years: 1975, 1985, and 2003. The frequency and distribution of statistics used in the AJODO original articles for 2008 were dichotomized into those using statistics and those not using statistics. Statistical procedures were then broadly divided into descriptive statistics (mean, standard deviation, range, percentage) and inferential statistics (t-test, analysis of variance). Descriptive statistics were used to make comparisons. In 1975, 1985, 2003, and 2008, AJODO published 72, 87, 134, and 141 original articles, respectively. The percentage of original articles using statistics was 43.1% in 1975, 75.9% in 1985, 94.0% in 2003, and 92.9% in 2008; original articles using statistics stayed relatively the same from 2003 to 2008, with only a small 1.1% decrease. The percentage of articles using inferential statistical analyses was 23.7% in 1975, 74.2% in 1985, 92.9% in 2003, and 84.4% in 2008. Comparing AJODO publications in 2003 and 2008, there was an 8.5% increase in the use of descriptive articles (from 7.1% to 15.6%), and there was an 8.5% decrease in articles using inferential statistics (from 92.9% to 84.4%).

Reservoir characterization using core, well log, and seismic data and intelligent software

NASA Astrophysics Data System (ADS)

Soto Becerra, Rodolfo

We have developed intelligent software, Oilfield Intelligence (OI), as an engineering tool to improve the characterization of oil and gas reservoirs. OI integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphics design, and inference engine modules. More than 1,200 lines of programming code as M-files using the language MATLAB been written. The degree of success of many oil and gas drilling, completion, and production activities depends upon the accuracy of the models used in a reservoir description. Neural networks have been applied for identification of nonlinear systems in almost all scientific fields of humankind. Solving reservoir characterization problems is no exception. Neural networks have a number of attractive features that can help to extract and recognize underlying patterns, structures, and relationships among data. However, before developing a neural network model, we must solve the problem of dimensionality such as determining dominant and irrelevant variables. We can apply principal components and factor analysis to reduce the dimensionality and help the neural networks formulate more realistic models. We validated OI by obtaining confident models in three different oil field problems: (1) A neural network in-situ stress model using lithology and gamma ray logs for the Travis Peak formation of east Texas, (2) A neural network permeability model using porosity and gamma ray and a neural network pseudo-gamma ray log model using 3D seismic attributes for the reservoir VLE 196 Lamar field located in Block V of south-central Lake Maracaibo (Venezuela), and (3) Neural network primary ultimate oil recovery (PRUR), initial waterflooding ultimate oil recovery (IWUR), and infill drilling ultimate oil recovery (IDUR) models using reservoir parameters for San Andres and Clearfork carbonate formations in west Texas. In all cases, we compared the results from the neural network models with the results from regression statistical and non-parametric approach models. The results show that it is possible to obtain the highest cross-correlation coefficient between predicted and actual target variables, and the lowest average absolute errors using the integrated techniques of multivariate statistical analysis and neural networks in our intelligent software.

Depression, Anxiety, and Stress Symptoms in Menopausal Arab Women: Shedding More Light on a Complex Relationship.

PubMed

Bener, A; Saleh, N M; Bakir, A; Bhugra, D

2016-01-01

The association between depression, anxiety, and stress among Arab menopause and postmenopausal women have been explored in detailed. The objective of this study was to determine the correlation between depression, anxiety, and stress in menopausal and postmenopausal women and shedding more light on a complex relationship. A cross-sectional descriptive study was used to generate menopause symptoms experienced by Arabian women at the primary health care centers in Qatar. A representative sample of 1468 women aged 45-65 years were approached during July 2012 and May 2014 and 1101 women agreed to participate (75.0%) and responded to the study. Depression, anxiety, and stress were measured using the Depression Anxiety Stress Scales 21. Data on body mass index (BMI), clinical and other parameters were used. Univariate, multivariate, and matrix correlation analysis were performed for statistical analysis. A total of 1101 women agreed to participate after informed consent was obtained. The mean age and standard deviation (SD) of the menopausal age were 49.55 (3.12), the mean and SD of postmenopausal age was 58.08 (3.26) ( P < 0.001). There were statistically significant differences between menopausal stages with regards to age, ethnicity, educational status, occupation status, and place of living. Furthermore, there were statistically significant differences between menopausal stages with regards to BMI, systolic and diastolic blood pressure (BP), Vitamin D deficiency, and diseases. Depression and anxiety were more common among postmenopause women. Furthermore, there were no differences between the groups regarding the frequency of certain levels of stress among menopause and postmenopause. The multivariate regression analyses revealed that age in years, diastolic BP, consanguinity, regular exercise were a predictor for depression. Meanwhile, diastolic BP, occupation, and physical activity considered the main risk factors for anxiety. Furthermore, age in years, occupation, and sheesha smoking habits were considered as the main risk factors associated with stress. A large number of factors were associated with experiencing menopausal and psycho-social problems and which had negative effects on the quality of life among Arabian women. Depression, anxiety, and stress should be considered as important risk factors for osteoporosis.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

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…

A Multivariate Solution of the Multivariate Ranking and Selection Problem

DTIC Science & Technology

1980-02-01

Taneja (1972)), a ’a for a vector of constants c (Krishnaiah and Rizvi (1966)), the generalized variance ( Gnanadesikan and Gupta (1970)), iegier (1976...Olk-in, I. and Sobel, M. (1977). Selecting and Ordering Populations: A New Statistical Methodology, John Wiley & Sons, Inc., New York. Gnanadesikan

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.

Job Satisfaction DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

focuses more specifically on satisfaction with the job. Included is a review of the 4.0 description and items, followed by the proposed modifications to...the factor. The DEOCS 4.0 description provided for job satisfaction is “the perception of personal fulfillment in a specific vocation, and sense of...piloting items on the DEOCS; (4) examining the descriptive statistics, exploratory factor analysis results, and aggregation statistics; and (5

Crop identification technology assessment for remote sensing. (CITARS) Volume 9: Statistical analysis of results

NASA Technical Reports Server (NTRS)

Davis, B. J.; Feiveson, A. H.

1975-01-01

Results are presented of CITARS data processing in raw form. Tables of descriptive statistics are given along with descriptions and results of inferential analyses. The inferential results are organized by questions which CITARS was designed to answer.

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Visual classification of very fine-grained sediments: Evaluation through univariate and multivariate statistics

USGS Publications Warehouse

Hohn, M. Ed; Nuhfer, E.B.; Vinopal, R.J.; Klanderman, D.S.

1980-01-01

Classifying very fine-grained rocks through fabric elements provides information about depositional environments, but is subject to the biases of visual taxonomy. To evaluate the statistical significance of an empirical classification of very fine-grained rocks, samples from Devonian shales in four cored wells in West Virginia and Virginia were measured for 15 variables: quartz, illite, pyrite and expandable clays determined by X-ray diffraction; total sulfur, organic content, inorganic carbon, matrix density, bulk density, porosity, silt, as well as density, sonic travel time, resistivity, and ??-ray response measured from well logs. The four lithologic types comprised: (1) sharply banded shale, (2) thinly laminated shale, (3) lenticularly laminated shale, and (4) nonbanded shale. Univariate and multivariate analyses of variance showed that the lithologic classification reflects significant differences for the variables measured, difference that can be detected independently of stratigraphic effects. Little-known statistical methods found useful in this work included: the multivariate analysis of variance with more than one effect, simultaneous plotting of samples and variables on canonical variates, and the use of parametric ANOVA and MANOVA on ranked data. ?? 1980 Plenum Publishing Corporation.

Multivariate probability distribution for sewer system vulnerability assessment under data-limited conditions.

PubMed

Del Giudice, G; Padulano, R; Siciliano, D

2016-01-01

The lack of geometrical and hydraulic information about sewer networks often excludes the adoption of in-deep modeling tools to obtain prioritization strategies for funds management. The present paper describes a novel statistical procedure for defining the prioritization scheme for preventive maintenance strategies based on a small sample of failure data collected by the Sewer Office of the Municipality of Naples (IT). Novelty issues involve, among others, considering sewer parameters as continuous statistical variables and accounting for their interdependences. After a statistical analysis of maintenance interventions, the most important available factors affecting the process are selected and their mutual correlations identified. Then, after a Box-Cox transformation of the original variables, a methodology is provided for the evaluation of a vulnerability map of the sewer network by adopting a joint multivariate normal distribution with different parameter sets. The goodness-of-fit is eventually tested for each distribution by means of a multivariate plotting position. The developed methodology is expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections in order to fulfill rehabilitation requirements.

Ensembles of radial basis function networks for spectroscopic detection of cervical precancer

NASA Technical Reports Server (NTRS)

Tumer, K.; Ramanujam, N.; Ghosh, J.; Richards-Kortum, R.

1998-01-01

The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms.

SPReM: Sparse Projection Regression Model For High-dimensional Linear Regression *

PubMed Central

Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.

2014-01-01

The aim of this paper is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issue of many standard statistical approaches, such as the Hotelling’s T2 test statistic or a mass univariate analysis, for high-dimensional data. We formulate the estimation problem of SPREM as a novel sparse unit rank projection (SURP) problem and propose a fast optimization algorithm for SURP. Furthermore, we extend SURP to the sparse multi-rank projection (SMURP) by adopting a sequential SURP approximation. Theoretically, we have systematically investigated the convergence properties of SURP and the convergence rate of SURP estimates. Our simulation results and real data analysis have shown that SPReM out-performs other state-of-the-art methods. PMID:26527844

Prison Radicalization: The New Extremist Training Grounds?

DTIC Science & Technology

2007-09-01

distributing and collecting survey data , and the data analysis. The analytical methodology includes descriptive and inferential statistical methods, in... statistical analysis of the responses to identify significant correlations and relationships. B. SURVEY DATA COLLECTION To effectively access a...Q18, Q19, Q20, and Q21. Due to the exploratory nature of this small survey, data analyses were confined mostly to descriptive statistics and

A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

PubMed

Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

2015-01-01

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity.

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.

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.

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from homogeneous groundwaters in the Great Artesian Basin, Australia

NASA Astrophysics Data System (ADS)

O'Shea, Bethany; Jankowski, Jerzy

2006-12-01

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright

Multiple Versus Single Set Validation of Multivariate Models to Avoid Mistakes.

PubMed

Harrington, Peter de Boves

2018-01-02

Validation of multivariate models is of current importance for a wide range of chemical applications. Although important, it is neglected. The common practice is to use a single external validation set for evaluation. This approach is deficient and may mislead investigators with results that are specific to the single validation set of data. In addition, no statistics are available regarding the precision of a derived figure of merit (FOM). A statistical approach using bootstrapped Latin partitions is advocated. This validation method makes an efficient use of the data because each object is used once for validation. It was reviewed a decade earlier but primarily for the optimization of chemometric models this review presents the reasons it should be used for generalized statistical validation. Average FOMs with confidence intervals are reported and powerful, matched-sample statistics may be applied for comparing models and methods. Examples demonstrate the problems with single validation sets.

Effectiveness of an Alternative Dental Workforce Model on the Oral Health of Low-Income Children in a School-Based Setting

PubMed Central

Walker, Mary; Gadbury-Amyot, Cynthia; Liu, Ying; Kelly, Patricia; Branson, Bonnie

2015-01-01

Objectives. We evaluated the effect of an alternative dental workforce program—Kansas’s Extended Care Permit (ECP) program—as a function of changes in oral health. Methods. We examined data from the 2008 to 2012 electronic medical records of children (n = 295) in a Midwestern US suburb who participated in a school-based oral health program in which preventive oral health care was delivered by ECP dental hygienists. We examined changes in oral health status as a function of sealants, caries, restorations, and treatment urgency with descriptive statistics, multivariate analysis of variance, Kruskal–Wallis test, and Pearson correlations. Results. The number of encounters with the ECP dental hygienist had a statistically significant effect on changes in decay (P = .014), restorations (P = .002), and treatment urgency (P = .038). Based on Pearson correlations, as encounters increased, there was a significant decrease in decay (–0.12), increase in restorations (0.21), and decrease in treatment urgency (–0.15). Conclusions. Increasing numbers of encounters with alternative providers (ECP dental hygienists), such as with school-based oral health programs, can improve the oral health status of low-income children who would not otherwise have received oral health services. PMID:26180957

Caregivers' health literacy and their young children's oral-health-related expenditures.

PubMed

Vann, W F; Divaris, K; Gizlice, Z; Baker, A D; Lee, J Y

2013-07-01

Caregivers' health literacy has emerged as an important determinant of young children's health care and outcomes. We examined the hypothesis that caregivers' health literacy influences children's oral-health-care-related expenditures. This was a prospective cohort study of 1,132 child/caregiver dyads (children's mean age = 19 months), participating in the Carolina Oral Health Literacy Project. Health literacy was measured by the REALD-30 (word recognition based) and NVS (comprehension based) instruments. Follow-up data included child Medicaid claims for CY2008-10. We quantified expenditures using annualized 2010 fee-adjusted Medicaid-paid dollars for oral-health-related visits involving preventive, restorative, and emergency care. We used descriptive, bivariate, and multivariate statistical methods based on generalized gamma models. Mean oral-health-related annual expenditures totaled $203: preventive--$81, restorative--$99, and emergency care--$22. Among children who received services, mean expenditures were: emergency hospital-based--$1282, preventive--$106, and restorative care--$343. Caregivers' low literacy in the oral health context was associated with a statistically non-significant increase in total expenditures (average annual difference = $40; 95% confidence interval, -32, 111). Nevertheless, with both instruments, emergency dental care expenditures were consistently elevated among children of low-literacy caregivers. These findings provide initial support for health literacy as an important determinant of the meaningful use and cost of oral health care.

Secondary analysis of data can inform care delivery for Indigenous women in an acute mental health inpatient unit.

PubMed

Bradley, Pat; Cunningham, Teresa; Lowell, Anne; Nagel, Tricia; Dunn, Sandra

2017-02-01

There is a paucity of research exploring Indigenous women's experiences in acute mental health inpatient services in Australia. Even less is known of Indigenous women's experience of seclusion events, as published data are rarely disaggregated by both indigeneity and gender. This research used secondary analysis of pre-existing datasets to identify any quantifiable difference in recorded experience between Indigenous and non-Indigenous women, and between Indigenous women and Indigenous men in an acute mental health inpatient unit. Standard separation data of age, length of stay, legal status, and discharge diagnosis were analysed, as were seclusion register data of age, seclusion grounds, and number of seclusion events. Descriptive statistics were used to summarize the data, and where warranted, inferential statistical methods used SPSS software to apply analysis of variance/multivariate analysis of variance testing. The results showed evidence that secondary analysis of existing datasets can provide a rich source of information to describe the experience of target groups, and to guide service planning and delivery of individualized, culturally-secure mental health care at a local level. The results are discussed, service and policy development implications are explored, and suggestions for further research are offered. © 2016 Australian College of Mental Health Nurses Inc.

Typology of public outreach for biodiversity conservation projects in Spain.

PubMed

Jiménez, Amanda; Iniesta-Arandia, Irene; Muñoz-Santos, Maria; Martín-López, Berta; Jacobson, Susan K; Benayas, Javier

2014-06-01

Conservation education and outreach programs are a key approach to promote public understanding of the importance of biodiversity conservation. We reviewed 85 biodiversity conservation projects supported by the Spanish Ministry of Environment's Biodiversity Foundation. Through content analysis and descriptive statistics, we examined how the projects carried out communication, education, and public awareness and participation (CEPA) actions. We also used multivariate statistical analysis to develop a typology of 4 classes of biodiversity conservation projects on the basis of CEPA implementation. The classifications were delineated by purpose of CEPA, level of integration of CEPA actions, type of CEPA goals, main CEPA stakeholders, and aim of conservation. Our results confirm the existence of 2 key positions: CEPA has intrinsic value (i.e., they supposed the implementation of any CEPA action indirectly supported conservation) and CEPA is an instrument for achieving conservation goals. We also found that most CEPA actions addressed general audiences and school children, ignored minority groups and women, and did not include evaluation. The characteristics of the 4 types of projects and their frequency of implementation in the sample reflect the need for better integration of different types of actions (communication, education, and participation) and improved fostering of participation of multiple stakeholders in developing policy and implementing management strategies. © 2014 Society for Conservation Biology.

An assessment of quality characteristics of randomised control trials published in dental journals.

PubMed

Pandis, Nikolaos; Polychronopoulou, Argy; Eliades, Theodore

2010-09-01

The purpose of this study was to investigate the quality of reporting of randomised clinical trials (RCTs) published in dental specialty journals. The journals possessing the highest impact factor (2008 data) in the six major dental specialties were included in the study. The contents of the 24 most recent issues of each journal were hand-searched and research articles identified as randomised controlled trials (RCTs) were selected. Quality evaluation was performed using the modified Consolidated Standards of Reporting Trials (CONSORT) statement checklist. The data were analysed using descriptive statistics followed by univariate and multivariate examination of statistical associations (alpha=0.05). Ninety-five RCTs were identified with generally suboptimal scores on quality reporting on key CONSORT areas. Significant differences were found among journals with the Journal of Clinical Periodontology achieving the highest score, followed by the American Journal of Orthodontics and Dentofacial Orthopedics. There was a positive association between quality score and number of authors, involvement of statistician/epidemiologist, and multicentre trials. The quality scores of RCTs in major dental journals are considered suboptimal in key CONSORT areas. This receives critical importance considering that improved quality of RCTs is a fundamental prerequisite for improved dental care. Copyright 2010 Elsevier Ltd. All rights reserved.

Allowing and Using Foods of Low Nutritional Value in Elementary School Classrooms: The Implications of Teachers' Beliefs.

PubMed

Lambert, Laurel G; Chang, Yunhee; Varner, Jennifer; Monroe, Ann

2016-02-01

To investigate elementary teachers' behavior toward allowing and using foods with low nutritional value in the classroom. A survey guided by the Theory of Planned Behavior was administered in fall, 2012 in 10 schools. Elementary public school teachers in grades pre-kindergarten through 6. Teachers' behavior and beliefs regarding allowing and using foods with low nutritional value in the classroom and Theory of Planned Behavior determinants. Pairwise correlation coefficients and multivariate linear regression to assess relationships between theory determinants and descriptive statistics. All 3 determinants, Attitude Toward the Behavior (t = 4.04; P < .01), Subjective Norms (t = 3.78; P < .01), and Perceived Behavioral Control (t = 5.19; p < .01), were statistically significant predictors of behavior. The majority of teachers (94%) allowed foods of low nutritional value for celebrations at least some of the time, and 75% stated that they had control over what foods they allow. Discussions among teachers and school health professionals should ensue to improve nutritional content of foods allowed in classrooms. School policies can be developed and evaluated for effectiveness to have a positive impact on childhood obesity and school nutrition environments. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Brachial neuropraxia in Canadian Atlantic University sport football players: what is the incidence of "stingers"?

PubMed

Charbonneau, Rebecca M E; McVeigh, Sonja A; Thompson, Kara

2012-11-01

The objectives of this study were (1) to determine the incidence of brachial neuropraxia (stingers) among varsity football players during the 2010 season; (2) to determine if associations exist between sustaining a stinger and previous history of stingers, years played, equipment, age, body mass index (BMI), and conditioning; and (3) to provide descriptive statistics regarding stingers and position played, symptoms, activity during injury, mechanism of tackling, and reporting of stingers. Retrospective. Canadian Atlantic University Sport football league. Two hundred forty-four players. Two written questionnaires. Number of players experiencing stingers that occurred during the 2010 season. The incidence was 26% (64 of 244). A multivariate analysis revealed that previous history of a stinger (P < 0.0001) and years played (P = 0.0018) were associated with sustaining a stinger. There was no statistically significant effect related to additional equipment, a player's age, BMI, or participation in a strength training program. Linebackers, offensive linemen, and wide receivers had the highest incidence of stingers. The most frequent symptoms reported were tingling, numbness, burning, and weakness. Of all stingers sustained, only 59% (38 of 64) were reported to medical staff. Stingers are a common injury in Canadian university football and are underreported to medical staff. Education of players at increased risk is needed.

Sources of Information During the 2014 West Virginia Water Crisis: A Cross-Sectional Survey.

PubMed

Savoia, Elena; Lin, Leesa; Viswanath, Kasisomayajula

2017-04-01

On January 9, 2014, a faulty storage tank leaked 10,000 gallons of an industrial coal-processing liquid into the Elk River in West Virginia, contaminating the drinking water of 9 counties collectively known as the Kanawha Valley. In the context of this event, we explored the relationship between social determinants and (1) the timeliness with which residents learned about the crisis, (2) the source of information, (3) opinions on the source of information, (4) information-seeking behaviors, and (5) knowledge acquired. Between February 7 and 26, 2014, we conducted a survey of 690 adult residents of West Virginia. Descriptive statistics and multivariable statistical models were performed. Information about water contamination spread quickly, with 88% of respondents from the affected counties hearing about the incident on the same day it occurred. Most people received the information from local television news (73%); social media users had 120% increased odds of knowing about the recommended behaviors. People who had a favorable opinion of the source of information demonstrated better knowledge of recommended behaviors. The use of local television news during a crisis is important for timely dissemination of information. Information exposure across segments of the population differed on the basis of the population's background characteristics. (Disaster Med Public Health Preparedness. 2017;11:196-206).

Determinants of Chronic Respiratory Symptoms among Pharmaceutical Factory Workers

PubMed Central

Enquselassie, Fikre; Tefera, Yifokire; Gizaw, Muluken; Wakuma, Samson; Woldemariam, Messay

2018-01-01

Background Chronic respiratory symptoms including chronic cough, chronic phlegm, wheezing, shortness of breath, and chest pain are manifestations of respiratory problems which are mainly evolved as a result of occupational exposures. This study aims to assess determinants of chronic respiratory symptoms among pharmaceutical factory workers. Methods A case control study was carried out among 453 pharmaceutical factory workers with 151 cases and 302 controls. Data was collected using pretested and structured questionnaire. The data was analyzed using descriptive statistics and bivariate and multivariate analysis. Result Previous history of chronic respiratory diseases (AOR = 3.36, 95% CI = 1.85–6.12), family history of chronic respiratory diseases (AOR = 2.55, 95% CI = 1.51–4.32), previous dusty working environment (AOR = 2.26, 95% CI = 1.07–4.78), ever smoking (AOR = 3.66, 95% CI = 1.05–12.72), and service years (AOR = 1.86, 95% CI = 1.16–2.99) showed statistically significant association with chronic respiratory symptoms. Conclusion Previous history of respiratory diseases, family history of chronic respiratory diseases, previous dusty working environment, smoking, and service years were determinants of chronic respiratory symptoms. Public health endeavors to prevent the burden of chronic respiratory symptoms among pharmaceutical factory workers should target the reduction of adverse workplace exposures and discouragement of smoking. PMID:29666655

Comparison of long-term mortality of acute ST-segment elevation myocardial infarction and non-ST-segment elevation acute coronary syndrome patients after percutaneous coronary intervention

PubMed Central

Ren, Lihui; Ye, Huiming; Wang, Ping; Cui, Yuxia; Cao, Shichang; Lv, Shuzheng

2014-01-01

Background and aims: This study is to compare the short-term and long-term mortality in patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation acute coronary syndrome (NSTE-ACS) after percutaneous coronary intervention (PCI). Methods and results: A total of 266 STEMI patients and 140 NSTE-ACS patients received PCI. Patients were followed up by telephone or at medical record or case statistics center and were followed up for 4 years. Descriptive statistics and multivariate survival analyses were employed to compare the mortality in STEMI and NSTE-ACS. All statistical analyses were performed by SPSS19.0 software package. NSTE-ACS patients had significantly higher clinical and angiographic risk profiles at baseline. During the 4-year follow-up, all-cause mortality in STEMI was significantly higher than that in NSTE-ACS after coronary stent placement (HR 1.496, 95% CI 1.019-2.197). In a landmark analysis no difference was seen in all-cause mortality for both STEMI and NSTE-ACS between 6 month and 4 years of follow-up (HR 1.173, 95% CI 0.758-1.813). Conclusions: Patients with STEMI have a worse long-term prognosis compared to patients with NSTE-ACS after PCI, due to higher short-term mortality. However, NSTE-ACS patients have a worse long-term survival after 6 months. PMID:25664077

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.

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

A new species of Acanthodactylus Fitzinger 1834 (Sauria: Lacertidae) from southern Iran.

PubMed

Nastaran, Heidari; Nasrullah Rastegar, Pouyani; Eskandar, Rastegar-Pouyani; Mehdi, Rajabizadeh

2013-01-01

A new and distinctive species of lacertid genus Acanthodactylus Fitzinger, 1834 is described from 7 km east of Khamir Port, Hormozgan Province, southern Iran at an elevation of 30-40m above sea level (asl). Analyses of morphological characters and the comparison with other formerly known species of this genus have proven the status of this taxon as a new, distinct species. Combinations of scalation characters and distinct morphology, coloration and habitat peculiarities in calcareous mountains distinguish Acanthodactylus khamirensis sp.nov from all remaining species of the genus in the area. In order to show the validity of the new species, we carried out a comparative statistical analysis using 13 metric and six meristic morphological characters on all of the neighboring congeners of the new species using descriptive (one-way ANOVA) as well as multivariate analyses (PCA and DFA). The results confirm the specific status of the new taxon. Detailed information and an updated identification key for the genus A canthodactylus in Iran are presented.

Seroadaptive Strategies of Gay & Bisexual Men (GBM) with the Highest Quartile Number of Sexual Partners in Vancouver, Canada.

PubMed

Card, Kiffer G; Lachowsky, Nathan J; Cui, Zishan; Sereda, Paul; Rich, Ashleigh; Jollimore, Jody; Howard, Terry; Birch, Robert; Carter, Allison; Montaner, Julio; Moore, David; Hogg, Robert S; Roth, Eric Abella

2017-05-01

Despite continued research among men with more sexual partners, little information exists on their seroadaptive behavior. Therefore, we examined seroadaptive anal sex strategies among 719 Vancouver gay and bisexual men (GBM) recruited using respondent-driven sampling. We provide descriptive, bivariable, and multivariable adjusted statistics, stratified by HIV status, for the covariates of having ≥7 male anal sex partners in the past 6 months (Population fourth quartile versus <7). Sensitivity Analysis were also performed to assess the robustness of this cut-off. Results suggest that GBM with more sexual partners are more likely to employ seroadaptive strategies than men with fewer partners. These strategies may be used in hopes of offsetting risk, assessing needs for subsequent HIV testing, and balancing personal health with sexual intimacy. Further research is needed to determine the efficacy of these strategies, assess how GBM perceive their efficacy, and understand the social and health impacts of their widespread uptake.

Low human papillomavirus (HPV) vaccine knowledge among Latino parents in Utah.

PubMed

Kepka, Deanna; Warner, Echo L; Kinney, Anita Y; Spigarelli, Michael G; Mooney, Kathi

2015-02-01

Latinas have the highest incidence of cervical cancer, yet Latino parents/guardians' knowledge about and willingness to have their children receive the human papillomavirus (HPV) vaccine is unknown. Latino parents/guardians (N = 67) of children aged 11-17 were recruited from two community organizations to complete a survey, including HPV vaccine knowledge, child's uptake, demographic characteristics, and acculturation. Descriptive statistics and correlates of parents' HPV knowledge and uptake were calculated using Chi square tests and multivariable logistic regression. Receipt of at least one dose of the HPV vaccine was moderate for daughters (49.1%) and low for sons (23.4%). Parents/guardians reported limited knowledge as the main barrier to vaccine receipt. Among parents/guardians with vaccinated daughters, 92.6% did not know the vaccine requires three doses. Adjusting for income, low-acculturated parents were more likely than high-acculturated parents to report inadequate information (OR 8.59, 95% CI 2.11-34.92). Interventions addressing low knowledge and children's uptake of the HPV vaccine are needed among Latino parents/guardians.

Health behaviors of head and neck cancer patients the first year after diagnosis.

PubMed

Duffy, Sonia A; Khan, Mumtaz J; Ronis, David L; Fowler, Karen E; Gruber, Stephen B; Wolf, Gregory T; Terrell, Jeffrey E

2008-01-01

This prospective, cohort study is the first to describe 5 health behaviors of head and neck cancer patients the first year after diagnosis. Patients (N = 283) were recruited in otolaryngology clinic waiting rooms and asked to complete written surveys. A medical record audit was also conducted. Descriptive statistics and multivariate analyses were conducted to determine which variables were associated with the 5 health behaviors. Half of the patients smoked and 25% were problem drinkers. Over half of the smokers and drinkers quit 1 year post-diagnosis. Smoking and problem drinking were highly associated and both were associated with lower body mass index (BMI) (p < .01). Moreover, physical activity and sleep were associated with each other (p < .01). Low SLEEP (Medical Outcomes Study Sleep Scale) scores were common and highly associated with depression (p < .01). The health behaviors of head and neck cancer patients are interrelated, and assessing and treating these behaviors together may be beneficial. Copyright (c) 2007 Wiley Periodicals, Inc.

Examining the Relationship Between Symptomatic Burden and Self-reported Productivity Losses Among Patients With Uterine Fibroids in the United States.

PubMed

Soliman, Ahmed M; Anand, Savita Bakhshi; Coyne, Karin S; Castelli-Haley, Jane; Snabes, Michael; Owens, Charlotte D

2017-10-01

To evaluate the impact of uterine fibroid symptoms on employment and household productivity. An online survey of US women between 18 and 54 was conducted. Productivity was assessed using the health related productivity questionnaire (HRPQ). Descriptive statistics and logistic multivariable regressions examined the relationship between uterine fibroids (UF) symptom experience and employment and household productivity. Of 1365 eligible women, 873 (64.0%) were employed. Women lost an average of 0.8 hours to employment-related absenteeism and 4.4 hours due to employment-related presenteeism for 5.1 hours of employment productivity lost/week. Women lost an average of 1.4 hours due to household-related absenteeism and 1.6 hours due to household-related presenteeism for a total of 3.0 hours of household lost productivity. Productivity losses increased with increases in symptom burden. UF has a substantial impact on employment-related and household-related productivity.

Implementation of the presence of companions during hospital admission for childbirth: data from the Birth in Brazil national survey.

PubMed

Diniz, Carmen Simone Grilo; d'Orsi, Eleonora; Domingues, Rosa Maria Soares Madeira; Torres, Jacqueline Alves; Dias, Marcos Augusto Bastos; Schneck, Camilla A; Lansky, Sônia; Teixeira, Neuma Zamariano Fanaia; Rance, Susanna; Sandall, Jane

2014-08-01

Robust evidence of the benefits of continuous support during childbirth led to the recommendation that it should be offered for all women. In Brazil, it has been guaranteed by law since 2005, but scarce data on implementation is available. We aimed to estimate the frequency and associated socio-demographic, obstetric and institutional predictors of women having companionship during childbirth in the Birth in Brazil survey. Descriptive statistical analysis was done for the characterization of companions (at different moments of hospital stay), maternal and institutional factors; associations were investigated in bivariate and multivariate models. We found that 24.5% of women had no companion at all, 18.8% had continuous companionship and 56.7% had partial companionship. Independent predictors of having no or partial companionship at birth were: lower income and education, brown color of skin, using the public sector, multiparity, and vaginal delivery. Implementation of companionship was associated with having an appropriate environment, and clear institution al rules about women's rights to companionship.

Tax revenue in Mississippi communities following implementation of smoke-free ordinances: an examination of tourism and economic development tax revenues.

PubMed

McMillen, Robert; Shackelford, Signe

2012-10-01

There is no safe level of exposure to tobacco smoke. More than 60 Mississippi communities have passed smoke-free ordinances in the past six years. Opponents claim that these ordinances harm local businesses. Mississippi law allows municipalities to place a tourism and economic development (TED) tax on local restaurants and hotels/motels. The objective of this study is to examine the impact of these ordinances on TED tax revenues. This study applies a pre/post quasi-experimental design to compare TED tax revenue before and after implementing ordinances. Descriptive analyses indicated that inflation-adjusted tax revenues increased during the 12 months following implementation of smoke-free ordinances while there was no change in aggregated control communities. Multivariate fixed-effects analyses found no statistically significant effect of smoke-free ordinances on hospitality tax revenue. No evidence was found that smoke-free ordinances have an adverse effect on the local hospitality industry.

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.

Longitudinal Assessment of Self-Reported Recent Back Pain and Combat Deployment in the Millennium Cohort Study

DTIC Science & Technology

2016-11-15

participants who were followed for the development of back pain for an average of 3.9 years. Methods. Descriptive statistics and longitudinal...health, military personnel, occupational health, outcome assessment, statistics, survey methodology . Level of Evidence: 3 Spine 2016;41:1754–1763ack...based on the National Health and Nutrition Examination Survey.21 Statistical Analysis Descriptive and univariate analyses compared character- istics

Rebuilding Government Legitimacy in Post-conflict Societies: Case Studies of Nepal and Afghanistan

DTIC Science & Technology

2015-09-09

administered via the verbal scales due to reduced time spent explaining the visual show cards. Statistical results corresponded with observations from...a three-step strategy for dealing with item non-response. First, basic descriptive statistics are calculated to determine the extent of item...descriptive statistics for all items in the survey), however this section of the report highlights just some of the findings. Thus, the results

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...

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Facilitating the Transition from Bright to Dim Environments

DTIC Science & Technology

2016-03-04

For the parametric data, a multivariate ANOVA was used in determining the systematic presence of any statistically significant performance differences...performed. All significance levels were p < 0.05, and statistical analyses were performed with the Statistical Package for Social Sciences ( SPSS ...1950. Age changes in rate and level of visual dark adaptation. Journal of Applied Physiology, 2, 407–411. Field, A. 2009. Discovering statistics

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

PubMed Central

Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.

2016-01-01

Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design

PubMed Central

Lu, Tsui-Shan; Longnecker, Matthew P.; Zhou, Haibo

2016-01-01

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data and the general ODS design for a continuous response. While substantial work has been done for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome dependent sampling (Multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the Multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the Multivariate-ODS or the estimator from a simple random sample with the same sample size. The Multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of PCB exposure to hearing loss in children born to the Collaborative Perinatal Study. PMID:27966260

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Applying Descriptive Statistics to Teaching the Regional Classification of Climate.

ERIC Educational Resources Information Center

Lindquist, Peter S.; Hammel, Daniel J.

1998-01-01

Describes an exercise for college and high school students that relates descriptive statistics to the regional climatic classification. The exercise introduces students to simple calculations of central tendency and dispersion, the construction and interpretation of scatterplots, and the definition of climatic regions. Forces students to engage…

Outcomes Definitions and Statistical Tests in Oncology Studies: A Systematic Review of the Reporting Consistency.

PubMed

Rivoirard, Romain; Duplay, Vianney; Oriol, Mathieu; Tinquaut, Fabien; Chauvin, Franck; Magne, Nicolas; Bourmaud, Aurelie

2016-01-01

Quality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology. From a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts. 826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 [0.31-0.89] (P value = 0.009). Variables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies.

Outcomes Definitions and Statistical Tests in Oncology Studies: A Systematic Review of the Reporting Consistency

PubMed Central

Rivoirard, Romain; Duplay, Vianney; Oriol, Mathieu; Tinquaut, Fabien; Chauvin, Franck; Magne, Nicolas; Bourmaud, Aurelie

2016-01-01

Background Quality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology. Methods From a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts. Results 826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 [0.31–0.89] (P value = 0.009). Conclusion Variables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies. PMID:27716793

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data

PubMed Central

Chen, Yi-Hau

2017-01-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA. PMID:28622336

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

PubMed

Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin

2017-06-01

Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA.

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.

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.

Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches.

PubMed

Willis, Cameron D; Gabbe, Belinda J; Jolley, Damien; Harrison, James E; Cameron, Peter A

2010-11-01

The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)-10-based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V-TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD-10-AM codes as predictors. Models were investigated for discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic). The multivariable approach had the highest level of discrimination (C-statistic 0.90) and calibration (H-L 7.65, P= 0.468). Worst injury ICISS, V-TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C-statistic 0.80) and poorest calibration (H-L 50.23, P < 0.001). The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD-10-AM codes was the best-performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS-based methods and may have comparable predictive performance to locally derived TRISS models. © 2010 The Authors. ANZ Journal of Surgery © 2010 Royal Australasian College of Surgeons.

Somatotype analysis of physically active individuals.

PubMed

Almeida, A H S; Santos, S A G; Castro, P J P; Rizzo, J A; Batista, G R

2013-06-01

The present study aimed at comparing demographic variables, physical activity level, and health-related anthropometric indicators according to somatotype among physically active individuals. This is a descriptive cross-sectional study, in which the sample consisted of 304 individuals, who are users of the jogging track at the Federal University of Pernambuco (UFPE) in Recife, state of Pernambuco, northeastern Brazil. Somatotypes were analyzed using the anthropometric technique proposed by Heath & Carter (1990). To assess physical activity level, we used the short version of the International Physical Activity Questionnaire (IPAQ). We used as health-related anthropometric indicators: body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and conicity index (CI). We used descriptive statistics to characterize the sample, and then used a multivariate analysis of variance (a = 0.05) to test for differences. In the somatotype analysis, we observed among women significant predominance of the endomorphy and lower predominance of the ectomorphy in comparison to men. In the age group ≤ 29 years significantly lower values were found for endomorphy than in other age groups. Irregularly active individuals had significantly lower values of endomorphy. We observed that individuals with obesity and risk in WHR, WC and CI had higher scores of endomorphy and mesomorphy and lower scores of ectomorphy. The somatotype of physically active individuals in the present study raises health concern, mainly related to high relative adiposity represented by endomorphy.

Comparison of patterns and knowledge of benefits and warnings of fish consumption between parents and children.

PubMed

Herdt-Losavio, Michele L; Lin, Shao; Chen, Ming; Luo, Ming; Tang, Jianzhong; Hwang, Syni-An

2014-07-01

We examined generational differences in fish consumption and knowledge of benefits/warnings of fish consumption among parents and children. This cross-sectional study gathered self-administered questionnaire data, including demographics, fish consumption behavior (including specific fish species) and knowledge of fish consumption warnings and benefits. Fish were later grouped into four categories by potential mercury contamination. Descriptive statistics were conducted for all variables comparing all adults and children. Benefit/risk knowledge variables were also descriptively analyzed among parent-child pairs only. Multivariate Poisson regression was conducted on pairs to assess risk factors for children eating higher mercury fish. 421 adults and 207 children (171 adult-child pairs) participated (family response rate: 71%). Slightly more adults (97.6%) ate fish in the last year than children (92.3%); however, there was no difference between consumption of fish by category of potential mercury contamination. Both adults (44%) and children (45%) ate high-mercury fish. In 71% of parent-child pairs, both the parent and the child knew of benefits of consuming fish; only 31% knew of warnings. Parental consumption of high or moderately-high-mercury fish was related to the child's consumption of fish in the same category. Parents and children need additional education to make better choices about fish consumption. Education should target the family and include specifics about benefits and risks.

NONPARAMETRIC MANOVA APPROACHES FOR NON-NORMAL MULTIVARIATE OUTCOMES WITH MISSING VALUES

PubMed Central

He, Fanyin; Mazumdar, Sati; Tang, Gong; Bhatia, Triptish; Anderson, Stewart J.; Dew, Mary Amanda; Krafty, Robert; Nimgaonkar, Vishwajit; Deshpande, Smita; Hall, Martica; Reynolds, Charles F.

2017-01-01

Between-group comparisons often entail many correlated response variables. The multivariate linear model, with its assumption of multivariate normality, is the accepted standard tool for these tests. When this assumption is violated, the nonparametric multivariate Kruskal-Wallis (MKW) test is frequently used. However, this test requires complete cases with no missing values in response variables. Deletion of cases with missing values likely leads to inefficient statistical inference. Here we extend the MKW test to retain information from partially-observed cases. Results of simulated studies and analysis of real data show that the proposed method provides adequate coverage and superior power to complete-case analyses. PMID:29416225

Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be.

PubMed

Forcino, Frank L; Leighton, Lindsey R; Twerdy, Pamela; Cahill, James F

2015-01-01

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.

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…

Statistics Anxiety and Worry: The Roles of Worry Beliefs, Negative Problem Orientation, and Cognitive Avoidance

ERIC Educational Resources Information Center

Williams, Amanda S.

2015-01-01

Statistics anxiety is a common problem for graduate students. This study explores the multivariate relationship between a set of worry-related variables and six types of statistics anxiety. Canonical correlation analysis indicates a significant relationship between the two sets of variables. Findings suggest that students who are more intolerant…

Statistics in three biomedical journals.

PubMed

Pilcík, T

2003-01-01

In this paper we analyze the use of statistics and associated problems, in three Czech biological journals in the year 2000. We investigated 23 articles Folia Biologica, 60 articles in Folia Microbiologica, and 88 articles in Physiological Research. The highest frequency of publications with statistical content have used descriptive statistics and t-test. The most usual mistake concerns the absence of reference about the used statistical software and insufficient description of the data. We have compared our results with the results of similar studies in some other medical journals. The use of important statistical methods is comparable with those used in most medical journals, the proportion of articles, in which the applied method is described insufficiently is moderately low.

[Multivariate study of the psychosocial factors affecting public attitude towards organ donation].

PubMed

Conesa, C; Ríos, A; Ramírez, P; Canteras, M; Rodríguez, M M; Parrilla, P

2005-01-01

Organ transplantation is a therapy which depends on society for its development. The objectives here are: 1) to understand the structure of public opinion towards organ donation in the population aged over 15 years of age in our Community; 2) to analyse the psychosocial variables which affect this opinion and 3) to define the population profiles on this matter. Random sample (n = 2.000) stratified for age, sex and geographical location (error for 95.5%, e +/- 2.24) to whom we apply a questionnaire about the psychosocial aspects of organ donation. Descriptive statistics, Student's t-test, Chi-squared test and logistical regression analysis. 63% have a favourable attitude towards organ donation, of which 11% have a donor's card. A statistical association has been observed between favourable public opinion and different psychosocial variables (p < 0.05), with some independent variables persisting in the multivariate analysis such as age, level of education (OR = 1.78), information given by family members (OR = 1.62), health workers (OR = 2.01) and talks in educational centres (OR = 2.13); previous experience with donation and transplantation (OR = 2.02), knowledge of the concept of brain death (OR = 1.4); partner's favourable opinion towards donation (OR = 2.6), being a blood donor (OR = 3), taking part in prosocial activities (OR = 1.6) and attitude towards incineration of the cadaver after death (OR = 1.8). The profile of a person who is against donation is of a man or woman, > 50 years of age, with primary studies or below, with no previous experience of the matter, who does not understand the concept of brain death nor their partner's opinion towards donation, who has not found out any information about donation through specialised forums, with an unfavourable opinion towards blood donation or pro-social activities and who is fearful of manipulation of the cadaver after death.

A cross-sectional study of vitamin D levels in a large cohort of patients with rheumatic diseases.

PubMed

Nikiphorou, Elena; Uksila, Jaakko; Sokka, Tuulikki

2018-03-01

The objective of this study is to examine 25-hydroxyvitamin D [25(OH)D] (D-25) levels and associations with patient- and disease-related factors in rheumatic diseases. This is a register-based study of D-25 levels in adult patients seen at the Central Finland Hospital rheumatology clinic (January 2011-April 2015). Demographic, clinical, laboratory, and patient-reported outcomes (PROs) were collected as part of the normal infrastructure of the outpatient clinic and examined for their association with D-25 level. Statistical analysis included descriptive statistics and univariable and multivariable regression analyses adjusting for age and gender. D-25 was measured in 3203 patients (age range 15-91 years, mean 54; 68% female) with diagnoses including RA (n = 1386), unspecified arthralgia/myalgia (n = 413), and connective tissues diseases (n = 213). The overall D-25 mean (SD) level was 78 (31) and median (IQR) 75 (55, 97). At baseline, 17.8% had D-25 deficiency, and only 1.6% severe deficiency  (< 25 nmol/l); 34%/49% had sufficient/optimal D-25 levels. Higher D-25 levels were associated with older age, lower BMI, and regular exercise (all p < 0.001) among other factors. In multivariable analyses, younger age, non-white background, higher BMI, smoking, less frequent exercise (p < 0.001), and first visit to the clinic (p = 0.033) remained significantly associated with D-25 deficiency. Among those with sub-optimal D-25 levels, 64% had improved to sufficient/optimal levels after a median (IQR) of 13 (7.8, 22) months. The proportion of patients with D-25 deficiency in this study was generally low. Older patients had considerably higher D-25 levels compared to younger patients. Lower physical exercise and higher BMI were associated with higher risk of deficiency. The study supports the benefit of strategies to help minimize the risk of D-25 deficiency.

Predictive factors of Gastrointestinal motility Dysfunction after gastrojejunostomy for peptic ulcer stenosis.

PubMed

Ayadi, Sofiene; Daghfous, Amine; Saidani, Ahmed; Haddad, Anis; Magherbi, Houcine; Jouini, Mohamed; Kacem, Montassar; Ben Safta, Zoubeir

2014-10-01

Despite the establishment of effective medical therapies in peptic ulcer disease, gastric outlet obstruction remains one of the most common health problem in Tunisia. Various operations have been attempted, which may lead to postoperative morbidity. Gastrointestinal (GI) motility dysfunction is the most common complications. to determine the predictive factor of gastrointestinal motility dysfunction after gastrojejunostomy for peptic ulcer stenosis. We carried out a retrospective study to evaluate the postoperative recovery of the motility of the upper gastrointestinal tract after gastrojejunostomy for peptic ulcer stenosis. During the 9- year study, 138 patients underwent operations for ulcer peptic stenosis. Among the patients, 116 (84,1%) were treated with gastrojejunostomy. Descriptive statistics, univariate and multivariate analyses were performed. The mean age of patients was 47.85 years (range: 19- 92years) and most. Were male (84, 5 %). Ninety two (79.3%) patients had a documented history of peptic ulcer disease. The duration of symptoms ranged from 10 to 372 days (mean: 135.86 days). Eighty two (71%) patients were operated on through laparotomy. Laparoscopic procedure was performed in 29% of the patients. There was no operative mortality. Perioperative morbidity occurred in 12.4% (14 patients). Gastrointestinal motility dysfunction occurred in 12 patients (10.3%). It was treated by nasogastric aspiration and prokinetics. By univariate analysis; diabetes (0,010), cachexia (0,049), ASA class (0.05) were all statistically associated with gastrointestinal motility dysfunction in this series. Multivariate logistic regression analysis (table 2) showed that the cachexia (0,009), ASA class (0.02) were the main predictors of gastrointestinal motility dysfunction after gastrojejunostomy for peptic ulcer stenosis in the followed patients. Gastrointestinal motility dysfunction is the most common complications after gastrojejunostomy for pyloric adult stenosis. Surgery must be preceded by careful medical preparation. It is more likely to occur in patients with an ASA class 2 or greater. Those patients should be considered for other treatment options, such as endoscopic balloon dilation.

Psychosocial predictors of breast self-examination behavior among female students: an application of the health belief model using logistic regression.

PubMed

Didarloo, Alireza; Nabilou, Bahram; Khalkhali, Hamid Reza

2017-11-03

Breast cancer is a life-threatening condition affecting women around the world. The early detection of breast lumps using a breast self-examination (BSE) is important for the prevention and control of this disease. The aim of this study was to examine BSE behavior and its predictive factors among female university students using the Health Belief Model (HBM). This investigation was a cross-sectional survey carried out with 334 female students at Urmia University of Medical Sciences in the northwest of Iran. To collect the necessary data, researchers applied a valid and reliable three-part questionnaire. The data were analyzed using descriptive statistics and a chi-square test, in addition to multivariate logistic regression statistics in SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). The results indicated that 82 of the 334 participants (24.6%) reported practicing BSEs. Multivariate logistic regression analyses showed that high perceived severity [OR = 2.38, 95% CI = (1.02-5.54)], high perceived benefits [OR = 1.94, 95% CI = (1.09-3.46)], and high perceived self-efficacy [OR = 13.15, 95% CI = (3.64-47.51)] were better predictors of BSE behavior (P < 0.05) than low perceived severity, benefits, and self-efficacy. The findings also showed that a high level of knowledge compared to a low level of knowledge [OR = 5.51, 95% CI = (1.79-16.86)] and academic undergraduate and graduate degrees compared to doctoral degrees [OR = 2.90, 95% CI = (1.42-5.92)] of the participants were predictors of BSE performance (P < 0.05). The study revealed that the HBM constructs are able to predict BSE behavior. Among these constructs, self-efficacy was the most important predictor of the behavior. Interventions based on the constructs of perceived self-efficacy, benefits, and severity are recommended for increasing women's regular screening for breast cancer.

Quality of reporting of multivariable logistic regression models in Chinese clinical medical journals.

PubMed

Zhang, Ying-Ying; Zhou, Xiao-Bin; Wang, Qiu-Zhen; Zhu, Xiao-Yan

2017-05-01

Multivariable logistic regression (MLR) has been increasingly used in Chinese clinical medical research during the past few years. However, few evaluations of the quality of the reporting strategies in these studies are available.To evaluate the reporting quality and model accuracy of MLR used in published work, and related advice for authors, readers, reviewers, and editors.A total of 316 articles published in 5 leading Chinese clinical medical journals with high impact factor from January 2010 to July 2015 were selected for evaluation. Articles were evaluated according 12 established criteria for proper use and reporting of MLR models.Among the articles, the highest quality score was 9, the lowest 1, and the median 5 (4-5). A total of 85.1% of the articles scored below 6. No significant differences were found among these journals with respect to quality score (χ = 6.706, P = .15). More than 50% of the articles met the following 5 criteria: complete identification of the statistical software application that was used (97.2%), calculation of the odds ratio and its confidence interval (86.4%), description of sufficient events (>10) per variable, selection of variables, and fitting procedure (78.2%, 69.3%, and 58.5%, respectively). Less than 35% of the articles reported the coding of variables (18.7%). The remaining 5 criteria were not satisfied by a sufficient number of articles: goodness-of-fit (10.1%), interactions (3.8%), checking for outliers (3.2%), collinearity (1.9%), and participation of statisticians and epidemiologists (0.3%). The criterion of conformity with linear gradients was applicable to 186 articles; however, only 7 (3.8%) mentioned or tested it.The reporting quality and model accuracy of MLR in selected articles were not satisfactory. In fact, severe deficiencies were noted. Only 1 article scored 9. We recommend authors, readers, reviewers, and editors to consider MLR models more carefully and cooperate more closely with statisticians and epidemiologists. Journals should develop statistical reporting guidelines concerning MLR.

Health Literacy is associated with Healthy Eating Index Scores and Sugar-Sweetened Beverage Intake: Findings from the Rural Lower Mississippi Delta

PubMed Central

Zoellner, Jamie; You, Wen; Connell, Carol; Smith-Ray, Renae L.; Allen, Kacie; Tucker, Katherine L; Davy, Brenda M.; Estabrooks, Paul A.

2011-01-01

Background Although health literacy has been a public health priority area for over a decade, the relationship between health literacy and dietary quality has not been thoroughly explored. Objective To evaluate health literacy skills in relation to Healthy Eating Index scores (HEI) and Sugar-Sweetened Beverage (SSB) consumption, while accounting for demographic variables. Design Cross-sectional survey. Participants/setting A community-based proportional sample of adults residing in the rural Lower Mississippi Delta. Methods Instruments included a validated 158-item regional food frequency questionnaire and the Newest Vital Sign (scores range 0–6) to assess health literacy. Statistical analyses performed Descriptive statistics, ANOVA, and multivariate linear regression. Results Of 376 participants, the majority were African American (67.6%), without a college degree (71.5%), and household income level <$20,000/year (55.0%). Most participants (73.9%) scored in the two lowest health literacy categories. The multivariate linear regression model to predict total HEI scores was significant (R2=0.24; F=18.8; p<0.01), such that every 1 point increase in health literacy was associated with a 1.21 point increase in healthy eating index scores, while controlling for all other variables. Other significant predictors of HEI scores included age, gender, and SNAP participation. Health literacy also significantly predicted sugar-sweetened beverages consumption (R2=0.15; F=6.3; p<0.01), while accounting for demographic variables. Every 1 point in health literacy scores was associated with 34 fewer SSB kilocalories/day. Age was the only significant covariate in the SSB model. Conclusion While health literacy has been linked to numerous poor health outcomes, to our knowledge this is the first investigation to establish a relationship between health literacy and HEI scores and SSB consumption. Our study suggests that understanding the causes and consequences of limited health literacy is an important factor in promoting compliance to the Dietary Guidelines for Americans. PMID:21703379

Impact of Different Surgeons on Dental Implant Failure.

PubMed

Chrcanovic, Bruno Ramos; Kisch, Jenö; Albrektsson, Tomas; Wennerberg, Ann

To assess the influence of several factors on the prevalence of dental implant failure, with special consideration of the placement of implants by different dental surgeons. This retrospective study is based on 2,670 patients who received 10,096 implants at one specialist clinic. Only the data of patients and implants treated by surgeons who had inserted a minimum of 200 implants at the clinic were included. Kaplan-Meier curves were stratified with respect to the individual surgeon. A generalized estimating equation (GEE) method was used to account for the fact that repeated observations (several implants) were placed in a single patient. The factors bone quantity, bone quality, implant location, implant surface, and implant system were analyzed with descriptive statistics separately for each individual surgeon. A total of 10 surgeons were eligible. The differences between the survival curves of each individual were statistically significant. The multivariate GEE model showed the following variables to be statistically significant: surgeon, bruxism, intake of antidepressants, location, implant length, and implant system. The surgeon with the highest absolute number of failures was also the one who inserted the most implants in sites of poor bone and used turned implants in most cases, whereas the surgeon with the lowest absolute number of failures used mainly modern implants. Separate survival analyses of turned and modern implants stratified for the individual surgeon showed statistically significant differences in cumulative survival. Different levels of failure incidence could be observed between the surgeons, occasionally reaching significant levels. Although a direct causal relationship could not be ascertained, the results of the present study suggest that the surgeons' technique, skills, and/or judgment may negatively influence implant survival rates.

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Interfaces between statistical analysis packages and the ESRI geographic information system

NASA Technical Reports Server (NTRS)

Masuoka, E.

1980-01-01

Interfaces between ESRI's geographic information system (GIS) data files and real valued data files written to facilitate statistical analysis and display of spatially referenced multivariable data are described. An example of data analysis which utilized the GIS and the statistical analysis system is presented to illustrate the utility of combining the analytic capability of a statistical package with the data management and display features of the GIS.

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error.

PubMed

Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Alejandro Q; Musolf, Anthony; Matise, Tara C; Finch, Stephen J; Gordon, Derek

2012-01-01

As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci. Copyright © 2013 S. Karger AG, Basel.

Single variant and multi-variant trend tests for genetic association with next generation sequencing that are robust to sequencing error

PubMed Central

Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Andrew; Musolf, Anthony; Matise, Tara C.; Finch, Stephen J.; Gordon, Derek

2013-01-01

As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci. PMID:23594495

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

Treesearch

Denis Valle; Benjamin Baiser; Christopher W. Woodall; Robin Chazdon; Jerome Chave

2014-01-01

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates...

Departure from Normality in Multivariate Normative Comparison: The Cramer Alternative for Hotelling's "T[squared]"

ERIC Educational Resources Information Center

Grasman, Raoul P. P. P.; Huizenga, Hilde M.; Geurts, Hilde M.

2010-01-01

Crawford and Howell (1998) have pointed out that the common practice of z-score inference on cognitive disability is inappropriate if a patient's performance on a task is compared with relatively few typical control individuals. Appropriate univariate and multivariate statistical tests have been proposed for these studies, but these are only valid…

Unlawful Discrimination DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

Included is a review of the 4.0 description and items, followed by the proposed modifications to the factor. The current DEOCS (4.0) contains multiple...Officer (E7 – E9) 586 10.8% Junior Officer (O1 – O3) 474 9% Senior Officer (O4 and above) 391 6.1% Descriptive Statistics and Reliability This section...displays descriptive statistics for the items on the Unlawful Discrimination scale. All items had a range from 1 to 7 (strongly disagree to strongly

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

A socioecological model of posttraumatic stress among Australian midwives.

PubMed

Leinweber, Julia; Creedy, Debra K; Rowe, Heather; Gamble, Jenny

2017-02-01

to develop a comprehensive model of personal, trauma event-related and workplace-related risk factors for posttraumatic stress subsequent to witnessing birth trauma among Australian midwives. a descriptive, cross-sectional design was used. members of the Australian College of Midwives were invited to complete an online survey. the survey included items about witnessing a traumatic birth event and previous experiences of life trauma. Trauma symptoms were assessed with the Posttraumatic Stress Disorder Symptom Scale Self-Report measure. Empathy was assessed with the Interpersonal Reactivity Index. Decision authority and psychological demand in the workplace were measured with the Job Content Questionnaire. Variables that showed a significant univariate association with probable posttraumatic stress disorder were entered into a multivariate logistic regression model. 601 completed survey responses were analysed. The multivariable model was statistically significant and explained 27.7% (Nagelkerke R square) of the variance in posttraumatic stress symptoms and correctly classified 84.1% of cases. Odds ratios indicated that intention to leave the profession, a peritraumatic reaction of horror, peritraumatic feelings of guilt, and a personal traumatic birth experience were strongly associated with probable Posttraumatic Stress Disorder. risk factors for posttraumatic stress following professional exposure to traumatic birth events among midwives are complex and multi-factorial. Posttraumatic stress may contribute to attrition in midwifery. Trauma-informed care and practice may reduce the incidence of traumatic births and subsequent posttraumatic stress reactions in women and midwives providing care. Copyright © 2016 Elsevier Ltd. All rights reserved.

Oncology trial abstracts showed suboptimal improvement in reporting: a comparative before-and-after evaluation using CONSORT for Abstract guidelines.

PubMed

Ghimire, Saurav; Kyung, Eunjung; Lee, Heeyoung; Kim, Eunyoung

2014-06-01

The aims of this study were to evaluate the quality of randomized controlled trial (RCT) abstracts published in the field of oncology and identify characteristics associated with better reporting quality. All phase III trials published during 2005-2007 [before Consolidated Standards of Reporting Trials (CONSORT)] and 2010-2012 (after CONSORT) were searched electronically in MEDLINE/PubMed and retrieved for review using an 18-point overall quality score (OQS) for reporting based on the CONSORT for Abstract guidelines. Descriptive statistics followed by multivariate linear regression were used to identify features associated with improved reporting quality. The mean OQS was 8.2 (range: 5-13; 95% confidence interval (CI): 8.0, 8.3) and 9.9 (range: 5-18; 95% CI: 9.7, 10.2) in the pre- and post-CONSORT periods, respectively. The method for random sequence generation, allocation concealment, blinding details, and funding sources were missing in pre-CONSORT abstracts and insufficiently reported (<20%) in post-CONSORT abstracts. A high impact factor (P < 0.001) and the journal of publication (P < 0.001) were independent factors that were significantly associated with higher reporting quality on multivariate analysis. The reporting quality of RCT abstracts in oncology showed suboptimal improvement over time. Thus, stricter adherence to the CONSORT for Abstract guidelines is needed to improve the reporting quality of RCT abstracts published in oncology. Copyright © 2014 Elsevier Inc. All rights reserved.

Implications of Supermarket Access, Neighborhood Walkability, and Poverty Rates for Diabetes Risk in an Employee Population

PubMed Central

Herrick, Cynthia J.; Yount, Byron W.; Eyler, Amy A.

2016-01-01

Objective Diabetes is a growing public health problem, and the environment in which people live and work may affect diabetes risk. The goal of this study was to examine the association between multiple aspects of environment and diabetes risk in an employee population. Design This was a retrospective cross-sectional analysis. Home environment variables were derived using employee zip code. Descriptive statistics were run on all individual and zip code level variables, stratified by diabetes risk and worksite. A multivariable logistic regression analysis was then conducted to determine the strongest associations with diabetes risk. Setting Data was collected from employee health fairs in a Midwestern health system 2009–2012. Subjects The dataset contains 25,227 unique individuals across four years of data. From this group, using an individual’s first entry into the database, 15,522 individuals had complete data for analysis. Results The prevalence of high diabetes risk in this population was 2.3%. There was significant variability in individual and zip code level variables across worksites. From the multivariable analysis, living in a zip code with higher percent poverty and higher walk score was positively associated with high diabetes risk, while living in a zip code with higher supermarket density was associated with a reduction in high diabetes risk. Conclusions Our study underscores the important relationship between poverty, home neighborhood environment, and diabetes risk, even in a relatively healthy employed population, and suggests a role for the employer in promoting health. PMID:26638995

Implications of supermarket access, neighbourhood walkability and poverty rates for diabetes risk in an employee population.

PubMed

Herrick, Cynthia J; Yount, Byron W; Eyler, Amy A

2016-08-01

Diabetes is a growing public health problem, and the environment in which people live and work may affect diabetes risk. The goal of the present study was to examine the association between multiple aspects of environment and diabetes risk in an employee population. This was a retrospective cross-sectional analysis. Home environment variables were derived using employees' zip code. Descriptive statistics were run on all individual- and zip-code-level variables, stratified by diabetes risk and worksite. A multivariable logistic regression analysis was then conducted to determine the strongest associations with diabetes risk. Data were collected from employee health fairs in a Midwestern health system, 2009-2012. The data set contains 25 227 unique individuals across four years of data. From this group, using an individual's first entry into the database, 15 522 individuals had complete data for analysis. The prevalence of high diabetes risk in this population was 2·3 %. There was significant variability in individual- and zip-code-level variables across worksites. From the multivariable analysis, living in a zip code with higher percentage of poverty and higher walk score was positively associated with high diabetes risk, while living in a zip code with higher supermarket density was associated with a reduction in high diabetes risk. Our study underscores the important relationship between poverty, home neighbourhood environment and diabetes risk, even in a relatively healthy employed population, and suggests a role for the employer in promoting health.

[Excessive Daytime Sleepiness, Poor Quality Sleep, and Low Academic Performance in Medical Students].

PubMed

Machado-Duque, Manuel Enrique; Echeverri Chabur, Jorge Enrique; Machado-Alba, Jorge Enrique

2015-01-01

Quality of sleep and excessive daytime sleepiness (EDS) affect cognitive ability and performance of medical students. This study attempts to determine the prevalence of EDS, sleep quality, and assess their association with poor academic performance in this population. A descriptive, observational study was conducted on a random sample of 217 medical students from the Universidad Tecnológica de Pereira, who completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the Epworth sleepiness scale. Sociodemographic, clinic and academic variables were also measured. Multivariate analyses for poor academic performance were performed. The included students had a mean age of 21.7±3.3 years, of whom 59.4% were men. Almost half (49.8%) had EDS criteria, and 79.3% were poor sleepers (PSQI ≥ 5), while 43.3% had poor academic performance during the last semester. The bivariate analysis showed that having used tobacco or alcohol until intoxicated, fairly bad subjective sleep quality, sleep efficiency < 65%, and being a poor sleeper were associated with increased risk of low performance. Sleep efficiency < 65% was statistically associated with poor academic performance (P=.024; OR = 4.23; 95% CI, 1.12-15.42) in the multivariate analysis. A poor sleep quality determined by low efficiency was related to poor academic achievement at the end of semester in medical students. Copyright © 2015 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

[Prevalence and risk factors of urinary incontinence in women who visit the doctor with low back pain: multicentre study].

PubMed

Gavira Pavón, Alberto; Walker Chao, Carolina; Rodríguez Rodríguez, Nicomedes; Gavira Iglesias, Francisco Javier

2014-02-01

Estimating prevalence and risk factors of urinary incontinence (UI) in women with low back pain (LBP) and describing their social and demographic and clinical features. Cross-sectional study. Two primary care health centres in south of Cordoba and a private center in Madrid. 364 women of 20-65 years of age (of 466 who were contacted, 33 of them were excluded and 69 refused to participate) who had low back pain located between the twelfth rib and the gluteal fold. Medical questionnaire. Questionnaires (Oswestry Disability Index and UI questionnaires [International Consultation on Incontinence Questionnaire SF and Incontinence Impact Questionnaire-7]), functional test (ASLR Test) and comorbidity of interest for the UI. Descriptive and multivariate statistical analysis. UI was detected in 155 women (43%, 95% CI: 37%-48%), the majority of stress (83%) and a minimal impact (60%). Front of the continents, incontinent women showed significant differences in age, body mass index, marital status, level of education, coexistence, consumption of drugs/day, number of vaginal and total deliveries, abdominal and pelvic surgery, asthma, constipation, hypertension, diabetes, percentage of disability and functional ASLR test. In multivariate analysis, the variables influencing the probability of being incontinent were asthma, hypertension, constipation, total parity, BMI and the percentage of disability. Prevalence of UI is higher than in women without low back pain. Asthma, constipation and parity are the most influential factors in the occurrence of UI. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Heteronormativity and Sexual Partnering Among Bisexual Latino Men

PubMed Central

Garcia, Jonathan; Wilson, Patrick A.; Parker, Richard G.; Severson, Nicolette

2015-01-01

Our analyses address the question of how bisexual Latino men organize their sexual partnerships. Heteronormativity can be understood as the set of social norms and normative structures that guide sexual partnering among men and women. We provide descriptive statistics to describe bisexual Latino men’s sexual partnerships. Logistic and linear regression modeling were used to explore bivariate and multivariate relationships. Of our total sample (N = 142), 41.6% had unprotected vaginal intercourse 2 months prior to the interview; 21.8 % had unprotected anal intercourse with female partners; 37.5 % had unprotected insertive anal intercourse with male partners; and 22.5 % had unprotected receptive anal intercourse with male partners. In our multivariate model, machismo was directly associated with meeting female partners through formal spaces (workplace, school, and/or church), but inversely associated with meeting male partners in formal spaces. Machismo was positively associated with meeting male sex partners through social networks (i.e., friendship and kinship networks). The more comfortable men were with homosexuality the less likely they were to meet men online and the more likely they were to meet men through social networks of friends and kinship. Interventions to reduce sexually transmitted diseases that target bisexual behavior as an epidemiological “bridge” of transmission from homosexual to heterosexual networks might very well benefit from a more complex understanding of how Latino bisexuality is patterned. Thus, this exploratory analysis might lead to a rethinking of how to address risk and vulnerability among Latino bisexual men and their sexual networks. PMID:25128415

Heteronormativity and sexual partnering among bisexual Latino men.

PubMed

Muñoz-Laboy, Miguel; Garcia, Jonathan; Wilson, Patrick A; Parker, Richard G; Severson, Nicolette

2015-05-01

Our analyses address the question of how bisexual Latino men organize their sexual partnerships. Heteronormativity can be understood as the set of social norms and normative structures that guide sexual partnering among men and women. We provide descriptive statistics to describe bisexual Latino men's sexual partnerships. Logistic and linear regression modeling were used to explore bivariate and multivariate relationships. Of our total sample (N = 142), 41.6 % had unprotected vaginal intercourse 2 months prior to the interview; 21.8 % had unprotected anal intercourse with female partners; 37.5 % had unprotected insertive anal intercourse with male partners; and 22.5 % had unprotected receptive anal intercourse with male partners. In our multivariate model, machismo was directly associated with meeting female partners through formal spaces (workplace, school, and/or church), but inversely associated with meeting male partners in formal spaces. Machismo was positively associated with meeting male sex partners through social networks (i.e., friendship and kinship networks). The more comfortable men were with homosexuality the less likely they were to meet men online and the more likely they were to meet men through social networks of friends and kinship. Interventions to reduce sexually transmitted diseases that target bisexual behavior as an epidemiological "bridge" of transmission from homosexual to heterosexual networks might very well benefit from a more complex understanding of how Latino bisexuality is patterned. Thus, this exploratory analysis might lead to a rethinking of how to address risk and vulnerability among Latino bisexual men and their sexual networks.

Using Microsoft Excel[R] to Calculate Descriptive Statistics and Create Graphs

ERIC Educational Resources Information Center

Carr, Nathan T.

2008-01-01

Descriptive statistics and appropriate visual representations of scores are important for all test developers, whether they are experienced testers working on large-scale projects, or novices working on small-scale local tests. Many teachers put in charge of testing projects do not know "why" they are important, however, and are utterly convinced…

Self-Esteem and Academic Achievement of High School Students

ERIC Educational Resources Information Center

Moradi Sheykhjan, Tohid; Jabari, Kamran; Rajeswari, K.

2014-01-01

The primary purpose of this study was to determine the influence of self-esteem on academic achievement among high school students in Miandoab City of Iran. The methodology of the research is descriptive and correlation that descriptive and inferential statistics were used to analyze the data. Statistical Society includes male and female high…

Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design.

PubMed

Selvarasu, Suresh; Kim, Do Yun; Karimi, Iftekhar A; Lee, Dong-Yup

2010-10-01

We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in the feed medium can be inferred, potentially leading to an increase in cell viability and productivity, as well as a decrease in toxic waste production. The study demonstrated how the current methodological framework using multivariate statistical analysis techniques can serve as a potential tool for deriving rational medium design strategies. Copyright © 2010 Elsevier B.V. All rights reserved.

Multivariate model of female black bear habitat use for a Geographic Information System

USGS Publications Warehouse

Clark, Joseph D.; Dunn, James E.; Smith, Kimberly G.

1993-01-01

Simple univariate statistical techniques may not adequately assess the multidimensional nature of habitats used by wildlife. Thus, we developed a multivariate method to model habitat-use potential using a set of female black bear (Ursus americanus) radio locations and habitat data consisting of forest cover type, elevation, slope, aspect, distance to roads, distance to streams, and forest cover type diversity score in the Ozark Mountains of Arkansas. The model is based on the Mahalanobis distance statistic coupled with Geographic Information System (GIS) technology. That statistic is a measure of dissimilarity and represents a standardized squared distance between a set of sample variates and an ideal based on the mean of variates associated with animal observations. Calculations were made with the GIS to produce a map containing Mahalanobis distance values within each cell on a 60- × 60-m grid. The model identified areas of high habitat use potential that could not otherwise be identified by independent perusal of any single map layer. This technique avoids many pitfalls that commonly affect typical multivariate analyses of habitat use and is a useful tool for habitat manipulation or mitigation to favor terrestrial vertebrates that use habitats on a landscape scale.

Multivariate analysis of heavy metal contamination using river sediment cores of Nankan River, northern Taiwan

NASA Astrophysics Data System (ADS)

Lee, An-Sheng; Lu, Wei-Li; Huang, Jyh-Jaan; Chang, Queenie; Wei, Kuo-Yen; Lin, Chin-Jung; Liou, Sofia Ya Hsuan

2016-04-01

Through the geology and climate characteristic in Taiwan, generally rivers carry a lot of suspended particles. After these particles settled, they become sediments which are good sorbent for heavy metals in river system. Consequently, sediments can be found recording contamination footprint at low flow energy region, such as estuary. Seven sediment cores were collected along Nankan River, northern Taiwan, which is seriously contaminated by factory, household and agriculture input. Physico-chemical properties of these cores were derived from Itrax-XRF Core Scanner and grain size analysis. In order to interpret these complex data matrices, the multivariate statistical techniques (cluster analysis, factor analysis and discriminant analysis) were introduced to this study. Through the statistical determination, the result indicates four types of sediment. One of them represents contamination event which shows high concentration of Cu, Zn, Pb, Ni and Fe, and low concentration of Si and Zr. Furthermore, three possible contamination sources of this type of sediment were revealed by Factor Analysis. The combination of sediment analysis and multivariate statistical techniques used provides new insights into the contamination depositional history of Nankan River and could be similarly applied to other river systems to determine the scale of anthropogenic contamination.

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

PubMed

Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P; Gonzalez-Zacarias, Clio; Zhao, Lu; D'Arcy, Mike; Kesselman, Carl; Herting, Megan M; Dinov, Ivo D; Toga, Arthur W; Clark, Kristi A

2018-05-15

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases). Copyright © 2018 Elsevier Inc. All rights reserved.

Multivariate Statistical Approach Applied to Sediment Source Tracking Through Quantification and Mineral Identification, Cheyenne River, South Dakota

NASA Astrophysics Data System (ADS)

Valder, J.; Kenner, S.; Long, A.

2008-12-01

Portions of the Cheyenne River are characterized as impaired by the U.S. Environmental Protection Agency because of water-quality exceedences. The Cheyenne River watershed includes the Black Hills National Forest and part of the Badlands National Park. Preliminary analysis indicates that the Badlands National Park is a major contributor to the exceedances of the water-quality constituents for total dissolved solids and total suspended solids. Water-quality data have been collected continuously since 2007, and in the second year of collection (2008), monthly grab and passive sediment samplers are being used to collect total suspended sediment and total dissolved solids in both base-flow and runoff-event conditions. In addition, sediment samples from the river channel, including bed, bank, and floodplain, have been collected. These samples are being analyzed at the South Dakota School of Mines and Technology's X-Ray Diffraction Lab to quantify the mineralogy of the sediments. A multivariate statistical approach (including principal components, least squares, and maximum likelihood techniques) is applied to the mineral percentages that were characterized for each site to identify the contributing source areas that are causing exceedances of sediment transport in the Cheyenne River watershed. Results of the multivariate analysis demonstrate the likely sources of solids found in the Cheyenne River samples. A further refinement of the methods is in progress that utilizes a conceptual model which, when applied with the multivariate statistical approach, provides a better estimate for sediment sources.

MANCOVA for one way classification with homogeneity of regression coefficient vectors

NASA Astrophysics Data System (ADS)

Mokesh Rayalu, G.; Ravisankar, J.; Mythili, G. Y.

2017-11-01

The MANOVA and MANCOVA are the extensions of the univariate ANOVA and ANCOVA techniques to multidimensional or vector valued observations. The assumption of a Gaussian distribution has been replaced with the Multivariate Gaussian distribution for the vectors data and residual term variables in the statistical models of these techniques. The objective of MANCOVA is to determine if there are statistically reliable mean differences that can be demonstrated between groups later modifying the newly created variable. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates. In this research article, an extension has been made to the MANCOVA technique with more number of covariates and homogeneity of regression coefficient vectors is also tested.

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

PubMed

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Noncentral Chi-Square versus Normal Distributions in Describing the Likelihood Ratio Statistic: The Univariate Case and Its Multivariate Implication

ERIC Educational Resources Information Center

Yuan, Ke-Hai

2008-01-01

In the literature of mean and covariance structure analysis, noncentral chi-square distribution is commonly used to describe the behavior of the likelihood ratio (LR) statistic under alternative hypothesis. Due to the inaccessibility of the rather technical literature for the distribution of the LR statistic, it is widely believed that the…

Some Tests of Randomness with Applications

DTIC Science & Technology

1981-02-01

freedom. For further details, the reader is referred to Gnanadesikan (1977, p. 169) wherein other relevant tests are also given, Graphical tests, as...sample from a gamma distri- bution. J. Am. Statist. Assoc. 71, 480-7. Gnanadesikan , R. (1977). Methods for Statistical Data Analysis of Multivariate

Statistical polarization in greenhouse gas emissions: Theory and evidence.

PubMed

Remuzgo, Lorena; Trueba, Carmen

2017-11-01

The current debate on climate change is over whether global warming can be limited in order to lessen its impacts. In this sense, evidence of a decrease in the statistical polarization in greenhouse gas (GHG) emissions could encourage countries to establish a stronger multilateral climate change agreement. Based on the interregional and intraregional components of the multivariate generalised entropy measures (Maasoumi, 1986), Gigliarano and Mosler (2009) proposed to study the statistical polarization concept from a multivariate view. In this paper, we apply this approach to study the evolution of such phenomenon in the global distribution of the main GHGs. The empirical analysis has been carried out for the time period 1990-2011, considering an endogenous grouping of countries (Aghevli and Mehran, 1981; Davies and Shorrocks, 1989). Most of the statistical polarization indices showed a slightly increasing pattern that was similar regardless of the number of groups considered. Finally, some policy implications are commented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design.

PubMed

Lu, Tsui-Shan; Longnecker, Matthew P; Zhou, Haibo

2017-03-15

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data, and the general ODS design for a continuous response. While substantial work has been carried out for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome-dependent sampling (multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the multivariate-ODS or the estimator from a simple random sample with the same sample size. The multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of polychlorinated biphenyl exposure to hearing loss in children born to the Collaborative Perinatal Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

Quantitative investigation of inappropriate regression model construction and the importance of medical statistics experts in observational medical research: a cross-sectional study.

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

To investigate under what circumstances inappropriate use of 'multivariate analysis' is likely to occur and to identify the population that needs more support with medical statistics. The frequency of inappropriate regression model construction in multivariate analysis and related factors were investigated in observational medical research publications. The inappropriate algorithm of using only variables that were significant in univariate analysis was estimated to occur at 6.4% (95% CI 4.8% to 8.5%). This was observed in 1.1% of the publications with a medical statistics expert (hereinafter 'expert') as the first author, 3.5% if an expert was included as coauthor and in 12.2% if experts were not involved. In the publications where the number of cases was 50 or less and the study did not include experts, inappropriate algorithm usage was observed with a high proportion of 20.2%. The OR of the involvement of experts for this outcome was 0.28 (95% CI 0.15 to 0.53). A further, nation-level, analysis showed that the involvement of experts and the implementation of unfavourable multivariate analysis are associated at the nation-level analysis (R=-0.652). Based on the results of this study, the benefit of participation of medical statistics experts is obvious. Experts should be involved for proper confounding adjustment and interpretation of statistical models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Multivariate postprocessing techniques for probabilistic hydrological forecasting

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2016-04-01

Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power generation, Applied Energy, 96, 12-20, DOI: 10.1016/j.apenergy.2011.11.004. Schefzik, R., T. L. Thorarinsdottir, and T. Gneiting (2013), Uncertainty quantification in complex simulation models using ensemble copula coupling, Statistical Science, 28, 616-640, DOI: 10.1214/13-STS443.

Statistical description and transport in stochastic magnetic fields

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

Vanden Eijnden, E.; Balescu, R.

1996-03-01

The statistical description of particle motion in a stochastic magnetic field is presented. Starting form the stochastic Liouville equation (or, hybrid kinetic equation) associated with the equations of motion of a test particle, the probability distribution function of the system is obtained for various magnetic fields and collisional processes. The influence of these two ingredients on the statistics of the particle dynamics is stressed. In all cases, transport properties of the system are discussed. {copyright} {ital 1996 American Institute of Physics.}

Identification of Differential Item Functioning in Multiple-Group Settings: A Multivariate Outlier Detection Approach

ERIC Educational Resources Information Center

Magis, David; De Boeck, Paul

2011-01-01

We focus on the identification of differential item functioning (DIF) when more than two groups of examinees are considered. We propose to consider items as elements of a multivariate space, where DIF items are outlying elements. Following this approach, the situation of multiple groups is a quite natural case. A robust statistics technique is…

Uses of Multivariate Analytical Techniques in Online and Blended Business Education: An Assessment of Current Practice and Recommendations for Future Research

ERIC Educational Resources Information Center

Arbaugh, J. B.; Hwang, Alvin

2013-01-01

Seeking to assess the analytical rigor of empirical research in management education, this article reviews the use of multivariate statistical techniques in 85 studies of online and blended management education over the past decade and compares them with prescriptions offered by both the organization studies and educational research communities.…

On Some Multiple Decision Problems

DTIC Science & Technology

1976-08-01

parameter space. Some recent results in the area of subset selection formulation are Gnanadesikan and Gupta [28], Gupta and Studden [43], Gupta and...York, pp. 363-376. [27) Gnanadesikan , M. (1966). Some Selection and Ranking Procedures for Multivariate Normal Populations. Ph.D. Thesis. Dept. of...Statist., Purdue Univ., West Lafayette, Indiana 47907. [28) Gnanadesikan , M. and Gupta, S. S. (1970). Selection procedures for multivariate normal

Stress among Academic Staff and Students' Satisfaction of Their Performances in Payame Noor University of Miandoab

ERIC Educational Resources Information Center

Jabari, Kamran; Moradi Sheykhjan, Tohid

2015-01-01

Present study examined the relationship between stress among academic staff and students' satisfaction of their performances in Payame Noor University (PNU) of Miandoab City, Iran in 2014. The methodology of the research is descriptive and correlation that descriptive and inferential statistics were used to analyze the data. Statistical Society…

Quantitative Methods in Library and Information Science Literature: Descriptive vs. Inferential Statistics.

ERIC Educational Resources Information Center

Brattin, Barbara C.

Content analysis was performed on the top six core journals for 1990 in library and information science to determine the extent of research in the field. Articles (n=186) were examined for descriptive or inferential statistics and separately for the presence of mathematical models. Results show a marked (14%) increase in research for 1990,…

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

PubMed

Yang, James J; Williams, L Keoki; Buu, Anne

2017-08-24

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

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.

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

The RS4939827 polymorphism in the SMAD7 GENE and its association with Mediterranean diet in colorectal carcinogenesis.

PubMed

Alonso-Molero, Jéssica; González-Donquiles, Carmen; Palazuelos, Camilo; Fernández-Villa, Tania; Ramos, Elena; Pollán, Marina; Aragonés, Nuria; Llorca, Javier; Henar Alonso, M; Tardón, Adonina; Amiano, Pilar; Moleon, José Juan Jiménez; Pérez, Rosana Peiró; Capelo, Rocío; Molina, Antonio J; Acebo, Inés Gómez; Guevara, Marcela; Perez-Gomez, Beatriz; Lope, Virginia; Huerta, José María; Castaño-Vinyals, Gemma; Kogevinas, Manolis; Moreno, Victor; Martín, Vicente

2017-10-30

The objective of our investigation is to study the relationship between the rs4939827 SNP in the SMAD7 gene, Mediterranean diet pattern and the risk of colorectal cancer. We examined 1087 cases of colorectal cancer and 2409 population controls with available DNA samples from the MCC-Spain study, 2008-2012. Descriptive statistical analyses, and multivariate logistic mixed models were performed. The potential synergistic effect of rs4939827 and the Mediterranean diet pattern was evaluated with logistic regression in different strata of of adherence to the Mediterranean diet and the genotype. High adherence to Mediterrenean diet was statistically significantly associated with colorectal cancer risk. A decreased risk for CRC cancer was observed for the CC compared to the TT genotype (OR = 0.65 and 95% CI = 0.51-0.81) of the rs4939827 SNP Also, we could show an association between the Mediterranean diet pattern (protective factor) and rs4939827. Although the decreased risk for the CC genotype was slightly more pronounced in subjects with high adherence to Mediterrenean diet, there was no statistically significant synergistic effect between genotype CC and adherence to the Mediterranean dietary pattern factors. The SMAD7 gene and specifically the allele C could be protective for colorectal cancer. An independent protective association was also observed between high adherence Mediterranean diet pattern and CRC risk. Findings form this study indicate that high adherence to Mediterranean diet pattern has a protective role for CRC cancer probably involving the Tumor Growth Factor- β pathway in this cancer.

Epidemiology of Road Traffic Injury Fatalities among Car Users; A Study Based on Forensic Medicine Data in East Azerbaijan of Iran

PubMed Central

Sadeghi-Bazargani, Homayoun; Samadirad, Bahram; Shahedifar, Nasrin; Golestani, Mina

2018-01-01

Objective: To study the epidemiology of car user road traffic fatalities (CURTFs) during eight years, in East Azerbaijan, Iran. Methods: A total of 3051 CURTFs registered in East Azerbaijan forensic medicine organization database, Iran, during 2006-2014, were analyzed using Stata 13 statistical software package. Descriptive statistics (p<0.05) and inferential statistical methods such as Chi-squared test and multivariate logistic regression with p<0.1 were applied.               Results: Of the 7818 road traffic injury (RTI) deaths, 3051 (39%) were car users of whom 71% were male (mean age of 36.7±18.5 years). The majority of accident mechanisms were vehicle-vehicle crashes (63.95%), followed by rollover (26.24%). Crash causing vehicle fall increased the pre-hospital death likelihood by 2.34 times. The prominent trauma causing death was head trauma (in 62.5%). In assessing the role of type of counterpart vehicle on pre-hospital mortality, considering the other cars to be the reference group for comparison, deceased victims were 1.83 times more likely to die before hospital when the counterpart vehicle was a truck and 1.66 times more for buses. Conclusion: Decreasing the car users’ fatalities using appropriate strategies such as separating the roads for heavy and light vehicles and improving the injury related facilitation may be effective. Male drivers with low education could be prioritized for being trained. PMID:29719846

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.

Height for age z score and cognitive function are associated with Academic performance among school children aged 8-11 years old.

PubMed

Haile, Demewoz; Nigatu, Dabere; Gashaw, Ketema; Demelash, Habtamu

2016-01-01

Academic achievement of school age children can be affected by several factors such as nutritional status, demographics, and socioeconomic factors. Though evidence about the magnitude of malnutrition is well established in Ethiopia, there is a paucity of evidence about the association of nutritional status with academic performance among the nation's school age children. Hence, this study aimed to determine how nutritional status and cognitive function are associated with academic performance of school children in Goba town, South East Ethiopia. An institution based cross-sectional study was conducted among 131 school age students from primary schools in Goba town enrolled during the 2013/2014 academic year. The nutritional status of students was assessed by anthropometric measurement, while the cognitive assessment was measured by the Kaufman Assessment Battery for Children (KABC-II) and Ravens colored progressive matrices (Raven's CPM) tests. The academic performance of the school children was measured by collecting the preceding semester academic result from the school record. Descriptive statistics, bivariate and multivariable linear regression were used in the statistical analysis. This study found a statistically significant positive association between all cognitive test scores and average academic performance except for number recall (p = 0.12) and hand movements (p = 0.08). The correlation between all cognitive test scores and mathematics score was found positive and statistically significant (p < 0.05). In the multivariable linear regression model, better wealth index was significantly associated with higher mathematics score (ß = 0.63; 95 % CI: 0.12-0.74). Similarly a unit change in height for age z score resulted in 2.11 unit change in mathematics score (ß = 2.11; 95 % CI: 0.002-4.21). A single unit change of wealth index resulted 0.53 unit changes in average score of all academic subjects among school age children (ß = 0.53; 95 % CI: 0.11-0.95). A single unit change of age resulted 3.23 unit change in average score of all academic subjects among school age children (ß = 3.23; 95 % CI: 1.20-5.27). Nutritional status (height for age Z score) and wealth could be modifiable factors to improve academic performance of school age children. Moreover, interventions to improve nutrition for mothers and children may be an important contributor to academic success and national economic growth in Ethiopia. Further study with strong design and large sample size is needed.

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

Multivariate statistical analysis to investigate the subduction zone parameters favoring the occurrence of giant megathrust earthquakes

NASA Astrophysics Data System (ADS)

Brizzi, S.; Sandri, L.; Funiciello, F.; Corbi, F.; Piromallo, C.; Heuret, A.

2018-03-01

The observed maximum magnitude of subduction megathrust earthquakes is highly variable worldwide. One key question is which conditions, if any, favor the occurrence of giant earthquakes (Mw ≥ 8.5). Here we carry out a multivariate statistical study in order to investigate the factors affecting the maximum magnitude of subduction megathrust earthquakes. We find that the trench-parallel extent of subduction zones and the thickness of trench sediments provide the largest discriminating capability between subduction zones that have experienced giant earthquakes and those having significantly lower maximum magnitude. Monte Carlo simulations show that the observed spatial distribution of giant earthquakes cannot be explained by pure chance to a statistically significant level. We suggest that the combination of a long subduction zone with thick trench sediments likely promotes a great lateral rupture propagation, characteristic of almost all giant earthquakes.

Spatial Dynamics and Determinants of County-Level Education Expenditure in China

ERIC Educational Resources Information Center

Gu, Jiafeng

2012-01-01

In this paper, a multivariate spatial autoregressive model of local public education expenditure determination with autoregressive disturbance is developed and estimated. The existence of spatial interdependence is tested using Moran's I statistic and Lagrange multiplier test statistics for both the spatial error and spatial lag models. The full…

Establishing Benchmarks for Outcome Indicators: A Statistical Approach to Developing Performance Standards.

ERIC Educational Resources Information Center

Henry, Gary T.; And Others

1992-01-01

A statistical technique is presented for developing performance standards based on benchmark groups. The benchmark groups are selected using a multivariate technique that relies on a squared Euclidean distance method. For each observation unit (a school district in the example), a unique comparison group is selected. (SLD)

MULTIVARIATE STATISTICAL MODELS FOR EFFECTS OF PM AND COPOLLUTANTS IN A DAILY TIME SERIES EPIDEMIOLOGY STUDY

EPA Science Inventory

Most analyses of daily time series epidemiology data relate mortality or morbidity counts to PM and other air pollutants by means of single-outcome regression models using multiple predictors, without taking into account the complex statistical structure of the predictor variable...

Challenging Conventional Wisdom for Multivariate Statistical Models with Small Samples

ERIC Educational Resources Information Center

McNeish, Daniel

2017-01-01

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

The contribution of collective attack tactics in differentiating handball score efficiency.

PubMed

Rogulj, Nenad; Srhoj, Vatromir; Srhoj, Ljerka

2004-12-01

The prevalence of 19 elements of collective tactics in score efficient and score inefficient teams was analyzed in 90 First Croatian Handball League--Men games during the 1998-1999 season. Prediction variables were used to describe duration, continuity, system, organization and spatial direction of attacks. Analysis of the basic descriptive and distribution statistical parameters revealed normal distribution of all variables and possibility to use multivariate methods. Canonic discrimination analysis and analysis of variance showed the use of collective tactics elements on attacks to differ statistically significantly between the winning and losing teams. Counter-attacks and uninterrupted attacks predominate in winning teams. Other types of attacks such as long position attack, multiply interrupted attack, attack with one circle runner attack player/pivot, attack based on basic principles, attack based on group cooperation, attack based on independent action, attack based on group maneuvering, rightward directed attack and leftward directed attack predominate in losing teams. Winning teams were found to be clearly characterized by quick attacks against unorganized defense, whereas prolonged, interrupted position attacks against organized defense along with frequent and diverse tactical actions were characteristic of losing teams. The choice and frequency of using a particular tactical activity in position attack do not warrant score efficiency but usually are consequential to the limited anthropologic potential and low level of individual technical-tactical skills of the players in low-quality teams.

Predictors of certification in infection prevention and control among infection preventionists: APIC MegaSurvey findings.

PubMed

Kalp, Ericka L; Harris, Jeanette J; Zawistowski, Grace

2018-06-06

The 2015 APIC MegaSurvey was completed by 4,078 members to assess infection prevention practices. This study's purpose was to examine MegaSurvey results to relate infection preventionist (IP) certification status with demographic characteristics, organizational structure, compensation benefits, and practice and competency factors. Descriptive statistics were used to examine population characteristics and certification status. Bivariate logistic regression was performed to evaluate relationships between independent variables and certification status. Variables demonstrating statistical significance (P <.05) were included in multivariable logistic regression analyses. Forty-seven percent of survey respondents had their CIC. IPs were less likely certified if their educational attainment was less than a bachelor's degree, they were aged 18-45 years, they worked in rural facilities, they had <16 years' experience in health care before becoming an IP, and the percentage of job dedicated to infection prevention was <75%. However, certification was associated with CIC benefit paid fully by employer, self-rating as proficient and expert-advanced, and surveillance and epidemiologic investigation competency obtained via professional development and training. CIC attainment was associated with IP characteristics. Additional research should focus on identifying strategies to increase certification among noncertified IPs because CIC is a measure of proficiency that should be a goal for all IPs. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Role of gynecologists in reproductive education of adolescent girls in Hungary.

PubMed

Varga-Tóth, Andrea; Paulik, Edit

2015-05-01

The aim of this study was to assess whether the socioeconomic characteristics of adolescent girls, their knowledge about cervical cancer screening, and their sexual activity are associated with whether or not they have already visited a gynecologist. A self-administered questionnaire-based study was performed among secondary school girls (n = 589) who participated in professional education provided by a pediatric and adolescent gynecologist. The questionnaire comprised sociodemographic characteristics, sexual activity, knowledge on contraceptive methods, cervical screening and sources of their knowledge. Simple descriptive statistics, χ(2) and one-way-anova tests, multivariate logistic regression analysis and Pearson correlation were applied. All statistical analyses were carried out using spss 17.0 for Windows. A total of 50.3% of adolescent girls had already had a sexual contact. Half of the sexually active participants had already visited a gynecologist, and most of them did so due to some kind of complaint. The overall knowledge about cervical screening was quite low; higher knowledge was found among those having visited a gynecologist. Adolescent girls' knowledge on cervical screening was improved by previous visits to a gynecologist. The participation of an expert--a gynecologist--in a comprehensive sexual education program of teenage girls is of high importance in Hungary. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

Reporting quality of randomised controlled trials published in prosthodontic and implantology journals.

PubMed

Kloukos, D; Papageorgiou, S N; Doulis, I; Petridis, H; Pandis, N

2015-12-01

The purpose of this study was to examine the reporting quality of randomised controlled trials (RCTs) published in prosthodontic and implantology journals. Thirty issues of nine journals in prosthodontics and implant dentistry were searched for RCTs, covering the years 2005-2012: The Journal of Prosthetic Dentistry, Journal of Oral Rehabilitation, The International Journal of Prosthodontics, The International Journal of Periodontics & Restorative Dentistry, Clinical Oral Implants Research, Clinical Implant Dentistry & Related Research, The International Journal of Oral & Maxillofacial Implants, Implant Dentistry and Journal of Dentistry. The reporting quality was assessed using a modified Consolidated Standards of Reporting Trials (CONSORT) statement checklist. Data were analysed using descriptive statistics followed by univariable and multivariable examination of statistical associations (α = 0·05). A total of 147 RCTs were identified with a mean CONSORT score of 69·4 (s.d. = 9·7). Significant differences were found among journals with the Journal of Oral Rehabilitation achieving the highest score (80·6, s.d. = 5·5) followed by Clinical Oral Implants Research (73·7, s.d. = 8·3). Involvement of a statistician/methodologist was significantly associated with increased CONSORT scores. Overall, the reporting quality of RCTs in major prosthodontic and implantology journals requires improvement. This is of paramount importance considering that optimal reporting of RCTs is an important prerequisite for clinical decision-making. © 2015 John Wiley & Sons Ltd.

Domestic Violence Against Women Working in Four Educational Hospitals in Iran.

PubMed

Sheikhbardsiri, Hojat; Raeisi, Ahmadreza; Khademipour, Gholamreza

2017-07-01

Domestic violence is a serious threat to the health of women in the world and derives from several factors. Therefore, due to the importance of this issue, this study aimed to determine domestic violence against women in four educational hospitals in Iran as a Muslim country. The study employed a cross-sectional design and was conducted in four educational hospitals supervised by the Kerman University of Medical Sciences in 2016. Using a researcher-made questionnaire, we assessed factors associated with domestic violence in female employees using a census method ( N = 400). Data were analyzed using descriptive statistics including mean and SD and analytic statistics such as Kolmogorov-Smirnov, ANOVA, t test, and Pearson and multivariate regression tests using SPSS 16 and p ≤ .05. This study showed that most common types of violence against women are psychological/verbal (58%), physical (29.25%), and sexual (10%), respectively. There was a significant relationship between couples' age gap, forced marriage, husband addiction, income, and history of violence experienced by the husband with domestic violence against women. This study examines the basic prevalence of partner violence victimization among Iranian women who work in hospitals in southeast Iran. Findings suggest that national and local policies in Iran may need to examine factors that contribute to violence against women as well as focusing on how to reduce partner violence.

Sexual violence against female university students in Ethiopia.

PubMed

Adinew, Yohannes Mehretie; Hagos, Mihiret Abreham

2017-07-24

Though many women are suffering the consequences of sexual violence, only few victims speak out as it is sensitive and prone to stigma. This lack of data made it difficult to get full picture of the problem and design proper interventions. Thus, the aim of this study was to assess the prevalence and factors associated with sexual violence among female students of Wolaita Sodo University, south Ethiopia. Institution based cross-sectional study was conducted among 462 regular female Wolaita Sodo University students on April 7/2015. Participants were selected by simple random sampling. Data were collected by self-administered questionnaire. Data entry and analysis was done by EPI info and SPSS statistical packages respectively. Descriptive statistics were done. Moreover, bivariate and multivariate analyses were also carried out to identify predictors of sexual violence. The age of respondents ranged from 18 to 26 years. Lifetime sexual violence was found to be 45.4%. However, 36.1% and 24.4% of respondents reported experiencing sexual violence since entering university and in the current academic year respectively. Life time sexual violence was positively associated with witnessing inter-parental violence as a child, rural childhood residence, having regular boyfriend, alcohol consumption and having friends who drink regularly; while it was negatively associated with discussing sexual issues with parents. Sexual violence is a common phenomenon among the students. More detailed research has to be conducted to develop prevention and intervention strategies.

Psychosocial predictors of depression among older African American patients with cancer.

PubMed

Hamilton, Jill B; Deal, Allison M; Moore, Angelo D; Best, Nakia C; Galbraith, Kayoll V; Muss, Hyman

2013-07-01

To determine whether psychosocial factors predict depression among older African American patients with cancer. A descriptive correlational study. Outpatient oncology clinic of a National Cancer Institute-designated cancer center in the southeastern United States. African American patients with cancer aged 50-88 years. Fisher's exact and Wilcoxon rank-sum tests were used to evaluate differences between patients who were possibly depressed (Geriatric Depression Scale) or not. Multivariate linear regression statistics were used to identify the psychosocial factors that predicted higher depression scores. Education and gender were included as covariates. Religiosity, emotional support, collectivism, perceived stigma, and depression. Participants (N = 77) had a mean age of 61 years (SD = 8.4), and a majority were well-educated, insured, religiously affiliated, and currently in treatment. Participants who were in the lowest income category, not married, or male had higher depression scores. The multivariable model consisting of organized religion, emotional support, collectivism, education, and gender explained 52% (adjusted R2) of the variation in depression scores. Stigma became insignificant in the multivariable model. Psychosocial factors are important predictors of depression. Emotional support and organized religious activities may represent protective factors against depression, whereas collectivism may increase their risk. Nurses need to be particularly aware of the potential psychological strain for patients with collectivist values, experienced stigma, disruptions in church attendance, and lack of emotional support. In addition, the treatment plans for these patients should ensure that family members are knowledgeable about cancer, its treatment, and side effects so they are empowered to meet support needs. Among older African American patients with cancer, emotional support and reassurance from family and friends that they will not abandon them decreases the likelihood of depressive symptoms and minimizes the impact of stigmatizing responses, but the perception that the illness is placing a strain on the family increases the likelihood of such symptoms. Emotional support likely is a stronger predictor of depressive symptoms than religious service attendance.

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

PubMed

Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

2013-03-01

Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

A Semi-parametric Multivariate Gap-filling Model for Eddy Covariance Latent Heat Flux

NASA Astrophysics Data System (ADS)

Li, M.; Chen, Y.

2010-12-01

Quantitative descriptions of latent heat fluxes are important to study the water and energy exchanges between terrestrial ecosystems and the atmosphere. The eddy covariance approaches have been recognized as the most reliable technique for measuring surface fluxes over time scales ranging from hours to years. However, unfavorable micrometeorological conditions, instrument failures, and applicable measurement limitations may cause inevitable flux gaps in time series data. Development and application of suitable gap-filling techniques are crucial to estimate long term fluxes. In this study, a semi-parametric multivariate gap-filling model was developed to fill latent heat flux gaps for eddy covariance measurements. Our approach combines the advantages of a multivariate statistical analysis (principal component analysis, PCA) and a nonlinear interpolation technique (K-nearest-neighbors, KNN). The PCA method was first used to resolve the multicollinearity relationships among various hydrometeorological factors, such as radiation, soil moisture deficit, LAI, and wind speed. The KNN method was then applied as a nonlinear interpolation tool to estimate the flux gaps as the weighted sum latent heat fluxes with the K-nearest distances in the PCs’ domain. Two years, 2008 and 2009, of eddy covariance and hydrometeorological data from a subtropical mixed evergreen forest (the Lien-Hua-Chih Site) were collected to calibrate and validate the proposed approach with artificial gaps after standard QC/QA procedures. The optimal K values and weighting factors were determined by the maximum likelihood test. The results of gap-filled latent heat fluxes conclude that developed model successful preserving energy balances of daily, monthly, and yearly time scales. Annual amounts of evapotranspiration from this study forest were 747 mm and 708 mm for 2008 and 2009, respectively. Nocturnal evapotranspiration was estimated with filled gaps and results are comparable with other studies. Seasonal and daily variability of latent heat fluxes were also discussed.

[Monitoring method of extraction process for Schisandrae Chinensis Fructus based on near infrared spectroscopy and multivariate statistical process control].

PubMed

Xu, Min; Zhang, Lei; Yue, Hong-Shui; Pang, Hong-Wei; Ye, Zheng-Liang; Ding, Li

2017-10-01

To establish an on-line monitoring method for extraction process of Schisandrae Chinensis Fructus, the formula medicinal material of Yiqi Fumai lyophilized injection by combining near infrared spectroscopy with multi-variable data analysis technology. The multivariate statistical process control (MSPC) model was established based on 5 normal batches in production and 2 test batches were monitored by PC scores, DModX and Hotelling T2 control charts. The results showed that MSPC model had a good monitoring ability for the extraction process. The application of the MSPC model to actual production process could effectively achieve on-line monitoring for extraction process of Schisandrae Chinensis Fructus, and can reflect the change of material properties in the production process in real time. This established process monitoring method could provide reference for the application of process analysis technology in the process quality control of traditional Chinese medicine injections. Copyright© by the Chinese Pharmaceutical Association.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

75 FR 4323 - Additional Quantitative Fit-testing Protocols for the Respiratory Protection Standard

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-27

... respirators (500 and 1000 for protocols 1 and 2, respectively). However, OSHA could not evaluate the results... the values of these descriptive statistics for revised PortaCount[supreg] QNFT protocols 1 (at RFFs of 100 and 500) and 2 (at RFFs of 200 and 1000). Table 2--Descriptive Statistics for RFFs of 100 and 200...

Exploring Marine Corps Officer Quality: An Analysis of Promotion to Lieutenant Colonel

DTIC Science & Technology

2017-03-01

44 G. DESCRIPTIVE STATISTICS ................................................................44 1. Dependent...Variable Summary Statistics ...................................44 2. Performance...87 4. Further Research .........................................................................88 APPENDIX A. SUMMARY STATISTICS OF FITREP AND

The relationship between patients' perceptions of care quality and three factors: nursing staff job satisfaction, organizational characteristics and patient age.

PubMed

Kvist, Tarja; Voutilainen, Ari; Mäntynen, Raija; Vehviläinen-Julkunen, Katri

2014-10-18

The relationship between nurses' job satisfaction and their perceptions of quality of care has been examined in previous studies. There is little evidence, however, about relationships between the job satisfaction of nursing staff and quality of care perceived by the patients. The aim of this study was to analyze, how the job satisfaction of nursing staff, organizational characteristics (hospital and unit type), and patients' age relate to patients' perceptions of the quality of care. The study was cross-sectional and descriptive, based on a secondary analysis of survey data acquired during the At Safe study in Finland. The study included 98 units at four acute care hospitals between autumn 2008 and spring 2009. The participants were 1909 patients and 929 nursing staff. Patients' perceptions of quality of care were measured using the 42-item RHCS questionnaire. Job satisfaction of nursing staff was measured with the 37-item KUHJSS scale. Statistical analyses included descriptive statistics, principal component analysis, t-tests, analysis of variance, linear regression, and multivariate analysis of variance. Patients' perceptions of overall quality of care were positively related to general job satisfaction of nursing staff. Adequate numbers of staff appeared to be the clearest aspect affecting quality of care. Older patients were more satisfied with staff number than younger patients. Patients cared for in outpatient departments felt more respected than patients in wards, whereas patients in wards reported better care of basic needs (e.g., hygiene, food) than outpatients. The evaluation of resources by nursing staff is related to patients' perceptions of the adequacy of nursing staff levels in the unit. The results emphasize the importance of considering patients' perceptions of the quality of care and assessments by nurses of their job satisfaction at the hospital unit level when evaluating quality of care.

Statistics of the geomagnetic secular variation for the past 5Ma

NASA Technical Reports Server (NTRS)

Constable, C. G.; Parker, R. L.

1986-01-01

A new statistical model is proposed for the geomagnetic secular variation over the past 5Ma. Unlike previous models, the model makes use of statistical characteristics of the present day geomagnetic field. The spatial power spectrum of the non-dipole field is consistent with a white source near the core-mantle boundary with Gaussian distribution. After a suitable scaling, the spherical harmonic coefficients may be regarded as statistical samples from a single giant Gaussian process; this is the model of the non-dipole field. The model can be combined with an arbitrary statistical description of the dipole and probability density functions and cumulative distribution functions can be computed for declination and inclination that would be observed at any site on Earth's surface. Global paleomagnetic data spanning the past 5Ma are used to constrain the statistics of the dipole part of the field. A simple model is found to be consistent with the available data. An advantage of specifying the model in terms of the spherical harmonic coefficients is that it is a complete statistical description of the geomagnetic field, enabling us to test specific properties for a general description. Both intensity and directional data distributions may be tested to see if they satisfy the expected model distributions.

Statistics of the geomagnetic secular variation for the past 5 m.y

NASA Technical Reports Server (NTRS)

Constable, C. G.; Parker, R. L.

1988-01-01

A new statistical model is proposed for the geomagnetic secular variation over the past 5Ma. Unlike previous models, the model makes use of statistical characteristics of the present day geomagnetic field. The spatial power spectrum of the non-dipole field is consistent with a white source near the core-mantle boundary with Gaussian distribution. After a suitable scaling, the spherical harmonic coefficients may be regarded as statistical samples from a single giant Gaussian process; this is the model of the non-dipole field. The model can be combined with an arbitrary statistical description of the dipole and probability density functions and cumulative distribution functions can be computed for declination and inclination that would be observed at any site on Earth's surface. Global paleomagnetic data spanning the past 5Ma are used to constrain the statistics of the dipole part of the field. A simple model is found to be consistent with the available data. An advantage of specifying the model in terms of the spherical harmonic coefficients is that it is a complete statistical description of the geomagnetic field, enabling us to test specific properties for a general description. Both intensity and directional data distributions may be tested to see if they satisfy the expected model distributions.

Factors associated with Institutional delivery service utilization among mothers in Bahir Dar City administration, Amhara region: a community based cross sectional study

PubMed Central

2014-01-01

Background High maternal mortality is a continued challenge for the achievement of the fifth millennium development goal in Sub-Saharan African countries including Ethiopia. Although institutional delivery service utilization ensures safe birth and a key to reduce maternal mortality, interventions at the community and/or institutions were unsatisfactorily reduced maternal mortality. Institutional delivery service utilization is affected by the interaction of personal, socio-cultural, behavioral and institutional factors. Therefore this study was designed to assess factors associated with institutional delivery service use among mothers in Bahir Dar city administration. Methods A community based cross sectional study was conducted in Bahir Dar City administration Northwest of Addis Ababa, Ethiopia. Four hundred eighty four mothers were included in the study. Data were collected by trained female data collectors. Descriptive statistics, binary and multivariable logistic regression analyses were computed. Statistical significance was considered at p < 0.05 and the strength of statistical association was assessed by odds ratios (OR) with 95% confidence intervals. Result In this study, 78.8% of women gave birth to their current child at health institution. The multivariable logistic regression showed that, attending primary education (AOR = 4.7[95% CI:1.3-16.7], secondary education (AOR = 3.5[95% CI:1.1-10.7]), age at first marriage; first time marriage at 15–19 years (AOR = 5.4[95% CI:2.0-15.0]) and first time marriage at 20–24 years (AOR = 5.0[95% CI:1.5-16.8] and gestational age at first ANC visit (first trimester) (AOR = 5.3[1.3-22.2]) and second trimester (AOR = 2.8[95% CI:0.7-11.]) were independent factors affecting institutional delivery service utilization. Conclusion In this study, institutional delivery service utilization is optimal, urban mothers were more likely to practice institutional delivery. This study indicated that age at first marriage, educational status of the women and gestational age at first ANC visit are independent predictors of delivery service utilization. Hence, intensifying education for women and behavior change communication (BCC) interventions to increase early initiation and up-take of ANC service use in the first trimester and delaying marriage are recommended to promote institutional delivery service utilization. PMID:24629278

Knowledge of neonatal danger signs among mothers attending well baby clinic in Nakuru Central District, Kenya: cross sectional descriptive study.

PubMed

Kibaru, Elizabeth Gathoni; Otara, Amos Magembe

2016-10-25

Neonatal mortality has remained high in Kenya despite various efforts being applied to reduce this negative trend. Early detection of neonatal illness is an important step towards improving new born survival. Toward this end there is need for the mothers to be able to identify signs in neonates that signifies severe neonatal illnesses. The objective of the study was to determine the level of knowledge of mothers attending well baby clinics on postnatal neonatal danger signs and determine the associated factors. Cross sectional descriptive study. Purposive sampling of Health care facilities that provide antenatal, delivery and postnatal services were identified. In each of the selected health facility structured questionnaires were administered to mothers with children aged six weeks to nine months attending well baby clinics. Frequencies, Chi square and multivariate logistic regression were determined using the SPSS software (version 20). During the period of study 414 mothers attending well baby clinics were interviewed. Information on neonatal dangers was not provided to 237 (57.2%) of the postnatal mothers during their antenatal clinic attendance by the health care providers. Majority of mothers 350 (84.5%) identified less than three neonatal danger signs. Hotness of the body (fever) was the commonly recognized danger sign by 310 (74.9%) postnatal mothers. Out of 414 mothers 193 (46.6%), 166 (40.1%), 146 (35.3%) and 24 (5.8%) identified difficulty in breathing, poor sucking, jaundice and lethargy/unconsciousness as new born danger signs respectively. Only 46 (11.1%) and 40 (9.7%) identified convulsion and hypothermia as new born danger signs respectively. Education Level, PNC accompaniment by Spouse, Danger signs information to Mother, Explanation of MCH booklet by Care provider during ANC and Mother read MCH Booklet were factors positively associated with improved knowledge of neonatal danger sign. In multivariate logistic regression none of the factors tested were statistically significant in relation to level of knowledge. Knowledge of neonatal danger signs was low among mothers attending well baby clinic despite the information being available in the MCH booklets provided to the mothers during antenatal clinics.

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.

Defining the ecological hydrology of Taiwan Rivers using multivariate statistical methods

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Wu, Tzu-Ching; Tsai, Wen-Ping; Herricks, Edwin E.

2009-09-01

SummaryThe identification and verification of ecohydrologic flow indicators has found new support as the importance of ecological flow regimes is recognized in modern water resources management, particularly in river restoration and reservoir management. An ecohydrologic indicator system reflecting the unique characteristics of Taiwan's water resources and hydrology has been developed, the Taiwan ecohydrological indicator system (TEIS). A major challenge for the water resources community is using the TEIS to provide environmental flow rules that improve existing water resources management. This paper examines data from the extensive network of flow monitoring stations in Taiwan using TEIS statistics to define and refine environmental flow options in Taiwan. Multivariate statistical methods were used to examine TEIS statistics for 102 stations representing the geographic and land use diversity of Taiwan. The Pearson correlation coefficient showed high multicollinearity between the TEIS statistics. Watersheds were separated into upper and lower-watershed locations. An analysis of variance indicated significant differences between upstream, more natural, and downstream, more developed, locations in the same basin with hydrologic indicator redundancy in flow change and magnitude statistics. Issues of multicollinearity were examined using a Principal Component Analysis (PCA) with the first three components related to general flow and high/low flow statistics, frequency and time statistics, and quantity statistics. These principle components would explain about 85% of the total variation. A major conclusion is that managers must be aware of differences among basins, as well as differences within basins that will require careful selection of management procedures to achieve needed flow regimes.

Mathematical background and attitudes toward statistics in a sample of Spanish college students.

PubMed

Carmona, José; Martínez, Rafael J; Sánchez, Manuel

2005-08-01

To examine the relation of mathematical background and initial attitudes toward statistics of Spanish college students in social sciences the Survey of Attitudes Toward Statistics was given to 827 students. Multivariate analyses tested the effects of two indicators of mathematical background (amount of exposure and achievement in previous courses) on the four subscales. Analysis suggested grades in previous courses are more related to initial attitudes toward statistics than the number of mathematics courses taken. Mathematical background was related with students' affective responses to statistics but not with their valuing of statistics. Implications of possible research are discussed.

Multivariate Phylogenetic Comparative Methods: Evaluations, Comparisons, and Recommendations.

PubMed

Adams, Dean C; Collyer, Michael L

2018-01-01

Recent years have seen increased interest in phylogenetic comparative analyses of multivariate data sets, but to date the varied proposed approaches have not been extensively examined. Here we review the mathematical properties required of any multivariate method, and specifically evaluate existing multivariate phylogenetic comparative methods in this context. Phylogenetic comparative methods based on the full multivariate likelihood are robust to levels of covariation among trait dimensions and are insensitive to the orientation of the data set, but display increasing model misspecification as the number of trait dimensions increases. This is because the expected evolutionary covariance matrix (V) used in the likelihood calculations becomes more ill-conditioned as trait dimensionality increases, and as evolutionary models become more complex. Thus, these approaches are only appropriate for data sets with few traits and many species. Methods that summarize patterns across trait dimensions treated separately (e.g., SURFACE) incorrectly assume independence among trait dimensions, resulting in nearly a 100% model misspecification rate. Methods using pairwise composite likelihood are highly sensitive to levels of trait covariation, the orientation of the data set, and the number of trait dimensions. The consequences of these debilitating deficiencies are that a user can arrive at differing statistical conclusions, and therefore biological inferences, simply from a dataspace rotation, like principal component analysis. By contrast, algebraic generalizations of the standard phylogenetic comparative toolkit that use the trace of covariance matrices are insensitive to levels of trait covariation, the number of trait dimensions, and the orientation of the data set. Further, when appropriate permutation tests are used, these approaches display acceptable Type I error and statistical power. We conclude that methods summarizing information across trait dimensions, as well as pairwise composite likelihood methods should be avoided, whereas algebraic generalizations of the phylogenetic comparative toolkit provide a useful means of assessing macroevolutionary patterns in multivariate data. Finally, we discuss areas in which multivariate phylogenetic comparative methods are still in need of future development; namely highly multivariate Ornstein-Uhlenbeck models and approaches for multivariate evolutionary model comparisons. © The Author(s) 2017. Published by Oxford University Press on behalf of the Systematic Biology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Multidisciplinary Approach for Teaching Statistics and Probability

ERIC Educational Resources Information Center

Rao, C. Radhakrishna

1971-01-01

The author presents a syllabus for an introductory (first year after high school) course in statistics and probability and some methods of teaching statistical techniques. The description comes basically from the procedures used at the Indian Statistical Institute, Calcutta. (JG)

The Performance and Retention of Female Navy Officers with a Military Spouse

DTIC Science & Technology

2017-03-01

5 2. Female Officer Retention and Dual-Military Couples ...............7 3. Demographic Statistics ...23 III. DATA DESCRIPTION AND STATISTICS ...28 2. Independent Variables.................................................................31 C. SUMMARY STATISTICS

Characterizations of linear sufficient statistics

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Reoner, R.; Decell, H. P., Jr.

1977-01-01

A surjective bounded linear operator T from a Banach space X to a Banach space Y must be a sufficient statistic for a dominated family of probability measures defined on the Borel sets of X. These results were applied, so that they characterize linear sufficient statistics for families of the exponential type, including as special cases the Wishart and multivariate normal distributions. The latter result was used to establish precisely which procedures for sampling from a normal population had the property that the sample mean was a sufficient statistic.

Feasibility Study on the Use of On-line Multivariate Statistical Process Control for Safeguards Applications in Natural Uranium Conversion Plants

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

Ladd-Lively, Jennifer L

2014-01-01

The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component inmore » the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.« less

Integrated environmental monitoring and multivariate data analysis-A case study.

PubMed

Eide, Ingvar; Westad, Frank; Nilssen, Ingunn; de Freitas, Felipe Sales; Dos Santos, Natalia Gomes; Dos Santos, Francisco; Cabral, Marcelo Montenegro; Bicego, Marcia Caruso; Figueira, Rubens; Johnsen, Ståle

2017-03-01

The present article describes integration of environmental monitoring and discharge data and interpretation using multivariate statistics, principal component analysis (PCA), and partial least squares (PLS) regression. The monitoring was carried out at the Peregrino oil field off the coast of Brazil. One sensor platform and 3 sediment traps were placed on the seabed. The sensors measured current speed and direction, turbidity, temperature, and conductivity. The sediment trap samples were used to determine suspended particulate matter that was characterized with respect to a number of chemical parameters (26 alkanes, 16 PAHs, N, C, calcium carbonate, and Ba). Data on discharges of drill cuttings and water-based drilling fluid were provided on a daily basis. The monitoring was carried out during 7 campaigns from June 2010 to October 2012, each lasting 2 to 3 months due to the capacity of the sediment traps. The data from the campaigns were preprocessed, combined, and interpreted using multivariate statistics. No systematic difference could be observed between campaigns or traps despite the fact that the first campaign was carried out before drilling, and 1 of 3 sediment traps was located in an area not expected to be influenced by the discharges. There was a strong covariation between suspended particulate matter and total N and organic C suggesting that the majority of the sediment samples had a natural and biogenic origin. Furthermore, the multivariate regression showed no correlation between discharges of drill cuttings and sediment trap or turbidity data taking current speed and direction into consideration. Because of this lack of correlation with discharges from the drilling location, a more detailed evaluation of chemical indicators providing information about origin was carried out in addition to numerical modeling of dispersion and deposition. The chemical indicators and the modeling of dispersion and deposition support the conclusions from the multivariate statistics. Integr Environ Assess Manag 2017;13:387-395. © 2016 SETAC. © 2016 SETAC.

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

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.

Revision of Gymnotus (Gymnotiformes: Gymnotidae) from the Upper Madeira Basin of Bolivia and Peru, with descriptions of two new species.

PubMed

Craig, Jack M; Correa-roldÁn, Vanessa; Ortega, HernÁn; Crampton, William G R; Albert, James S

2018-04-20

Banded Knifefishes (Gymnotus, Gymnotidae) comprise the most species-rich genus of Neotropical electric fishes, with 41 species currently described from throughout the humid Neotropics, from Mexico to Argentina. Despite substantial alpha-taxonomic work in recent years, the diversity of Gymnotus in some regions remains poorly understood. Here we describe the Gymnotus fauna of the Upper Madeira basin of Bolivia and Peru from examination of more than 240 adult specimens. Species are delimited and described using body proportions (traditional morphometrics), fin-ray, squamation and laterosensory-pore counts (meristics), quantitative shape differences (geometric morphometrics), osteological traits, and color patterns. Comparisons of standardized linear measures as well as multivariate statistical methods validate the presence in the Upper Madeira basin of three previously described species, two with wide-spread geographic distributions throughout Greater Amazonia (G. carapo and G. coropinae), and one (G. chaviro) endemic to southwestern Amazonia. We also diagnose and describe two new species that are endemic to the Upper Madeira basin: G. eyra n. sp., morphologically most similar to G. mamiraua from lowland Amazonia, and G. riberalta n. sp., morphologically most similar to G. pantanal from the Paraguay-Paraná basin. The five Gymnotus species from the Upper Madeira basin are not monophyletic, each species being more closely related to a different species from another region; i.e. the Gymnotus species from the Upper Madeira represents a polyphyletic assemblage. These descriptions to 43 the number of valid Gymnotus species.

[The relationship between adolescent body size and health promoting behavior and biochemical indicator factors].

PubMed

Chen, Hsiu-Chih; Chen, Hsing-Mei; Chen, Min-Li; Chiang, Chih-Ming; Chen, Mei-Yen

2012-06-01

Tainan City has the third highest prevalence of junior high school student obesity of all administrative districts in Taiwan. School nurses play an important role in promoting student health. Understanding the factors that significantly impact student weight is critical to designing effective student health promotion programs. This study explored the relationships between health promotion behavior and serum biomarker variables and body size. Researchers used a cross-sectional descriptive study design and stratified cluster random sampling. Subjects were 7th graders who received an in-school health checkup with blood test at 41 public junior high schools in Tainan City between July 2010 and May 2011. Research instruments included the adolescent health promotion (AHP) scale, serum biochemical profile and BMI (body mass index). Obtained data were analyzed using descriptive and inferential statistics. Of the 726 students who participated in this study, 22.2% were underweight and 23.8% were overweight or obese. Higher AHP scores correlated with better biomarkers and body size. Multivariate analysis found factors that increased the risk of being overweight included: being male, having a father with a relatively low level of education, playing video games frequently, and doing little or no exercise (odds ratio = 1.93, 1.75, 1.07, 1.04, respectively). Participants with relatively healthy behaviors had better biomarkers and a lower risk of being overweight. Findings can support the development of evidence-based school programs to promote student health.

The Effect of Hospital Service Quality on Patient's Trust.

PubMed

Zarei, Ehsan; Daneshkohan, Abbas; Khabiri, Roghayeh; Arab, Mohammad

2015-01-01

The trust is meant the belief of the patient to the practitioner or the hospital based on the concept that the care provider seeks the best for the patient and will provide the suitable care and treatment for him/her. One of the main determinants of patient's trust is the service quality. This study aimed to examine the effect of quality of services provided in private hospitals on the patient's trust. In this descriptive cross-sectional study, 969 patients were selected using the consecutive method from eight private general hospitals of Tehran, Iran, in 2010. Data were collected through a questionnaire containing 20 items (14 items for quality, 6 items for trust) and its validity and reliability were confirmed. Data were analyzed using descriptive statistics and multivariate regression. The mean score of patients' perception of trust was 3.80 and 4.01 for service quality. Approximately 38% of the variance in patient trust was explained by service quality dimensions. Quality of interaction and process (P < 0.001) were the strongest factors in predicting patient's trust, but the quality of the environment had no significant effect on the patients' degree of trust. The interaction quality and process quality were the key determinants of patient's trust in the private hospitals of Tehran. To enhance the patients' trust, quality improvement efforts should focus on service delivery aspects such as scheduling, timely and accurate doing of the service, and strengthening the interpersonal aspects of care and communication skills of doctors, nurses and staff.

Back to basics: an introduction to statistics.

PubMed

Halfens, R J G; Meijers, J M M

2013-05-01

In the second in the series, Professor Ruud Halfens and Dr Judith Meijers give an overview of statistics, both descriptive and inferential. They describe the first principles of statistics, including some relevant inferential tests.

Students' attitudes towards learning statistics

NASA Astrophysics Data System (ADS)

Ghulami, Hassan Rahnaward; Hamid, Mohd Rashid Ab; Zakaria, Roslinazairimah

2015-05-01

Positive attitude towards learning is vital in order to master the core content of the subject matters under study. This is unexceptional in learning statistics course especially at the university level. Therefore, this study investigates the students' attitude towards learning statistics. Six variables or constructs have been identified such as affect, cognitive competence, value, difficulty, interest, and effort. The instrument used for the study is questionnaire that was adopted and adapted from the reliable instrument of Survey of Attitudes towards Statistics(SATS©). This study is conducted to engineering undergraduate students in one of the university in the East Coast of Malaysia. The respondents consist of students who were taking the applied statistics course from different faculties. The results are analysed in terms of descriptive analysis and it contributes to the descriptive understanding of students' attitude towards the teaching and learning process of statistics.

Creativity, Bipolar Disorder Vulnerability and Psychological Well-Being: A Preliminary Study

ERIC Educational Resources Information Center

Gostoli, Sara; Cerini, Veronica; Piolanti, Antonio; Rafanelli, Chiara

2017-01-01

The aim of this research was to investigate the relationships between creativity, subclinical bipolar disorder symptomatology, and psychological well-being. The study method was of descriptive, correlational type. Significant tests were performed using multivariate regression analysis. Students of the 4th grade of 6 different Italian colleges…

The Therapeutic Alliance: Clients' Categorization of Client-Identified Factors

ERIC Educational Resources Information Center

Simpson, Arlene J.; Bedi, Robinder P.

2012-01-01

Clients' perspectives on the therapeutic alliance were examined using written descriptions of factors that clients believed to be helpful in developing a strong alliance. Fifty participants sorted previously collected statements into thematically similar piles and then gave each set of statements a title. Multivariate concept mapping statistical…

Self-Esteem, Study Habits and Academic Performance among University Students

ERIC Educational Resources Information Center

Chilca Alva, Manuel L.

2017-01-01

This study was intended to establish whether self-esteem and study habits correlate with academic performance among university students. Research conducted was descriptive observational, multivariate or cross-sectional factorial in nature. The study population consisted of 196 students enrolled in a Basic Mathematics 1 class at the School of…

Students' Conceptions of the Nature of Science: Perspectives from Canadian and Korean Middle School Students

NASA Astrophysics Data System (ADS)

Park, Hyeran; Nielsen, Wendy; Woodruff, Earl

2014-05-01

This study examined and compared students' understanding of nature of science (NOS) with 521 Grade 8 Canadian and Korean students using a mixed methods approach. The concepts of NOS were measured using a survey that had both quantitative and qualitative elements. Descriptive statistics and one-way multivariate analysis of variances examined the quantitative data while a conceptually clustered matrix classified the open-ended responses. The country effect could explain 3-12 % of the variances of subjectivity, empirical testability and diverse methods, but it was not significant for the concepts of tentativeness and socio-cultural embeddedness of science. The open-ended responses showed that students believed scientific theories change due to errors or discoveries. Students regarded empirical evidence as undeniable and objective although they acknowledged experiments depend on theories or scientists' knowledge. The open responses revealed that national situations and curriculum content affected their views. For our future democratic citizens to gain scientific literacy, science curricula should include currently acknowledged NOS concepts and should be situated within societal and cultural perspectives.

Data on cardiac defects, morbidity and mortality in patients affected by RASopathies. CARNET study results.

PubMed

Calcagni, Giulio; Limongelli, Giuseppe; D'Ambrosio, Angelo; Gesualdo, Francesco; Digilio, Maria Cristina; Baban, Anwar; Albanese, Sonia B; Versacci, Paolo; De Luca, Enrica; Ferrero, Giovanni B; Baldassarre, Giuseppina; Agnoletti, Gabriella; Banaudi, Elena; Marek, Jan; Kaski, Juan P; Tuo, Giulia; Russo, Maria Giovanna; Pacileo, Giuseppe; Milanesi, Ornella; Messina, Daniela; Marasini, Maurizio; Cairello, Francesca; Formigari, Roberto; Brighenti, Maurizio; Dallapiccola, Bruno; Tartaglia, Marco; Marino, Bruno

2018-02-01

A comprehensive description of morbidity and mortality in patients affected by mutations in genes encoding for signal transducers of the RAS-MAPK cascade (RASopathies) was performed in our study recently published in the International Journal of Cardiology. Seven European cardiac centres participating to the CArdiac Rasopathy NETwork (CARNET), collaborated in this multicentric, observational, retrospective data analysis and collection. In this study, clinical records of 371 patients with confirmed molecular diagnosis of RASopathy were reviewed. Cardiac defects, crude mortality, survival rate of patients with 1) hypertrophic cardiomyopathy (HCM) and age <2 years or young adults; 2) individuals with Noonan syndrome and pulmonary stenosis carrying PTPN11 mutations; 3) biventricular obstruction and PTPN11 mutations; 4) Costello syndrome or cardiofaciocutaneous syndrome were analysed. Mortality was described as crude mortality, cumulative survival and restricted estimated mean survival. In particular, with this Data In Brief (DIB) paper, the authors aim to report specific statistic highlights of the multivariable regression analysis that was used to assess the impact of mutated genes on number of interventions and overall prognosis.

Organizational commitment and job satisfaction among nurses in Serbia: a factor analysis.

PubMed

Veličković, Vladica M; Višnjić, Aleksandar; Jović, Slađana; Radulović, Olivera; Šargić, Čedomir; Mihajlović, Jovan; Mladenović, Jelena

2014-01-01

One of the basic prerequisites of efficient organizational management in health institutions is certainly monitoring and measuring satisfaction of employees and their commitment to the health institution in which they work. The aim of this article was to identify and test factors that may have a predictive effect on job satisfaction and organizational commitment. We conducted a cross-sectional study that included 1,337 nurses from Serbia. Data were analyzed by using exploratory factor analysis, multivariate regressions, and descriptive statistics. The study identified three major factors of organizational commitment: affective commitment, disloyalty, and continuance commitment. The most important predictors of these factors were positive professional identification, extrinsic job satisfaction, and intrinsic job satisfaction (p < .0001). Predictors significantly affecting both job satisfaction and organizational commitment were identified as well; the most important of which was positive professional identification (p < .0001). This study identified the main factors affecting job satisfaction and organizational commitment of nurses, which formed a good basis for the creation of organizational management policy and human resource management policy in health institutions in Serbia. Copyright © 2014 Elsevier Inc. All rights reserved.

Jaggery: an avoidable cause of severe, deadly pediatric burns.

PubMed

Light, T D; Latenser, B A; Heinle, J A; Stolpen, M S; Quinn, K A; Ravindran, V; Chacko, J

2009-05-01

Jaggery is the non-industrial refinement of sugar cane into a sugar product. Sugar cane cultivation, harvest and refinement are central aspects of rural Indian life. We present a retrospective review of pediatric burns at a single institution in Southern India, drawing special attention to scald burns incurred when young children fall into the cauldron of boiling jaggery. Descriptive statistics comparing children burned by jaggery and children burned by other mechanisms were performed. Multivariable logistic regression including burn size and mechanism of burn (jaggery and non-jaggery) was performed to determine the increased risk of death when burned by jaggery. Children burned by jaggery immersions are older, more likely male, and have larger burns. They have longer hospital stays, more operations, and are more likely to die. When controlling for age, gender, size of burn, and mechanism, jaggery exposure was associated with a higher mortality. Jaggery burns are deadly, devastating burns which could be prevented. While jaggery and sugar cane production can lead to economic independence for rural Indian villages, the cost it exacts from burns and death to the youngest and most vulnerable children must be addressed and prevented.

Interpersonal violence, circumstances of aggressions and patterns of maxillofacial injuries in the metropolitan area of Campina Grande, State of Paraíba, Brazil (2008-2011).

PubMed

Bernardino, Ítalo Macedo; Barbosa, Kevan Guilherme Nóbrega; Nóbrega, Lorena Marques; Cavalcante, Gigliana Maria Sobral; Ferreira, Efigenia Ferreira E; d'Ávila, Sérgio

2017-09-01

The aim of this study was to determine the circumstances of aggressions and patterns of maxillofacial injuries among victims of interpersonal violence. This was a cross-sectional and exploratory study conducted from the analysis of 7,132 medical-legal and social records of interpersonal violence victims seen in a Forensic Medicine and Dentistry Center. Descriptive and multivariate statistics were performed using Multiple Correspondence Analysis. Three groups with different victimization profiles were identified. The first group was mainly composed of men of different age groups, victims of community violence that resulted in facial bones or dentoalveolar fracture. The second group was mainly composed of adolescents (10-19 years) of both sexes, victims of interpersonal violence and without specific pattern of injuries. The third group was composed of adult women (≥ 20 years) victims of domestic violence that resulted in injuries of soft tissues of face or other body regions. The results suggest that sociodemographic and circumstantial characteristics are important factors in victimization by maxillofacial injuries and interpersonal violence.

Exploring HIV-testing intentions in young Asian/Pacific Islander (API) women as it relates to acculturation, theory of gender and power (TGP), and the AIDS risk reduction model (ARRM).

PubMed

Salud, Margaret C; Marshak, Helen Hopp; Natto, Zuhair S; Montgomery, Susanne

2014-01-01

While HIV rates are low for Asian/Pacific Islanders (APIs), they have been increasing, especially for API women in the USA. We conducted a cross-sectional study with 299 young API women (18-24 years old) in the Inland Empire region of Southern California to better understand their intention for HIV testing and their perceptions about HIV/AIDS. Data analyses included descriptive statistics, bivariate exploration for model building and multivariate analyses to determine variables associated with HIV-testing intentions. Results suggest that more lifetime sexual partners, greater perceived gender susceptibility, higher HIV/AIDS knowledge, sexually active, more positive attitudes about HIV testing and higher self-perceptions/experiences related to risk contribute to stronger intentions for HIV testing in young API women. Findings from this study will contribute to the limited literature on HIV/AIDS in API women and provide information that can be used for developing and implementing culturally appropriate programs that encourage HIV prevention and testing in this population.

Exploring HIV-testing intentions in young Asian/Pacific Islander (API) women as it relates to acculturation, theory of gender and power (TGP), and the AIDS risk reduction model (ARRM)

PubMed Central

Salud, Margaret C.; Marshak, Helen Hopp; Natto, Zuhair S.; Montgomery, Susanne

2015-01-01

While HIV rates are low for Asian/Pacific Islanders (APIs), they have been increasing, especially for API women in the USA. We conducted a cross-sectional study with 299 young API women (18–24 years old) in the Inland Empire region of Southern California to better understand their intention for HIV testing and their perceptions about HIV/AIDS. Data analyses included descriptive statistics, bivariate exploration for model building and multivariate analyses to determine variables associated with HIV-testing intentions. Results suggest that more lifetime sexual partners, greater perceived gender susceptibility, higher HIV/AIDS knowledge, sexually active, more positive attitudes about HIV testing and higher self-perceptions/experiences related to risk contribute to stronger intentions for HIV testing in young API women. Findings from this study will contribute to the limited literature on HIV/AIDS in API women and provide information that can be used for developing and implementing culturally appropriate programs that encourage HIV prevention and testing in this population. PMID:24111859

[Investigation of metabolites of Triptergium wilfordii on liver toxicity by LC-MS].

PubMed

Zhao, Xiao-mei; Liu, Xin-ying; Xu, Chang; Ye, Tao; Jin, Cheng; Zhao, Kui-jun; Ma, Zhi-jie; Xiao, Xiao-he

2015-10-01

In this paper, biomarkers of liver toxicity of Triptergium wilfordii based on metabolomics was screened, and mechanism of liver toxicity was explored to provide a reference for the clinical diagnosis for liver toxicity of Triptergium wilfordii. MS method was carried on the analysis to metabolic fingerprint spectrum between treatment group and control group. The potential biomarkers were compared and screened using the multivariate statistical methods. As well, metabolic pathway would be detailed description. Combined with PCA and OPLS-DA pattern recognition analysis, 20 metabolites were selected which showed large differences between model group and blank group (VIP > 1.0). Seven possible endogenous biomarkers were analyzed and identified. They were 6-phosphate glucosamine, lysophospholipid, tryptophan, guanidine acetic acid, 3-indole propionic acid, cortisone, and ubiquinone. The level changes of above metabolites indicated that the metabolism pathways of amino acid, glucose, phospholipid and hormone were disordered. It is speculated that liver damage of T. wilfordii may be associated with the abnormal energy metabolism in citric acid cycle, amino acid metabolism in urea cycle, and glucose metabolism. It will be helpful to further research liver toxicity ingredients of Triptergium wilfordii.

Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties

NASA Astrophysics Data System (ADS)

Robotham, A. S. G.; Obreschkow, D.

2015-09-01

Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimensional data points can be described by a (D - 1)-dimensional plane with intrinsic scatter, we derive the general likelihood function to be maximised to recover the best fitting model. Alongside the mathematical description, we also release the hyper-fit package for the R statistical language (http://github.com/asgr/hyper.fit) and a user-friendly web interface for online fitting (http://hyperfit.icrar.org). The hyper-fit package offers access to a large number of fitting routines, includes visualisation tools, and is fully documented in an extensive user manual. Most of the hyper-fit functionality is accessible via the web interface. In this paper, we include applications to toy examples and to real astronomical data from the literature: the mass-size, Tully-Fisher, Fundamental Plane, and mass-spin-morphology relations. In most cases, the hyper-fit solutions are in good agreement with published values, but uncover more information regarding the fitted model.

Substance abuse among migrant workers of Thai-Laos border, Thailand.

PubMed

Jaichuang, Siriluk; Ratanasiri, Amornrat; Kanato, Manop

2012-09-01

Study the impact of substance abuse among migrant workers along the Thai-Laos border region in Nakhon Phanom Province. The target population included migrant workers aged 15 years and over and were selected using the snowball technique. Data were collected from 300 migrant workers and in-depth interviews and focus group discussion were carried out. Data analysis used content analysis, descriptive statistics, and multivariate logistic regression. Fifty-five point seven percent of migrant workers used stimulants namely tobacco, energy drinks, coffee, and methamphetamine. Males were at greater risk for substance abuse than females (AOR 16.03; 95% CI 8.43-30.45) and those who received news and information from community radios and news broadcasting towers were at more risk than other media (AOR 5.38; 95% CI 2.88-10.05). The impact of substance abuse were found to be chronic cough, moodiness, lack of interest in food, headache, wakefulness, sleeplessness, tremor heart palpitation, and accidents. Health promotion strategy must be implemented to minimize the harm. Motivating behavioral modification while keeping in mind the lifestyle, work, and environment of these people could help.

Doula care, birth outcomes, and costs among Medicaid beneficiaries.

PubMed

Kozhimannil, Katy Backes; Hardeman, Rachel R; Attanasio, Laura B; Blauer-Peterson, Cori; O'Brien, Michelle

2013-04-01

We compared childbirth-related outcomes for Medicaid recipients who received prenatal education and childbirth support from trained doulas with outcomes from a national sample of similar women and estimated potential cost savings. We calculated descriptive statistics for Medicaid-funded births nationally (from the 2009 Nationwide Inpatient Sample; n = 279,008) and births supported by doula care (n = 1079) in Minneapolis, Minnesota, in 2010 to 2012; used multivariate regression to estimate impacts of doula care; and modeled potential cost savings associated with reductions in cesarean delivery for doula-supported births. The cesarean rate was 22.3% among doula-supported births and 31.5% among Medicaid beneficiaries nationally. The corresponding preterm birth rates were 6.1% and 7.3%, respectively. After control for clinical and sociodemographic factors, odds of cesarean delivery were 40.9% lower for doula-supported births (adjusted odds ratio = 0.59; P < .001). Potential cost savings to Medicaid programs associated with such cesarean rate reductions are substantial but depend on states' reimbursement rates, birth volume, and current cesarean rates. State Medicaid programs should consider offering coverage for birth doulas to realize potential cost savings associated with reduced cesarean rates.

Breast Cancer and Mammography Screening: Knowledge, Beliefs and Predictors for Asian Immigrant Women Attending a Specialized Clinic in British Columbia, Canada.

PubMed

Hippman, Catriona; Moshrefzadeh, Arezu; Lohn, Zoe; Hodgson, Zoë G; Dewar, Kathryn; Lam, Melanie; Albert, Arianne Y K; Kwong, Juliet

2016-12-01

Screening mammography (MMG) reduces breast cancer mortality; however, Asian immigrant women underutilize MMG. The Asian Women's Health Clinic (AWHC) was established to promote women's cancer screening amongst this population. This study evaluated the rate, and predictors, of MMG amongst women attending the AWHC. Women (N = 98) attending the AWHC completed a questionnaire. Descriptive statistics and multivariable logistic regression evaluated rate and predictors of MMG. Most participants (87 %, n = 85) reported having had a mammogram. Significant MMG predictors were: lower perceived MMG barriers [lifetime: OR (CI) 1.19 (1.01-1.49); past 2 years: OR (CI) 1.11 (1.01-1.25)], and knowing someone with breast cancer [past year: OR (CI) 3.42 (1.25-9.85); past 2 years: OR (CI) 4.91 (1.32-2.13)]. Even amongst women using preventive medicine, 13 % report never having had a mammogram. More research is needed into innovative interventions, e.g. the AWHC, and breast cancer-related outcomes amongst Asian immigrant women.

The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

PubMed

Warton, David I; Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

The PIT-trap—A “model-free” bootstrap procedure for inference about regression models with discrete, multivariate responses

PubMed Central

Thibaut, Loïc; Wang, Yi Alice

2017-01-01

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)—common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of “model-free bootstrap”, adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods. PMID:28738071

Multivariate pattern dependence

PubMed Central

Saxe, Rebecca

2017-01-01

When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD): a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS) and to the fusiform face area (FFA), using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity. PMID:29155809

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

Statistical Knowledge for Teaching: Exploring it in the Classroom

ERIC Educational Resources Information Center

Burgess, Tim

2009-01-01

This paper first reports on the methodology of a study of teacher knowledge for statistics, conducted in a classroom at the primary school level. The methodology included videotaping of a sequence of lessons that involved students in investigating multivariate data sets, followed up by audiotaped interviews with each teacher. These stimulated…

Performance of the S - [chi][squared] Statistic for Full-Information Bifactor Models

ERIC Educational Resources Information Center

Li, Ying; Rupp, Andre A.

2011-01-01

This study investigated the Type I error rate and power of the multivariate extension of the S - [chi][squared] statistic using unidimensional and multidimensional item response theory (UIRT and MIRT, respectively) models as well as full-information bifactor (FI-bifactor) models through simulation. Manipulated factors included test length, sample…

Exploring the Replicability of a Study's Results: Bootstrap Statistics for the Multivariate Case.

ERIC Educational Resources Information Center

Thompson, Bruce

Conventional statistical significance tests do not inform the researcher regarding the likelihood that results will replicate. One strategy for evaluating result replication is to use a "bootstrap" resampling of a study's data so that the stability of results across numerous configurations of the subjects can be explored. This paper…

Spatial Statistical Model and Optimal Survey Design for Rapid Geophysical Characterization of UXO Sites

DTIC Science & Technology

2003-07-01

4, Gnanadesikan , 1977). An entity whose measured features fall into one of the regions is classified accordingly. For the approaches we discuss here... Gnanadesikan , R. 1977. Methods for Statistical Data Analysis of Multivariate Observations. John Wiley & Sons, New York. Hassig, N. L., O’Brien, R. F

Evaluation of statistical protocols for quality control of ecosystem carbon dioxide fluxes

Treesearch

Jorge F. Perez-Quezada; Nicanor Z. Saliendra; William E. Emmerich; Emilio A. Laca

2007-01-01

The process of quality control of micrometeorological and carbon dioxide (CO2) flux data can be subjective and may lack repeatability, which would undermine the results of many studies. Multivariate statistical methods and time series analysis were used together and independently to detect and replace outliers in CO2 flux...

Conceptual and statistical problems associated with the use of diversity indices in ecology.

PubMed

Barrantes, Gilbert; Sandoval, Luis

2009-09-01

Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.

Texture as a basis for acoustic classification of substrate in the nearshore region

NASA Astrophysics Data System (ADS)

Dennison, A.; Wattrus, N. J.

2016-12-01

Segmentation and classification of substrate type from two locations in Lake Superior, are predicted using multivariate statistical processing of textural measures derived from shallow-water, high-resolution multibeam bathymetric data. During a multibeam sonar survey, both bathymetric and backscatter data are collected. It is well documented that the statistical characteristic of a sonar backscatter mosaic is dependent on substrate type. While classifying the bottom-type on the basis on backscatter alone can accurately predict and map bottom-type, it lacks the ability to resolve and capture fine textural details, an important factor in many habitat mapping studies. Statistical processing can capture the pertinent details about the bottom-type that are rich in textural information. Further multivariate statistical processing can then isolate characteristic features, and provide the basis for an accurate classification scheme. Preliminary results from an analysis of bathymetric data and ground-truth samples collected from the Amnicon River, Superior, Wisconsin, and the Lester River, Duluth, Minnesota, demonstrate the ability to process and develop a novel classification scheme of the bottom type in two geomorphologically distinct areas.

Student's Conceptions in Statistical Graph's Interpretation

ERIC Educational Resources Information Center

Kukliansky, Ida

2016-01-01

Histograms, box plots and cumulative distribution graphs are popular graphic representations for statistical distributions. The main research question that this study focuses on is how college students deal with interpretation of these statistical graphs when translating graphical representations into analytical concepts in descriptive statistics.…

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

The intervals method: a new approach to analyse finite element outputs using multivariate statistics

PubMed Central

De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep

2017-01-01

Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107

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.

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.

Burnout and Alcohol Abuse/Dependence Among U.S. Medical Students.

PubMed

Jackson, Eric R; Shanafelt, Tait D; Hasan, Omar; Satele, Daniel V; Dyrbye, Liselotte N

2016-09-01

To explore the relationship between alcohol abuse/dependence with burnout and other forms of distress among a national cohort of medical students. In 2012, the authors completed a national survey of medical students from the American Medical Association's Physician Masterfile containing validated items assessing alcohol abuse/dependence, burnout, depression, suicidality, quality of life (QOL), and fatigue. Descriptive and comparative statistical analyses were computed, including chi-square and multivariate logistic regression, to determine relationships between variables. Of the 12,500 students, 4,402 (35.2%) responded. Of these, 1,411 (32.4%) met diagnostic criteria for alcohol abuse/dependence. Students who were burned out (P = .01), depressed (P = .01), or reported low mental (P =.03) or emotional (P = .016) QOL were more likely to have alcohol abuse/dependence. Emotional exhaustion and depersonalization domains of burnout were strongly associated with alcohol abuse/dependence. On multivariate analysis, burnout (OR 1.20; 95% CI 1.05-1.37; P < .01), having $50,000 to $100,000 (OR 1.21 versus < $50,000; CI 1.02-1.44; P < .05) or > $100,000 (OR 1.27 versus < $50,000; CI 1.08-1.48; P < .01) of educational debt, being unmarried (OR 1.89; CI 1.57-2.27; P < .001), and being younger (for every five years, OR 1.15; CI 1.02-1.28; P = .01) were independently associated with increased risk for alcohol abuse/dependence. Burnout was strongly related to alcohol abuse/dependence among sampled medical students and increased educational debt predicted a higher risk. A multifaceted approach addressing burnout, medical education costs, and alcohol use is needed.

Palliative care research in Latin America: results of a survey within the scope of the Declaration of Venice.

PubMed

Wenk, Roberto; De Lima, Liliana; Eisenchlas, Jorge

2008-06-01

In recent years, there has been an increase in the amount of palliative care research in developing countries. However, it is still very limited in the developing regions of the world, including Latin America. To determine the current status of palliative care research in Latin America. A survey was developed in Spanish and translated to Portuguese. Questions included demographic characteristics and specific research issues. Distribution was done through e-mail and personal hand-outs. Data were collected and analyzed using descriptive statistics and multivariate analysis. Two hundred sixty-three surveys (17.5% response rate) were received from 17 countries. A small number (10%, n = 263) reported participating in research within the last 5 years. Slightly over half of them received some training and had access to mentorship and guidance from an expert: multivariate analysis showed that training in research (odds ratio [OR] 3.46; 95% confidence interval [CI] 1.71-6.98) and support from an expert (OR 3.03; 95% CI 1.51-6.10) were positive predictor factors, even when adjusted for gender, age, years since graduation, and years working in palliative care. Barriers to conduct research most frequently cited were: lack of funding, insufficient knowledge and expertise, and lack of interest (54%, 21%, and 15%, respectively). Palliative care research in Latin America is very limited. Regional palliative care teams must adopt and implement systematic research in their practice to improve, guarantee, and sustain quality. Changes in policy, education, and allocation of funds are needed to guarantee the development of research in Latin America.

Spirituality and spiritual care perspectives among baccalaureate nursing students in Saudi Arabia: A cross-sectional study.

PubMed

Cruz, Jonas Preposi; Alshammari, Farhan; Alotaibi, Khalaf Aied; Colet, Paolo C

2017-02-01

No study has been undertaken to understand how spirituality and spiritual care is perceived and implemented by Saudi nursing students undergoing training for their future professional roles as nurses. This study was conducted to investigate the perception of Baccalaureate nursing students toward spirituality and spiritual care. A descriptive, cross-sectional design was employed. A convenience sample of 338 baccalaureate nursing students in two government-run universities in Saudi Arabia was included in this study. A self-administered questionnaire, consisting of a demographic and spiritual care background information sheet and the Spiritual Care-Giving Scale Arabic version (SCGS-A), was used for data collection. A multivariate multiple regression analysis and multiple linear regression analyses were performed accordingly. The mean value on the SCGS-A was 3.84±1.26. Spiritual perspective received the highest mean (4.14±1.45), followed by attribute for spiritual care (3.96±1.48), spiritual care attitude (3.81±1.47), defining spiritual care (3.71±1.51) and spiritual care values (3.57±1.47). Gender, academic level and learning spiritual care from classroom or clinical discussions showed a statistically significant multivariate effect on the five factors of SCGS-A. Efforts should be done to formally integrate holistic concept including all the facets of spirituality and spiritual care in the nursing curriculum. The current findings can be used to inform the development and testing of holistic nursing conceptual framework in nursing education in Saudi Arabia and other Arab Muslim countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Workload and quality of life of medical doctors in the field of oncology in Germany--a survey of the working group quality of life of the AIO for the study group of internal oncology.

PubMed

Hipp, Matthias; Pilz, Lothar; Al-Batran, Salah E; Hautmann, Matthias G; Hofheinz, Ralf-Dieter

2015-01-01

An increasing number of surveys have investigated professional stress and satisfaction among oncologists. Coevally, structural development has changed the oncological working environment. This survey investigated the quality of life and job stress among German oncological physicians. A 48-item questionnaire, which included the 'Stress questionnaire of physicians and nurses' (FBAS), was developed by the 'Quality of life' working group of the Internal oncology study group (AIO), and distributed anonymously at the annual meeting of the AIO working group in 2010. Descriptive statistics as well as univariate and multivariate analysis were performed. 261 oncologists, mostly male (64%), older than 40 years (38%), and medical specialists (78%), took part in the survey. 'Structural conditions' were identified as causing the highest mean stress levels, followed by 'professional and private life'. Female participants showed a significantly lower global quality of life than male participants (p = 0.020). 'Structural conditions' induced more stress among younger oncologists < 50 years old (p < 0.001). Qualification status was influenced by gender (p < 0.001); the multivariate analysis described the dependence of gender (p = 0.0045), working situation (p = 0.0317) and global stress (p = 0.0008). Structural conditions, age younger than 50 years and female gender were identified as stress risk factors among the AIO members, and showed that job stress is present in German oncology. Further research is warranted to develop evidence-based intervention strategies. © 2015 S. Karger GmbH, Freiburg.

Quantifying surgical complexity with machine learning: looking beyond patient factors to improve surgical models.

PubMed

Van Esbroeck, Alexander; Rubinfeld, Ilan; Hall, Bruce; Syed, Zeeshan

2014-11-01

To investigate the use of machine learning to empirically determine the risk of individual surgical procedures and to improve surgical models with this information. American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data from 2005 to 2009 were used to train support vector machine (SVM) classifiers to learn the relationship between textual constructs in current procedural terminology (CPT) descriptions and mortality, morbidity, Clavien 4 complications, and surgical-site infections (SSI) within 30 days of surgery. The procedural risk scores produced by the SVM classifiers were validated on data from 2010 in univariate and multivariate analyses. The procedural risk scores produced by the SVM classifiers achieved moderate-to-high levels of discrimination in univariate analyses (area under receiver operating characteristic curve: 0.871 for mortality, 0.789 for morbidity, 0.791 for SSI, 0.845 for Clavien 4 complications). Addition of these scores also substantially improved multivariate models comprising patient factors and previously proposed correlates of procedural risk (net reclassification improvement and integrated discrimination improvement: 0.54 and 0.001 for mortality, 0.46 and 0.011 for morbidity, 0.68 and 0.022 for SSI, 0.44 and 0.001 for Clavien 4 complications; P < .05 for all comparisons). Similar improvements were noted in discrimination and calibration for other statistical measures, and in subcohorts comprising patients with general or vascular surgery. Machine learning provides clinically useful estimates of surgical risk for individual procedures. This information can be measured in an entirely data-driven manner and substantially improves multifactorial models to predict postoperative complications. Copyright © 2014 Elsevier Inc. All rights reserved.

Inhospital and Post-discharge Changes in Renal Function After Transcatheter Aortic Valve Replacement.

PubMed

Blair, John E A; Brummel, Kent; Friedman, Julie L; Atri, Prashant; Sweis, Ranya N; Russell, Hyde; Ricciardi, Mark J; Malaisrie, S Chris; Davidson, Charles J; Flaherty, James D

2016-02-15

The aim of this study was to determine the influence of inhospital and post-discharge worsening renal function (WRF) on prognosis after transcatheter aortic valve replacement (TAVR). Severe chronic kidney disease and inhospital WRF are both associated with poor outcomes after TAVR. There are no data available on post-discharge WRF and outcomes. This was a single-center study evaluating all TAVR from June 1, 2008, to June 31, 2014. WRF was defined as an increase in serum creatinine of ≥0.3 mg/dl. Inhospital WRF was measured from day 0 until discharge or day 7 if the hospitalization was >7 days. Post-discharge WRF was measured at 30 days after discharge. Descriptive statistics, Kaplan-Meier time-to-event analysis, and multivariate logistic regression were used. In a series of 208 patients who underwent TAVR, 204 with complete renal function data were used in the inhospital analysis and 168 who returned for the 30-day follow-up were used in the post-discharge analysis. Inhospital WRF was seen in 28%, whereas post-discharge WRF in 12%. Inhospital and post-discharge WRF were associated with lower rates of survival; however, after multivariate analysis, only post-discharge WRF remained a predictor of 1-year mortality (hazard ratio 1.18, p = 0.030 for every 1 mg/dl increase in serum creatinine). In conclusion, the rate of inhospital WRF is higher than the rate of post-discharge WRF after TAVR, and post-discharge WRF is more predictive of mortality than inhospital WRF. Copyright © 2016 Elsevier Inc. All rights reserved.

Binge eating disorder and depressive symptoms among females of child-bearing age: the Korea Nurses' Health Study.

PubMed

Kim, O; Kim, M S; Kim, J; Lee, J E; Jung, H

2018-01-17

Most studies regarding the relationship between binge eating disorder (BED) and depression have targeted obese populations. However, nurses, particularly female nurses, are one of the vocations that face these issues due to various reasons including high stress and shift work. This study investigated the prevalence of BED and the correlation between BED and severity of self-reported depressive symptoms among female nurses in South Korea. Participants were 7,267 female nurses, of which 502 had symptoms of BED. Using the propensity score matching (PSM) technique, 502 nurses with BED and 502 without BED were included in the analyses. Data were analyzed using descriptive statistics, Spearman's correlation, and multivariable ordinal logistic regression analysis. The proportion of binge eating disorder was 6.90% among the nurses, and 81.3% of nurses displayed some levels of depressive symptoms. Multivariable ordinal logistic regression analysis revealed that age (40 years old and older), alcohol consumption (frequent drinkers), self-rated health, sleep problems, and stress were associated with self-reported depression symptoms. Overall, after adjusting for confounders, nurses with BED had 1.80 times the risk (95% CI = [1.41-2.30]; p-value < 0.001) of experiencing a greater severity of self-reported depression symptoms. Korean female nurse showed a higher prevalence of both binge eating disorder and depressive symptoms, and the association between the two factors was proven in the study. Therefore, hospital management and health policy makers should be alarmed and agreed on both examining nurses on such problems and providing organized and systematic assistance.

The Environment and Children's Health Care in Northwest China.

PubMed

Trasande, Leonardo; Niu, Jingping; Li, Juansheng; Liu, Xingrong; Zhang, Benzhong; Li, Zhilan; Ding, Guowu; Sun, Yingbiao; Chen, Meichi; Hu, Xiaobin; Chen, Lung-Chi; Mendelsohn, Alan; Chen, Yu; Qu, Qingshan

2014-03-27

Industrialization in the northwest provinces of the People's Republic of China is accelerating rapid increases in early life environmental exposures, yet no publications have assessed health care provider capacity to manage common hazards. To assess provider attitudes and beliefs regarding the environment in children's health, determine self-efficacy in managing concerns, and identify common approaches to managing patients with significant exposures or environmentally-mediated conditions, a two-page survey was administered to pediatricians, child care specialists, and nurses in five provinces (Gansu, Shaanxi, Xinjiang, Qinghai, and Ningxia). Descriptive and multivariable analyses assessed predictors of strong self-efficacy, beliefs or attitudes. 960 surveys were completed with <5% refusal; 695 (72.3%) were valid for statistical analyses. The role of environment in health was rated highly (mean 4.35 on a 1-5 scale). Self-efficacy reported with managing lead, pesticide, air pollution, mercury, mold and polychlorinated biphenyl exposures were generally modest (2.22-2.52 mean). 95.4% reported patients affected with 11.9% reporting seeing >20 affected patients. Only 12.0% reported specific training in environmental history taking, and 12.0% reported owning a text on children's environmental health. Geographic disparities were most prominent in multivariable analyses, with stronger beliefs in environmental causation yet lower self-efficacy in managing exposures in the northwestern-most province. Health care providers in Northwest China have strong beliefs regarding the role of environment in children's health, and frequently identify affected children. Few are trained in environmental history taking or rate self-efficacy highly in managing common hazards. Enhancing provider capacity has promise for improving children's health in the region.

Health Behaviors Predict Higher Interleukin-6 levels Among Patients Newly Diagnosed with Head and Neck Squamous Cell Carcinoma

PubMed Central

Duffy, Sonia A.; Teknos, Theodoros; Taylor, Jeremy M.G.; Fowler, Karen E.; Islam, Mozaffarul; Wolf, Gregory T.; McLean, Scott; Ghanem, Tamer A.; Terrell, Jeffrey E.

2013-01-01

Background Health behaviors have been shown to be associated with recurrence risk and survival rates in cancer patients and are also associated with Interleukin-6 levels, but few epidemiologic studies have investigated the relationship of health behaviors and Interleukin-6 among cancer populations. The purpose of the study is to look at the relationship between five health behaviors: smoking, alcohol problems, body mass index (a marker of nutritional status), physical activity, and sleep and pretreatment Interleukin-6 levels in persons with head and neck cancer. Methods Patients (N=409) were recruited in otolaryngology clinic waiting rooms and invited to complete written surveys. A medical record audit was also conducted. Descriptive statistics and multivariate analyses were conducted to determine which health behaviors were associated with higher Interleukin-6 levels controlling for demographic and clinical variables among newly diagnosed head and neck cancer patients. Results While smoking, alcohol problems, body mass index, physical activity, and sleep were associated with Interleukin-6 levels in bivariate analysis, only smoking (current and former) and decreased sleep were independent predictors of higher Interleukin-6 levels in multivariate regression analysis. Covariates associated with higher Interleukin-6 levels were age and higher tumor stage, while comorbidities were marginally significant. Conclusion Health behaviors, particularly smoking and sleep disturbances, are associated with higher Interleukin-6 levels among head and neck cancer patients. Impact Treating health behavior problems, especially smoking and sleep disturbances, may be beneficial to decreasing Interleukin-6 levels which could have a beneficial effect on overall cancer treatment outcomes. PMID:23300019

Health behaviors predict higher interleukin-6 levels among patients newly diagnosed with head and neck squamous cell carcinoma.

PubMed

Duffy, Sonia A; Teknos, Theodoros; Taylor, Jeremy M G; Fowler, Karen E; Islam, Mozaffarul; Wolf, Gregory T; McLean, Scott; Ghanem, Tamer A; Terrell, Jeffrey E

2013-03-01

Health behaviors have been shown to be associated with recurrence risk and survival rates in patients with cancer and are also associated with interleukin-6 (IL-6) levels, but few epidemiologic studies have investigated the relationship of health behaviors and IL-6 among cancer populations. The purpose of the study is to look at the relationship between five health behaviors, viz.: smoking, alcohol problems, body mass index (BMI; a marker of nutritional status), physical activity, and sleep and pretreatment IL-6 levels in persons with head and neck cancer. Patients (N = 409) were recruited in otolaryngology clinic waiting rooms and invited to complete written surveys. A medical record audit was also conducted. Descriptive statistics and multivariate analyses were conducted to determine which health behaviors were associated with higher IL-6 levels controlling for demographic and clinical variables among patients with newly diagnosed head and neck cancer. While smoking, alcohol problems, BMI, physical activity, and sleep were associated with IL-6 levels in bivariate analysis, only smoking (current and former) and decreased sleep were independent predictors of higher IL-6 levels in multivariate regression analysis. Covariates associated with higher IL-6 levels were age and higher tumor stage, whereas comorbidities were marginally significant. Health behaviors, particularly smoking and sleep disturbances, are associated with higher IL-6 levels among patients with head and neck cancer. Treating health behavior problems, especially smoking and sleep disturbances, may be beneficial to decreasing IL-6 levels, which could have a beneficial effect on overall cancer treatment outcomes.

Access to health care and religion among young American men.

PubMed

Gillum, R Frank; Jarrett, Nicole; Obisesan, Thomas O

2009-12-01

In order to elucidate cultural correlates of utilization of primary health services by young adult men, we investigated religion in which one was raised and service utilization. Using data from a national survey we tested the hypothesis that religion raised predicts access to and utilization of a regular medical care provider, examinations, HIV and other STD testing and counseling at ages 18-44 years in men born between 1958 and 1984. We also hypothesized that religion raised would be more predictive of utilization for Hispanic Americans and non-Hispanic Black Americans than for non-Hispanic White Americans. The study included a national sample of 4276 men aged 18-44 years. Descriptive and multivariate statistics were used to assess the hypotheses using data on religion raised and responses to 14 items assessing health care access and utilization. Compared to those raised in no religion, those raised mainline Protestant were more likely (p < 0.01) to report a usual source of care (67% vs. 79%), health insurance coverage (66% vs. 80%) and physical examination (43% vs. 48%). Religion raised was not associated with testicular exams, STD counseling or HIV testing. In multivariate analyses controlling for confounders, significant associations of religion raised with insurance coverage, a physician as usual source of care and physical examination remained which varied by race/ethnicity. In conclusion, although religion is a core aspect of culture that deserves further study as a possible determinant of health care utilization, we were not able to document any consistent pattern of significant association even in a population with high rates of religious participation.

Access to Health Care and Religion among Young American Men

PubMed Central

Gillum, R. Frank; Jarrett, Nicole; Obisesan, Thomas O.

2009-01-01

In order to elucidate cultural correlates of utilization of primary health services by young adult men, we investigated religion in which one was raised and service utilization. Using data from a national survey we tested the hypothesis that religion raised predicts access to and utilization of a regular medical care provider, examinations, HIV and other STD testing and counseling at ages 18–44 years in men born between 1958 and 1984. We also hypothesized that religion raised would be more predictive of utilization for Hispanic Americans and non-Hispanic Black Americans than for non-Hispanic White Americans. The study included a national sample of 4276 men aged 18–44 years. Descriptive and multivariate statistics were used to assess the hypotheses using data on religion raised and responses to 14 items assessing health care access and utilization. Compared to those raised in no religion, those raised mainline Protestant were more likely (p < 0.01) to report a usual source of care (67% vs. 79%), health insurance coverage (66% vs. 80%) and physical examination (43% vs. 48%). Religion raised was not associated with testicular exams, STD counseling or HIV testing. In multivariate analyses controlling for confounders, significant associations of religion raised with insurance coverage, a physician as usual source of care and physical examination remained which varied by race/ethnicity. In conclusion, although religion is a core aspect of culture that deserves further study as a possible determinant of health care utilization, we were not able to document any consistent pattern of significant association even in a population with high rates of religious participation. PMID:20049258

Trends in diabetes-related visits to US EDs from 1997 to 2007.

PubMed

Menchine, Michael D; Wiechmann, Warren; Peters, Anne L; Arora, Sanjay

2012-06-01

The aims of the study were to describe temporal trends in the number, proportion, and per capita use of diabetes-related emergency department (ED) visits and to examine any racial/ethnic disparity in ED use for diabetes-related reasons. We analyzed the ED portion of the National Hospital Ambulatory Medical Care Survey from 1997 through 2007. Diabetes-related ED visits were identified by International Classification of Diseases, Ninth Revision codes. Descriptive statistics were developed. Weighted linear and logistic regression models were used to determine significance of temporal trends, and multivariate logistic regression was used to examine racial/ethnic disparities. A total of 20.2 million (1.69%; 95% confidence interval [CI], 1.59%-1.78%) ED visits were diabetes-related during the study period. We observed significant increases in the number and proportion of diabetes-related ED visits. Overall, there was a 5.6% relative annual increase in the proportion of ED visits that were diabetes-related during the study period. However, the per capita ED use among the population with diabetes did not change over time (P>.05 for trend). On multivariate analysis, black race (odds ratio, 1.8; 95% CI, 1.7-2.0), Hispanic ethnicity (odds ratio, 1.6; 95% CI, 1.4-1.8), and advancing age were associated with significantly higher odds of having a diabetes-related visit. Despite a marked increase in number and proportion of diabetes-related ED visits during the study period, the per capita use of ED services for diabetes-related visits among the diabetic population remained stable. Copyright © 2012 Elsevier Inc. All rights reserved.

The Religiosity/Spirituality of Latina Breast Cancer Survivors and Influence on Health-Related Quality of Life

PubMed Central

Wildes, Kimberly A.; Miller, Alexander R.; de Majors, Sandra San Miguel; Ramirez, Amelie G.

2010-01-01

Objective The study evaluated the association of religiosity/spirituality (R/S) and health-related quality of life (HRQOL) among Latina breast cancer survivors (BCS) in order to determine whether R/S would be positively correlated with HRQOL and whether R/S would significantly influence HRQOL. Methods The cross-sectional study utilized self-report data from 117 Latina BCS survivors. R/S was measured with the Systems of Belief Inventory - 15 Revised (SBI-15R) and HRQOL was measured with the Functional Assessment of Cancer Therapy – General (FACT-G). Analyses included calculation of descriptive statistics, t-tests, bivariate correlations, and multivariate analyses. Results Latina BCS had very high levels of R/S and generally good HRQOL. The SBI-15R total score was positively correlated with FACT-G social well-being (r=0.266, p=0.005), relationship with doctor (r=0.219, p=0.020), and functional well-being (r=0.216, p=0.022). Multivariate analyses revealed that SBI-15R was a significant predictor of FACT-G functional well-being (p=0.041) and satisfaction with the relationship with the doctor (p=0.050), where higher levels of R/S predicted higher levels of well-being. Conclusions Latina BCS had very high levels of R/S, which were significantly, positively correlated with dimensions of HRQOL (social well-being, functional well-being, relationship with doctor). Further, these high levels of R/S predicted better functional well-being and satisfaction with the patient-doctor relationship while controlling for potentially confounding variables. Implications are discussed. PMID:19034922

Risk factors for acute surgical site infections after lumbar surgery: a retrospective study.

PubMed

Lai, Qi; Song, Quanwei; Guo, Runsheng; Bi, Haidi; Liu, Xuqiang; Yu, Xiaolong; Zhu, Jianghao; Dai, Min; Zhang, Bin

2017-07-19

Currently, many scholars are concerned about the treatment of postoperative infection; however, few have completed multivariate analyses to determine factors that contribute to the risk of infection. Therefore, we conducted a multivariate analysis of a retrospectively collected database to analyze the risk factors for acute surgical site infection following lumbar surgery, including fracture fixation, lumbar fusion, and minimally invasive lumbar surgery. We retrospectively reviewed data from patients who underwent lumbar surgery between 2014 and 2016, including lumbar fusion, internal fracture fixation, and minimally invasive surgery in our hospital's spinal surgery unit. Patient demographics, procedures, and wound infection rates were analyzed using descriptive statistics, and risk factors were analyzed using logistic regression analyses. Twenty-six patients (2.81%) experienced acute surgical site infection following lumbar surgery in our study. The patients' mean body mass index, smoking history, operative time, blood loss, draining time, and drainage volume in the acute surgical site infection group were significantly different from those in the non-acute surgical site infection group (p < 0.05). Additionally, diabetes mellitus, chronic obstructive pulmonary disease, osteoporosis, preoperative antibiotics, type of disease, and operative type in the acute surgical site infection group were significantly different than those in the non-acute surgical site infection group (p < 0.05). Using binary logistic regression analyses, body mass index, smoking, diabetes mellitus, osteoporosis, preoperative antibiotics, fracture, operative type, operative time, blood loss, and drainage time were independent predictors of acute surgical site infection following lumbar surgery. In order to reduce the risk of infection following lumbar surgery, patients should be evaluated for the risk factors noted above.

Human Milk Handling and Storage Practices Among Peer Milk-Sharing Mothers.

PubMed

Reyes-Foster, Beatriz M; Carter, Shannon K; Hinojosa, Melanie Sberna

2017-02-01

Peer milk sharing, the noncommercial sharing of human milk from one parent or caretaker directly to another for the purposes of feeding a child, appears to be an increasing infant-feeding practice. Although the U.S. Food and Drug Administration has issued a warning against the practice, little is known about how people who share human milk handle and store milk and whether these practices are consistent with clinical safety protocols. Research aim: This study aimed to learn about the milk-handling practices of expressed human milk by milk-sharing donors and recipient caretakers. In this article, we explore the degree to which donors and recipients adhere to the Academy of Breastfeeding Medicine clinical recommendations for safe handling and storage. Online surveys were collected from 321 parents engaged in peer milk sharing. Univariate descriptive statistics were used to describe the safe handling and storage procedures for milk donors and recipients. A two-sample t-test was used to compare safety items common to each group. Multivariate ordinary least squares regression analysis was used to examine sociodemographic correlates of milk safety practices within the sample group. Findings indicate that respondents engaged in peer milk sharing report predominantly positive safety practices. Multivariate analysis did not reveal any relationship between safety practices and sociodemographic characteristics. The number of safe practices did not differ between donors and recipients. Parents and caretakers who participate in peer human milk sharing report engaging in practices that should reduce risk of bacterial contamination of expressed peer shared milk. More research on this particular population is recommended.

Modelling the immunological response to a tetravalent dengue vaccine from multiple phase-2 trials in Latin America and South East Asia.

PubMed

Dorigatti, Ilaria; Aguas, Ricardo; Donnelly, Christl A; Guy, Bruno; Coudeville, Laurent; Jackson, Nicholas; Saville, Melanie; Ferguson, Neil M

2015-07-17

The most advanced dengue vaccine candidate is a live-attenuated recombinant vaccine containing the four dengue viruses on the yellow fever vaccine backbone (CYD-TDV) developed by Sanofi Pasteur. Several analyses have been published on the safety and immunogenicity of the CYD-TDV vaccine from single trials but none modelled the heterogeneity observed in the antibody responses elicited by the vaccine. We analyse the immunogenicity data collected in five phase-2 trials of the CYD-TDV vaccine. We provide a descriptive analysis of the aggregated datasets and fit the observed post-vaccination PRNT50 titres against the four dengue (DENV) serotypes using multivariate regression models. We find that the responses to CYD-TDV are principally predicted by the baseline immunological status against DENV, but the trial is also a significant predictor. We find that the CYD-TDV vaccine generates similar titres against all serotypes following the third dose, though DENV4 is immunodominant after the first dose. This study contributes to a better understanding of the immunological responses elicited by CYD-TDV. The recent availability of phase-3 data is a unique opportunity to further investigate the immunogenicity and efficacy of the CYD-TDV vaccine, especially in subjects with different levels of pre-existing immunity against DENV. Modelling multiple immunological outcomes with a single multivariate model offers advantages over traditional approaches, capturing correlations between response variables, and the statistical method adopted in this study can be applied to a variety of infections with interacting strains. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Are men's misogynistic attitudes associated with poor mental health and substance use behaviors? An exploratory study of men in Tijuana, Mexico.

PubMed

Fleming, Paul J; Patterson, Thomas L; Chavarin, Claudia V; Semple, Shirley J; Magis-Rodriguez, Carlos; Pitpitan, Eileen V

2018-04-01

Men's misogynistic attitudes (i.e., dislike or contempt for women) have been shown to be associated with men's perpetration of physical/sexual violence against women and poor health outcomes for women. However, these attitudes have rarely been examined for their influence on men's own health. This paper examines the socio-demographic, substance use, and mental health correlates of misogynistic attitudes among a binational sample of men (n=400) in Tijuana, Mexico with high-risk substance use and sexual behaviors. We used a 6-item scale to measure misogynistic attitudes ( α = .72), which was developed specifically for this context. We used descriptive statistics to describe our sample population and the extent to which they hold misogynistic attitudes. Then, using misogynistic attitudes as our dependent variable, we conducted bivariate linear regression and multivariable linear regression to examine the relationship between these attitudes and socio-demographic characteristics, substance use behaviors (i.e., use of alcohol, marijuana, heroin, methamphetamines, cocaine), and mental health (i.e., depression, self-esteem). In the multivariable model, we found significant relationships between misogynistic attitudes and education level ( t = -4.34, p < 0.01), heroin use in the past 4 months ( t = 2.50, p = 0.01), and depressive symptoms ( t = 3.37, p < 0.01). These findings suggest that misogynistic attitudes are linked to poor health outcomes for men and future research needs to further explore the temporality of these relationships and identify strategies for reducing men's misogynistic attitudes with the ultimate aim of improving the health and well-being of both women and men.

Predictors and Patterns of Local, Regional, and Distant Failure in Squamous Cell Carcinoma of the Vulva.

PubMed

Bogani, Giorgio; Cromi, Antonella; Serati, Maurizio; Uccella, Stefano; Donato, Violante Di; Casarin, Jvan; Naro, Edoardo Di; Ghezzi, Fabio

2017-06-01

To identify factors predicting for recurrence in vulvar cancer patients undergoing surgical treatment. We retrospectively evaluated data of consecutive patients with squamous cell vulvar cancer treated between January 1, 1990 and December 31, 2013. Basic descriptive statistics and multivariable analysis were used to design predicting models influencing outcomes. Five-year disease-free survival (DFS) and overall survival (OS) were analyzed using the Cox model. The study included 101 patients affected by vulvar cancer: 64 (63%) stage I, 12 (12%) stage II, 20 (20%) stage III, and 5 (5%) stage IV. After a mean (SD) follow-up of 37.6 (22.1) months, 21 (21%) recurrences occurred. Local, regional, and distant failures were recorded in 14 (14%), 6 (6%), and 3 (3%) patients, respectively. Five-year DFS and OS were 77% and 82%, respectively. At multivariate analysis only stromal invasion >2 mm (hazard ratio: 4.9 [95% confidence interval, 1.17-21.1]; P=0.04) and extracapsular lymph node involvement (hazard ratio: 9.0 (95% confidence interval, 1.17-69.5); P=0.03) correlated with worse DFS, although no factor independently correlated with OS. Looking at factors influencing local and regional failure, we observed that stromal invasion >2 mm was the only factor predicting for local recurrence, whereas lymph node extracapsular involvement predicted for regional recurrence. Stromal invasion >2 mm and lymph node extracapsular spread are the most important factors predicting for local and regional failure, respectively. Studies evaluating the effectiveness of adjuvant treatment in high-risk patients are warranted.

One thing leads to another: the cascade of obligations when researchers report genetic research results to study participants.

PubMed

Miller, Fiona Alice; Hayeems, Robin Zoe; Li, Li; Bytautas, Jessica Peace

2012-08-01

Even as debate continues about the putative obligation to proactively report genetic research results to study participants, there is an increasing need to attend to the obligations that might cascade from any initial report. We conducted an international, quasi-experimental survey of researchers involved in autism spectrum disorders (ASD) and cystic fibrosis (CF) genetics to explore perceived obligations to ensure updated information or relevant clinical care subsequent to any initial communication of research results, and factors influencing these attitudes. 5-point Likert scales of dis/agreement were analyzed using descriptive and multivariate statistics. Of the 343 respondents (44% response rate), large majorities agreed that in general and in a variety of hypothetical research contexts, research teams that report results should ensure that participants gain subsequent access to updated information (74-83%) and implicated clinical services (79-87%). At the same time, researchers perceived barriers restricting access to relevant clinical care, though this was significantly more pronounced (P<0.001) for ASD (64%) than CF (34%). In the multivariate model, endorsement of cascading obligations was positively associated with researcher characteristics (eg, clinical role/training) and attitudes (eg, perceived initial reporting obligation), and negatively associated with the initial report of less scientifically robust hypothetical results, but unaffected by perceived or hypothetical barriers to care. These results suggest that researchers strongly endorse information and care-based obligations that cascade from the initial report of research results to study participants. In addition, they raise challenging questions about how any cascading obligations are to be met, especially where access challenges are already prevalent.

Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who, What, Why, When, Where, and a Sixth, So What?

PubMed

Vetter, Thomas R

2017-11-01

Descriptive statistics are specific methods basically used to calculate, describe, and summarize collected research data in a logical, meaningful, and efficient way. Descriptive statistics are reported numerically in the manuscript text and/or in its tables, or graphically in its figures. This basic statistical tutorial discusses a series of fundamental concepts about descriptive statistics and their reporting. The mean, median, and mode are 3 measures of the center or central tendency of a set of data. In addition to a measure of its central tendency (mean, median, or mode), another important characteristic of a research data set is its variability or dispersion (ie, spread). In simplest terms, variability is how much the individual recorded scores or observed values differ from one another. The range, standard deviation, and interquartile range are 3 measures of variability or dispersion. The standard deviation is typically reported for a mean, and the interquartile range for a median. Testing for statistical significance, along with calculating the observed treatment effect (or the strength of the association between an exposure and an outcome), and generating a corresponding confidence interval are 3 tools commonly used by researchers (and their collaborating biostatistician or epidemiologist) to validly make inferences and more generalized conclusions from their collected data and descriptive statistics. A number of journals, including Anesthesia & Analgesia, strongly encourage or require the reporting of pertinent confidence intervals. A confidence interval can be calculated for virtually any variable or outcome measure in an experimental, quasi-experimental, or observational research study design. Generally speaking, in a clinical trial, the confidence interval is the range of values within which the true treatment effect in the population likely resides. In an observational study, the confidence interval is the range of values within which the true strength of the association between the exposure and the outcome (eg, the risk ratio or odds ratio) in the population likely resides. There are many possible ways to graphically display or illustrate different types of data. While there is often latitude as to the choice of format, ultimately, the simplest and most comprehensible format is preferred. Common examples include a histogram, bar chart, line chart or line graph, pie chart, scatterplot, and box-and-whisker plot. Valid and reliable descriptive statistics can answer basic yet important questions about a research data set, namely: "Who, What, Why, When, Where, How, How Much?"

Significant Pre-Accession Factors Predicting Success or Failure During a Marine Corps Officer’s Initial Service Obligation

DTIC Science & Technology

2015-12-01

WAIVERS ..............................................................................................49  APPENDIX C. DESCRIPTIVE STATISTICS ... Statistics of Dependent Variables. .............................................23  Table 6.  Summary Statistics of Academics Variables...24  Table 7.  Summary Statistics of Application Variables ............................................25  Table 8

21 CFR 314.50 - Content and format of an application.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...

21 CFR 314.50 - Content and format of an application.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...

21 CFR 314.50 - Content and format of an application.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...

21 CFR 314.50 - Content and format of an application.

Code of Federal Regulations, 2011 CFR

2011-04-01

... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...

21 CFR 314.50 - Content and format of an application.

Code of Federal Regulations, 2010 CFR

2010-04-01

... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...

Multivariate Statistical Modelling of Drought and Heat Wave Events

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Vrac, Mathieu; Maraun, Douglas; Bevaqua, Emanuele

2016-04-01

Multivariate Statistical Modelling of Drought and Heat Wave Events C. Manning1,2, M. Widmann1, M. Vrac2, D. Maraun3, E. Bevaqua2,3 1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK 2. Laboratoire des Sciences du Climat et de l'Environnement, (LSCE-IPSL), Centre d'Etudes de Saclay, Gif-sur-Yvette, France 3. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria Compound extreme events are a combination of two or more contributing events which in themselves may not be extreme but through their joint occurrence produce an extreme impact. Compound events are noted in the latest IPCC report as an important type of extreme event that have been given little attention so far. As part of the CE:LLO project (Compound Events: muLtivariate statisticaL mOdelling) we are developing a multivariate statistical model to gain an understanding of the dependence structure of certain compound events. One focus of this project is on the interaction between drought and heat wave events. Soil moisture has both a local and non-local effect on the occurrence of heat waves where it strongly controls the latent heat flux affecting the transfer of sensible heat to the atmosphere. These processes can create a feedback whereby a heat wave maybe amplified or suppressed by the soil moisture preconditioning, and vice versa, the heat wave may in turn have an effect on soil conditions. An aim of this project is to capture this dependence in order to correctly describe the joint probabilities of these conditions and the resulting probability of their compound impact. We will show an application of Pair Copula Constructions (PCCs) to study the aforementioned compound event. PCCs allow in theory for the formulation of multivariate dependence structures in any dimension where the PCC is a decomposition of a multivariate distribution into a product of bivariate components modelled using copulas. A copula is a multivariate distribution function which allows one to model the dependence structure of given variables separately from the marginal behaviour. We firstly look at the structure of soil moisture drought over the entire of France using the SAFRAN dataset between 1959 and 2009. Soil moisture is represented using the Standardised Precipitation Evapotranspiration Index (SPEI). Drought characteristics are computed at grid point scale where drought conditions are identified as those with an SPEI value below -1.0. We model the multivariate dependence structure of drought events defined by certain characteristics and compute return levels of these events. We initially find that drought characteristics such as duration, mean SPEI and the maximum contiguous area to a grid point all have positive correlations, though the degree to which they are correlated can vary considerably spatially. A spatial representation of return levels then may provide insight into the areas most prone to drought conditions. As a next step, we analyse the dependence structure between soil moisture conditions preceding the onset of a heat wave and the heat wave itself.

One Yard Below: Education Statistics from a Different Angle.

ERIC Educational Resources Information Center

Education Intelligence Agency, Carmichael, CA.

This report offers a different perspective on education statistics by highlighting rarely used "stand-alone" statistics on public education, inputs, outputs, and descriptions, and it uses interactive statistics that combine two or more statistics in an unusual way. It is a report that presents much evidence, but few conclusions. It is not intended…

A Bibliography of Statistical Applications in Geography, Technical Paper No. 9.

ERIC Educational Resources Information Center

Greer-Wootten, Bryn; And Others

Included in this bibliography are resource materials available to both college instructors and students on statistical applications in geographic research. Two stages of statistical development are treated in the bibliography. They are 1) descriptive statistics, in which the sample is the focus of interest, and 2) analytical statistics, in which…

Predicting Outcomes After Chemo-Embolization in Patients with Advanced-Stage Hepatocellular Carcinoma: An Evaluation of Different Radiologic Response Criteria

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

Gunn, Andrew J., E-mail: agunn@uabmc.edu; Sheth, Rahul A.; Luber, Brandon

2017-01-15

PurposeThe purpse of this study was to evaluate the ability of various radiologic response criteria to predict patient outcomes after trans-arterial chemo-embolization with drug-eluting beads (DEB-TACE) in patients with advanced-stage (BCLC C) hepatocellular carcinoma (HCC).Materials and methodsHospital records from 2005 to 2011 were retrospectively reviewed. Non-infiltrative lesions were measured at baseline and on follow-up scans after DEB-TACE according to various common radiologic response criteria, including guidelines of the World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), the European Association for the Study of the Liver (EASL), and modified RECIST (mRECIST). Statistical analysis was performed to see which,more » if any, of the response criteria could be used as a predictor of overall survival (OS) or time-to-progression (TTP).Results75 patients met inclusion criteria. Median OS and TTP were 22.6 months (95 % CI 11.6–24.8) and 9.8 months (95 % CI 7.1–21.6), respectively. Univariate and multivariate Cox analyses revealed that none of the evaluated criteria had the ability to be used as a predictor for OS or TTP. Analysis of the C index in both univariate and multivariate models showed that the evaluated criteria were not accurate predictors of either OS (C-statistic range: 0.51–0.58 in the univariate model; range: 0.54–0.58 in the multivariate model) or TTP (C-statistic range: 0.55–0.59 in the univariate model; range: 0.57–0.61 in the multivariate model).ConclusionCurrent response criteria are not accurate predictors of OS or TTP in patients with advanced-stage HCC after DEB-TACE.« less

Predicting Outcomes After Chemo-Embolization in Patients with Advanced-Stage Hepatocellular Carcinoma: An Evaluation of Different Radiologic Response Criteria.

PubMed

Gunn, Andrew J; Sheth, Rahul A; Luber, Brandon; Huynh, Minh-Huy; Rachamreddy, Niranjan R; Kalva, Sanjeeva P

2017-01-01

The purpse of this study was to evaluate the ability of various radiologic response criteria to predict patient outcomes after trans-arterial chemo-embolization with drug-eluting beads (DEB-TACE) in patients with advanced-stage (BCLC C) hepatocellular carcinoma (HCC). Hospital records from 2005 to 2011 were retrospectively reviewed. Non-infiltrative lesions were measured at baseline and on follow-up scans after DEB-TACE according to various common radiologic response criteria, including guidelines of the World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), the European Association for the Study of the Liver (EASL), and modified RECIST (mRECIST). Statistical analysis was performed to see which, if any, of the response criteria could be used as a predictor of overall survival (OS) or time-to-progression (TTP). 75 patients met inclusion criteria. Median OS and TTP were 22.6 months (95 % CI 11.6-24.8) and 9.8 months (95 % CI 7.1-21.6), respectively. Univariate and multivariate Cox analyses revealed that none of the evaluated criteria had the ability to be used as a predictor for OS or TTP. Analysis of the C index in both univariate and multivariate models showed that the evaluated criteria were not accurate predictors of either OS (C-statistic range: 0.51-0.58 in the univariate model; range: 0.54-0.58 in the multivariate model) or TTP (C-statistic range: 0.55-0.59 in the univariate model; range: 0.57-0.61 in the multivariate model). Current response criteria are not accurate predictors of OS or TTP in patients with advanced-stage HCC after DEB-TACE.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

Research Education in Undergraduate Occupational Therapy Programs.

ERIC Educational Resources Information Center

Petersen, Paul; And Others

1992-01-01

Of 63 undergraduate occupational therapy programs surveyed, the 38 responses revealed some common areas covered: elementary descriptive statistics, validity, reliability, and measurement. Areas underrepresented include statistical analysis with or without computers, research design, and advanced statistics. (SK)

Policy Safeguards and the Legitimacy of Highway Interdiction

DTIC Science & Technology

2016-12-01

17 B. BIAS WITHIN LAW ENFORCEMENT ..............................................19 C. STATISTICAL DATA GATHERING...32 3. Controlling Discretion .................................................................36 4. Statistical Data Collection for Traffic Stops...49 A. DESCRIPTION OF STATISTICAL DATA COLLECTED ...............50 B. DATA ORGANIZATION AND ANALYSIS

A simple rapid approach using coupled multivariate statistical methods, GIS and trajectory models to delineate areas of common oil spill risk

NASA Astrophysics Data System (ADS)

Guillen, George; Rainey, Gail; Morin, Michelle

2004-04-01

Currently, the Minerals Management Service uses the Oil Spill Risk Analysis model (OSRAM) to predict the movement of potential oil spills greater than 1000 bbl originating from offshore oil and gas facilities. OSRAM generates oil spill trajectories using meteorological and hydrological data input from either actual physical measurements or estimates generated from other hydrological models. OSRAM and many other models produce output matrices of average, maximum and minimum contact probabilities to specific landfall or target segments (columns) from oil spills at specific points (rows). Analysts and managers are often interested in identifying geographic areas or groups of facilities that pose similar risks to specific targets or groups of targets if a spill occurred. Unfortunately, due to the potentially large matrix generated by many spill models, this question is difficult to answer without the use of data reduction and visualization methods. In our study we utilized a multivariate statistical method called cluster analysis to group areas of similar risk based on potential distribution of landfall target trajectory probabilities. We also utilized ArcView™ GIS to display spill launch point groupings. The combination of GIS and multivariate statistical techniques in the post-processing of trajectory model output is a powerful tool for identifying and delineating areas of similar risk from multiple spill sources. We strongly encourage modelers, statistical and GIS software programmers to closely collaborate to produce a more seamless integration of these technologies and approaches to analyzing data. They are complimentary methods that strengthen the overall assessment of spill risks.

Socio-Demographic and Clinical Characteristics are Not Clinically Useful Predictors of Refill Adherence in Patients with Hypertension

PubMed Central

Steiner, John F.; Ho, P. Michael; Beaty, Brenda L.; Dickinson, L. Miriam; Hanratty, Rebecca; Zeng, Chan; Tavel, Heather M.; Havranek, Edward P.; Davidson, Arthur J.; Magid, David J.; Estacio, Raymond O.

2009-01-01

Background Although many studies have identified patient characteristics or chronic diseases associated with medication adherence, the clinical utility of such predictors has rarely been assessed. We attempted to develop clinical prediction rules for adherence with antihypertensive medications in two health care delivery systems. Methods and Results Retrospective cohort studies of hypertension registries in an inner-city health care delivery system (N = 17176) and a health maintenance organization (N = 94297) in Denver, Colorado. Adherence was defined by acquisition of 80% or more of antihypertensive medications. A multivariable model in the inner-city system found that adherent patients (36.3% of the total) were more likely than non-adherent patients to be older, white, married, and acculturated in US society, to have diabetes or cerebrovascular disease, not to abuse alcohol or controlled substances, and to be prescribed less than three antihypertensive medications. Although statistically significant, all multivariate odds ratios were 1.7 or less, and the model did not accurately discriminate adherent from non-adherent patients (C-statistic = 0.606). In the health maintenance organization, where 72.1% of patients were adherent, significant but weak associations existed between adherence and older age, white race, the lack of alcohol abuse, and fewer antihypertensive medications. The multivariate model again failed to accurately discriminate adherent from non-adherent individuals (C-statistic = 0.576). Conclusions Although certain socio-demographic characteristics or clinical diagnoses are statistically associated with adherence to refills of antihypertensive medications, a combination of these characteristics is not sufficiently accurate to allow clinicians to predict whether their patients will be adherent with treatment. PMID:20031876

Fish: A New Computer Program for Friendly Introductory Statistics Help

ERIC Educational Resources Information Center

Brooks, Gordon P.; Raffle, Holly

2005-01-01

All introductory statistics students must master certain basic descriptive statistics, including means, standard deviations and correlations. Students must also gain insight into such complex concepts as the central limit theorem and standard error. This article introduces and describes the Friendly Introductory Statistics Help (FISH) computer…

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

PubMed

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimation and model selection of semiparametric multivariate survival functions under general censorship.

PubMed

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2010-07-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

Estimation and model selection of semiparametric multivariate survival functions under general censorship

PubMed Central

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2013-01-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided. PMID:24790286

Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis.

PubMed

Neyeloff, Jeruza L; Fuchs, Sandra C; Moreira, Leila B

2012-01-20

Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software.

Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis

PubMed Central

2012-01-01

Background Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. Findings We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. Conclusions It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software. PMID:22264277

Edward J. Wolfrum | NREL

Science.gov Websites

. Another project used multivariate statistics to develop a novel device to non-invasively measure hydrogen Cellulosic Ethanol Production due to Experimental Measurement Uncertainty," Biotechnology for Biofuels

Application of Maxent Multivariate Analysis to Define Climate-Change Effects on Species Distributions and Changes

DTIC Science & Technology

2014-09-01

approaches. Ecological Modelling Volume 200, Issues 1–2, 10, pp 1–19. Buhlmann, Kurt A ., Thomas S.B. Akre , John B. Iverson, Deno Karapatakis, Russell A ...statistical multivariate analysis to define the current and projected future range probability for species of interest to Army land managers. A software...15 Figure 4. RCW omission rate and predicted area as a function of the cumulative threshold

Deterministic annealing for density estimation by multivariate normal mixtures

NASA Astrophysics Data System (ADS)

Kloppenburg, Martin; Tavan, Paul

1997-03-01

An approach to maximum-likelihood density estimation by mixtures of multivariate normal distributions for large high-dimensional data sets is presented. Conventionally that problem is tackled by notoriously unstable expectation-maximization (EM) algorithms. We remove these instabilities by the introduction of soft constraints, enabling deterministic annealing. Our developments are motivated by the proof that algorithmically stable fuzzy clustering methods that are derived from statistical physics analogs are special cases of EM procedures.

A Note on Asymptotic Joint Distribution of the Eigenvalues of a Noncentral Multivariate F Matrix.

DTIC Science & Technology

1984-11-01

Krishnaiah (1982). Now, let us consider the samples drawn from the k multivariate normal popuiejons. Let (Xlt....Xpt) denote the mean vector of the t...to maltivariate problems. Sankh-ya, 4, 381-39(s. (71 KRISHNAIAH , P. R. (1982). Selection of variables in discrimlnant analysis. In Handbook of...Statistics, Volume 2 (P. R. Krishnaiah , editor), 805-820. North-Holland Publishing Company. 6. Unclassifie INSTRUCTIONS REPORT DOCUMENTATION PAGE

LIKELIHOOD RATIO TESTS OF HYPOTHESES ON MULTIVARIATE POPULATIONS, VOLUME II, TEST OF HYPOTHESIS--STATISTICAL MODELS FOR THE EVALUATION AND INTERPRETATION OF EDUCATIONAL CRITERIA. PART 4.

ERIC Educational Resources Information Center

SAW, J.G.

THIS PAPER DEALS WITH SOME TESTS OF HYPOTHESIS FREQUENTLY ENCOUNTERED IN THE ANALYSIS OF MULTIVARIATE DATA. THE TYPE OF HYPOTHESIS CONSIDERED IS THAT WHICH THE STATISTICIAN CAN ANSWER IN THE NEGATIVE OR AFFIRMATIVE. THE DOOLITTLE METHOD MAKES IT POSSIBLE TO EVALUATE THE DETERMINANT OF A MATRIX OF HIGH ORDER, TO SOLVE A MATRIX EQUATION, OR TO…

Determining the Number of Component Clusters in the Standard Multivariate Normal Mixture Model Using Model-Selection Criteria.

DTIC Science & Technology

1983-06-16

has been advocated by Gnanadesikan and 𔃾ilk (1969), and others in the literature. This suggests that, if we use the formal signficance test type...American Statistical Asso., 62, 1159-1178. Gnanadesikan , R., and Wilk, M..B. (1969). Data Analytic Methods in Multi- variate Statistical Analysis. In

What is a good index? Problems with statistically based indicators and the Malmquist index as alternative

USDA-ARS?s Scientific Manuscript database

Conventional multivariate statistical methods have been used for decades to calculate environmental indicators. These methods generally work fine if they are used in a situation where the method can be tailored to the data. But there is some skepticism that the methods might fail in the context of s...

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation

PubMed Central

Wilke, Marko; Altaye, Mekibib; Holland, Scott K.

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating “unusual” populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php. PMID:28275348

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation.

PubMed

Wilke, Marko; Altaye, Mekibib; Holland, Scott K

2017-01-01

Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php.

VOXEL-LEVEL MAPPING OF TRACER KINETICS IN PET STUDIES: A STATISTICAL APPROACH EMPHASIZING TISSUE LIFE TABLES.

PubMed

O'Sullivan, Finbarr; Muzi, Mark; Mankoff, David A; Eary, Janet F; Spence, Alexander M; Krohn, Kenneth A

2014-06-01

Most radiotracers used in dynamic positron emission tomography (PET) scanning act in a linear time-invariant fashion so that the measured time-course data are a convolution between the time course of the tracer in the arterial supply and the local tissue impulse response, known as the tissue residue function. In statistical terms the residue is a life table for the transit time of injected radiotracer atoms. The residue provides a description of the tracer kinetic information measurable by a dynamic PET scan. Decomposition of the residue function allows separation of rapid vascular kinetics from slower blood-tissue exchanges and tissue retention. For voxel-level analysis, we propose that residues be modeled by mixtures of nonparametrically derived basis residues obtained by segmentation of the full data volume. Spatial and temporal aspects of diagnostics associated with voxel-level model fitting are emphasized. Illustrative examples, some involving cancer imaging studies, are presented. Data from cerebral PET scanning with 18 F fluoro-deoxyglucose (FDG) and 15 O water (H2O) in normal subjects is used to evaluate the approach. Cross-validation is used to make regional comparisons between residues estimated using adaptive mixture models with more conventional compartmental modeling techniques. Simulations studies are used to theoretically examine mean square error performance and to explore the benefit of voxel-level analysis when the primary interest is a statistical summary of regional kinetics. The work highlights the contribution that multivariate analysis tools and life-table concepts can make in the recovery of local metabolic information from dynamic PET studies, particularly ones in which the assumptions of compartmental-like models, with residues that are sums of exponentials, might not be certain.

AASC Recommendations for the Education of an Applied Climatologist

NASA Astrophysics Data System (ADS)

Nielsen-Gammon, J. W.; Stooksbury, D.; Akyuz, A.; Dupigny-Giroux, L.; Hubbard, K. G.; Timofeyeva, M. M.

2011-12-01

The American Association of State Climatologists (AASC) has developed curricular recommendations for the education of future applied and service climatologists. The AASC was founded in 1976. Membership of the AASC includes state climatologists and others who work in state climate offices; climate researchers in academia and educators; applied climatologists in NOAA and other federal agencies; and the private sector. The AASC is the only professional organization dedicated solely to the growth and development of applied and service climatology. The purpose of the recommendations is to offer a framework for existing and developing academic climatology programs. These recommendations are intended to serve as a road map and to help distinguish the educational needs for future applied climatologists from those of operational meteorologists or other scientists and practitioners. While the home department of climatology students may differ from one program to the next, the most essential factor is that students can demonstrate a breadth and depth of understanding in the knowledge and tools needed to be an applied climatologist. Because the training of an applied climatologist requires significant depth and breadth, the Masters degree is recommended as the minimum level of education needed. This presentation will highlight the AASC recommendations. These include a strong foundation in: - climatology (instrumentation and data collection, climate dynamics, physical climatology, synoptic and regional climatology, applied climatology, climate models, etc.) - basic natural sciences and mathematics including calculus, physics, chemistry, and biology/ecology - fundamental atmospheric sciences (atmospheric dynamics, atmospheric thermodynamics, atmospheric radiation, and weather analysis/synoptic meteorology) and - data analysis and spatial analysis (descriptive statistics, statistical methods, multivariate statistics, geostatistics, GIS, etc.). The recommendations also include a secondary area of concentration (agriculture, economics, geography, hydrology, marine sciences, natural resources, policy, etc.) and a major applied climate research component.

Full-text publication of abstracts presented at European Orthodontic Society congresses.

PubMed

Livas, Christos; Pandis, Nikolaos; Ren, Yijin

2014-10-01

Empirical evidence has indicated that only a subsample of studies conducted reach full-text publication and this phenomenon has become known as publication bias. A form of publication bias is the selectively delayed full publication of conference abstracts. The objective of this article was to examine the publication status of oral abstracts and poster-presentation abstracts, included in the scientific program of the 82nd and 83rd European Orthodontic Society (EOS) congresses, held in 2006 and 2007, and to identify factors associated with full-length publication. A systematic search of PubMed and Google Scholar databases was performed in April 2013 using author names and keywords from the abstract title to locate abstract and full-article publications. Information regarding mode of presentation, type of affiliation, geographical origin, statistical results, and publication details were collected and analyzed using univariable and multivariable logistic regression. Approximately 51 per cent of the EOS 2006 and 55 per cent of the EOS 2007 abstracts appeared in print more than 5 years post congress. A mean period of 1.32 years elapsed between conference and publication date. Mode of presentation (oral or poster), use of statistical analysis, and research subject area were significant predictors for publication success. Inherent discrepancies of abstract reporting, mainly related to presentation of preliminary results and incomplete description of methods, may be considered in analogous studies. On average 52.2 per cent of the abstracts presented at the two EOS conferences reached full publication. Abstracts presented orally, including statistical analysis, were more likely to get published. © The Author 2013. Published by Oxford University Press on behalf of the European Orthodontic Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Costs explained by function rather than diagnosis--results from the SNAC Nordanstig elderly cohort in Sweden.

PubMed

Lindholm, C; Gustavsson, A; Jönsson, L; Wimo, A

2013-05-01

Because the prevalence of many brain disorders rises with age, and brain disorders are costly, the economic burden of brain disorders will increase markedly during the next decades. The purpose of this study is to analyze how the costs to society vary with different levels of functioning and with the presence of a brain disorder. Resource utilization and costs from a societal viewpoint were analyzed versus cognition, activities of daily living (ADL), instrumental activities of daily living (IADL), brain disorder diagnosis and age in a population-based cohort of people aged 65 years and older in Nordanstig in Northern Sweden. Descriptive statistics, non-parametric bootstrapping and a generalized linear model (GLM) were used for the statistical analyses. Most people were zero users of care. Societal costs of dementia were by far the highest, ranging from SEK 262,000 (mild) to SEK 519,000 per year (severe dementia). In univariate analysis, all measures of functioning were significantly related to costs. When controlling for ADL and IADL in the multivariate GLM, cognition did not have a statistically significant effect on total cost. The presence of a brain disorder did not impact total cost when controlling for function. The greatest shift in costs was seen when comparing no dependency in ADL and dependency in one basic ADL function. It is the level of functioning, rather than the presence of a brain disorder diagnosis, which predicts costs. ADLs are better explanatory variables of costs than Mini mental state examination. Most people in a population-based cohort are zero users of care. Copyright © 2012 John Wiley & Sons, Ltd.

Factors influencing initiation and duration of breast feeding in Ireland.

PubMed

Leahy-Warren, Patricia; Mulcahy, Helen; Phelan, Agnes; Corcoran, Paul

2014-03-01

The aim of this research was to identify factors associated with mothers breast feeding and to identify, for those who breast fed, factors associated with breast feeding for as long as planned. breast feeding rates in Ireland are amongst the lowest in Europe. Research evidence indicates that in order for mothers to be successful at breast feeding, multiplicities of supports are necessary for both initiation and duration. The nature of these supports in tandem with other influencing factors requires analysis from an Irish perspective. cross-sectional study involving public health nurses and mothers in Ireland. This paper presents the results of the mothers' evaluation. mothers (n=1715) with children less than three years were offered a choice of completing the self-report questionnaires online or by mail. Data were analysed and reported using descriptive and inferential statistics. four in every five participants breast fed their infant and two thirds of them breast fed as long as planned. The multivariate logistic regression analysis identified that third level education, being a first time mother or previously having breast fed, participating online, having more than two public health nurse visits, and having a positive infant feeding attitude were independently and statistically significantly associated with breast feeding. Among mothers who breast fed, being aged at least 35 years, participating online, having a positive infant feeding attitude and high breast feeding self-efficacy were independently and statistically significantly associated with breast feeding for as long as planned. findings from this study reinforce health inequalities therefore there needs to be a renewed commitment to reducing health inequalities in relation to breast feeding. this study has identified factors associated with initiation and duration of breast feeding that are potentially modifiable through public health interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantitative chromatin pattern description in Feulgen-stained nuclei as a diagnostic tool to characterize the oligodendroglial and astroglial components in mixed oligo-astrocytomas.

PubMed

Decaestecker, C; Lopes, B S; Gordower, L; Camby, I; Cras, P; Martin, J J; Kiss, R; VandenBerg, S R; Salmon, I

1997-04-01

The oligoastrocytoma, as a mixed glioma, represents a nosologic dilemma with respect to precisely defining the oligodendroglial and astroglial phenotypes that constitute the neoplastic cell lineages of these tumors. In this study, cell image analysis with Feulgen-stained nuclei was used to distinguish between oligodendroglial and astrocytic phenotypes in oligodendrogliomas and astrocytomas and then applied to mixed oligoastrocytomas. Quantitative features with respect to chromatin pattern (30 variables) and DNA ploidy (8 variables) were evaluated on Feulgen-stained nuclei in a series of 71 gliomas using computer-assisted microscopy. These included 32 oligodendrogliomas (OLG group: 24 grade II and 8 grade III tumors according to the WHO classification), 32 astrocytomas (AST group: 13 grade II and 19 grade III tumors), and 7 oligoastrocytomas (OLGAST group). Initially, image analysis with multivariate statistical analyses (Discriminant Analysis) could identify each glial tumor group. Highly significant statistical differences were obtained distinguishing the morphonuclear features of oligodendrogliomas from those of astrocytomas, regardless of their histological grade. When compared with the 7 mixed oligoastrocytomas under study, 5 exhibited DNA ploidy and chromatin pattern characteristics similar to grade II oligodendrogliomas, I to grade III oligodendrogliomas, and I to grade II astrocytomas. Using multifactorial statistical analyses (Discriminant Analysis combined with Principal Component Analysis). It was possible to quantify the proportion of "typical" glial cell phenotypes that compose grade II and III oligodendrogliomas and grade II and III astrocytomas in each mixed glioma. Cytometric image analysis may be an important adjunct to routine histopathology for the reproducible identification of neoplasms containing a mixture of oligodendroglial and astrocytic phenotypes.

Evolutionary Losses? The Growth of Graduate Programs at Undergraduate Colleges.

ERIC Educational Resources Information Center

McCormick, Alexander C.; Staklis, Sandra

This study examined the addition and expansion of graduate programs at primarily undergraduate colleges. The primary approach of the study was quantitative, consisting of descriptive and multivariate analysis of master's degree programs at colleges that were classified in 1994 as Baccalaureate Colleges. Data came from the 1994 and 2000 Carnegie…

Immigrants and Wealth Stratification in the U.S. JCPR Working Paper.

ERIC Educational Resources Information Center

Hao, Lingxin

This study examines the importance of including immigrants in studies of wealth stratification by race/ethnicity, using data from the 1992 and 1993 panels of the Survey of Income and Program Participation. It addresses the uniqueness of immigrants using descriptive and multivariate analyses by constructing a measure of wealth age that considers…

Gas-water two-phase flow characterization with Electrical Resistance Tomography and Multivariate Multiscale Entropy analysis.

PubMed

Tan, Chao; Zhao, Jia; Dong, Feng

2015-03-01

Flow behavior characterization is important to understand gas-liquid two-phase flow mechanics and further establish its description model. An Electrical Resistance Tomography (ERT) provides information regarding flow conditions at different directions where the sensing electrodes implemented. We extracted the multivariate sample entropy (MSampEn) by treating ERT data as a multivariate time series. The dynamic experimental results indicate that the MSampEn is sensitive to complexity change of flow patterns including bubbly flow, stratified flow, plug flow and slug flow. MSampEn can characterize the flow behavior at different direction of two-phase flow, and reveal the transition between flow patterns when flow velocity changes. The proposed method is effective to analyze two-phase flow pattern transition by incorporating information of different scales and different spatial directions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Effect of sexual steroids on boar kinematic sperm subpopulations.

PubMed

Ayala, E M E; Aragón, M A

2017-11-01

Here, we show the effects of sexual steroids, progesterone, testosterone, or estradiol on motility parameters of boar sperm. Sixteen commercial seminal doses, four each of four adult boars, were analyzed using computer assisted sperm analysis (CASA). Mean values of motility parameters were analyzed by bivariate and multivariate statistics. Principal component analysis (PCA), followed by hierarchical clustering, was applied on data of motility parameters, provided automatically as intervals by the CASA system. Effects of sexual steroids were described in the kinematic subpopulations identified from multivariate statistics. Mean values of motility parameters were not significantly changed after addition of sexual steroids. Multivariate graphics showed that sperm subpopulations were not sensitive to the addition of either testosterone or estradiol, but sperm subpopulations responsive to progesterone were found. Distribution of motility parameters were wide in controls but sharpened at distinct concentrations of progesterone. We conclude that kinematic sperm subpopulations responsive to progesterone are present in boar semen, and these subpopulations are masked in evaluations of mean values of motility parameters. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

The association of 83 plasma proteins with CHD mortality, BMI, HDL-, and total-cholesterol in men: applying multivariate statistics to identify proteins with prognostic value and biological relevance.

PubMed

Heidema, A Geert; Thissen, Uwe; Boer, Jolanda M A; Bouwman, Freek G; Feskens, Edith J M; Mariman, Edwin C M

2009-06-01

In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch monitoring project for cardiovascular disease risk factors, men who died of CHD between initial participation (1987-1991) and end of follow-up (January 1, 2000) (N = 44) and matched controls (N = 44) were selected. Baseline plasma concentrations of proteins were measured by a multiplex immunoassay. With the use of PLS, we identified 15 proteins with prognostic value for CHD mortality and sets of proteins associated with the intermediate end points. Subsequently, sets of proteins and intermediate end points were analyzed together by Principal Components Analysis, indicating that proteins involved in inflammation explained most of the variance, followed by proteins involved in metabolism and proteins associated with total-C. This study is one of the first in which the association of a large number of plasma proteins with CHD mortality and intermediate end points is investigated by applying multivariate statistics, providing insight in the relationships among proteins, intermediate end points and CHD mortality, and a set of proteins with prognostic value.

Multivariate Statistical Analysis: a tool for groundwater quality assessment in the hidrogeologic region of the Ring of Cenotes, Yucatan, Mexico.

NASA Astrophysics Data System (ADS)

Ye, M.; Pacheco Castro, R. B.; Pacheco Avila, J.; Cabrera Sansores, A.

2014-12-01

The karstic aquifer of Yucatan is a vulnerable and complex system. The first fifteen meters of this aquifer have been polluted, due to this the protection of this resource is important because is the only source of potable water of the entire State. Through the assessment of groundwater quality we can gain some knowledge about the main processes governing water chemistry as well as spatial patterns which are important to establish protection zones. In this work multivariate statistical techniques are used to assess the groundwater quality of the supply wells (30 to 40 meters deep) in the hidrogeologic region of the Ring of Cenotes, located in Yucatan, Mexico. Cluster analysis and principal component analysis are applied in groundwater chemistry data of the study area. Results of principal component analysis show that the main sources of variation in the data are due sea water intrusion and the interaction of the water with the carbonate rocks of the system and some pollution processes. The cluster analysis shows that the data can be divided in four clusters. The spatial distribution of the clusters seems to be random, but is consistent with sea water intrusion and pollution with nitrates. The overall results show that multivariate statistical analysis can be successfully applied in the groundwater quality assessment of this karstic aquifer.

Extracting chemical information from high-resolution Kβ X-ray emission spectroscopy

NASA Astrophysics Data System (ADS)

Limandri, S.; Robledo, J.; Tirao, G.

2018-06-01

High-resolution X-ray emission spectroscopy allows studying the chemical environment of a wide variety of materials. Chemical information can be obtained by fitting the X-ray spectra and observing the behavior of some spectral features. Spectral changes can also be quantified by means of statistical parameters calculated by considering the spectrum as a probability distribution. Another possibility is to perform statistical multivariate analysis, such as principal component analysis. In this work the performance of these procedures for extracting chemical information in X-ray emission spectroscopy spectra for mixtures of Mn2+ and Mn4+ oxides are studied. A detail analysis of the parameters obtained, as well as the associated uncertainties is shown. The methodologies are also applied for Mn oxidation state characterization of double perovskite oxides Ba1+xLa1-xMnSbO6 (with 0 ≤ x ≤ 0.7). The results show that statistical parameters and multivariate analysis are the most suitable for the analysis of this kind of spectra.

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

DOE PAGES

Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; ...

2014-12-02

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signaturemore » and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

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

Belianinov, Alex, E-mail: belianinova@ornl.gov; Ganesh, Panchapakesan; Lin, Wenzhi

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe{sub 0.55}Se{sub 0.45} (T{sub c} = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe{sub 1−x}Se{sub x} structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified bymore » their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

A Study of Strengths and Weaknesses of Descriptive Assessment from Principals, Teachers and Experts Points of View in Chaharmahal and Bakhteyari Primary Schools

ERIC Educational Resources Information Center

Sharief, Mostafa; Naderi, Mahin; Hiedari, Maryam Shoja; Roodbari, Omolbanin; Jalilvand, Mohammad Reza

2012-01-01

The aim of current study is to determine the strengths and weaknesses of descriptive evaluation from the viewpoint of principals, teachers and experts of Chaharmahal and Bakhtiari province. A descriptive survey was performed. Statistical population includes 208 principals, 303 teachers, and 100 executive experts of descriptive evaluation scheme in…

Detecting event-related changes of multivariate phase coupling in dynamic brain networks.

PubMed

Canolty, Ryan T; Cadieu, Charles F; Koepsell, Kilian; Ganguly, Karunesh; Knight, Robert T; Carmena, Jose M

2012-04-01

Oscillatory phase coupling within large-scale brain networks is a topic of increasing interest within systems, cognitive, and theoretical neuroscience. Evidence shows that brain rhythms play a role in controlling neuronal excitability and response modulation (Haider B, McCormick D. Neuron 62: 171-189, 2009) and regulate the efficacy of communication between cortical regions (Fries P. Trends Cogn Sci 9: 474-480, 2005) and distinct spatiotemporal scales (Canolty RT, Knight RT. Trends Cogn Sci 14: 506-515, 2010). In this view, anatomically connected brain areas form the scaffolding upon which neuronal oscillations rapidly create and dissolve transient functional networks (Lakatos P, Karmos G, Mehta A, Ulbert I, Schroeder C. Science 320: 110-113, 2008). Importantly, testing these hypotheses requires methods designed to accurately reflect dynamic changes in multivariate phase coupling within brain networks. Unfortunately, phase coupling between neurophysiological signals is commonly investigated using suboptimal techniques. Here we describe how a recently developed probabilistic model, phase coupling estimation (PCE; Cadieu C, Koepsell K Neural Comput 44: 3107-3126, 2010), can be used to investigate changes in multivariate phase coupling, and we detail the advantages of this model over the commonly employed phase-locking value (PLV; Lachaux JP, Rodriguez E, Martinerie J, Varela F. Human Brain Map 8: 194-208, 1999). We show that the N-dimensional PCE is a natural generalization of the inherently bivariate PLV. Using simulations, we show that PCE accurately captures both direct and indirect (network mediated) coupling between network elements in situations where PLV produces erroneous results. We present empirical results on recordings from humans and nonhuman primates and show that the PCE-estimated coupling values are different from those using the bivariate PLV. Critically on these empirical recordings, PCE output tends to be sparser than the PLVs, indicating fewer significant interactions and perhaps a more parsimonious description of the data. Finally, the physical interpretation of PCE parameters is straightforward: the PCE parameters correspond to interaction terms in a network of coupled oscillators. Forward modeling of a network of coupled oscillators with parameters estimated by PCE generates synthetic data with statistical characteristics identical to empirical signals. Given these advantages over the PLV, PCE is a useful tool for investigating multivariate phase coupling in distributed brain networks.

Intercomparison of textural parameters of intertidal sediments generated by different statistical procedures, and implications for a unifying descriptive nomenclature

NASA Astrophysics Data System (ADS)

Fan, Daidu; Tu, Junbiao; Cai, Guofu; Shang, Shuai

2015-06-01

Grain-size analysis is a basic routine in sedimentology and related fields, but diverse methods of sample collection, processing and statistical analysis often make direct comparisons and interpretations difficult or even impossible. In this paper, 586 published grain-size datasets from the Qiantang Estuary (East China Sea) sampled and analyzed by the same procedures were merged and their textural parameters calculated by a percentile and two moment methods. The aim was to explore which of the statistical procedures performed best in the discrimination of three distinct sedimentary units on the tidal flats of the middle Qiantang Estuary. A Gaussian curve-fitting method served to simulate mixtures of two normal populations having different modal sizes, sorting values and size distributions, enabling a better understanding of the impact of finer tail components on textural parameters, as well as the proposal of a unifying descriptive nomenclature. The results show that percentile and moment procedures yield almost identical results for mean grain size, and that sorting values are also highly correlated. However, more complex relationships exist between percentile and moment skewness (kurtosis), changing from positive to negative correlations when the proportions of the finer populations decrease below 35% (10%). This change results from the overweighting of tail components in moment statistics, which stands in sharp contrast to the underweighting or complete amputation of small tail components by the percentile procedure. Intercomparisons of bivariate plots suggest an advantage of the Friedman & Johnson moment procedure over the McManus moment method in terms of the description of grain-size distributions, and over the percentile method by virtue of a greater sensitivity to small variations in tail components. The textural parameter scalings of Folk & Ward were translated into their Friedman & Johnson moment counterparts by application of mathematical functions derived by regression analysis of measured and modeled grain-size data, or by determining the abscissa values of intersections between auxiliary lines running parallel to the x-axis and vertical lines corresponding to the descriptive percentile limits along the ordinate of representative bivariate plots. Twofold limits were extrapolated for the moment statistics in relation to single descriptive terms in the cases of skewness and kurtosis by considering both positive and negative correlations between percentile and moment statistics. The extrapolated descriptive scalings were further validated by examining entire size-frequency distributions simulated by mixing two normal populations of designated modal size and sorting values, but varying in mixing ratios. These were found to match well in most of the proposed scalings, although platykurtic and very platykurtic categories were questionable when the proportion of the finer population was below 5%. Irrespective of the statistical procedure, descriptive nomenclatures should therefore be cautiously used when tail components contribute less than 5% to grain-size distributions.

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean

Harnessing Multivariate Statistics for Ellipsoidal Data in Structural Geology

NASA Astrophysics Data System (ADS)

Roberts, N.; Davis, J. R.; Titus, S.; Tikoff, B.

2015-12-01

Most structural geology articles do not state significance levels, report confidence intervals, or perform regressions to find trends. This is, in part, because structural data tend to include directions, orientations, ellipsoids, and tensors, which are not treatable by elementary statistics. We describe a full procedural methodology for the statistical treatment of ellipsoidal data. We use a reconstructed dataset of deformed ooids in Maryland from Cloos (1947) to illustrate the process. Normalized ellipsoids have five degrees of freedom and can be represented by a second order tensor. This tensor can be permuted into a five dimensional vector that belongs to a vector space and can be treated with standard multivariate statistics. Cloos made several claims about the distribution of deformation in the South Mountain fold, Maryland, and we reexamine two particular claims using hypothesis testing: 1) octahedral shear strain increases towards the axial plane of the fold; 2) finite strain orientation varies systematically along the trend of the axial trace as it bends with the Appalachian orogen. We then test the null hypothesis that the southern segment of South Mountain is the same as the northern segment. This test illustrates the application of ellipsoidal statistics, which combine both orientation and shape. We report confidence intervals for each test, and graphically display our results with novel plots. This poster illustrates the importance of statistics in structural geology, especially when working with noisy or small datasets.

Frequency of TV viewing and prevalence of overweight and obesity among adult women in Bangladesh: a cross-sectional study.

PubMed

Ghose, Bishwajit

2017-01-31

Research in developed countries has demonstrated an association of varying degrees between watching TV and the risk of being overweight and obese. However, there is no evidence of such an association in the context of the South Asian population. To investigate whether watching TV increases the risk of being overweight and obese among women in Bangladesh. Rural and urban areas in Bangladesh. Participants were 16 624 non-pregnant women aged between 15 and 49 years. The study was based on cross-sectional data from the Bangladesh Demographic and Health Survey (BDHS) conducted in 2014. The main outcome variables were overweight and obesity measured by body mass index. Data were analysed by using descriptive statistics, cross-tabulation and multivariable logistic regression models. The prevalence of overweight and obesity in the sample population were, respectively, 4.5% (4.18% to 4.82%) and 20% (95% CI 19.39% to 20.61%). In the multivariable analysis, no statistically significant association was found between watching TV and being overweight. However, the odds of being obese among rural women were 63% higher (adjusted OR (AOR) 1.625, 95% CI 1.179 to 2.241) among those who watched less than once a week, and 68% (AOR 1.683, 95% CI 1.029 to 2.751) higher among women who watched TV at least once a week compared to those who did not watch TV at all. Urban women who watched TV at least once a week were 67% more likely to be obese (AOR 1.665, 95% CI 1.079 to 2.568) compared to those who did not watch at all. Prevalence of overweight and obesity has risen considerably among women aged between 15 and 49 years since the previous estimates based on BDHS data. Frequent TV watching was associated with a higher risk of being obese among adult women in rural areas. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Multivariate test power approximations for balanced linear mixed models in studies with missing data.

PubMed

Ringham, Brandy M; Kreidler, Sarah M; Muller, Keith E; Glueck, Deborah H

2016-07-30

Multilevel and longitudinal studies are frequently subject to missing data. For example, biomarker studies for oral cancer may involve multiple assays for each participant. Assays may fail, resulting in missing data values that can be assumed to be missing completely at random. Catellier and Muller proposed a data analytic technique to account for data missing at random in multilevel and longitudinal studies. They suggested modifying the degrees of freedom for both the Hotelling-Lawley trace F statistic and its null case reference distribution. We propose parallel adjustments to approximate power for this multivariate test in studies with missing data. The power approximations use a modified non-central F statistic, which is a function of (i) the expected number of complete cases, (ii) the expected number of non-missing pairs of responses, or (iii) the trimmed sample size, which is the planned sample size reduced by the anticipated proportion of missing data. The accuracy of the method is assessed by comparing the theoretical results to the Monte Carlo simulated power for the Catellier and Muller multivariate test. Over all experimental conditions, the closest approximation to the empirical power of the Catellier and Muller multivariate test is obtained by adjusting power calculations with the expected number of complete cases. The utility of the method is demonstrated with a multivariate power analysis for a hypothetical oral cancer biomarkers study. We describe how to implement the method using standard, commercially available software products and give example code. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Testing for significance of phase synchronisation dynamics in the EEG.

PubMed

Daly, Ian; Sweeney-Reed, Catherine M; Nasuto, Slawomir J

2013-06-01

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

Processes and subdivisions in diogenites, a multivariate statistical analysis

NASA Technical Reports Server (NTRS)

Harriott, T. A.; Hewins, R. H.

1984-01-01

Multivariate statistical techniques used on diogenite orthopyroxene analyses show the relationships that occur within diogenites and the two orthopyroxenite components (class I and II) in the polymict diogenite Garland. Cluster analysis shows that only Peckelsheim is similar to Garland class I (Fe-rich) and the other diogenites resemble Garland class II. The unique diogenite Y 75032 may be related to type I by fractionation. Factor analysis confirms the subdivision and shows that Fe does not correlate with the weakly incompatible elements across the entire pyroxene composition range, indicating that igneous fractionation is not the process controlling total diogenite composition variation. The occurrence of two groups of diogenites is interpreted as the result of sampling or mixing of two main sequences of orthopyroxene cumulates with slightly different compositions.

Evaluating the role of admixture in cancer therapy via in vitro drug response and multivariate genome-wide associations

PubMed Central

Jack, John; Havener, Tammy M; McLeod, Howard L; Motsinger-Reif, Alison A; Foster, Matthew

2015-01-01

Aim: We investigate the role of ethnicity and admixture in drug response across a broad group of chemotherapeutic drugs. Also, we generate hypotheses on the genetic variants driving differential drug response through multivariate genome-wide association studies. Methods: Immortalized lymphoblastoid cell lines from 589 individuals (Hispanic or non-Hispanic/Caucasian) were used to investigate dose-response for 28 chemotherapeutic compounds. Univariate and multivariate statistical models were used to elucidate associations between genetic variants and differential drug response as well as the role of ethnicity in drug potency and efficacy. Results & Conclusion: For many drugs, the variability in drug response appears to correlate with self-reported race and estimates of genetic ancestry. Additionally, multivariate genome-wide association analyses offered interesting hypotheses governing these differential responses. PMID:26314407

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Spousal Caregiver Burden and Its Relation with Disability in Schizophrenia

PubMed Central

Arun, R.; Inbakamal, S.; Tharyan, Anna; Premkumar, Prasanna S.

2018-01-01

Background: Schizophrenia, a chronic psychiatric disorder, can affect one's productivity and psychosocial functioning. In Indian context, the responsibility of caring persons with schizophrenia is increasingly on their spouses. Spousal caregiver experience and its relation with disability in schizophrenia need to be studied. Materials and Methods: We conducted a cross-sectional study among 52 outpatients with schizophrenia and their spouses attending a tertiary psychiatric center. The objectives were: (a) to explore spousal caregiver burden in schizophrenia and (b) to assess the relation between disability and spousal caregiver burden. The study adopted recommended ethical principles. Scales such as Burden Assessment Schedule, Indian Disability Evaluation and Assessment Scale (IDEAS), and Positive and Negative Syndrome Scale were used to collect appropriate data. Descriptive analysis, bivariate analysis, and multivariate analysis were done in SPSS software version 16.0. Results: The mean spousal caregiver burden score was 73.5 (standard deviation: 14.0). In bivariate analysis, disability, duration of schizophrenia, severity of schizophrenia, place of residence, and socioeconomic status had statistically significant relation with spousal caregiver burden. Adjusted for spouses’ age, gender, and other significant factors in bivariate analysis, the IDEAS global disability score (2.6, [confidence interval 0.5–3.8, P = 0.013]) retained statistically significant association with spousal caregiver burden. Conclusion: Spouses of persons with schizophrenia experience significant caregiver burden. Disability was found to be the most powerful determinant of spousal caregiver burden in the sample. Focus on disability alleviation in the management of schizophrenia may help reduce spousal caregiver burden. PMID:29403125

Perceived difficulty quitting predicts enrollment in a smoking-cessation program for patients with head and neck cancer.

PubMed

Duffy, Sonia A; Scheumann, Angela L; Fowler, Karen E; Darling-Fisher, Cynthia; Terrell, Jeffrey E

2010-05-01

To determine the predictors of participation in a smoking-cessation program among patients with head and neck cancer. This cross-sectional study is a substudy of a larger, randomized trial of patients with head and neck cancer that determined the predictors of smokers' participation in a cessation intervention. Otolaryngology clinics at three Veterans Affairs medical centers (Ann Arbor, MI, Gainesville, FL, and Dallas, TX), and the University of Michigan Hospital in Ann Arbor. 286 patients who had smoked within six months of the screening survey were eligible for a smoking-cessation intervention. Descriptive statistics and bivariate and multivariate logistic regression were used to determine the independent predictors of smokers' participation in an intervention study. Perceived difficulty quitting (as a construct of self-efficacy), health behaviors (i.e., smoking and problem drinking), clinical characteristics (i.e., depression and cancer site and stage), and demographic variables. Forty-eight percent of those eligible participated. High perceived difficulty quitting was the only statistically significant predictor of participation, whereas problem drinking, lower depressive symptoms, and laryngeal cancer site approached significance. Special outreach may be needed to reach patients with head and neck cancer who are overly confident in quitting, problem drinkers, and patients with laryngeal cancer. Oncology nurses are in an opportune position to assess patients' perceived difficulty quitting smoking and motivate them to enroll in cessation programs, ultimately improving quality of life, reducing risk of recurrence, and increasing survival for this population.

Impact of patient and environmental factors on capillary refill time in adults.

PubMed

Anderson, Bronwyn; Kelly, Anne-Maree; Kerr, Debra; Clooney, Megan; Jolley, Damien

2008-01-01

Capillary refill time (CRT) has been taught as a rapid indicator of circulatory status. The aim of this study was to define normal CRT in the Australian context and the environmental, patient, and drug factors that influence it. This prospective observational study included healthy adults at hospital clinics, workplaces, universities, and community groups. Volunteer participants provided their age, sex, ethnic group, and use of hypertensive or cardiac medications. Capillary refill time, ambient temperature, and patient temperature were recorded in a standard manner. Data were analyzed using descriptive statistics and regression analyses. The 95th percentile was used to define the upper limit of normal. One thousand participants were included; 57% were women, 90% were white, and 21% were taking cardiac medications. The median CRT was 1.9 seconds (95th percentile, 3.5 seconds). The CRT increased 3.3% for each additional decade of age. The CRT was also on average 7% lower in men than in women. The CRT decreased by 1.2% per degree-Celsius rise of ambient temperature, independently of patient's temperature, and decreased by 5% for each degree-Celsius rise in patient temperature, independently of ambient temperature. On multivariant analysis, age, sex, ambient temperature, and patient temperature were statistically significant predictors of CRT, but together explain only 8% of the observed variability. Capillary refill time varies with environmental and patient factors, but these account for only a small proportion of the variability observed. Its suitability as a reliable clinical test is doubtful.

Earth-System Scales of Biodiversity Variability in Shallow Continental Margin Seafloor Ecosystems

NASA Astrophysics Data System (ADS)

Moffitt, S. E.; White, S. M.; Hill, T. M.; Kennett, J.

2015-12-01

High-resolution paleoceanographic sedimentary sequences allow for the description of ecosystem sensitivity to earth-system scales of climate and oceanographic change. Such archives from Santa Barbara Basin, California record the ecological consequences to seafloor ecosystems of climate-forced shifts in the California Current Oxygen Minimum Zone (OMZ). Here we use core MV0508-20JPC dated to 735,000±5,000 years ago (Marine Isotope Stage 18) as a "floating window" of millennial-scale ecological variability. For this investigation, previously published archives of planktonic δ18O (Globigerina bulloides) record stadial and interstadial oscillations in surface ocean temperature. Core MV0508-20JPC is an intermittently laminated archive, strongly influenced by the California Current OMZ, with continuously preserved benthic foraminifera and discontinuously preserved micro-invertebrates, including ophiuroids, echinoderms, ostracods, gastropods, bivalves and scaphopods. Multivariate statistical approaches, such as ordinations and cluster analyses, describe climate-driven changes in both foraminiferal and micro-invertebrate assemblages. Statistical ordinations illustrate that the shallow continental margin seafloor underwent predictable phase-shifts in oxygenation and biodiversity across stadial and interstadial events. A narrow suite of severely hypoxic taxa characterized foraminiferal communities from laminated intervals, including Bolivina tumida, Globobulimina spp., and Nonionella stella. Foraminiferal communities from bioturbated intervals are diverse and >60% similar to each other, and they are associated with echinoderm, ostracod and mollusc fossils. As with climate shifts in the latest Quaternary, there is a sensitive benthic ecosystem response in mid-Pleistocene continental margins to climatically related changes in OMZ strength.

Prognostic factors in pediatric sepsis study, from the Spanish Society of Pediatric Intensive Care.

PubMed

Vila Pérez, David; Jordan, Iolanda; Esteban, Elisabeth; García-Soler, Patricia; Murga, Vega; Bonil, Vanesa; Ortiz, Irene; Flores, Carlos; Bustinza, Amaya; Cambra, Francisco Jose

2014-02-01

Sepsis and septic shock represent up to 30% of admitted patients in pediatric intensive care units, with a mortality that can exceed 10%. The objective of this study is to determine the prognostic factors for mortality in sepsis. Multicenter prospective descriptive study with patients (aged 7 days to 18 years) admitted to the pediatric intensive care units for sepsis, between January 2011 and April 2012. Data from 136 patients were collected. Eighty-seven were male (63.9%). The median age was a year and a half (P25-75 0.3-5.5 years). In 41 cases (30.1%), there were underlying diseases. The most common etiology was Neisseria meningitidis (31 cases, 22.8%) followed by Streptococcus pneumoniae (16 patients, 11.8%). Seventeen cases were fatal (12.5%). In the statistical analysis, the factors associated with mortality were nosocomial infection (P = 0.004), hypotension (P <0.001) and heart and kidney failure (P < 0.001 and P = 0.004, respectively). The numbers of leukocytes, neutrophils and platelets on admission were statistically lower in the group that died (P was 0.006, 0.013 and <0.001, respectively). Multivariate analysis showed that multiple organ failure, neutropenia, purpura or coagulopathy and nosocomial infection were independent risk factors for increased mortality (odds ratio: 17, 4.9, 9 and 9.2, respectively). Patients with sepsis and multiorgan failure, especially those with nosocomial infection or the presence of neutropenia or purpura, have a worse prognosis and should be monitored and treated early.

The prevalence and practice of academies of medical educators: a survey of U.S. medical schools.

PubMed

Searle, Nancy S; Thompson, Britta M; Friedland, Joan A; Lomax, James W; Drutz, Jan E; Coburn, Michael; Nelson, Elizabeth A

2010-01-01

Academies of medical educators can be defined as formal organizations of academic teaching faculty recognized for excellence in their contributions to their school's education mission and who, as a group, serve specific needs of the institution. The authors studied the characteristics of academies, including the processes for admission, selection, and retention of academy members; the types of faculty who are academy members; program goals; benefits offered by academies to the individual and to the institution; funding sources and amounts; and the rapid increase in academies since 2003. In 2008, the authors sent an online questionnaire to 127 U.S. medical schools. Responses were analyzed using descriptive statistics. To determine differences between groups, multivariate analysis of variance was performed. Correlation analysis (Pearson r) was used to identify association between variables. Effect size was determined using eta squared (eta2). Thirty-six of the 122 responding schools (96% response rate) reported having academies; 21 schools had initiated academies since 2003, and 33 schools were planning or considering academies. There was a statistically significant difference between academies established before 2004 and in 2004 regarding benefits offered to individuals, membership terms and maintenance requirements, and goals. Rogers' theory of the diffusion of innovation may explain the recent spread of academies. When beginning or reexamining existing academy programs, institutions should consider goals, application process, benefits offered to members as well as the institution, expendable resources, and means of support, because the final product depends on the choices made at the beginning.