Testing Mean Differences among Groups: Multivariate and Repeated Measures Analysis with Minimal Assumptions

PubMed Central

Bathke, Arne C.; Friedrich, Sarah; Pauly, Markus; Konietschke, Frank; Staffen, Wolfgang; Strobl, Nicolas; Höller, Yvonne

2018-01-01

ABSTRACT To date, there is a lack of satisfactory inferential techniques for the analysis of multivariate data in factorial designs, when only minimal assumptions on the data can be made. Presently available methods are limited to very particular study designs or assume either multivariate normality or equal covariance matrices across groups, or they do not allow for an assessment of the interaction effects across within-subjects and between-subjects variables. We propose and methodologically validate a parametric bootstrap approach that does not suffer from any of the above limitations, and thus provides a rather general and comprehensive methodological route to inference for multivariate and repeated measures data. As an example application, we consider data from two different Alzheimer’s disease (AD) examination modalities that may be used for precise and early diagnosis, namely, single-photon emission computed tomography (SPECT) and electroencephalogram (EEG). These data violate the assumptions of classical multivariate methods, and indeed classical methods would not have yielded the same conclusions with regards to some of the factors involved. PMID:29565679

Experiments with a three-dimensional statistical objective analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

Baker, Wayman E.; Bloom, Stephen C.; Woollen, John S.; Nestler, Mark S.; Brin, Eugenia

1987-01-01

A three-dimensional (3D), multivariate, statistical objective analysis scheme (referred to as optimum interpolation or OI) has been developed for use in numerical weather prediction studies with the FGGE data. Some novel aspects of the present scheme include: (1) a multivariate surface analysis over the oceans, which employs an Ekman balance instead of the usual geostrophic relationship, to model the pressure-wind error cross correlations, and (2) the capability to use an error correlation function which is geographically dependent. A series of 4-day data assimilation experiments are conducted to examine the importance of some of the key features of the OI in terms of their effects on forecast skill, as well as to compare the forecast skill using the OI with that utilizing a successive correction method (SCM) of analysis developed earlier. For the three cases examined, the forecast skill is found to be rather insensitive to varying the error correlation function geographically. However, significant differences are noted between forecasts from a two-dimensional (2D) version of the OI and those from the 3D OI, with the 3D OI forecasts exhibiting better forecast skill. The 3D OI forecasts are also more accurate than those from the SCM initial conditions. The 3D OI with the multivariate oceanic surface analysis was found to produce forecasts which were slightly more accurate, on the average, than a univariate version.

Risk Factors for Central Serous Chorioretinopathy: Multivariate Approach in a Case-Control Study.

PubMed

Chatziralli, Irini; Kabanarou, Stamatina A; Parikakis, Efstratios; Chatzirallis, Alexandros; Xirou, Tina; Mitropoulos, Panagiotis

2017-07-01

The purpose of this prospective study was to investigate the potential risk factors associated independently with central serous retinopathy (CSR) in a Greek population, using multivariate approach. Participants in the study were 183 consecutive patients diagnosed with CSR and 183 controls, matched for age. All participants underwent complete ophthalmological examination and information regarding their sociodemographic, clinical, medical and ophthalmological history were recorded, so as to assess potential risk factors for CSR. Univariate and multivariate analysis was performed. Univariate analysis showed that male sex, high educational status, high income, alcohol consumption, smoking, hypertension, coronary heart disease, obstructive sleep apnea, autoimmune disorders, H. pylori infection, type A personality and stress, steroid use, pregnancy and hyperopia were associated with CSR, while myopia was found to protect from CSR. In multivariate analysis, alcohol consumption, hypertension, coronary heart disease and autoimmune disorders lost their significance, while the remaining factors were all independently associated with CSR. It is important to take into account the various risk factors for CSR, so as to define vulnerable groups and to shed light into the pathogenesis of the disease.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

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

The potential use of cuticular hydrocarbons and multivariate analysis to age empty puparial cases of Calliphora vicina and Lucilia sericata.

PubMed

Moore, Hannah E; Pechal, Jennifer L; Benbow, M Eric; Drijfhout, Falko P

2017-05-16

Cuticular hydrocarbons (CHC) have been successfully used in the field of forensic entomology for identifying and ageing forensically important blowfly species, primarily in the larval stages. However in older scenes where all other entomological evidence is no longer present, Calliphoridae puparial cases can often be all that remains and therefore being able to establish the age could give an indication of the PMI. This paper examined the CHCs present in the lipid wax layer of insects, to determine the age of the cases over a period of nine months. The two forensically important species examined were Calliphora vicina and Lucilia sericata. The hydrocarbons were chemically extracted and analysed using Gas Chromatography - Mass Spectrometry. Statistical analysis was then applied in the form of non-metric multidimensional scaling analysis (NMDS), permutational multivariate analysis of variance (PERMANOVA) and random forest models. This study was successful in determining age differences within the empty cases, which to date, has not been establish by any other technique.

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.

Association between Adult Romantic Attachment Styles and Family-of-Origin Expressive Atmosphere

ERIC Educational Resources Information Center

Smith, Shannon D.; Ng, Kok-Mun

2009-01-01

This study examined the associations between attachment quality and perceived family-of-origin expressive atmosphere (FOEA) in a convenience sample of 279 participants. Multivariate analysis of variance (MAN-OVA) was used to examine the associations between attachment style and FOEA, and hierarchical regression was used to analyze FOEA as a…

Variation of heavy metals in recent sediments from Piratininga Lagoon (Brazil): interpretation of geochemical data with the aid of multivariate analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Campredon, R.; Abrao, J. J.; Bernat, M.; Latouche, C.

1994-06-01

In the last decade, the Atlantic coast of south-eastern Brazil has been affected by increasing deforestation and anthropogenic effluents. Sediments in the coastal lagoons have recorded the process of such environmental change. Thirty-seven sediment samples from three cores in Piratininga Lagoon, Rio de Janeiro, were analyzed for their major components and minor element concentrations in order to examine geochemical characteristics and the depositional environment and to investigate the variation of heavy metals of environmental concern. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed on the analytical data set to help visualize the sample clusters and the element associations. On the whole, the sediment samples from each core are similar and the sample clusters corresponding to the three cores are clearly separated, as a result of the different conditions of sedimentation. Some changes in the depositional environment are recognized using the results of multivariate analysis. The enrichment of Pb, Cu, and Zn in the upper parts of cores is in agreement with increasing anthropogenic influx (pollution).

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Handwriting Examination: Moving from Art to Science

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

Jarman, K.H.; Hanlen, R.C.; Manzolillo, P.A.

In this document, we present a method for validating the premises and methodology of forensic handwriting examination. This method is intuitively appealing because it relies on quantitative measurements currently used qualitatively by FDE's in making comparisons, and it is scientifically rigorous because it exploits the power of multivariate statistical analysis. This approach uses measures of both central tendency and variation to construct a profile for a given individual. (Central tendency and variation are important for characterizing an individual's writing and both are currently used by FDE's in comparative analyses). Once constructed, different profiles are then compared for individuality using clustermore » analysis; they are grouped so that profiles within a group cannot be differentiated from one another based on the measured characteristics, whereas profiles between groups can. The cluster analysis procedure used here exploits the power of multivariate hypothesis testing. The result is not only a profile grouping but also an indication of statistical significance of the groups generated.« less

Identification of Enterococcus, Streptococcus, and Staphylococcus by Multivariate Analysis of Proton Magnetic Resonance Spectroscopic Data from Plate Cultures

PubMed Central

Bourne, Roger; Himmelreich, Uwe; Sharma, Ansuiya; Mountford, Carolyn; Sorrell, Tania

2001-01-01

A new fingerprinting technique with the potential for rapid identification of bacteria was developed by combining proton magnetic resonance spectroscopy (1H MRS) with multivariate statistical analysis. This resulted in an objective identification strategy for common clinical isolates belonging to the bacterial species Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Streptococcus pneumoniae, Streptococcus pyogenes, Streptococcus agalactiae, and the Streptococcus milleri group. Duplicate cultures of 104 different isolates were examined one or more times using 1H MRS. A total of 312 cultures were examined. An optimized classifier was developed using a bootstrapping process and a seven-group linear discriminant analysis to provide objective classification of the spectra. Identification of isolates was based on consistent high-probability classification of spectra from duplicate cultures and achieved 92% agreement with conventional methods of identification. Fewer than 1% of isolates were identified incorrectly. Identification of the remaining 7% of isolates was defined as indeterminate. PMID:11474013

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

ERIC Educational Resources Information Center

Park, Hyeran; Nielsen, Wendy; Woodruff, Earl

2014-01-01

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…

The College Application Gauntlet: A Systematic Analysis of the Steps to Four-Year College Enrollment

ERIC Educational Resources Information Center

Klasik, Daniel

2012-01-01

Few studies have examined the steps to college enrollment between college aspiration and college enrollment and how these steps might present a barrier to four-year college enrollment. This study used data from the Education Longitudinal Study: 2002 and employed a multivariate random effects logistic framework to examine the completion of nine…

Gender Differences in Intrahousehold Schooling Outcomes: The Role of Sibling Characteristics and Birth-Order Effects

ERIC Educational Resources Information Center

Rammohan, Anu; Dancer, Diane

2008-01-01

In this paper we examine the influence of gender, sibling characteristics and birth order on the schooling attainment of school-age Egyptian children. We use multivariate analysis to simultaneously examine three different schooling outcomes of a child having "no schooling", "less than the desired level of schooling", and an…

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Waddell non-organic signs: new evidence suggests somatic amplification among outpatient chronic pain patients.

PubMed

Wygant, Dustin B; Arbisi, Paul A; Bianchini, Kevin J; Umlauf, Robert L

2017-04-01

Waddell et al. identified a set of eight non-organic signs in 1980. There has been controversy about their meaning, particularly with respect to their use as validity indicators. The current study examined the Waddell signs in relation to measures of somatic amplification or over-reporting in a sample of outpatient chronic pain patients. We examined the degree to which these signs were associated with measures of over-reporting. This study examined scores on the Waddell signs in relation to over-reporting indicators in an outpatient chronic pain sample. We examined 230 chronic pain patients treated at a multidisciplinary pain clinic. The majority of these patients presented with primary back or spinal injuries. The outcome measures used in the study were Waddell signs, Modified Somatic Perception Questionnaire, Pain Disability Index, and the Minnesota Multiphasic Personality Inventory-2 Restructured Form. We examined Waddell signs using multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA), receiver operating characteristic analysis, classification accuracy, and relative risk ratios. Multivariate analysis of variance and ANOVA showed a significant association between Waddell signs and somatic amplification. Classification analyses showed increased odds of somatic amplification at a Waddell score of 2 or 3. Our results found significant evidence of an association between Waddell signs and somatic over-reporting. Elevated scores on the Waddell signs (particularly scores higher than 2 and 3) were associated with increased odds of exhibiting somatic over-reporting. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of the Child and Youth Resilience Measure (CYRM-28) on a Sample of At-Risk New Zealand Youth

ERIC Educational Resources Information Center

Sanders, Jackie; Munford, Robyn; Thimasarn-Anwar, Tewaporn; Liebenberg, Linda

2017-01-01

Purpose: This article reports on an examination of the psychometric properties of the 28-item Child and Youth Resilience Measure (CYRM-28). Methods: Exploratory factor analysis, confirmatory factor analysis, Cronbach's a, "t"-tests, correlations, and multivariate analysis of variance were applied to data collected via interviews from 593…

ANALYSIS OF LOTIC MACROINVERTEBRATE ASSEMBLAGES IN CALIFORNIA'S CENTRAL VALLEY

EPA Science Inventory

Using multivariate and cluster analyses, we examined the relaitonships between chemical and physical characteristics and macroinvertebrate assemblages at sites sampled by R-EMAP in California's Central Valley. By contrasting results where community structure was summarized as met...

Is there a relationship between periodontal conditions and number of medications among the elderly?

PubMed

Natto, Zuhair S; Aladmawy, Majdi; Alshaeri, Heba K; Alasqah, Mohammed; Papas, Athena

2016-03-01

To investigate possible correlations of clinical attachment level and pocket depth with number of medications in elderly individuals. Intra-oral examinations for 139 patients visiting Tufts dental clinic were done. Periodontal assessments were performed with a manual UNC-15 periodontal probe to measure probing depth (PD) and clinical attachment level (CAL) at 6 sites. Complete lists of patients' medications were obtained during the examinations. Statistical analysis involved Kruskal-Wallis, chi square and multivariate logistic regression analyses. Age and health status attained statistical significance (p< 0.05), in contingency table analysis with number of medications. Number of medications had an effect on CAL: increased attachment loss was observed when 4 or more medications were being taken by the patient. Number of medications did not have any effect on periodontal PD. In multivariate logistic regression analysis, 6 or more medications had a higher risk of attachment loss (>3mm) when compared to the no-medication group, in crude OR (1.20, 95% CI:0.22-6.64), and age adjusted (OR=1.16, 95% CI:0.21-6.45), but not with the multivariate model (OR=0.71, 95% CI:0.11-4.39). CAL seems to be more sensitive to the number of medications taken, when compared to PD. However, it is not possible to discriminate at exactly what number of drug combinations the breakdown in CAL will happen. We need to do further analysis, including more subjects, to understand the possible synergistic mechanisms for different drug and periodontal responses.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

Common Aetiology for Diverse Language Skills in 4 1/2-Year-Old Twins

ERIC Educational Resources Information Center

Hayiou-Thomas, Marianna E.; Kovas, Yulia; Harlaar, Nicole; Plomin, Robert; Bishop, Dorothy V. M.; Dale, Philip S.

2006-01-01

Multivariate genetic analysis was used to examine the genetic and environmental aetiology of the interrelationships of diverse linguistic skills. This study used data from a large sample of 4 1/2-year-old twins who were tested on measures assessing articulation, phonology, grammar, vocabulary, and verbal memory. Phenotypic analysis suggested two…

The Relationship of Self-Concept and Perceived Athletic Competence to Physical Activity Level and Gender among Turkish Early Adolescents.

ERIC Educational Resources Information Center

Kosar, F. Hulya Asci S. Nazan; Isler, Ayse Kin

2001-01-01

Examined self-concept and perceived athletic competence of Turkish early adolescents in relation to physical activity level and gender. Multivariate analysis of variance revealed significant main effects for gender and physical activity level but no significant gender by physical activity interaction. Univariate analysis demonstrated significant…

Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

ERIC Educational Resources Information Center

Muslihah, Oleh Eneng

2015-01-01

The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

Making Waves or Treading Water? An Analysis of Charter Schools in New York State

ERIC Educational Resources Information Center

Silverman, Robert Mark

2013-01-01

This article compares charter schools and other public schools in New York State. School Report Card (SRC) data measuring student, teacher, and school characteristics from the state's 16 urban school districts with charter schools were examined. Descriptive and multivariate analysis was used. The findings suggest that there are more similarities…

A simple prognostic model for overall survival in metastatic renal cell carcinoma.

PubMed

Assi, Hazem I; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis.

A simple prognostic model for overall survival in metastatic renal cell carcinoma

PubMed Central

Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

Describing the complexity of systems: multivariable "set complexity" and the information basis of systems biology.

PubMed

Galas, David J; Sakhanenko, Nikita A; Skupin, Alexander; Ignac, Tomasz

2014-02-01

Context dependence is central to the description of complexity. Keying on the pairwise definition of "set complexity," we use an information theory approach to formulate general measures of systems complexity. We examine the properties of multivariable dependency starting with the concept of interaction information. We then present a new measure for unbiased detection of multivariable dependency, "differential interaction information." This quantity for two variables reduces to the pairwise "set complexity" previously proposed as a context-dependent measure of information in biological systems. We generalize it here to an arbitrary number of variables. Critical limiting properties of the "differential interaction information" are key to the generalization. This measure extends previous ideas about biological information and provides a more sophisticated basis for the study of complexity. The properties of "differential interaction information" also suggest new approaches to data analysis. Given a data set of system measurements, differential interaction information can provide a measure of collective dependence, which can be represented in hypergraphs describing complex system interaction patterns. We investigate this kind of analysis using simulated data sets. The conjoining of a generalized set complexity measure, multivariable dependency analysis, and hypergraphs is our central result. While our focus is on complex biological systems, our results are applicable to any complex system.

Influence of comorbidities on the implementation of the fundus examination in patients with newly diagnosed type 2 diabetes.

PubMed

Kawamura, Taichi; Sato, Izumi; Tamura, Hiroshi; Nakao, Yoko M; Kawakami, Koji

2018-01-01

To investigate the influence of comorbidities on undergoing a diabetic eye examination in patients with newly diagnosed type 2 diabetes mellitus (T2DM). Retrospective cohort study METHODS: This was a retrospective cohort study using data from health insurance claims made between January 2005 and March 2013 in Japan. The primary outcome was implementation of the fundus examination that includes fundus photography, ophthalmoscopy and optical coherence tomography by a doctor within one year of initial drug therapy for Type2 Diabetes Mellitus (T2DM). We used multivariable logistic regression models with adjustment for demographic parameters to investigate the influence of comorbidities (hypertension and/or hyperlipidemia) on patients with T2DM receiving fundus examinations. We conducted an additional analysis to investigate whether the site of treatment might influence the performance of fundus examinations in patients with T2DM. A total of 6,492 patients were eligible for this analysis, of which 1,044 (16.1%) had comorbidities and 2,212 (34.1%) received the fundus examination. In the multivariable analysis, there was a significant association between comorbidities and a lower proportion of examination implementation (odds ratio [OR], 0.57; 95% confidence interval [CI], 0.48-0.68; P<0.001). The implementation proportion for patients treated for comorbidities and T2DM in the same facility was also low (OR, 0.52; 95% CI, 0.43-0.63; P<0.001). These results suggest that the proportion of taking fundus examination is low among patients with comorbidities, especially in patients treated at the same facility for comorbidities and T2DM. This may help to increase the proportion of T2DM patients receiving fundus examinations.

Family Influences on College Students' Occupational Identity

ERIC Educational Resources Information Center

Berrios-Allison, Ana C.

2005-01-01

The occupational identity statuses of 232 college students were analyzed by examining their family emotional environment and the identity control processes that drive career decision making. Results of multivariate analysis showed that each family differentiation construct, family tolerance for connectedness, and separateness explained significant…

Effect of Components in Water on the Extraction of Herbal Medicine
—Advanced Approach Using Multivariate Analysis—

NASA Astrophysics Data System (ADS)

Kanzaki, Yasushi

Many kinds of water products have been offered commercially suggesting some strange efficacy beyond our scientific knowledge even now at which various advanced scientific and technological research have been highly promoted. However, it seems quite obvious that such a strange efficacy must be nonexistent. If such efficacy were really existing, it must be solved by some suitable scientific procedure. In this study, the extraction of paeoniflorin from paeoniae radix was examined by varying the kind of extracting water. Then, the result was analyzed using multivariate analysis where the effect on the extraction was assumed to be ascribed to the ionic species dissolved in each water examined. The dissolved species were analyzed by chemical and instrumental analyses. According to the multivariate analysis, the amount of extracted paeoniflorin (Y) was presented by the following regression equation. The result shows that pH, [Ca2+], and [HCO3 -] were significant parameters and the combination of Ca2+ and HCO3 - affected negatively on the extraction of paeoniflorin.
Y=28.11-0.71 pH-0.0034[Ca2+]-0.93[HCO3 -]
where [Ca2+] is the concentration of calcium ion and [HCO3 -] is that of bicarbonate ion.

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

ERIC Educational Resources Information Center

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

2017-01-01

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

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

PubMed

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

2018-05-01

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

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

PubMed

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

2017-10-01

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

College Student Invulnerability Beliefs and HIV Vaccine Acceptability

ERIC Educational Resources Information Center

Ravert, Russell D.; Zimet, Gregory D.

2009-01-01

Objective: To examine behavioral history, beliefs, and vaccine characteristics as predictors of HIV vaccine acceptability. Methods: Two hundred forty-five US under graduates were surveyed regarding their sexual history, risk beliefs, and likelihood of accepting hypothetical HIV vaccines. Results: Multivariate regression analysis indicated that…

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

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.

Technicians, Technical Education, and Global Economic Development: A Cross National Examination.

ERIC Educational Resources Information Center

Honig, Benson; Ramirez, Francisco

Although the relationship among education, science, technology, and economic development is nearly universally accepted, the link among education, infrastructure, and economic growth has yet to be empirically demonstrated. A multivariate analysis of cross-national data regarding 48 countries was performed to document relationships between…

Reading Ability as a Predictor of Academic Procrastination among African American Graduate Students

ERIC Educational Resources Information Center

Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G.

2008-01-01

The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading…

Simultaneous Analysis of the Behavioural Phenotype, Physical Factors, and Parenting Stress in People with Cornelia De Lange Syndrome

ERIC Educational Resources Information Center

Wulffaert, J.; van Berckelaer-Onnes, I.; Kroonenberg, P.; Scholte, E.; Bhuiyan, Z.; Hennekam, R.

2009-01-01

Background: Studies into the phenotype of rare genetic syndromes largely rely on bivariate analysis. The aim of this study was to describe the phenotype of Cornelia de Lange syndrome (CdLS) in depth by examining a large number of variables with varying measurement levels. Virtually the only suitable multivariate technique for this is categorical…

Diagnostic value of history and physical examination in patients suspected of lumbosacral nerve root compression

PubMed Central

Vroomen, P; de Krom, M C T F M; Wilmink, J; Kester, A; Knottnerus, J

2002-01-01

Objective: To evaluate patient characteristics, symptoms, and examination findings in the clinical diagnosis of lumbosacral nerve root compression causing sciatica. Methods: The study involved 274 patients with pain radiating into the leg. All had a standardised clinical assessment and magnetic resonance (MR) imaging. The associations between patient characteristics, clinical findings, and lumbosacral nerve root compression on MR imaging were analysed. Results: Nerve root compression was associated with three patient characteristics, three symptoms, and four physical examination findings (paresis, absence of tendon reflexes, a positive straight leg raising test, and increased finger-floor distance). Multivariate analysis, analysing the independent diagnostic value of the tests, showed that nerve root compression was predicted by two patient characteristics, four symptoms, and two signs (increased finger-floor distance and paresis). The straight leg raise test was not predictive. The area under the curve of the receiver-operating characteristic was 0.80 for the history items. It increased to 0.83 when the physical examination items were added. Conclusions: Various clinical findings were found to be associated with nerve root compression on MR imaging. While this set of findings agrees well with those commonly used in daily practice, the tests tended to have lower sensitivity and specificity than previously reported. Stepwise multivariate analysis showed that most of the diagnostic information revealed by physical examination findings had already been revealed by the history items. PMID:11971050

Neurodevelopmental Status and Adaptive Behaviors in Preschool Children with Chronic Kidney Disease

ERIC Educational Resources Information Center

Duquette, Peter J.; Hooper, Stephen R.; Icard, Phil F.; Hower, Sarah J.; Mamak, Eva G.; Wetherington, Crista E.; Gipson, Debbie S.

2009-01-01

This study examines the early neurodevelopmental function of infants and preschool children who have chronic kidney disease (CKD). Fifteen patients with CKD are compared to a healthy control group using the "Mullen Scales of Early Learning" (MSEL) and the "Vineland Adaptive Behavior Scale" (VABS). Multivariate analysis reveals…

Turkish Student Teachers' Concerns about Teaching

ERIC Educational Resources Information Center

Boz, Yezdan

2008-01-01

The purpose of this study was to examine the teaching concerns of Turkish student teachers and how these concerns differ among year groups within the teacher education programme. Data were collected from 339 student teachers using the Teacher Concerns Checklist. Analysis of the data, including both descriptive statistics and multivariate analysis…

Individualism-Collectivism: Links to Occupational Plans and Work Values

ERIC Educational Resources Information Center

Hartung, Paul J.; Fouad, Nadya A.; Leong, Frederick T. L.; Hardin, Erin E.

2010-01-01

Individualism-collectivism (IC) constitutes a cultural variable thought to influence a wide variety of variables including career planning and decision making. To examine this possibility, college students (216 women, 106 men, 64% racial-ethnic minorities) responded to measures of IC, occupational plans, and work values. Multivariate analysis of…

The HOME Inventory and Family Demographics.

ERIC Educational Resources Information Center

Bradley, Robert H.; Caldwell, Bettye M.

1984-01-01

Examines the relation between the Home Observation for Measurement of Environment (HOME) Inventory and sex, race, socioeconomic status, the amount of crowding in the home, and birth order. Performs multivariate analysis of covariance on an intact family sample using HOME subscales as criterion measures and status and structural variables as…

Maternal Sensitivity and Child Responsiveness: Associations with Social Context, Maternal Characteristics, and Child Characteristics in a Multivariate Analysis

ERIC Educational Resources Information Center

Bornstein, Marc H.; Hendricks, Charlene; Haynes, O. Maurice; Painter, Kathleen M.

2007-01-01

This study examined unique associations of multiple distal context variables (family socioeconomic status [SES], maternal employment, and paternal parenting) and proximal maternal (personality, intelligence, and knowledge; behavior, self-perceptions, and attributions) and child (age, gender, representation, language, and sociability)…

Adolescents' Relationships to Siblings and Mothers: A Multivariate Genetic Analysis.

ERIC Educational Resources Information Center

Bussell, Danielle A.; And Others

1999-01-01

Examined relative contributions of genetic and environmental influences to the covariation between sibling relationships and mother/adolescent relationships in 719 same-sex sibling pairs of varying degrees of genetic relatedness. Found that the overlapping effects of shared environment on the two relationship subsystems explained most of the…

Factors Associated with Sexual Behavior among Adolescents: A Multivariate Analysis.

ERIC Educational Resources Information Center

Harvey, S. Marie; Spigner, Clarence

1995-01-01

A self-administered survey examining multiple factors associated with engaging in sexual intercourse was completed by 1,026 high school students in a classroom setting. Findings suggest that effective interventions to address teenage pregnancy need to utilize a multifaceted approach to the prevention of high-risk behaviors. (JPS)

Disfluency in Spasmodic Dysphonia: A Multivariate Analysis.

ERIC Educational Resources Information Center

Cannito, Michael P.; Burch, Annette Renee; Watts, Christopher; Rappold, Patrick W.; Hood, Stephen B.; Sherrard, Kyla

1997-01-01

This study examined visual analog scaling judgments of disfluency by normal listeners in response to oral reading by 20 adults with spasmodic dysphonia (SD) and nondysphonic controls. Findings suggest that although dysfluency is not a defining feature of SD, it does contribute significantly to the overall clinical impression of severity of the…

Update and review of accuracy assessment techniques for remotely sensed data

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Heinen, J. T.; Oderwald, R. G.

1983-01-01

Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.

Multivariate Longitudinal Methods for Studying Developmental Relationships between Depression and Academic Achievement

ERIC Educational Resources Information Center

Grimm, Kevin J.

2007-01-01

Recent advances in methods and computer software for longitudinal data analysis have pushed researchers to more critically examine developmental theories. In turn, researchers have also begun to push longitudinal methods by asking more complex developmental questions. One such question involves the relationships between two developmental…

College Curriculum Competencies and Skills Former Students Found Essential to Their Careers

ERIC Educational Resources Information Center

Zekeri, Andrew A.

2004-01-01

In this paper, the author examines college curriculum competencies and skills acquired in college education that former students report as most essential to improve their career experiences. Multivariate analysis indicates that despite the technological changes occurring in places of work, skills in oral communication, written communication,…

Multivariate Models of Parent-Late Adolescent Gender Dyads: The Importance of Parenting Processes in Predicting Adjustment

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2008-01-01

Although parent-adolescent interactions have been examined, relevant variables have not been integrated into a multivariate model. As a result, this study examined a multivariate model of parent-late adolescent gender dyads in an attempt to capture important predictors in late adolescents' important and unique transition to adulthood. The sample…

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Job insecurity and risk of diabetes: a meta-analysis of individual participant data.

PubMed

Ferrie, Jane E; Virtanen, Marianna; Jokela, Markus; Madsen, Ida E H; Heikkilä, Katriina; Alfredsson, Lars; Batty, G David; Bjorner, Jakob B; Borritz, Marianne; Burr, Hermann; Dragano, Nico; Elovainio, Marko; Fransson, Eleonor I; Knutsson, Anders; Koskenvuo, Markku; Koskinen, Aki; Kouvonen, Anne; Kumari, Meena; Nielsen, Martin L; Nordin, Maria; Oksanen, Tuula; Pahkin, Krista; Pejtersen, Jan H; Pentti, Jaana; Salo, Paula; Shipley, Martin J; Suominen, Sakari B; Tabák, Adam; Theorell, Töres; Väänänen, Ari; Vahtera, Jussi; Westerholm, Peter J M; Westerlund, Hugo; Rugulies, Reiner; Nyberg, Solja T; Kivimäki, Mika

2016-12-06

Job insecurity has been associated with certain health outcomes. We examined the role of job insecurity as a risk factor for incident diabetes. We used individual participant data from 8 cohort studies identified in 2 open-access data archives and 11 cohort studies participating in the Individual-Participant-Data Meta-analysis in Working Populations Consortium. We calculated study-specific estimates of the association between job insecurity reported at baseline and incident diabetes over the follow-up period. We pooled the estimates in a meta-analysis to produce a summary risk estimate. The 19 studies involved 140 825 participants from Australia, Europe and the United States, with a mean follow-up of 9.4 years and 3954 incident cases of diabetes. In the preliminary analysis adjusted for age and sex, high job insecurity was associated with an increased risk of incident diabetes compared with low job insecurity (adjusted odds ratio [OR] 1.19, 95% confidence interval [CI] 1.09-1.30). In the multivariable-adjusted analysis restricted to 15 studies with baseline data for all covariates (age, sex, socioeconomic status, obesity, physical activity, alcohol and smoking), the association was slightly attenuated (adjusted OR 1.12, 95% CI 1.01-1.24). Heterogeneity between the studies was low to moderate (age- and sex-adjusted model: I 2 = 24%, p = 0.2; multivariable-adjusted model: I 2 = 27%, p = 0.2). In the multivariable-adjusted analysis restricted to high-quality studies, in which the diabetes diagnosis was ascertained from electronic medical records or clinical examination, the association was similar to that in the main analysis (adjusted OR 1.19, 95% CI 1.04-1.35). Our findings suggest that self-reported job insecurity is associated with a modest increased risk of incident diabetes. Health care personnel should be aware of this association among workers reporting job insecurity. © 2016 Canadian Medical Association or its licensors.

[Chronic kidney disease in 5 708 people receiving physical examination].

PubMed

Xu, Guo; Chen, Zhiheng; Zhang, Hao; Gong, Ni; Wang, Yan

2014-04-01

To investigate chronic kidney disease (CKD) and its risk factors in people receiving physical examination. This retrospective study included people over 20 years old who had physical examination in the Health Management Center of Third Xiangya Hospital from Janurary 2008 to June 2011. CKD and its risk factors as well as questionnaire were recorded. The risk factors were analyzed by multivariate logistic analysis. CKD was defined by kidney damage (microalbuminuria≥30 mg/L) and/or hematuria and/or reduced kidney function [evaluate glomerular filtration rate (eGFR)<60 mL/(min.1.73 m2)]. We counted eGFR according to the modification of diet in renal disease (MDRD). A total of 5 708 physical examination reports were included. The detection rate of albuminuria, reduced renal function and hematuria was 25.0%, 1.7% and 1.1%. The detection rate of CKD was 25.6%, and detection rate of CKD stage 1-5 was 17.8%, 6.7%, 1.1%, 0 and 0, respectively. Multivariate logistic analysis indicated that diabetes mellitus, hypertension, hypercholesterolemia, male, age, and smoking were the risk factors for CKD. Increasing physical activity was the protective factor against CKD. High prevalence of CKD in people receiving physical examination is found in Changsha, especially stage 1 and 2 CKD. Physical examination is important to screen CKD. Stopping smoking, control of blood glucose, blood pressure, blood lipids and increasing physical activity may help reduce the prevalence of CKD.

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.

Kenyan female sex workers' use of female-controlled nonbarrier modern contraception: do they use condoms less consistently?

PubMed

Yam, Eileen A; Okal, Jerry; Musyoki, Helgar; Muraguri, Nicholas; Tun, Waimar; Sheehy, Meredith; Geibel, Scott

2016-03-01

To examine whether nonbarrier modern contraceptive use is associated with less consistent condom use among Kenyan female sex workers (FSWs). Researchers recruited 579 FSWs using respondent-driven sampling. We conducted multivariate logistic regression to examine the association between consistent condom use and female-controlled nonbarrier modern contraceptive use. A total of 98.8% reported using male condoms in the past month, and 64.6% reported using female-controlled nonbarrier modern contraception. In multivariate analysis, female-controlled nonbarrier modern contraceptive use was not associated with decreased condom use with clients or nonpaying partners. Consistency of condom use is not compromised when FSWs use available female-controlled nonbarrier modern contraception. FSWs should be encouraged to use condoms consistently, whether or not other methods are used simultaneously. Copyright © 2016 Elsevier Inc. All rights reserved.

The natural mathematics of behavior analysis.

PubMed

Li, Don; Hautus, Michael J; Elliffe, Douglas

2018-04-19

Models that generate event records have very general scope regarding the dimensions of the target behavior that we measure. From a set of predicted event records, we can generate predictions for any dependent variable that we could compute from the event records of our subjects. In this sense, models that generate event records permit us a freely multivariate analysis. To explore this proposition, we conducted a multivariate examination of Catania's Operant Reserve on single VI schedules in transition using a Markov Chain Monte Carlo scheme for Approximate Bayesian Computation. Although we found systematic deviations between our implementation of Catania's Operant Reserve and our observed data (e.g., mismatches in the shape of the interresponse time distributions), the general approach that we have demonstrated represents an avenue for modelling behavior that transcends the typical constraints of algebraic models. © 2018 Society for the Experimental Analysis of Behavior.

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

Is math anxiety in the secondary classroom limiting physics mastery? A study of math anxiety and physics performance

NASA Astrophysics Data System (ADS)

Mercer, Gary J.

This quantitative study examined the relationship between secondary students with math anxiety and physics performance in an inquiry-based constructivist classroom. The Revised Math Anxiety Rating Scale was used to evaluate math anxiety levels. The results were then compared to the performance on a physics standardized final examination. A simple correlation was performed, followed by a multivariate regression analysis to examine effects based on gender and prior math background. The correlation showed statistical significance between math anxiety and physics performance. The regression analysis showed statistical significance for math anxiety, physics performance, and prior math background, but did not show statistical significance for math anxiety, physics performance, and gender.

Simple and Multivariate Relationships Between Spiritual Intelligence with General Health and Happiness.

PubMed

Amirian, Mohammad-Elyas; Fazilat-Pour, Masoud

2016-08-01

The present study examined simple and multivariate relationships of spiritual intelligence with general health and happiness. The employed method was descriptive and correlational. King's Spiritual Quotient scales, GHQ-28 and Oxford Happiness Inventory, are filled out by a sample consisted of 384 students, which were selected using stratified random sampling from the students of Shahid Bahonar University of Kerman. Data are subjected to descriptive and inferential statistics including correlations and multivariate regressions. Bivariate correlations support positive and significant predictive value of spiritual intelligence toward general health and happiness. Further analysis showed that among the Spiritual Intelligence' subscales, Existential Critical Thinking Predicted General Health and Happiness, reversely. In addition, happiness was positively predicted by generation of personal meaning and transcendental awareness. The findings are discussed in line with the previous studies and the relevant theoretical background.

Sampling effort affects multivariate comparisons of stream assemblages

USGS Publications Warehouse

Cao, Y.; Larsen, D.P.; Hughes, R.M.; Angermeier, P.L.; Patton, T.M.

2002-01-01

Multivariate analyses are used widely for determining patterns of assemblage structure, inferring species-environment relationships and assessing human impacts on ecosystems. The estimation of ecological patterns often depends on sampling effort, so the degree to which sampling effort affects the outcome of multivariate analyses is a concern. We examined the effect of sampling effort on site and group separation, which was measured using a mean similarity method. Two similarity measures, the Jaccard Coefficient and Bray-Curtis Index were investigated with 1 benthic macroinvertebrate and 2 fish data sets. Site separation was significantly improved with increased sampling effort because the similarity between replicate samples of a site increased more rapidly than between sites. Similarly, the faster increase in similarity between sites of the same group than between sites of different groups caused clearer separation between groups. The strength of site and group separation completely stabilized only when the mean similarity between replicates reached 1. These results are applicable to commonly used multivariate techniques such as cluster analysis and ordination because these multivariate techniques start with a similarity matrix. Completely stable outcomes of multivariate analyses are not feasible. Instead, we suggest 2 criteria for estimating the stability of multivariate analyses of assemblage data: 1) mean within-site similarity across all sites compared, indicating sample representativeness, and 2) the SD of within-site similarity across sites, measuring sample comparability.

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

PubMed Central

Bujkiewicz, Sylwia; Riley, Richard D

2016-01-01

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data. PMID:26988929

Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

PubMed

Riley, Richard D; Elia, Eleni G; Malin, Gemma; Hemming, Karla; Price, Malcolm P

2015-07-30

A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta-analysis is difficult because primary studies often use different methods of measurement and/or different cut-points to dichotomise continuous factors into 'high' and 'low' groups; selective reporting is also common. We illustrate how multivariate random effects meta-analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut-points and/or methods of measurement. The models account for within-study and between-study correlations, which utilises more information and reduces the impact of unreported cut-points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut-point to reduce the number of unknown parameters. The models provide important inferential results for each cut-point and method of measurement, including the summary prognostic effect, the between-study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta-analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut-points than previously thought. In the second, a multivariate meta-analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut-points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses.

PubMed

Buttigieg, Pier Luigi; Ramette, Alban

2014-12-01

The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. As a consequence, staying abreast of progress and debate in this arena poses an additional challenge to many microbial ecologists. To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynamic, web-based resource providing accessible descriptions of numerous multivariate techniques relevant to microbial ecologists. A combination of interactive elements allows users to discover and navigate between methods relevant to their needs and examine how they have been used by others in the field. We have designed GUSTA ME to become a community-led and -curated service, which we hope will provide a common reference and forum to discuss and disseminate analytical techniques relevant to the microbial ecology community. © 2014 The Authors. FEMS Microbiology Ecology published by John Wiley & Sons Ltd on behalf of Federation of European Microbiological Societies.

A Multivariate Analysis of Lost Work Time Due to On-the-Job Injuries at Marine Corps Commands

DTIC Science & Technology

2007-09-01

00893 F Chemistry 01320 F Civil Engineering 00810 F Communications Clerical 00394 F Computer Engineering 00854 F Computer Operation 00332 F...69001 H Packing 70002 H Small-Arms Repairing 66010 H Transportation Loss and Damage Claims Examining 02135 H Agronomy 00471 H Animal Caretaking

Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a glutathione S-transferase gene

USDA-ARS?s Scientific Manuscript database

Plants are attacked by pathogens representing diverse taxonomic groups, such that genes providing multiple disease resistance (MDR) would likely be under positive selection pressure. We examined the novel proposition that naturally occurring allelic variants may confer MDR. To do so, we applied a ...

Determinants of Anabolic-Androgenic Steroid Risk Perceptions in Youth Populations: A Multivariate Analysis

ERIC Educational Resources Information Center

Denham, Bryan E.

2009-01-01

Grounded conceptually in social cognitive theory, this research examines how personal, behavioral, and environmental factors are associated with risk perceptions of anabolic-androgenic steroids. Ordinal logistic regression and logit log-linear models applied to data gathered from high-school seniors (N = 2,160) in the 2005 Monitoring the Future…

Omnibus Tests for Interactions in Repeated Measures Designs with Dichotomous Dependent Variables.

ERIC Educational Resources Information Center

Serlin, Ronald C.; Marascuilo, Leonard A.

When examining a repeated measures design with independent groups for a significant group by trial interaction, classical analysis of variance or multivariate procedures can be used if the assumptions underlying the tests are met. Neither procedure may be justified for designs with small sample sizes and dichotomous dependent variables. An omnibus…

Uncovering Multivariate Structure in Classroom Observations in the Presence of Rater Errors

ERIC Educational Resources Information Center

McCaffrey, Daniel F.; Yuan, Kun; Savitsky, Terrance D.; Lockwood, J. R.; Edelen, Maria O.

2015-01-01

We examine the factor structure of scores from the CLASS-S protocol obtained from observations of middle school classroom teaching. Factor analysis has been used to support both interpretations of scores from classroom observation protocols, like CLASS-S, and the theories about teaching that underlie them. However, classroom observations contain…

A Cognitive Analysis of Credit Card Acquisition and College Student Financial Development.

ERIC Educational Resources Information Center

Kidwell, Blair; Turrisi, Robert

2000-01-01

Examines cognitions relevant to credit card decision making in college-aged participants (N=304). Assesses measures of beliefs, attitudes, and behavioral alternatives toward acquiring a credit card. Identifies a multivariate model predicting college student financial development of the attitudes and behavioral tendencies of acquiring a new card.…

Impact of an Adlerian Based Pretrial Diversion Program: Self Concept and Dissociation

ERIC Educational Resources Information Center

Norvell, Jeanell J.

2010-01-01

Clients' self concepts and dissociative experiences were examined to determine the impact of an Adlerian based pretrial diversion program. Clients completing the program displayed a significant change in self concepts and dissociative experiences. A repeated measures multivariate analysis of variance indicated a 35% change, made up of the…

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…

Confirmatory Factor Analysis on the Professional Suitability Scale for Social Work Practice

ERIC Educational Resources Information Center

Tam, Dora M. Y.; Twigg, Robert C.; Boey, Kam-Wing; Kwok, Siu-Ming

2013-01-01

Objective: This article presents a validation study to examine the factor structure of an instrument designed to measure professional suitability for social work practice. Method: Data were collected from registered social workers in a provincial mailed survey. The response rate was 23.2%. After eliminating five cases with multivariate outliers,…

Pupil Performance, Absenteeism and School Drop-out: A Multi-dimensional Analysis.

ERIC Educational Resources Information Center

Smyht, Emer

1999-01-01

Assesses whether second-level schools in Ireland are equally effective regarding examination performance, absenteeism, and potential dropouts, using multivariate analyses of data from 15- and 16-year-olds in 116 schools. Absenteeism and potential dropout rates are lower in schools that enhance pupils' academic progress. (Contains 22 references.)…

Income and Education in Turkey: A Multivariate Analysis

ERIC Educational Resources Information Center

Sari, Ramazan; Soytas, Ugur

2006-01-01

Although the role of education in an economy is emphasized in theoretical studies, empirical literature finds mixed results for the relationship between growth and education. We examine the relationship between Gross Domestic Product (GDP) and enrollments in primary, secondary, and high schools, as well as universities in Turkey for 1937-1996, in…

Examining a Comprehensive Model of Disaster-Related Posttraumatic Stress Disorder in Systematically Studied Survivors of 10 Disasters

PubMed Central

Oliver, Julianne; Pandya, Anand

2012-01-01

Objectives. Using a comprehensive disaster model, we examined predictors of posttraumatic stress disorder (PTSD) in combined data from 10 different disasters. Methods. The combined sample included data from 811 directly exposed survivors of 10 disasters between 1987 and 1995. We used consistent methods across all 10 disaster samples, including full diagnostic assessment. Results. In multivariate analyses, predictors of PTSD were female gender, younger age, Hispanic ethnicity, less education, ever-married status, predisaster psychopathology, disaster injury, and witnessing injury or death; exposure through death or injury to friends or family members and witnessing the disaster aftermath did not confer additional PTSD risk. Intentionally caused disasters associated with PTSD in bivariate analysis did not independently predict PTSD in multivariate analysis. Avoidance and numbing symptoms represented a PTSD marker. Conclusions. Despite confirming some previous research findings, we found no associations between PTSD and disaster typology. Prospective research is needed to determine whether early avoidance and numbing symptoms identify individuals likely to develop PTSD later. Our findings may help identify at-risk populations for treatment research. PMID:22897543

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

PubMed

Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

Correlates of HIV knowledge and Sexual risk behaviors among Female Military Personnel

PubMed Central

Essien, E. James; Monjok, Emmanuel; Chen, Hua; Abughosh, Susan; Ekong, Ernest; Peters, Ronald J.; Holmes, Laurens; Holstad, Marcia M.; Mgbere, Osaro

2010-01-01

Objective Uniformed services personnel are at an increased risk of HIV infection. We examined the HIV/AIDS knowledge and sexual risk behaviors among female military personnel to determine the correlates of HIV risk behaviors in this population. Method The study used a cross-sectional design to examine HIV/AIDS knowledge and sexual risk behaviors in a sample of 346 females drawn from two military cantonments in Southwestern Nigeria. Data was collected between 2006 and 2008. Using bivariate analysis and multivariate logistic regression, HIV/AIDS knowledge and sexual behaviors were described in relation to socio-demographic characteristics of the participants. Results Multivariate logistic regression analysis revealed that level of education and knowing someone with HIV/AIDS were significant (p<0.05) predictors of HIV knowledge in this sample. HIV prevention self-efficacy was significantly (P<0.05) predicted by annual income and race/ethnicity. Condom use attitudes were also significantly (P<0.05) associated with number of children, annual income, and number of sexual partners. Conclusion Data indicates the importance of incorporating these predictor variables into intervention designs. PMID:20387111

Immediate versus delayed intramedullary nailing for open fractures of the tibial shaft: a multivariate analysis of factors affecting deep infection and fracture healing.

PubMed

Yokoyama, Kazuhiko; Itoman, Moritoshi; Uchino, Masataka; Fukushima, Kensuke; Nitta, Hiroshi; Kojima, Yoshiaki

2008-10-01

The purpose of this study was to evaluate contributing factors affecting deep infection and fracture healing of open tibia fractures treated with locked intramedullary nailing (IMN) by multivariate analysis. We examined 99 open tibial fractures (98 patients) treated with immediate or delayed locked IMN in static fashion from 1991 to 2002. Multivariate analyses following univariate analyses were derived to determine predictors of deep infection, nonunion, and healing time to union. The following predictive variables of deep infection were selected for analysis: age, sex, Gustilo type, fracture grade by AO type, fracture location, timing or method of IMN, reamed or unreamed nailing, debridement time (< or =6 h or >6 h), method of soft-tissue management, skin closure time (< or =1 week or >1 week), existence of polytrauma (ISS< 18 or ISS> or =18), existence of floating knee injury, and existence of superficial/pin site infection. The predictive variables of nonunion selected for analysis was the same as those for deep infection, with the addition of deep infection for exchange of pin site infection. The predictive variables of union time selected for analysis was the same as those for nonunion, excluding of location, debridement time, and existence of floating knee and superficial infection. Six (6.1%; type II Gustilo n=1, type IIIB Gustilo n=5) of the 99 open tibial fractures developed deep infections. Multivariate analysis revealed that timing or method of IMN, debridement time, method of soft-tissue management, and existence of superficial or pin site infection significantly correlated with the occurrence of deep infection (P< 0.0001). In the immediate nailing group alone, the deep infection rate in type IIIB + IIIC was significantly higher than those in type I + II and IIIA (P = 0.016). Nonunion occurred in 17 fractures (20.3%, 17/84). Multivariate analysis revealed that Gustilo type, skin closure time, and existence of deep infection significantly correlated with occurrence of nonunion (P < 0.05). Gustilo type and existence of deep infection were significantly correlated with healing time to union on multivariate analysis (r(2) = 0.263, P = 0.0001). Multivariate analyses for open tibial fractures treated with IMN showed that IMN after EF (especially in existence of pin site infection) was at high risk of deep infection, and that debridement within 6 h and appropriate soft-tissue managements were also important factor in preventing deep infections. These analyses postulated that both the Gustilo type and the existence of deep infection is related with fracture healing in open fractures treated with IMN. In addition, immediate IMN for type IIIB and IIIC is potentially risky, and canal reaming did not increase the risk of complication for open tibial fractures treated with IMN.

Multivariate Analysis of Electron Detachment Dissociation and Infrared Multiphoton Dissociation Mass Spectra of Heparan Sulfate Tetrasaccharides Differing Only in Hexuronic acid Stereochemistry

NASA Astrophysics Data System (ADS)

Oh, Han Bin; Leach, Franklin E.; Arungundram, Sailaja; Al-Mafraji, Kanar; Venot, Andre; Boons, Geert-Jan; Amster, I. Jonathan

2011-03-01

The structural characterization of glycosaminoglycan (GAG) carbohydrates by mass spectrometry has been a long-standing analytical challenge due to the inherent heterogeneity of these biomolecules, specifically polydispersity, variability in sulfation, and hexuronic acid stereochemistry. Recent advances in tandem mass spectrometry methods employing threshold and electron-based ion activation have resulted in the ability to determine the location of the labile sulfate modification as well as assign the stereochemistry of hexuronic acid residues. To facilitate the analysis of complex electron detachment dissociation (EDD) spectra, principal component analysis (PCA) is employed to differentiate the hexuronic acid stereochemistry of four synthetic GAG epimers whose EDD spectra are nearly identical upon visual inspection. For comparison, PCA is also applied to infrared multiphoton dissociation spectra (IRMPD) of the examined epimers. To assess the applicability of multivariate methods in GAG mixture analysis, PCA is utilized to identify the relative content of two epimers in a binary mixture.

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.

The association of poverty with the prevalence of albuminuria: data from the Third National Health and Nutrition Examination Survey (NHANES III).

PubMed

Martins, David; Tareen, Naureen; Zadshir, Ashraf; Pan, Deyu; Vargas, Roberto; Nissenson, Allen; Norris, Keith

2006-06-01

Albuminuria is a major risk factor for the development and progression of chronic kidney disease (CKD) and cardiovascular disease. Socioeconomic factors also have been reported to modify CKD and cardiovascular risk factors and clinical outcomes. The extent to which poverty influences the prevalence of albuminuria, particularly among racial/ethnic minority populations, is not well established. The influence of poverty on the prevalence of albuminuria and the implication of this relationship for the racial and/or ethnic differences in the prevalence of albuminuria were examined. We examined data from 6,850 male and 7,634 female adults from a national probability survey conducted between 1988 and 1994. In univariate analysis, poverty, defined as less than 200% federal poverty level (FPL), was associated with the presence of both microalbuminuria (odds ratio [OR], 1.35; 95% confidence interval, 1.22 to 1.49) and macroalbuminuria (OR, 1.78; 95% confidence interval, 1.40 to 2.26). The association of less than 200% FPL with microalbuminuria persisted in a multivariate model controlling for age, sex, race, education, obesity, hypertension, diabetes, reduced glomerular filtration rate, and medication use (OR, 1.18; 95% confidence interval, 1.05 to 1.33). FPL less than 200% was not associated with macroalbuminuria in the multivariate model. When multivariate analysis is stratified by FPL (<200% and > or =200%), differences in ORs for microalbuminuria and macroalbuminuria among racial/ethnic minority participants compared with whites were more apparent among the less affluent participants in the FPL-less-than-200% stratum. FPL less than 200% is associated with microalbuminuria, and differences in FPL levels may account for some of the observed differences in prevalence of albuminuria between racial/ethnic minority participants and their white counterparts.

Vegetation characteristics important to common songbirds in east Texas

USGS Publications Warehouse

Conner, Richard N.; Dickson, James G.; Locke, Brian A.; Segelquist, Charles A.

1983-01-01

Multivariate studies of breeding bird communities have used principal component analysis (PCA) or several-group (three or more groups) discriminant function analysis (DFA) to ordinate bird species on vegetational continua (Cody 1968, James 1971, Whitmore 1975). In community studies, high resolution of habitat requirements for individual species is not always possible with either PCA or several-group DFA. When habitat characteristics of several species are examined with a DFA the resultant axes optimally discriminate among all species simultaneously. Hence, the characteristics assigned to a particular species reflect in part the presence of other species in the analyses. A better resolution of each species' habitat requirements may be obtained from a two-group DFA, wherein habitats selected by a species are discriminated from all other available habitats. Analyses using two-group DFAs to compare habitat used by a species with habitat unused by the same species have the potential to provide an optimal frame of reference from which to examine habitat variables (Martinka 1972, Conner and Adkisson 1976, Whitmore 1981). Mathematically (DFA) it is possible to maximally separate two groups of multivariate observations with a single axis (Harner and whitmore 1977). A line drawn in three or n-dimensional space can easily be positioned to intersect two multivariate means (centroids). If three or more centroids for species are analyzed simultaneously, a single line can no longer intersect all centroids unless a perfectly linear relationship exists for the species being examined. The probability of such an occurrence is extremely low. Thus, a high degree of resolution can be realized when a two-group DFA is used to determine habitat parameters important to individual species. We have used two-group DFA to identify vegetation variable important to 12 common species of songbirds in East Texas.

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

PubMed

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

2014-11-01

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

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.

Materials Approach to Dissecting Surface Responses in the Attachment Stages of Biofouling Organisms

DTIC Science & Technology

2016-04-25

their settlement behavior in regards to the coating surfaces. 5) Multivariate statistical analysis was used to examine the effect (if any) of the...applied to glass rods and were deployed in the field to evaluate settlement preferences. Canonical Analysis of Principal Coordinates were applied to...the influence of coating surface properties on the patterns in settlement observed in the field in the extension of this work over the coming year

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

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

Wang, Feng, E-mail: fwang@unu.edu; Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft; Huisman, Jaco

2013-11-15

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lackmore » of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.« less

Clinical and dermoscopic clues to differentiate pigmented nail bands: an International Dermoscopy Society study.

PubMed

Benati, E; Ribero, S; Longo, C; Piana, S; Puig, S; Carrera, C; Cicero, F; Kittler, H; Deinlein, T; Zalaudek, I; Stolz, W; Scope, A; Pellacani, G; Moscarella, E; Piraccini, B M; Starace, M; Argenziano, G

2017-04-01

Longitudinal melanonychia might be difficult to differentiate and the use of dermoscopy can be useful for the preoperative evaluation and management decision. The aim of our study was to investigate clinical and dermoscopic criteria of acquired longitudinal melanonychia in adults to identify the best predictors of melanoma using a multivariate analysis and to explore eventual new dermoscopic criteria for nail melanoma diagnosis. In this retrospective observational study, 82 histopathologically diagnosed, acquired nail pigmented bands were collected and examined. All variables were included in the analysis and examined as possible predictors of nail melanoma. Both univariate and multivariable analyses have been performed. Among 82 cases, 25 were diagnosed as nail melanoma and 57 as benign lesions (including 32 melanocytic nevi and 25 benign melanocytic hyperplasia). Melanoma cases were significantly associated with a width of the pigmented band higher than 2/3 of the nail plate, grey and black colours, irregularly pigmented lines, Hutchinson and micro-Hutchinson signs, and nail dystrophy. Granular pigmentation, a newly defined dermoscopic criterion, was found in 40% of melanomas and only in 3.51% of benign lesions. Dermoscopic examination of longitudinal melanonychia provides useful information that could help clinicians to improve melanoma recognition. © 2016 European Academy of Dermatology and Venereology.

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

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

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

Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

NASA Astrophysics Data System (ADS)

Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

2017-10-01

The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

Prognostic implications of adhesion molecule expression in colorectal cancer.

PubMed

Seo, Kyung-Jin; Kim, Maru; Kim, Jeana

2015-01-01

Research on the expression of adhesion molecules, E-cadherin (ECAD), CD24, CD44 and osteopontin (OPN) in colorectal cancer (CRC) has been limited, even though CRC is one of the leading causes of cancer-related deaths. This study was conducted to evaluate the expression of adhesion molecules in CRC and to determine their relationships with clinicopathologic variables, and the prognostic significance. The expression of ECAD, CD24, CD44 and OPN was examined in 174 stage II and III CRC specimens by immunohistochemistry of TMA. Negative ECAD expression was significantly correlated with advanced nodal stage and poor tumor differentiation. Multivariate analysis showed that both negative expression of ECAD and positive expression of CD24 were independent prognostic factors for disease-free survival (DFS) in CRC patients (P<0.001, relative risk [RR] = 5.596, 95% CI = 2.712-11.549; P = 0.038, RR = 3.768, 95% CI = 1.077-13.185, respectively). However, for overall survival (OS), only ECAD negativity showed statistically significant results in multivariate analysis (P<0.001, RR = 4.819, 95% CI = 2.515-9.234). Positive expression of CD24 was associated with poor OS in univariate analysis but was of no prognostic value in multivariate analysis. In conclusion, our study suggests that among these four adhesion molecules, ECAD and CD24 expression can be considered independent prognostic factors. The role of CD44 and OPN may need further evaluation.

Prognostic implications of adhesion molecule expression in colorectal cancer

PubMed Central

Seo, Kyung-Jin; Kim, Maru; Kim, Jeana

2015-01-01

Research on the expression of adhesion molecules, E-cadherin (ECAD), CD24, CD44 and osteopontin (OPN) in colorectal cancer (CRC) has been limited, even though CRC is one of the leading causes of cancer-related deaths. This study was conducted to evaluate the expression of adhesion molecules in CRC and to determine their relationships with clinicopathologic variables, and the prognostic significance. The expression of ECAD, CD24, CD44 and OPN was examined in 174 stage II and III CRC specimens by immunohistochemistry of TMA. Negative ECAD expression was significantly correlated with advanced nodal stage and poor tumor differentiation. Multivariate analysis showed that both negative expression of ECAD and positive expression of CD24 were independent prognostic factors for disease-free survival (DFS) in CRC patients (P<0.001, relative risk [RR] = 5.596, 95% CI = 2.712-11.549; P = 0.038, RR = 3.768, 95% CI = 1.077-13.185, respectively). However, for overall survival (OS), only ECAD negativity showed statistically significant results in multivariate analysis (P<0.001, RR = 4.819, 95% CI = 2.515-9.234). Positive expression of CD24 was associated with poor OS in univariate analysis but was of no prognostic value in multivariate analysis. In conclusion, our study suggests that among these four adhesion molecules, ECAD and CD24 expression can be considered independent prognostic factors. The role of CD44 and OPN may need further evaluation. PMID:26097606

A multivariate assessment of changes in wetland habitat for waterbirds at Moosehorn National Wildlife Refuge, Maine, USA

USGS Publications Warehouse

Hierl, L.A.; Loftin, C.S.; Longcore, J.R.; McAuley, D.G.; Urban, D.L.

2007-01-01

We assessed changes in vegetative structure of 49 impoundments at Moosehorn National Wildlife Refuge (MNWR), Maine, USA, between the periods 1984-1985 to 2002 with a multivariate, adaptive approach that may be useful in a variety of wetland and other habitat management situations. We used Mahalanobis Distance (MD) analysis to classify the refuge?s wetlands as poor or good waterbird habitat based on five variables: percent emergent vegetation, percent shrub, percent open water, relative richness of vegetative types, and an interspersion juxtaposition index that measures adjacency of vegetation patches. Mahalanobis Distance is a multivariate statistic that examines whether a particular data point is an outlier or a member of a data cluster while accounting for correlations among inputs. For each wetland, we used MD analysis to quantify a distance from a reference condition defined a priori by habitat conditions measured in MNWR wetlands used by waterbirds. Twenty-five wetlands declined in quality between the two periods, whereas 23 wetlands improved. We identified specific wetland characteristics that may be modified to improve habitat conditions for waterbirds. The MD analysis seems ideal for instituting an adaptive wetland management approach because metrics can be easily added or removed, ranges of target habitat conditions can be defined by field-collected data, and the analysis can identify priorities for single or multiple management objectives.

The Association between Electronic Bullying and School Absenteeism among High School Students in the United States

ERIC Educational Resources Information Center

Grinshteyn, Erin; Yang, Y. T.

2017-01-01

Background: We examined the relationship between exposure to electronic bullying and absenteeism as a result of being afraid. Methods: This multivariate, multinomial regression analysis of the 2013 Youth Risk Behavior Survey data assessed the association between experiencing electronic bullying in the past year and how often students were absent…

A Multivariate Analysis of Termination Status in a Rural Community Mental Health Center.

ERIC Educational Resources Information Center

Tutin, Judith; Kessler, Marc

It has been estimated that the most pressing problem in community mental health care clinics is dropout, defined as unilateral termination by the client without therapist approval. To clarify the nature of dropout patients, 133 outpatient records at a rural community mental health center were examined over a one year period. Variables expected to…

Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis

ERIC Educational Resources Information Center

Spain, Seth M.; Miner, Andrew G.; Kroonenberg, Pieter M.; Drasgow, Fritz

2010-01-01

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of…

Communication and Other Critical Predictors of Orientation to Change: A Multivariate Analysis.

ERIC Educational Resources Information Center

Edeani, David O.

A study was conducted to examine the contributions to the determination of individuals' orientation to change made by such factors as the individuals' demographic, social structural, personality, and cognitive characteristics. Data were collected in a field sample of 159 adult residents of New Athens, Illinois, a town of 2,000 inhabitants near…

Effects of Social Class and School Conditions on Educational Enrollment and Achievement of Boys and Girls in Rural Viet Nam

ERIC Educational Resources Information Center

Nguyen, Phuong L.

2006-01-01

This study examines the effects of parental SES, school quality, and community factors on children's enrollment and achievement in rural areas in Viet Nam, using logistic regression and ordered logistic regression. Multivariate analysis reveals significant differences in educational enrollment and outcomes by level of household expenditures and…

Studying the Relationship between Children's Self-Control and Academic Achievement: An Application of Second-Order Growth Curve Model Analysis.

ERIC Educational Resources Information Center

Kim, Sooyeon; Murry, Velma McBride; Brody, Gene H.

The functional relationships between developmental change in children's self-control and academic achievement were examined using longitudinal family data. Multivariate latent growth models (LGM) were specified to determine whether the rate of growth in academic achievement changes as a function of developmental change in self-control. Data came…

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

ERIC Educational Resources Information Center

Barone, Sandra

2006-01-01

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

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

ERIC Educational Resources Information Center

Barone, Sandra; Steiner, Matt; Teszler, Natali

2005-01-01

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

Comparisons of Self-Determination among Students with Autism, Intellectual Disability, and Learning Disabilities: A Multivariate Analysis

ERIC Educational Resources Information Center

Chou, Yu-Chi; Wehmeyer, Michael L.; Palmer, Susan B.; Lee, Jaehoon

2017-01-01

This study examined differences in self-determination among students with autism spectrum disorders (ASD), students with intellectual disability (ID), and students with learning disabilities (LD). A total of 222 participants with an equal size group for each of the three disability categories were selected to participate in the comparison of total…

Health Related Quality of Life among Insulin-Dependent Diabetics: Disease-Related and Psychosocial Correlates.

ERIC Educational Resources Information Center

Aalto, Anna-Mari; Uutela, Antti; Aro, Arja R.

1997-01-01

The associations of health and psychosocial factors with the Health Related Quality of Life Questionnaire were examined in adult type 1 diabetic patients (N=385). The most important factors from multivariate analysis were self-efficacy and diabetes-related social support, especially among those in good physical condition. Diabetes-specific factors…

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

PubMed

Abdel-Rahman, Omar

2018-02-01

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

Associations between bar patron alcohol intoxication and tobacco smoking.

PubMed

Rossheim, Matthew E; Thombs, Dennis L; O'Mara, Ryan J; Bastian, Nicholas; Suzuki, Sumihiro

2013-11-01

To examine the event-specific relationship between alcohol intoxication and nighttime tobacco smoking among college bar patrons. In this secondary analysis of existing data, we examined event-specific associations between self-report measures of tobacco smoking and breath alcohol concentration (BrAC) readings obtained from 424 patrons exiting on-premise drinking establishments. In a multivariable logistic regression analysis, acute alcohol intoxication was positively associated with same-night incidents of smoking tobacco, adjusting for the effects of established smoking practices and other potential confounders. This investigation is the first known study using data collected in an on-premise drinking setting to link alcohol intoxication to specific incidents of tobacco smoking.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

Examination of the association of sex and race/ethnicity with appearance concerns: a Scleroderma Patient-centered Intervention Network (SPIN) Cohort study.

PubMed

Jewett, Lisa R; Kwakkenbos, Linda; Carrier, Marie-Eve; Malcarne, Vanessa L; Bartlett, Susan J; Furst, Daniel E; Gottesman, Karen; Mayes, Maureen D; Assassi, Shervin; Harcourt, Diana; Williamson, Heidi; Johnson, Sindhu R; Körner, Annett; Steen, Virginia; Fox, Rina S; Gholizadeh, Shadi; Mills, Sarah D; Molnar, Jacqueline C; Rice, Danielle B; Thombs, Brett D

2016-01-01

Appearance concerns are common in systemic sclerosis (SSc) and have been linked to younger age and more severe disease. No study has examined their association with sex or race/ethnicity. SSc patients were sampled from the Scleroderma Patient-centered Intervention Network Cohort. Presence of appearance concerns was assessed with a single item, and medical and sociodemographic information were collected. Of 644 patients, appearance concerns were present in 72%, including 421 of 565 women (75%), 42 of 79 men (53%), 392 of 550 patients who identified as White (71%), 35 of 41 who identified as Black (85%), and 36 of 53 who identified as another race/ethnicity (68%). In multivariate analysis, women had significantly greater odds of reporting appearance concerns than men (odds ratio (OR)=2.97, 95% confidence interval (CI)=1.78-4.95, p<.001). Black patients had significantly greater odds of appearance concerns than White patients in unadjusted (OR=2.64, 95% CI=1.01-6.34, p=.030), but not multivariate analysis (OR=1.76, 95% CI=0.67-4.60, p=.250). Compared to a general population sample, appearance concerns were substantially more common in SSc, particularly for men across all age groups and for younger women. The most commonly reported features of concern were related to the face and head, followed by the hands and fingers; this did not differ by sex or race/ethnicity. Appearance concerns were common in SSc. Women were substantially more likely than men to have appearance concerns. Although non-significant in multivariate analysis, Black patients were more likely to have concerns than White patients, likely due to more severe changes in appearance.

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 information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

PubMed

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

Prevalence and risk factors of subclinical mastitis in lactating dairy cows in north and south regions of Bangladesh.

PubMed

Sarker, Swapan Chandra; Parvin, Mst Sonia; Rahman, A K M Anisur; Islam, Md Taohidul

2013-06-01

The purpose of the study was to identify the potential risk factors for subclinical mastitis (SCM) in lactating dairy cows in Bangladesh. A cross-sectional study was carried out on randomly selected 212 smallholder dairy farms of Sadar upazilas of Rangpur, Mymensingh, and Satkhira districts of Bangladesh during January to October 2011. The direct interview using a structured questionnaire and physical examination of the cows were done to collect data on 15 variables. Milk samples collected from study cows were subjected to California Mastitis Test (CMT). The diagnosis of SCM was based on the results of CMT and physical examination of udder and milk. The bivariable followed by multivariable analysis was done using SPSS 17.0. Of the total cows examined, 20.2 % had subclinical mastitis. In bivariable analysis, eight risk factors were identified. However, in the final model of multivariable analysis, four potential risk factors were identified. These were history of previous clinical mastitis (odds ratio (OR) 10.51, p<0.001), pendulous type of udder (OR 2.26, p=0.008), no grass feeding (OR 1.84, p=0.039), and body condition score (BCS) 2.5 or less (OR 7.25, p=0.054). Four different factors were significantly associated with the occurrence of subclinical mastitis, which need to be considered in the control of the disease. However, particular emphasis should be given on grass feeding and BCS because these traits can be modified or improved to allow prevention of SCM.

Multivariate methods to visualise colour-space and colour discrimination data.

PubMed

Hastings, Gareth D; Rubin, Alan

2015-01-01

Despite most modern colour spaces treating colour as three-dimensional (3-D), colour data is usually not visualised in 3-D (and two-dimensional (2-D) projection-plane segments and multiple 2-D perspective views are used instead). The objectives of this article are firstly, to introduce a truly 3-D percept of colour space using stereo-pairs, secondly to view colour discrimination data using that platform, and thirdly to apply formal statistics and multivariate methods to analyse the data in 3-D. This is the first demonstration of the software that generated stereo-pairs of RGB colour space, as well as of a new computerised procedure that investigated colour discrimination by measuring colour just noticeable differences (JND). An initial pilot study and thorough investigation of instrument repeatability were performed. Thereafter, to demonstrate the capabilities of the software, five colour-normal and one colour-deficient subject were examined using the JND procedure and multivariate methods of data analysis. Scatter plots of responses were meaningfully examined in 3-D and were useful in evaluating multivariate normality as well as identifying outliers. The extent and direction of the difference between each JND response and the stimulus colour point was calculated and appreciated in 3-D. Ellipsoidal surfaces of constant probability density (distribution ellipsoids) were fitted to response data; the volumes of these ellipsoids appeared useful in differentiating the colour-deficient subject from the colour-normals. Hypothesis tests of variances and covariances showed many statistically significant differences between the results of the colour-deficient subject and those of the colour-normals, while far fewer differences were found when comparing within colour-normals. The 3-D visualisation of colour data using stereo-pairs, as well as the statistics and multivariate methods of analysis employed, were found to be unique and useful tools in the representation and study of colour. Many additional studies using these methods along with the JND and other procedures have been identified and will be reported in future publications. © 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

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

2016-01-01

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

Does investor ownership of nursing homes compromise the quality of care?

PubMed

Harrington, C; Woolhandler, S; Mullan, J; Carrillo, H; Himmelstein, D U

2001-09-01

Two thirds of nursing homes are investor owned. This study examined whether investor ownership affects quality. We analyzed 1998 data from state inspections of 13,693 nursing facilities. We used a multivariate model and controlled for case mix, facility characteristics, and location. Investor-owned facilities averaged 5.89 deficiencies per home, 46.5% higher than nonprofit facilities and 43.0% higher than public facilities. In multivariate analysis, investor ownership predicted 0.679 additional deficiencies per home; chain ownership predicted an additional 0.633 deficiencies. Nurse staffing was lower at investor-owned nursing homes. Investor-owned nursing homes provide worse care and less nursing care than do not-for-profit or public homes.

Multielement analysis of Canadian wines by inductively coupled plasma mass spectrometry (ICP-MS) and multivariate statistics.

PubMed

Taylor, Vivien F; Longerich, Henry P; Greenough, John D

2003-02-12

Trace element fingerprints were deciphered for wines from Canada's two major wine-producing regions, the Okanagan Valley and the Niagara Peninsula, for the purpose of examining differences in wine element composition with region of origin and identifying elements important to determining provenance. Analysis by ICP-MS allowed simultaneous determination of 34 trace elements in wine (Li, Be, Mg, Al, P, Cl, Ca, Ti, V, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Mo, Ag, Cd, Sb, I, Cs, Ba, La, Ce, Tl, Pb, Bi, Th, and U) at low levels of detection, and patterns in trace element concentrations were deciphered by multivariate statistical analysis. The two regions were discriminated with 100% accuracy using 10 of these elements. Differences in soil chemistry between the Niagara and Okanagan vineyards were evident, without a good correlation between soil and wine composition. The element Sr was found to be a good indicator of provenance and has been reported in fingerprinting studies of other regions.

Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

NASA Astrophysics Data System (ADS)

Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

2014-05-01

The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

Prolonged instability prior to a regime shift

USGS Publications Warehouse

Spanbauer, Trisha; Allen, Craig R.; Angeler, David G.; Eason, Tarsha; Fritz, Sherilyn C.; Garmestani, Ahjond S.; Nash, Kirsty L.; Stone, Jeffery R.

2014-01-01

Regime shifts are generally defined as the point of ‘abrupt’ change in the state of a system. However, a seemingly abrupt transition can be the product of a system reorganization that has been ongoing much longer than is evident in statistical analysis of a single component of the system. Using both univariate and multivariate statistical methods, we tested a long-term high-resolution paleoecological dataset with a known change in species assemblage for a regime shift. Analysis of this dataset with Fisher Information and multivariate time series modeling showed that there was a∼2000 year period of instability prior to the regime shift. This period of instability and the subsequent regime shift coincide with regional climate change, indicating that the system is undergoing extrinsic forcing. Paleoecological records offer a unique opportunity to test tools for the detection of thresholds and stable-states, and thus to examine the long-term stability of ecosystems over periods of multiple millennia.

Multivariate analysis and geochemical approach for assessment of metal pollution state in sediment cores.

PubMed

Jamshidi-Zanjani, Ahmad; Saeedi, Mohsen

2017-07-01

Vertical distribution of metals (Cu, Zn, Cr, Fe, Mn, Pb, Ni, Cd, and Li) in four sediment core samples (C 1 , C 2 , C 3 , and C 4 ) from Anzali international wetland located southwest of the Caspian Sea was examined. Background concentration of each metal was calculated according to different statistical approaches. The results of multivariate statistical analysis showed that Fe and Mn might have significant role in the fate of Ni and Zn in sediment core samples. Different sediment quality indexes were utilized to assess metal pollution in sediment cores. Moreover, a new sediment quality index named aggregative toxicity index (ATI) based on sediment quality guidelines (SQGs) was developed to assess the degree of metal toxicity in an aggregative manner. The increasing pattern of metal pollution and their toxicity degree in upper layers of core samples indicated increasing effects of anthropogenic sources in the study area.

Discrimination of inflammatory bowel disease using Raman spectroscopy and linear discriminant analysis methods

NASA Astrophysics Data System (ADS)

Ding, Hao; Cao, Ming; DuPont, Andrew W.; Scott, Larry D.; Guha, Sushovan; Singhal, Shashideep; Younes, Mamoun; Pence, Isaac; Herline, Alan; Schwartz, David; Xu, Hua; Mahadevan-Jansen, Anita; Bi, Xiaohong

2016-03-01

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.

Cardiovascular reactivity patterns and pathways to hypertension: a multivariate cluster analysis.

PubMed

Brindle, R C; Ginty, A T; Jones, A; Phillips, A C; Roseboom, T J; Carroll, D; Painter, R C; de Rooij, S R

2016-12-01

Substantial evidence links exaggerated mental stress induced blood pressure reactivity to future hypertension, but the results for heart rate reactivity are less clear. For this reason multivariate cluster analysis was carried out to examine the relationship between heart rate and blood pressure reactivity patterns and hypertension in a large prospective cohort (age range 55-60 years). Four clusters emerged with statistically different systolic and diastolic blood pressure and heart rate reactivity patterns. Cluster 1 was characterised by a relatively exaggerated blood pressure and heart rate response while the blood pressure and heart rate responses of cluster 2 were relatively modest and in line with the sample mean. Cluster 3 was characterised by blunted cardiovascular stress reactivity across all variables and cluster 4, by an exaggerated blood pressure response and modest heart rate response. Membership to cluster 4 conferred an increased risk of hypertension at 5-year follow-up (hazard ratio=2.98 (95% CI: 1.50-5.90), P<0.01) that survived adjustment for a host of potential confounding variables. These results suggest that the cardiac reactivity plays a potentially important role in the link between blood pressure reactivity and hypertension and support the use of multivariate approaches to stress psychophysiology.

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.

Using ePortfolio-Based Learning Approach to Facilitate Knowledge Sharing and Creation among College Students

ERIC Educational Resources Information Center

Chang, Chi-Cheng; Chou, Pao-Nan; Liang, Chaoyan

2018-01-01

The purpose of the present study was to examine the effects of the ePortfolio-based learning approach (ePBLA) on knowledge sharing and creation with 92 college students majoring in electrical engineering as the participants. Multivariate analysis of covariance (MANCOVA) with a covariance of pretest on knowledge sharing and creation was conducted…

Does Learning to Read Improve Intelligence? A Longitudinal Multivariate Analysis in Identical Twins from Age 7 to 16

ERIC Educational Resources Information Center

Ritchie, Stuart J.; Bates, Timothy C.; Plomin, Robert

2015-01-01

Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross-lagged…

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

ERIC Educational Resources Information Center

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

2017-01-01

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

School Engagement Mediates Well-Being Differences in Students Attending Specialized versus Regular Classes

ERIC Educational Resources Information Center

Orkibi, Hod; Tuaf, Hila

2017-01-01

The authors examined (a) differences in school engagement and the subjective well-being (SWB) of 330 Israeli students (Grades 7-10, 52% girls) in specialized school classes (arts and science) versus students in classes with no specialized subject and (b) the role of engagement as a mediator between class choice and SWB. A multivariate analysis of…

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

ERIC Educational Resources Information Center

Steiner, Matt; Teszler, Natali

2005-01-01

In an effort to better understand student loan default behavior at Texas A&M University (TAMU), the research staff at TG, at the request of TAMU, conducted a study of the relationship between loan default, on the one hand, and many student and borrower characteristics, on the other hand. The study examines the default behavior of 12,776…

The Effect of Alcohol Abuse and Dependence and School Experiences on Depression: A National Study of Adolescents

ERIC Educational Resources Information Center

Merianos, Ashley L.; King, Keith A.; Vidourek, Rebecca A.; Hardee, Angelica M.

2016-01-01

The study purpose was to examine the effect alcohol abuse/dependence and school experiences have on depression among a nationwide sample of adolescents. A secondary analysis of the 2013 National Survey on Drug Use and Health was conducted. The results of the final multivariable logistic regression model revealed that adolescents who reported…

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

PubMed

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

2015-07-01

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

Musculoskeletal ultrasonography delineates ankle symptoms in rheumatoid arthritis.

PubMed

Toyota, Yukihiro; Tamura, Maasa; Kirino, Yohei; Sugiyama, Yumiko; Tsuchida, Naomi; Kunishita, Yosuke; Kishimoto, Daiga; Kamiyama, Reikou; Miura, Yasushi; Minegishi, Kaoru; Yoshimi, Ryusuke; Ueda, Atsuhisa; Nakajima, Hideaki

2017-05-01

To clarify the use of musculoskeletal ultrasonography (US) of ankle joints in rheumatoid arthritis (RA). Consecutive RA patients with or without ankle symptoms participated in the study. The US, clinical examination (CE), and patients' visual analog scale for pain (pVAS) for ankles were assessed. Prevalence of tibiotalar joint synovitis and tenosynovitis were assessed by grayscale (GS) and power Doppler (PD) US using a semi-quantitative grading (0-3). The positive US and CE findings were defined as GS score ≥2 and/or PD score ≥1, and joint swelling and/or tenderness, respectively. Multivariate analysis with the generalized linear mixed model was performed by assigning ankle pVAS as a dependent variable. Among a total of 120 ankles from 60 RA patients, positive ankle US findings were found in 21 (35.0%) patients. The concordance rate of CE and US was moderate (kappa 0.57). Of the 88 CE negative ankles, US detected positive findings in 9 (10.2%) joints. Multivariate analysis revealed that ankle US, clinical disease activity index, and foot Health Assessment Questionnaire, but not CE, was independently associated with ankle pVAS. US examination is useful to illustrate RA ankle involvement, especially for patients who complain ankle pain but lack CE findings.

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

Application of Multivariate Statistical Analysis to Biomarkers in Se-Turkey Crude Oils

NASA Astrophysics Data System (ADS)

Gürgey, K.; Canbolat, S.

2017-11-01

Twenty-four crude oil samples were collected from the 24 oil fields distributed in different districts of SE-Turkey. API and Sulphur content (%), Stable Carbon Isotope, Gas Chromatography (GC), and Gas Chromatography-Mass Spectrometry (GC-MS) data were used to construct a geochemical data matrix. The aim of this study is to examine the genetic grouping or correlations in the crude oil samples, hence the number of source rocks present in the SE-Turkey. To achieve these aims, two of the multivariate statistical analysis techniques (Principle Component Analysis [PCA] and Cluster Analysis were applied to data matrix of 24 samples and 8 source specific biomarker variables/parameters. The results showed that there are 3 genetically different oil groups: Batman-Nusaybin Oils, Adıyaman-Kozluk Oils and Diyarbakir Oils, in addition to a one mixed group. These groupings imply that at least, three different source rocks are present in South-Eastern (SE) Turkey. Grouping of the crude oil samples appears to be consistent with the geographic locations of the oils fields, subsurface stratigraphy as well as geology of the area.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

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

2016-01-01

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

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

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

2016-01-01

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

Optical assay for biotechnology and clinical diagnosis.

PubMed

Moczko, Ewa; Cauchi, Michael; Turner, Claire; Meglinski, Igor; Piletsky, Sergey

2011-08-01

In this paper, we present an optical diagnostic assay consisting of a mixture of environmental-sensitive fluorescent dyes combined with multivariate data analysis for quantitative and qualitative examination of biological and clinical samples. The performance of the assay is based on the analysis of spectrum of the selected fluorescent dyes with the operational principle similar to electronic nose and electronic tongue systems. This approach has been successfully applied for monitoring of growing cell cultures and identification of gastrointestinal diseases in humans.

Does placental inflammation relate to brain lesions and volume in preterm infants?

PubMed

Reiman, Milla; Kujari, Harry; Maunu, Jonna; Parkkola, Riitta; Rikalainen, Hellevi; Lapinleimu, Helena; Lehtonen, Liisa; Haataja, Leena

2008-05-01

To evaluate the association between histologic inflammation of placenta and brain findings in ultrasound examinations and regional brain volumes in magnetic resonance imaging in very-low-birth-weight (VLBW) or in very preterm infants. VLBW or very preterm infants (n = 121) were categorized into 3 groups according to the most pathologic brain finding on ultrasound examinations until term. The brain magnetic resonance imaging performed at term was analyzed for regional brain volumes. The placentas were analyzed for histologic inflammatory findings. Histologic chorioamnionitis on the fetal side correlated to brain lesions in univariate but not in multivariate analyses. Low gestational age was the only significant risk factor for brain lesions in multivariate analysis (P < .0001). Histologic chorioamnionitis was not associated with brain volumes in multivariate analyses. Female sex, low gestational age, and low birth weight z score correlated to smaller volumes in total brain tissue (P = .001, P = .0002, P < .0001, respectively) and cerebellum (P = .047, P = .003, P = .001, respectively). In addition, low gestational age and low-birth-weight z score correlated to a smaller combined volume of basal ganglia and thalami (P = .0002). Placental inflammation does not appear to correlate to brain lesions or smaller regional brain volumes in VLBW or in very preterm infants at term age.

Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis.

PubMed

Spain, Seth M; Miner, Andrew G; Kroonenberg, Pieter M; Drasgow, Fritz

2010-08-06

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of analyzing momentary work behavior using experience sampling methods. The article also examines a previously unused set of methods for analyzing data produced by experience sampling. These methods are known collectively as multiway component analysis. Two archetypal techniques of multimode factor analysis, the Parallel factor analysis and the Tucker3 models, are used to analyze data from Miner, Glomb, and Hulin's (2010) experience sampling study of work behavior. The efficacy of these techniques for analyzing experience sampling data is discussed as are the substantive multimode component models obtained.

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

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.

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

Using a Grocery List Is Associated With a Healthier Diet and Lower BMI Among Very High-Risk Adults.

PubMed

Dubowitz, Tamara; Cohen, Deborah A; Huang, Christina Y; Beckman, Robin A; Collins, Rebecca L

2015-01-01

Examine whether use of a grocery list is associated with healthier diet and weight among food desert residents. Cross-sectional analysis of in-person interview data from randomly selected household food shoppers in 2 low-income, primarily African American urban neighborhoods in Pittsburgh, PA with limited access to healthy foods. Multivariate ordinary least-square regressions conducted among 1,372 participants and controlling for sociodemographic factors and other potential confounding variables indicated that although most of the sample (78%) was overweight or obese, consistently using a list was associated with lower body mass index (based on measured height and weight) (adjusted multivariant coefficient = 0.095) and higher dietary quality (based on the Healthy Eating Index-2005) (adjusted multivariant coefficient = 0.103) (P < .05). Shopping with a list may be a useful tool for low-income individuals to improve diet or decrease body mass index. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Predictive factors in patients with hepatocellular carcinoma receiving sorafenib therapy using time-dependent receiver operating characteristic analysis.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

To investigate variables before sorafenib therapy on the clinical outcomes in hepatocellular carcinoma (HCC) patients receiving sorafenib and to further assess and compare the predictive performance of continuous parameters using time-dependent receiver operating characteristics (ROC) analysis. A total of 225 HCC patients were analyzed. We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of continuous parameters which were significant in the multivariate analysis in terms of OS and PFS. Total sum of area under the ROC in all time points (defined as TAAT score) in each case was calculated. Our cohort included 175 male and 50 female patients (median age, 72 years) and included 158 Child-Pugh A and 67 Child-Pugh B patients. The median OS time was 0.68 years, while the median PFS time was 0.24 years. On multivariate analysis, gender, body mass index (BMI), Child-Pugh classification, extrahepatic metastases, tumor burden, aspartate aminotransferase (AST) and alpha-fetoprotein (AFP) were identified as significant predictors of OS and ECOG-performance status, Child-Pugh classification and extrahepatic metastases were identified as significant predictors of PFS. Among three continuous variables (i.e., BMI, AST and AFP), AFP had the highest TAAT score for the entire cohort. In subgroup analyses, AFP had the highest TAAT score except for Child-Pugh B and female among three continuous variables. In continuous variables, AFP could have higher predictive accuracy for survival in HCC patients undergoing sorafenib therapy.

Does Investor Ownership of Nursing Homes Compromise the Quality of Care?

PubMed Central

Harrington, Charlene; Woolhandler, Steffie; Mullan, Joseph; Carrillo, Helen; Himmelstein, David U.

2001-01-01

Objectives. Two thirds of nursing homes are investor owned. This study examined whether investor ownership affects quality. Methods. We analyzed 1998 data from state inspections of 13 693 nursing facilities. We used a multivariate model and controlled for case mix, facility characteristics, and location. Results. Investor-owned facilities averaged 5.89 deficiencies per home, 46.5% higher than nonprofit facilities and 43.0% higher than public facilities. In multivariate analysis, investor ownership predicted 0.679 additional deficiencies per home; chain ownership predicted an additional 0.633 deficiencies. Nurse staffing was lower at investor-owned nursing homes. Conclusions. Investor-owned nursing homes provide worse care and less nursing care than do not-for-profit or public homes. PMID:11527781

The Impact of Female Schooling on Fertility and Contraceptive Use: A Study of Fourteen Sub-Saharan Countries. Living Standards Measurement Study Working Paper No. 110.

ERIC Educational Resources Information Center

Ainsworth, Martha; And Others

This paper examines the relationship between female schooling and two behaviors--cumulative fertility and contraceptive use--in 14 Sub-Saharan African countries where Demographic and Health Surveys (DHS) have been conducted since the mid-1980s. Using multivariate regression analysis, the paper compares the effect of schooling across countries, in…

Subjective Well-Being in a Multicultural Urban Population: Structural, and Multivariate Analyses of the Ontario Health Survey Well-Being Scale

ERIC Educational Resources Information Center

John, Lindsay Herbert

2004-01-01

The validity of a scale, from the Ontario Health Survey, measuring the subjective sense of well-being, for a large multicultural population in Metropolitan Toronto, is examined through principal components analysis with oblique rotation. Four factors are extracted. Factor 1, is a stress and strain factor, and consists of health worries, feeling…

How Large Is the Gap in Salaries of Male and Female Engineers? SRS Issue Brief.

ERIC Educational Resources Information Center

Lal, Bhavya; Yoon, Sam; Carlson, Ken

This issue brief examines the gender salary gap in engineering, an occupation in which women held 10% of the jobs in 1995. Using multivariate regression analysis, various potential explanations for the salary gap in this field are explored. It was concluded that the salary gap is primarily explained by the fact that female engineers, on average,…

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

PubMed

Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

2017-07-01

To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

Elemental analysis of soils using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS) with multivariate discrimination: tape mounting as an alternative to pellets for small forensic transfer specimens.

PubMed

Jantzi, Sarah C; Almirall, José R

2014-01-01

Elemental analysis of soil is a useful application of both laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS) in geological, agricultural, environmental, archeological, planetary, and forensic sciences. In forensic science, the question to be answered is often whether soil specimens found on objects (e.g., shoes, tires, or tools) originated from the crime scene or other location of interest. Elemental analysis of the soil from the object and the locations of interest results in a characteristic elemental profile of each specimen, consisting of the amount of each element present. Because multiple elements are measured, multivariate statistics can be used to compare the elemental profiles in order to determine whether the specimen from the object is similar to one of the locations of interest. Previous work involved milling and pressing 0.5 g of soil into pellets before analysis using LA-ICP-MS and LIBS. However, forensic examiners prefer techniques that require smaller samples, are less time consuming, and are less destructive, allowing for future analysis by other techniques. An alternative sample introduction method was developed to meet these needs while still providing quantitative results suitable for multivariate comparisons. The tape-mounting method involved deposition of a thin layer of soil onto double-sided adhesive tape. A comparison of tape-mounting and pellet method performance is reported for both LA-ICP-MS and LIBS. Calibration standards and reference materials, prepared using the tape method, were analyzed by LA-ICP-MS and LIBS. As with the pellet method, linear calibration curves were achieved with the tape method, as well as good precision and low bias. Soil specimens from Miami-Dade County were prepared by both the pellet and tape methods and analyzed by LA-ICP-MS and LIBS. Principal components analysis and linear discriminant analysis were applied to the multivariate data. Results from both the tape method and the pellet method were nearly identical, with clear groupings and correct classification rates of >94%.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

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

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

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

A microcomputer-based whole-body counter for personnel routine monitoring.

PubMed

Chou, H P; Tsai, T M; Lan, C Y

1993-05-01

The paper describes a cost-effective NaI(Tl) whole-body counter developed for routine examinations of worker intakes at an isotope production facility. Signal processing, data analysis and system operation are microcomputer-controlled for minimum human interactions. The pulse height analyzer is developed as an microcomputer add-on card for easy manipulation. The scheme for radionuclide analysis is aimed for fast running according to a knowledge base established from background samples and phantom experiments in conjunction with a multivariate regression analysis. Long-term stability and calibration with standards and in vivo measurements are reported.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

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

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

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

Associations between anthropometric factors and peripheral neuropathy defined by vibrotactile perception threshold among industrial vibrating tool operators in Japan.

PubMed

Takemura, Shigeki; Yoshimasu, Kouichi; Tsuno, Kanami; Fukumoto, Jin; Kuroda, Mototsugu; Miyashita, Kazuhisa

2016-05-25

The effect of anthropometric factors on the fingertip vibrotactile perception threshold (VPT) of industrial vibrating tool operators (IVTOs) is not well known. The purpose of this study was to investigate the associations between anthropometric factors and fingertip VPT. We included for analysis two groups of IVTOs: Group 1, predominantly forestry workers (n=325); and Group 2, public servants (n=68). These IVTOs regularly received medical examinations to evaluate hand-arm vibration syndrome. In the examination, measurements of their fingertip VPTs were taken before and after cold-water immersion (10 minutes at 10°C for Group 1 and 5 minutes at 12°C for Group 2). Their body height and weight were measured to calculate the body mass index (BMI). The presence of peripheral neuropathy (PN) was defined as a VPT ≥17.5 dB at 10 minutes after finishing immersion. In the univariate analysis, weight and BMI were associated with a decreased risk of PN in both Groups 1 and 2. The negative association between BMI and PN remained in the multivariate analysis consistently, but weight reached marginal significance only in the multivariate analysis without BMI in both the groups. Age was positively associated with PN consistently in Group 1 but not in Group 2. Years exposed to vibration showed positive association with PN only in the univariate analysis of Group 1. Among IVTOs, factors reflecting body heat production, such as weight and BMI, were associated with a decreased risk of VPT-defined PN, regardless of the task engaged.

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

Influence of diabetes on the risk of urothelial cancer according to body mass index: a 10-year nationwide population-based observational study.

PubMed

Bae, Woong Jin; Choi, Jin Bong; Moon, Hyong Woo; Park, Young Hyun; Cho, Hyuk Jin; Hong, Sung-Hoo; Lee, Ji Youl; Kim, Sae Woong; Han, Kyung-Do; Ha, U-Syn

2018-01-01

To examine the association between obesity and urothelial cancer, we used a representative data from the National Health Insurance System (NHIS). Participants included 826,170 men aged 20 years and older who experienced a health examination at least one time between 2004 and 2008. The study thus excluded people aged <20 years and women. We used a multivariate adjusted Cox regression analysis to examine the association between urothelial cancer and body mass index (BMI) via a hazard ratio (HR) and 95% confidence interval (CI). The age- or multivariable-adjusted HR for urothelial cancer was stratified by BMI. Men with a higher BMI were more likely to acquire urothelial cancer independent of variables. In the population with diabetes, there showed a considerable, increasing trend in the risk of urothelial cancer in the overweight and obesity group, compared to the group with the same BMI but without diabetes. This population-based study showed evidence of an association between obesity and the development of urothelial cancer, where the presence of diabetes increased the risk of urothelial cancer. Additionally, the higher the BMI, the higher the risk for urothelial cancer.

The prevalence of anxiety and depression in patients with or without hyperhidrosis (HH).

PubMed

Bahar, Rayeheh; Zhou, Pingyu; Liu, Yudan; Huang, Yuanshen; Phillips, Arlie; Lee, Tim K; Su, Mingwan; Yang, Sen; Kalia, Sunil; Zhang, Xuejun; Zhou, Youwen

2016-12-01

There are conflicting data about the correlation between hyperhidrosis (HH) and anxiety and depression. We sought to determine the prevalence of anxiety and depression in patients with or without HH. We examined 2017 consecutive dermatology outpatients from Vancouver, British Columbia, Canada, and Shanghai, China, using Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales for anxiety and depression assessments. Multivariable logistic regression analysis was performed to evaluate if the impact of HH on anxiety and depression is dependent on demographic factors and diagnoses of the patients' presenting skin conditions. The prevalence of anxiety and depression was 21.3% and 27.2% in patients with HH, respectively, and 7.5% and 9.7% in patients without HH, respectively (P value <.001 for both). There were positive correlations between HH severity and the prevalence of anxiety and depression. Multivariable analysis showed that HH-associated increase in anxiety and depression prevalence is independent of demographic factors and presenting skin conditions. The data from the questionnaires relied on the accuracy of patients' self-reports. Both single variant and multivariable analyses showed a significant association between HH and the prevalence of anxiety and depression in a HH severity-dependent manner. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Central sleep apnea detection from ECG-derived respiratory signals. Application of multivariate recurrence plot analysis.

PubMed

Maier, C; Dickhaus, H

2010-01-01

This study examines the suitability of recurrence plot analysis for the problem of central sleep apnea (CSA) detection and delineation from ECG-derived respiratory (EDR) signals. A parameter describing the average length of vertical line structures in recurrence plots is calculated at a time resolution of 1 s as 'instantaneous trapping time'. Threshold comparison of this parameter is used to detect ongoing CSA. In data from 26 patients (duration 208 h) we assessed sensitivity for detection of CSA and mixed apnea (MSA) events by comparing the results obtained from 8-channel Holter ECGs to the annotations (860 CSA, 480 MSA) of simultaneously registered polysomnograms. Multivariate combination of the EDR from different ECG leads improved the detection accuracy significantly. When all eight leads were considered, an average instantaneous vertical line length above 5 correctly identified 1126 of the 1340 events (sensitivity 84%) with a total number of 1881 positive detections. We conclude that recurrence plot analysis is a promising tool for detection and delineation of CSA epochs from EDR signals with high time resolution. Moreover, the approach is likewise applicable to directly measured respiratory signals.

Is Food Insufficiency Associated with Health Status and Health Care Utilization Among Adults with Diabetes?

PubMed Central

Nelson, Karin; Cunningham, William; Andersen, Ron; Harrison, Gail; Gelberg, Lillian

2001-01-01

OBJECTIVES Preliminary studies have shown that among adults with diabetes, food insufficiency has adverse health consequences, including hypoglycemic episodes and increased need for health care services. The purpose of this study was to determine the prevalence of food insufficiency and to describe the association of food insufficiency with health status and health care utilization in a national sample of adults with diabetes. METHODS We analyzed data from adults with diabetes (n = 1,503) interviewed in the Third National Health and Nutrition Examination Survey. Bivariate and multivariate analyses were used to examine the relationship of food insufficiency to self-reported health status and health care utilization. RESULTS Six percent of adults with diabetes reported food insufficiency, representing more than 568,600 persons nationally (95% confidence interval, 368,400 to 768,800). Food insufficiency was more common among those with incomes below the federal poverty level (17% vs 4%, P≤.001). Adults with diabetes who were food insufficient were more likely to report fair or poor health status than those who were not (63% vs 43%; odds ratio, 2.2; P =.05). In a multivariate analysis, fair or poor health status was independently associated with poverty, nonwhite race, low educational achievement, and number of chronic diseases, but not with food insufficiency. Diabetic adults who were food insufficient reported more physician encounters, either in clinic or by phone, than those who were food secure (12 vs 7, P <.05). In a multivariate linear regression, food insufficiency remained independently associated with increased physician utilization among adults with diabetes. There was no association between food insufficiency and hospitalization in bivariate analysis. CONCLUSIONS Food insufficiency is relatively common among low-income adults with diabetes and was associated with higher physician utilization. PMID:11422638

Racial/Ethnic Disparities in the Mental Health Care Utilization of Fifth Grade Children

PubMed Central

Coker, Tumaini R.; Elliott, Marc N.; Kataoka, Sheryl; Schwebel, David C.; Mrug, Sylvie; Grunbaum, Jo Anne; Cuccaro, Paula; Peskin, Melissa F.; Schuster, Mark A.

2015-01-01

Objective The aim of this study was to examine racial/ethnic differences in fifth grade children’s mental health care utilization. Methods We analyzed cross-sectional data from a study of 5147 fifth graders and their parents in 3 US metropolitan areas from 2004–06. Multivariate logistic regression was used to examine racial/ethnic differences in mental health care utilization. Results Nine percent of parents reported that their child had ever used mental health care services; fewer black (6%) and Hispanic (8%) children had used services than white children (14%). Fewer black and Hispanic children with recent symptoms of attention-deficit/hyperactivity disorder, oppositional defiant disorder, and conduct disorder, and fewer black children with symptoms of depression had ever utilized services compared with white children. In multivariate analyses controlling for demographic factors, parental mental health, social support, and symptoms of the 4 mental health conditions, we found that black children were less likely than white children to have ever used services (Odds ratio [OR] 0.3, 95% confidence interval [95% CI], 0.2–0.4, P <.001). The odds ratio for black children remained virtually unchanged when the analysis was restricted to children with symptoms of ≥1 mental health condition, and when the analysis was stratified by mental health condition. The difference in utilization for Hispanic compared with white children was fully explained by sociodemographics in all multivariate models. Conclusions Disparities exist in mental health care utilization for black and Hispanic children; the disparity for black children is independent of sociodemographics and child mental health need. Efforts to reduce this disparity may benefit from addressing not only access and diagnosis issues, but also parents’ help-seeking preferences for mental health care for their children. PMID:19329099

Multiple expression patterns of biopathological markers in primary invasive breast carcinoma: a useful tool for elucidating its biological behaviour.

PubMed

Ceccarelli, C; Santini, D; Chieco, P; Taffurelli, M; Marrano, D; Mancini, A M

1995-03-01

Commonly used clinical and morphologic criteria have been reported to be of limited value in predicting the outcome of malignant tumours of the breast. Integrated information from the quantitative analysis in tumour tissue of biological parameters such as oestrogen and progesterone receptors (ER and PGR), proliferative activity, and proto-oncogene p53, c-erB2, and bcl-2 expression, may be useful for defining the biology of growth of breast carcinoma and to plan effective therapeutic strategies. Immunohistochemistry with antibodies recognizing ER, PGR, Ki-67, and the p53, c-erbB2, and bcl-2 encoded proteins was performed on 291 primary breast carcinomas. Results were integrated with clinico-pathological indicators and examined with multivariate statistical procedures and modeling. P53, c-erbB2, and bcl-2 gene products were detected, respectively, in 30.6%, 31.6%, and 85.9% of the examined invasive breast carcinomas, revealing variable associations with cellular differentiation and proliferation as defined by ER/PGR status, Ki-67, tumour mass and histologic and nuclear grading. A multivariate graphical display on a subset of the most informative cases revealed that bcl-2 expression parallels ER/PGR status and is of importance in separating tumour clusters with different degrees of aggressiveness. The results of this study indicate that multivariate explorative analyses conducted on biological and clinico-pathological parameters might constitute an integrated approach to data analysis useful for distinguishing different biological behaviours and therapeutic groups in breast carcinoma. Our findings also suggest that bcl-2 expression may play a pivotal role in tumours lacking ER-mediated growth regulation.

A Statistical Portrait of Working at Home in the U.K.: Evidence from the Labour Force Survey. Working Paper.

ERIC Educational Resources Information Center

Felstead, Alan; Jewson, Nick; Phizacklea, Annie; Walters, Sally

The patterns, extent, and problems of working at home in the United Kingdom were examined through a multivariate analysis of data from the Labour Force Survey, which has questioned respondents about the location of their workplace since 1992. The numbers of people working "mainly" at home increased from 345,920 (1.5%) in 1981 to 680,612…

Rural-urban disparities in child abuse management resources in the emergency department.

PubMed

Choo, Esther K; Spiro, David M; Lowe, Robert A; Newgard, Craig D; Hall, Michael Kennedy; McConnell, Kenneth John

2010-01-01

To characterize differences in child abuse management resources between urban and rural emergency departments (EDs). We surveyed ED directors and nurse managers at hospitals in Oregon to gain information about available abuse-related resources. Chi-square analysis was used to test differences between urban and rural EDs. Multivariate analysis was performed to examine the association between a variety of hospital characteristics, in addition to rural location, and presence of child abuse resources. Fifty-five Oregon hospitals were surveyed. A smaller proportion of rural EDs had written abuse policies (62% vs 95%, P= .006) or on-site child abuse advocates (35% vs 71%, P= .009). Thirty-two percent of rural EDs had none of the examined abuse resources (vs 0% of urban EDs, P= .01). Of hospital characteristics studied in the multivariate model, only rural location was associated with decreased availability of child abuse resources (OR 0.19 [95% CI, 0.05-0.70]). Rural EDs have fewer resources than urban EDs for the management of child abuse. Other studied hospital characteristics were not associated with availability of abuse resources. Further work is needed to identify barriers to resource utilization and to create resources that can be made accessible to all ED settings. © 2010 National Rural Health Association.

The Impact of ART on the Economic Outcomes of People Living with HIV/AIDS.

PubMed

Nannungi, Annet; Wagner, Glenn; Ghosh-Dastidar, Bonnie

2013-01-01

Background. Clinical benefits of ART are well documented, but less is known about its effects on economic outcomes such as work status and income in sub-Saharan Africa. Methods. Data were examined from 482 adult clients entering HIV care (257 starting ART; 225 not yet eligible for ART) in Kampala, Uganda. Self-reported data on work status and income were assessed at baseline, months 6 and 12. Multivariate analysis examined the effects of ART over time, controlling for change in physical health functioning and baseline covariates. Results. Fewer ART patients worked at baseline compared to non-ART patients (25.5% versus 34.2%); 48.8% of those not working at baseline were now working at month 6, and 50% at month 12, with similar improvement in both the ART and non-ART groups. However, multivariate analysis revealed that the ART group experienced greater improvement over time. Average weekly income did not differ between the groups at baseline nor change significantly over time, among those who were working; being male gender and having any secondary education were predictive of higher income. Conclusions. ART was associated with greater improvement in work status, even after controlling for change in physical health functioning, suggesting other factors associated with ART may influence work.

Race and Older Mothers’ Differentiation: A Sequential Quantitative and Qualitative Analysis

PubMed Central

Sechrist, Jori; Suitor, J. Jill; Riffin, Catherine; Taylor-Watson, Kadari; Pillemer, Karl

2011-01-01

The goal of this paper is to demonstrate a process by which qualitative and quantitative approaches are combined to reveal patterns in the data that are unlikely to be detected and confirmed by either method alone. Specifically, we take a sequential approach to combining qualitative and quantitative data to explore race differences in how mothers differentiate among their adult children. We began with a standard multivariate analysis examining race differences in mothers’ differentiation among their adult children regarding emotional closeness and confiding. Finding no race differences in this analysis, we conducted an in-depth comparison of the Black and White mothers’ narratives to determine whether there were underlying patterns that we had been unable to detect in our first analysis. Using this method, we found that Black mothers were substantially more likely than White mothers to emphasize interpersonal relationships within the family when describing differences among their children. In our final step, we developed a measure of familism based on the qualitative data and conducted a multivariate analysis to confirm the patterns revealed by the in-depth comparison of the mother’s narratives. We conclude that using such a sequential mixed methods approach to data analysis has the potential to shed new light on complex family relations. PMID:21967639

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

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

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

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

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

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.

Is meat consumption associated with depression? A meta-analysis of observational studies.

PubMed

Zhang, Yi; Yang, Ye; Xie, Ming-Sheng; Ding, Xiang; Li, Hui; Liu, Zhi-Chen; Peng, Shi-Fang

2017-12-28

A number of epidemiological studies have examined the effect of meat consumption on depression. However, no conclusion has been reached. The aim of this study was to examine the relationship between meat consumption and depression. The electronic databases of PUBMED and EMBASE were searched up to March 2017, for observational studies that examined the relationship between meat consumption and depression. The pooled odds ratio (OR) for the prevalence of depression and the relative risk (RR) for the incidence of depression, as well as their corresponding 95% confidence interval (CI), were calculated respectively (the highest versus the lowest category of meat consumption). A total of eight observational studies (three cross-sectional, three cohort and two case-control studies) were included in this meta-analysis. Specifically, six studies were related to the prevalence of depression, and the overall multi-variable adjusted OR suggested no significant association between meat consumption and the prevalence of depression (OR = 0.89, 95% CI: 0.65 to 1.22; P = 0.469). In contrast, for the three studies related to the incidence of depression, the overall multi-variable adjusted RR evidenced an association between meat consumption and a moderately higher incidence of depression (RR = 1.13, 95% CI: 1.03 to 1.24; P = 0.013). Meat consumption may be associated with a moderately higher risk of depression. However, it still warrants further studies to confirm such findings due to the limited number of prospective studies.

Differentiating organically and conventionally grown oregano using ultraperformance liquid chromatography mass spectrometry (UPLC-MS), headspace gas chromatography with flame ionization detection (headspace-GC-FID), and flow injection mass spectrum (FIMS) fingerprints combined with multivariate data analysis.

PubMed

Gao, Boyan; Qin, Fang; Ding, Tingting; Chen, Yineng; Lu, Weiying; Yu, Liangli Lucy

2014-08-13

Ultraperformance liquid chromatography mass spectrometry (UPLC-MS), flow injection mass spectrometry (FIMS), and headspace gas chromatography (headspace-GC) combined with multivariate data analysis techniques were examined and compared in differentiating organically grown oregano from that grown conventionally. It is the first time that headspace-GC fingerprinting technology is reported in differentiating organically and conventionally grown spice samples. The results also indicated that UPLC-MS, FIMS, and headspace-GC-FID fingerprints with OPLS-DA were able to effectively distinguish oreganos under different growing conditions, whereas with PCA, only FIMS fingerprint could differentiate the organically and conventionally grown oregano samples. UPLC fingerprinting provided detailed information about the chemical composition of oregano with a longer analysis time, whereas FIMS finished a sample analysis within 1 min. On the other hand, headspace GC-FID fingerprinting required no sample pretreatment, suggesting its potential as a high-throughput method in distinguishing organically and conventionally grown oregano samples. In addition, chemical components in oregano were identified by their molecular weight using QTOF-MS and headspace-GC-MS.

Militarism and mortality. An international analysis of arms spending and infant death rates.

PubMed

Woolhandler, S; Himmelstein, D U

1985-06-15

Examination of data from 141 countries showed that infant mortality rates for 1979 were positively correlated with the proportion of gross national product devoted to military spending (r = 0.23, p less than 0.01) and negatively correlated with indicators of economic development, health resources, and social spending. In a multivariate analysis controlling for per caput gross national product, arms spending remained a significant positive predictor of infant mortality rate (p less than 0.0001), while the proportion of the population with access to clean water, the number of teachers per head, and caloric consumption per head were negative predictors. The multivariate model accounted for much of the observed variance in infant mortality rate (R2 = 0.78, p less than 0.0001), and showed good fit to similar data for the year 1972 (R2 = 0.80, p less than 0.0001). The model was also predictive of infant mortality rates in subgroup analysis of underdeveloped, middle developed, and developed nations. Analysis of time trends confirmed that an increase in military spending presages a poor record of improvement in infant mortality rate. These findings support the hypothesis that arms spending is causally related to infant mortality.

Health Literacy, Cognitive Abilities, and Mortality Among Elderly Persons

PubMed Central

Wolf, Michael S.; Feinglass, Joseph; Thompson, Jason A.

2008-01-01

Background Low health literacy and low cognitive abilities both predict mortality, but no study has jointly examined these relationships. Methods We conducted a prospective cohort study of 3,260 community-dwelling adults age 65 and older. Participants were interviewed in 1997 and administered the Short Test of Functional Health Literacy in Adults and the Mini Mental Status Examination. Mortality was determined using the National Death Index through 2003. Measurements and Main Results In multivariate models with only literacy (not cognition), the adjusted hazard ratio was 1.50 (95% confidence of interval [CI] 1.24–1.81) for inadequate versus adequate literacy. In multivariate models without literacy, delayed recall of 3 items and the ability to serial subtract numbers were associated with higher mortality (e.g., adjusted hazard ratios [AHR] 1.74 [95% CI 1.30–2.34] for recall of zero versus 3 items, and 1.32 [95% CI 1.09–1.60] for 0–2 vs 5 correct subtractions). In multivariate analysis with both literacy and cognition, the AHRs for the cognition items were similar, but the AHR for inadequate literacy decreased to 1.27 (95% CI 1.03 – 1.57). Conclusions Both health literacy and cognitive abilities independently predict mortality. Interventions to improve patient knowledge and self-management skills should consider both the reading level and cognitive demands of the materials. PMID:18330654

The Impact of Asking Intention or Self-Prediction Questions on Subsequent Behavior

PubMed Central

Wood, Chantelle; Conner, Mark; Miles, Eleanor; Sandberg, Tracy; Taylor, Natalie; Godin, Gaston; Sheeran, Paschal

2015-01-01

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE. PMID:26162771

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

PubMed

Lifshits, A M

1979-01-01

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

Multivariate Meta-Analysis of Preference-Based Quality of Life Values in Coronary Heart Disease.

PubMed

Stevanović, Jelena; Pechlivanoglou, Petros; Kampinga, Marthe A; Krabbe, Paul F M; Postma, Maarten J

2016-01-01

There are numerous health-related quality of life (HRQol) measurements used in coronary heart disease (CHD) in the literature. However, only values assessed with preference-based instruments can be directly applied in a cost-utility analysis (CUA). To summarize and synthesize instrument-specific preference-based values in CHD and the underlying disease-subgroups, stable angina and post-acute coronary syndrome (post-ACS), for developed countries, while accounting for study-level characteristics, and within- and between-study correlation. A systematic review was conducted to identify studies reporting preference-based values in CHD. A multivariate meta-analysis was applied to synthesize the HRQoL values. Meta-regression analyses examined the effect of study level covariates age, publication year, prevalence of diabetes and gender. A total of 40 studies providing preference-based values were detected. Synthesized estimates of HRQoL in post-ACS ranged from 0.64 (Quality of Well-Being) to 0.92 (EuroQol European"tariff"), while in stable angina they ranged from 0.64 (Short form 6D) to 0.89 (Standard Gamble). Similar findings were observed in estimates applying to general CHD. No significant improvement in model fit was found after adjusting for study-level covariates. Large between-study heterogeneity was observed in all the models investigated. The main finding of our study is the presence of large heterogeneity both within and between instrument-specific HRQoL values. Current economic models in CHD ignore this between-study heterogeneity. Multivariate meta-analysis can quantify this heterogeneity and offers the means for uncertainty around HRQoL values to be translated to uncertainty in CUAs.

The impact of lungs from diabetic donors on lung transplant recipients†.

PubMed

Ambur, Vishnu; Taghavi, Sharven; Jayarajan, Senthil; Kadakia, Sagar; Zhao, Huaqing; Gomez-Abraham, Jesus; Toyoda, Yoshiya

2017-02-01

We attempted to determine if transplants of lungs from diabetic donors (DDs) is associated with increased mortality of recipients in the modern era of the lung allocation score (LAS). The United Network for Organ Sharing (UNOS) database was queried for all adult lung transplant recipients from 2006 to 2014. Patients receiving a lung from a DD were compared to those receiving a transplant from a non-DD. Multivariate Cox regression analysis using variables associated with mortality was used to examine survival. A total of 13 159 adult lung transplants were performed between January 2006 and June 2014: 4278 (32.5%) were single-lung transplants (SLT) and 8881 (67.5%) were double-lung transplants (DLT). The log-rank test demonstrated a lower median survival in the DD group (5.6 vs 5.0 years, P = 0.003). We performed additional analysis by dividing this initial cohort into two cohorts by transplant type. On multivariate analysis, receiving an SLT from a DD was associated with increased mortality (HR 1.28, 95% CI 1.07–1.54, P = 0.011). Interestingly, multivariate analysis demonstrated no difference in mortality rates for patients receiving a DLT from a DD (HR 1.12, 95% CI 0.97–1.30, P = 0.14). DLT with DDs can be performed safely without increased mortality, but SLT using DDs results in worse survival and post-transplant outcomes. Preference should be given to DLT when using lungs from donors with diabetes. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

An Examination of the Domain of Multivariable Functions Using the Pirie-Kieren Model

ERIC Educational Resources Information Center

Sengul, Sare; Yildiz, Sevda Goktepe

2016-01-01

The aim of this study is to employ the Pirie-Kieren model so as to examine the understandings relating to the domain of multivariable functions held by primary school mathematics preservice teachers. The data obtained was categorized according to Pirie-Kieren model and demonstrated visually in tables and bar charts. The study group consisted of…

Influence of shifting cultivation practices on soil-plant-beetle interactions.

PubMed

Ibrahim, Kalibulla Syed; Momin, Marcy D; Lalrotluanga, R; Rosangliana, David; Ghatak, Souvik; Zothansanga, R; Kumar, Nachimuthu Senthil; Gurusubramanian, Guruswami

2016-08-01

Shifting cultivation (jhum) is a major land use practice in Mizoram. It was considered as an eco-friendly and efficient method when the cycle duration was long (15-30 years), but it poses the problem of land degradation and threat to ecology when shortened (4-5 years) due to increased intensification of farming systems. Studying beetle community structure is very helpful in understanding how shifting cultivation affects the biodiversity features compared to natural forest system. The present study examines the beetle species diversity and estimates the effects of shifting cultivation practices on the beetle assemblages in relation to change in tree species composition and soil nutrients. Scarabaeidae and Carabidae were observed to be the dominant families in the land use systems studied. Shifting cultivation practice significantly (P < 0.05) affected the beetle and tree species diversity as well as the soil nutrients as shown by univariate (one-way analysis of variance (ANOVA), correlation and regression, diversity indices) and multivariate (cluster analysis, principal component analysis (PCA), detrended correspondence analysis (DCA), canonical variate analysis (CVA), permutational multivariate analysis of variance (PERMANOVA), permutational multivariate analysis of dispersion (PERMDISP)) statistical analyses. Besides changing the tree species composition and affecting the soil fertility, shifting cultivation provides less suitable habitat conditions for the beetle species. Bioindicator analysis categorized the beetle species into forest specialists, anthropogenic specialists (shifting cultivation habitat specialist), and habitat generalists. Molecular analysis of bioindicator beetle species was done using mitochondrial cytochrome oxidase subunit I (COI) marker to validate the beetle species and describe genetic variation among them in relation to heterogeneity, transition/transversion bias, codon usage bias, evolutionary distance, and substitution pattern. The present study revealed the fact that shifting cultivation practice significantly affects the beetle species in terms of biodiversity pattern as well as evolutionary features. Spatiotemporal assessment of soil-plant-beetle interactions in shifting cultivation system and their influence in land degradation and ecology will be helpful in making biodiversity conservation decisions in the near future.

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

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

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

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

PubMed

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

2009-12-01

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

The association of nephrolithiasis with metabolic syndrome and its components: a cross-sectional analysis.

PubMed

Liu, Yen-Tze; Yang, Pei-Yu; Yang, Yu-Wen; Sun, Hung-Yu; Lin, I-Ching

2017-01-01

Metabolic syndrome is a worldwide disorder and also the major risk factor of several systemic diseases. Evidence identifying the association between metabolic syndrome and nephrolithiasis is lacking, especially in Taiwan. The aim of this study was to investigate the association between nephrolithiasis and metabolic syndrome and its components. This was a cross-sectional study conducted in the Health Examination Department of a medical center in Changhua, Taiwan, from January 2010 to December 2010. We reviewed the medical records of patients who had visited the Health Examination Center of Changhua Christian Hospital in 2010. A total of 3,886 individuals were enrolled. According to the exclusion criteria, those with an age <20 years and an abnormal renal function were excluded. A total of 3,793 subjects were included. All P -values are two tailed, and P <0.05 was defined as statistically significant. The results showed a correlation between nephrolithiasis and metabolic syndrome and its components. The multivariate-adjusted odds ratio (OR) (95% confidence interval [CI]) of metabolic syndrome for nephrolithiasis was 1.318 (1.083-1.604), with a P -value of 0.006. Larger waist circumference (multivariable-adjusted OR 1.338; 95% CI 1.098-1.631; P =0.004), higher blood pressure (multivariable-adjusted OR 1.333; 95% CI 1.106-1.607; P =0.003), and increased fasting glucose (multivariable-adjusted OR 1.276; 95% CI 1.054-1.546; P =0.01) were associated with nephrolithiasis. This is the first study in Taiwan to investigate the relationship between metabolic syndrome and nephrolithiasis. The mechanism is controversial, and several hypotheses are offered. Adequate lifestyle modification and proper treatment in metabolic syndrome management may both contribute to nephrolithiasis prevention.

Racial Differences in Circulating Natriuretic Peptide Levels: The Atherosclerosis Risk in Communities Study

PubMed Central

Gupta, Deepak K; Claggett, Brian; Wells, Quinn; Cheng, Susan; Li, Man; Maruthur, Nisa; Selvin, Elizabeth; Coresh, Josef; Konety, Suma; Butler, Kenneth R; Mosley, Thomas; Boerwinkle, Eric; Hoogeveen, Ron; Ballantyne, Christie M; Solomon, Scott D

2015-01-01

Background Natriuretic peptides promote natriuresis, diuresis, and vasodilation. Experimental deficiency of natriuretic peptides leads to hypertension (HTN) and cardiac hypertrophy, conditions more common among African Americans. Hospital-based studies suggest that African Americans may have reduced circulating natriuretic peptides, as compared to Caucasians, but definitive data from community-based cohorts are lacking. Methods and Results We examined plasma N-terminal pro B-type natriuretic peptide (NTproBNP) levels according to race in 9137 Atherosclerosis Risk in Communities (ARIC) Study participants (22% African American) without prevalent cardiovascular disease at visit 4 (1996–1998). Multivariable linear and logistic regression analyses were performed adjusting for clinical covariates. Among African Americans, percent European ancestry was determined from genetic ancestry informative markers and then examined in relation to NTproBNP levels in multivariable linear regression analysis. NTproBNP levels were significantly lower in African Americans (median, 43 pg/mL; interquartile range [IQR], 18, 88) than Caucasians (median, 68 pg/mL; IQR, 36, 124; P<0.0001). In multivariable models, adjusted log NTproBNP levels were 40% lower (95% confidence interval [CI], −43, −36) in African Americans, compared to Caucasians, which was consistent across subgroups of age, gender, HTN, diabetes, insulin resistance, and obesity. African-American race was also significantly associated with having nondetectable NTproBNP (adjusted OR, 5.74; 95% CI, 4.22, 7.80). In multivariable analyses in African Americans, a 10% increase in genetic European ancestry was associated with a 7% (95% CI, 1, 13) increase in adjusted log NTproBNP. Conclusions African Americans have lower levels of plasma NTproBNP than Caucasians, which may be partially owing to genetic variation. Low natriuretic peptide levels in African Americans may contribute to the greater risk for HTN and its sequalae in this population. PMID:25999400

Ten-year experiences on initial genetic examination in childhood acute lymphoblastic leukaemia in Hungary (1993-2002). Technical approaches and clinical implementation.

PubMed

Olah, Eva; Balogh, Erzsebet; Pajor, Laszlo; Jakab, Zsuzsanna

2011-03-01

A nationwide study was started in 1993 to provide genetic diagnosis for all newly diagnosed childhood ALL cases in Hungary using cytogenetic examination, DNA-index determination, FISH (aneuploidy, ABL/BCR, TEL/AML1) and molecular genetic tests (ABL/BCR, MLL/AF4, TEL/AML1). Aim of the study was to assess the usefulness of different genetic methods, to study the frequency of various aberrations and their prognostic significance. Results were synthesized for genetic subgrouping of patients. To assess the prognostic value of genetic aberrations overall and event-free survival of genetic subgroups were compared using Kaplan-Meier method. Prognostic role of aberrations was investigated by multivariate analysis (Cox's regression) as well in comparison with other factors (age, sex, major congenital abnormalities, initial WBC, therapy, immunophenotype). Five hundred eighty-eight ALL cases were diagnosed between 1993-2002. Cytogenetic examination was performed in 537 (91%) (success rate 73%), DNA-index in 265 (45%), FISH in 74 (13%), TEL/AML1 RT-PCR in 219 (37%) cases producing genetic diagnosis in 457 patients (78%). Proportion of subgroups with good prognosis in prae-B-cell ALL was lower than expected: hyperdiploidB 18% (73/400), TEL/AML1+ 9% (36/400). Univariate analysis showed significantly better 5-year EFS in TEL/AML1+ (82%) and hyperdiploidB cases (78%) than in tetraploid (44%) or pseudodiploid (52%) subgroups. By multivariate analysis main negative prognostic factors were: congenital abnormalities, high WBC, delay in therapy, specific translocations. Complementary use of each of genetic methods used is necessary for reliable genetic diagnosis according to the algorithm presented. Specific genetic alterations proved to be of prognostic significance.

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…

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…

Multivariate Statistical Analysis of MSL APXS Bulk Geochemical Data

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; Edwards, C. S.; Thompson, L. M.; Schmidt, M. E.

2014-12-01

We apply cluster and factor analyses to bulk chemical data of 130 soil and rock samples measured by the Alpha Particle X-ray Spectrometer (APXS) on the Mars Science Laboratory (MSL) rover Curiosity through sol 650. Multivariate approaches such as principal components analysis (PCA), cluster analysis, and factor analysis compliment more traditional approaches (e.g., Harker diagrams), with the advantage of simultaneously examining the relationships between multiple variables for large numbers of samples. Principal components analysis has been applied with success to APXS, Pancam, and Mössbauer data from the Mars Exploration Rovers. Factor analysis and cluster analysis have been applied with success to thermal infrared (TIR) spectral data of Mars. Cluster analyses group the input data by similarity, where there are a number of different methods for defining similarity (hierarchical, density, distribution, etc.). For example, without any assumptions about the chemical contributions of surface dust, preliminary hierarchical and K-means cluster analyses clearly distinguish the physically adjacent rock targets Windjana and Stephen as being distinctly different than lithologies observed prior to Curiosity's arrival at The Kimberley. In addition, they are separated from each other, consistent with chemical trends observed in variation diagrams but without requiring assumptions about chemical relationships. We will discuss the variation in cluster analysis results as a function of clustering method and pre-processing (e.g., log transformation, correction for dust cover) and implications for interpreting chemical data. Factor analysis shares some similarities with PCA, and examines the variability among observed components of a dataset so as to reveal variations attributable to unobserved components. Factor analysis has been used to extract the TIR spectra of components that are typically observed in mixtures and only rarely in isolation; there is the potential for similar results with data from APXS. These techniques offer new ways to understand the chemical relationships between the materials interrogated by Curiosity, and potentially their relation to materials observed by APXS instruments on other landed missions.

The Effect of Coffee and Quantity of Consumption on Specific Cardiovascular and All-Cause Mortality: Coffee Consumption Does Not Affect Mortality.

PubMed

Loomba, Rohit S; Aggarwal, Saurabh; Arora, Rohit R

2016-01-01

Previous studies have examined whether or not an association exists between the consumption of caffeinated coffee to all-cause and cardiovascular mortality. This study aimed to delineate this association using population representative data from the National Health and Nutrition Examination Survey III. Patients were included in the study if all the following criteria were met: (1) follow-up mortality data were available, (2) age of at least 45 years, and (3) reported amount of average coffee consumption. A total of 8608 patients were included, with patients stratified into the following groups of average daily coffee consumption: (1) no coffee consumption, (2) less than 1 cup, (3) 1 cup a day, (4) 2-3 cups, (5) 4-5 cups, (6) more than 6 cups a day. Odds ratios, 95% confidence intervals, and P values were calculated for univariate analysis to compare the prevalence of all-cause mortality, ischemia-related mortality, congestive heart failure-related mortality, and stroke-related mortality, using the no coffee consumption group as reference. These were then adjusted for confounding factors for a multivariate analysis. P < 0.05 were considered statistically significant. Univariate analysis demonstrated an association between coffee consumption and mortality, although this became insignificant on multivariate analysis. Coffee consumption, thus, does not seem to impact all-cause mortality or specific cardiovascular mortality. These findings do differ from those of recently published studies. Coffee consumption of any quantity seems to be safe without any increased mortality risk. There may be some protective effects but additional data are needed to further delineate this.

Impact of Rehabilitation on Outcomes in Patients With Ischemic Stroke: A Nationwide Retrospective Cohort Study in Japan.

PubMed

Yagi, Maiko; Yasunaga, Hideo; Matsui, Hiroki; Morita, Kojiro; Fushimi, Kiyohide; Fujimoto, Masashi; Koyama, Teruyuki; Fujitani, Junko

2017-03-01

We aimed to examine the concurrent effects of timing and intensity of rehabilitation on improving activities of daily living (ADL) among patients with ischemic stroke. Using the Japanese Diagnosis Procedure Combination inpatient database, we retrospectively analyzed consecutive patients with ischemic stroke at admission who received rehabilitation (n=100 719) from April 2012 to March 2014. Early rehabilitation was defined as that starting within 3 days after admission. The average rehabilitation intensity per day was calculated as the total units of rehabilitation during hospitalization divided by the length of hospital stay. A multivariable logistic regression analysis with multiple imputation and an instrumental variable analysis were performed to examine the association of early and intensive rehabilitation with the proportion of improved ADL score. The proportion of improved ADL score was higher in the early and intensive rehabilitation group. The multivariable logistic regression analysis showed that significant improvements in ADL were observed for early rehabilitation (odds ratio: 1.08; 95% confidence interval: 1.04-1.13; P <0.01) and intensive rehabilitation of >5.0 U/d (odds ratio: 1.87; 95% confidence interval: 1.69-2.07; P <0.01). The instrumental variable analysis showed that an increased proportion of improved ADL was associated with early rehabilitation (risk difference: 2.8%; 95% confidence interval: 2.0-3.4%; P <0.001) and intensive rehabilitation (risk difference: 5.6%; 95% confidence interval: 4.6-6.6%; P <0.001). The present results suggested that early and intensive rehabilitation improved ADL during hospitalization in patients with ischemic stroke. © 2017 American Heart Association, Inc.

[Comparison of arterial stiffness in non-hypertensive and hypertensive population of various age groups].

PubMed

Zhang, Y J; Wu, S L; Li, H Y; Zhao, Q H; Ning, C H; Zhang, R Y; Yu, J X; Li, W; Chen, S H; Gao, J S

2018-01-24

Objective: To investigate the impact of blood pressure and age on arterial stiffness in general population. Methods: Participants who took part in 2010, 2012 and 2014 Kailuan health examination were included. Data of brachial ankle pulse wave velocity (baPWV) examination were analyzed. According to the WHO criteria of age, participants were divided into 3 age groups: 18-44 years group ( n= 11 608), 45-59 years group ( n= 12 757), above 60 years group ( n= 5 002). Participants were further divided into hypertension group and non-hypertension group according to the diagnostic criteria for hypertension (2010 Chinese guidelines for the managemengt of hypertension). Multiple linear regression analysis was used to analyze the association between systolic blood pressure (SBP) with baPWV in the total participants and then stratified by age groups. Multivariate logistic regression model was used to analyze the influence of blood pressure on arterial stiffness (baPWV≥1 400 cm/s) of various groups. Results: (1)The baseline characteristics of all participants: 35 350 participants completed 2010, 2012 and 2014 Kailuan examinations and took part in baPWV examination. 2 237 participants without blood pressure measurement values were excluded, 1 569 participants with history of peripheral artery disease were excluded, we also excluded 1 016 participants with history of cardiac-cerebral vascular disease. Data from 29 367 participants were analyzed. The age was (48.0±12.4) years old, 21 305 were males (72.5%). (2) Distribution of baPWV in various age groups: baPWV increased with aging. In non-hypertension population, baPWV in 18-44 years group, 45-59 years group, above 60 years group were as follows: 1 299.3, 1 428.7 and 1 704.6 cm/s, respectively. For hypertension participants, the respective values of baPWV were: 1 498.4, 1 640.7 and 1 921.4 cm/s. BaPWV was significantly higher in hypertension group than non-hypertension group of respective age groups ( P< 0.05). (3) Multiple linear regression analysis defined risk factors of baPWV: Multivariate linear regression analysis showed that baPWV was positively correlated with SBP( t= 39.30, P< 0.001), and same results were found in the sub-age groups ( t -value was 37.72, 27.30, 9.15, all P< 0.001, respectively) after adjustment for other confounding factors, including age, sex, pulse pressure(PP), body mass index (BMI), fasting blood glucose (FBG), total cholesterol (TC), smoking, drinking, physical exercise, antihypertensive medications, lipid-lowering medication. (4) Multivariate logistic regression analysis of baPWV-related factors: After adjustment for other confounding factors, including age, sex, PP, BMI, FBG, TC, smoking, drinking, physical exercise, antihypertensive medication, lipid-lowering medication, multivariate logistic regression analysis showed that risks for increased arterial stiffness in hypertension group were higher than those in non-hypertension group, the OR in participants with hypertension was 2.54 (2.35-2.74) in the total participants, and same results were also found in sub-age groups, the OR s were 3.22(2.86-3.63), 2.48(2.23-2.76), and 1.91(1.42-2.56), respectively, in each sub-age group. Conclusion: SBP is positively related to arterial stiffness in different age groups, and hypertension is a risk factor for increased arterial stiffness in different age groups. Clinical Trial Registry Chinese Clinical Trial Registry, ChiCTR-TNC-11001489.

Carbon financial markets: A time-frequency analysis of CO2 prices

NASA Astrophysics Data System (ADS)

Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana

2014-11-01

We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.

Physical Activity Level of Korean Adults with Chronic Diseases: The Korean National Health and Nutritional Examination Survey, 2010-2012.

PubMed

Jin, Ho-Seong; An, Ah-Reum; Choi, Ho-Chun; Lee, Sang-Hyun; Shin, Dong-Heon; Oh, Seung-Min; Seo, Young-Gyun; Cho, Be-Long

2015-11-01

Proper physical activities are known to be helpful in the prevention and management of chronic diseases. However, the physical activity level of patients with chronic diseases is low. Therefore, this study aimed to investigate the physical activity compliance of patients with hypertension, diabetes, and dyslipidemia in Korea. This study analyzed the 2010-2012 Fifth Korean National Health and Nutrition Examination Survey data. We included 13,873 individuals in the analysis. The level of physical activity compliance was measured by performing multivariate logistic regression analyses. In the univariate analysis, the subjects with hypertension or diabetes tended to comply with the physical activity guidelines less faithfully than their healthy counterparts. The proportion of subjects with hypertension who were insufficiently physically active was 65.4% among the men and 75.8% among the women. For diabetes, the proportions were 66.7% and 76.8%, respectively. No significant difference was found between the subjects with dyslipidemia and their healthy counterparts. In the multivariate logistic regression analysis, no significant difference in physical activity compliance was observed between the subjects with hypertension, diabetes, or dyslipidemia and their healthy counterparts for both sexes. The patients with hypertension or diabetes tended to have lower physical activity prevlaence than their healthy counterparts. However, for dyslipidemia, no significant difference was found between the two groups. Given the significance of physical activities in the management of chronic diseases, the physical activities of these patients need to be improved.

Lymph node ratio may predict relapse free survival and overall survival in patients with stage II & III colorectal carcinoma.

PubMed

Zekri, Jamal; Ahmad, Imran; Fawzy, Ehab; Elkhodary, Tawfik R; Al-Gahmi, Aboelkhair; Hassouna, Ashraf; El Sayed, Mohamed E; Ur Rehman, Jalil; Karim, Syed M; Bin Sadiq, Bakr

2015-01-01

Lymph node ratio (LNR) defined as the number of lymph nodes (LNs) involved with metastases divided by number of LNs examined, has been shown to be an independent prognostic factor in breast, stomach and various other solid tumors. Its significance as a prognostic determinant in colorectal cancer (CRC) is still under investigation. This study investigated the prognostic value of LNR in patients with resected CRC. We retrospectively ex- amined 145 patients with stage II & III CRC diagnosed and treated at a single institution during 9 years pe- riod. Patients were grouped according to LNR in three groups. Group 1; LNR < 0.05, Group 2; LNR = 0.05-0.19 & Group 3 > 0.19. Chi square, life table analysis and multivariate Cox regression were used for statistical analysis. On multivariate analysis, number of involved LNs (NILN) (HR = 1.15, 95% CI 1.055-1.245; P = 0.001) and pathological T stage (P = 0.002) were statistically significant predictors of relapse free survival (RFS). LNR as a continuous variable (but not as a categorical variable) was statistically significant predictor of RFS (P = 0.02). LNR was also a statistically significant predictor of overall survival (OS) (P = 0.02). LNR may predict RFS and OS in patients with resected stage II & III CRC. Studies with larger cohorts and longer follow up are needed to further examine and validate theprognostic value of LNR.

The FIB-4 score predicts postoperative short-term outcomes of hepatocellular carcinoma fulfilling the milan criteria.

PubMed

Dong, J; Xu, X-h; Ke, M-y; Xiang, J-x; Liu, W-y; Liu, X-m; Wang, B; Zhang, X-f; Lv, Y

2016-05-01

The fibrosis score 4 (FIB-4) score is a useful tool to determine the degree of hepatic fibrosis. Liver fibrosis and cirrhosis are well-known predictors of postoperative complications after hepatectomy. This study examined the impact of FIB-4 on postoperative short-term outcomes of patients with hepatocellular carcinoma (HCC). Three hundred and fifty patients undergoing hepatectomy for HCC between 2008 and 2013 were enrolled. The receiver operating characteristic (ROC) curve analysis was performed to determine the cutoff value of the FIB-4. Univariate and multivariate analysis was performed to identify the risk factors. The correlation of the preoperative FIB-4 value with clinicopathological parameters was examined. Postoperative complications were observed in 202 (57.7%) patients. The optimal cutoff value of the FIB-4 was set at 2.88 and 3.85 for postoperative complications and intraoperative blood loss respectively. It was also an independent prognostic factor for postoperative complications (hazard ratio [HR], 1.202; 95% CI, 1.076-1.344; P = 0.001) and intraoperative blood loss (HR, 1.196; 95% CI, 1.091-1.343; P < 0.001) by multivariate analysis. The FIB-4 was significantly correlated with age, liver function, coagulation function, blood loss, intraoperative blood transfusion (all P < 0.05). Preoperative FIB-4 is a useful index to predict postoperative outcomes in patients with HCC. The FIB-4 should be assessed routinely for hepatocellular carcinoma patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring the Influence of Income and Geography on Access to Services for Older Adults in British Columbia: A Multivariate Analysis Using the Canadian Community Health Survey (Cycle 3.1)

ERIC Educational Resources Information Center

Allan, Diane E.; Funk, Laura M.; Reid, R. Colin; Cloutier-Fisher, Denise

2011-01-01

Existing research on the health care utilization patterns of older Canadians suggests that income does not usually restrict an individual's access to care. However, the role that income plays in influencing access to health services by older adults living in rural areas is relatively unknown. This article examines the relationship between income…

Analysis of Blood Glucose Distribution Characteristics and Its Risk Factors among a Health Examination Population in Wuhu (China)

PubMed Central

Song, Jiangen; Zha, Xiaojuan; Li, Haibo; Guo, Rui; Zhu, Yu; Wen, Yufeng

2016-01-01

Background: Diabetes mellitus (DM) and Impaired Fasting Glucose (IFG) represent serious threats to human health, and as a result, this study was aimed at understanding the blood glucose distribution characteristics and the risk factors among a large health examination population in China. Methods: An investigation with physical and biochemical examinations and questionnaires was conducted in the physical examination center from 2011 to 2014 and as a result 175,122 physical examination attendees were enrolled in this study. Multivariate logistic regression was used to explore the factors influencing blood sugar levels. Results: The rates of IFG and DM were 6.0% and 3.8%. Prevalence were 7.6%/5.1% in males and 5.1%/2.8% in females for IFG and DM, respectively. The prevalence of IFG and DM were thus higher in males than in females. In the normal group, except high density lipoprotein (HDL) that was significantly higher than in the IFG and DM group, the other indexes (age, body mass index (BMI), glucose (Glu), total cholesterol (TC) and total glycerides (TG) were lower than those in the IFG and DM group. The proportion of IFG and DM also increased with the increases in proportion of abnormal blood pressure, smoking and alcohol consumption. Multivariate logistic regression analysis showed that increasing age, high BMI, high TC, high TG and low HDL increased the risk of diabetes, while in males, in addition to the above factors, the smoking and drinking factors also increased the risk of diabetes. After the age of 65, the blood glucose level reached a peak in males, while in females, the increasing trends was on the rise. The inflexion age of the fast rise was younger in males than in females. Conclusion: The study population showed a high prevalence of DM and IFG among the adults. Regular physical examination for the early detection of diabetes is recommended in the high-risk population. PMID:27043603

Analysis of Blood Glucose Distribution Characteristics and Its Risk Factors among a Health Examination Population in Wuhu (China).

PubMed

Song, Jiangen; Zha, Xiaojuan; Li, Haibo; Guo, Rui; Zhu, Yu; Wen, Yufeng

2016-03-31

Diabetes mellitus (DM) and Impaired Fasting Glucose (IFG) represent serious threats to human health, and as a result, this study was aimed at understanding the blood glucose distribution characteristics and the risk factors among a large health examination population in China. An investigation with physical and biochemical examinations and questionnaires was conducted in the physical examination center from 2011 to 2014 and as a result 175,122 physical examination attendees were enrolled in this study. Multivariate logistic regression was used to explore the factors influencing blood sugar levels. The rates of IFG and DM were 6.0% and 3.8%. Prevalence were 7.6%/5.1% in males and 5.1%/2.8% in females for IFG and DM, respectively. The prevalence of IFG and DM were thus higher in males than in females. In the normal group, except high density lipoprotein (HDL) that was significantly higher than in the IFG and DM group, the other indexes (age, body mass index (BMI), glucose (Glu), total cholesterol (TC) and total glycerides (TG) were lower than those in the IFG and DM group. The proportion of IFG and DM also increased with the increases in proportion of abnormal blood pressure, smoking and alcohol consumption. Multivariate logistic regression analysis showed that increasing age, high BMI, high TC, high TG and low HDL increased the risk of diabetes, while in males, in addition to the above factors, the smoking and drinking factors also increased the risk of diabetes. After the age of 65, the blood glucose level reached a peak in males, while in females, the increasing trends was on the rise. The inflexion age of the fast rise was younger in males than in females. The study population showed a high prevalence of DM and IFG among the adults. Regular physical examination for the early detection of diabetes is recommended in the high-risk population.

Mental Health and Antiretroviral Adherence Among Youth Living With HIV in Rwanda.

PubMed

Smith Fawzi, Mary C; Ng, Lauren; Kanyanganzi, Fredrick; Kirk, Catherine; Bizimana, Justin; Cyamatare, Felix; Mushashi, Christina; Kim, Taehoon; Kayiteshonga, Yvonne; Binagwaho, Agnes; Betancourt, Theresa S

2016-10-01

In Rwanda, significant progress has been made in advancing access to antiretroviral therapy (ART) among youth. As availability of ART increases, adherence is critical for preventing poor clinical outcomes and transmission of HIV. The goals of the study are to (1) describe ART adherence and mental health problems among youth living with HIV aged 10 to 17; and (2) examine the association between these factors among this population in rural Rwanda. A cross-sectional analysis was conducted that examined the association of mental health status and ART adherence among youth (n = 193). ART adherence, mental health status, and related variables were examined based on caregiver and youth report. Nonadherence was defined as ever missing or refusing a dose of ART within the past month. Multivariate modeling was performed to examine the association between mental health status and ART adherence. Approximately 37% of youth missed or refused ART in the past month. In addition, a high level of depressive symptoms (26%) and attempt to hurt or kill oneself (12%) was observed in this population of youth living with HIV in Rwanda. In multivariate analysis, nonadherence was significantly associated with some mental health outcomes, including conduct problems (odds ratio 2.90, 95% confidence interval 1.55-5.43) and depression (odds ratio 1.02, 95% confidence interval 1.01-1.04), according to caregiver report. A marginally significant association was observed for youth report of depressive symptoms. The findings suggest that mental health should be considered among the factors related to ART nonadherence in HIV services for youth, particularly for mental health outcomes, such as conduct problems and depression. Copyright © 2016 by the American Academy of Pediatrics.

Performance of the disease risk score in a cohort study with policy-induced selection bias.

PubMed

Tadrous, Mina; Mamdani, Muhammad M; Juurlink, David N; Krahn, Murray D; Lévesque, Linda E; Cadarette, Suzanne M

2015-11-01

To examine the performance of the disease risk score (DRS) in a cohort study with evidence of policy-induced selection bias. We examined two cohorts of new users of bisphosphonates. Estimates for 1-year hip fracture rates between agents using DRS, exposure propensity scores and traditional multivariable analysis were compared. The results for the cohort with no evidence of policy-induced selection bias showed little variation across analyses (-4.1-2.0%). Analysis of the cohort with evidence of policy-induced selection bias showed greater variation (-13.5-8.1%), with the greatest difference seen with DRS analyses. Our findings suggest that caution may be warranted when using DRS methods in cohort studies with policy-induced selection bias, further research is needed.

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

PubMed

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

2016-01-01

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

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

Risk factors for low receptive vocabulary abilities in the preschool and early school years in the longitudinal study of Australian children.

PubMed

Christensen, Daniel; Zubrick, Stephen R; Lawrence, David; Mitrou, Francis; Taylor, Catherine L

2014-01-01

Receptive vocabulary development is a component of the human language system that emerges in the first year of life and is characterised by onward expansion throughout life. Beginning in infancy, children's receptive vocabulary knowledge builds the foundation for oral language and reading skills. The foundations for success at school are built early, hence the public health policy focus on reducing developmental inequalities before children start formal school. The underlying assumption is that children's development is stable, and therefore predictable, over time. This study investigated this assumption in relation to children's receptive vocabulary ability. We investigated the extent to which low receptive vocabulary ability at 4 years was associated with low receptive vocabulary ability at 8 years, and the predictive utility of a multivariate model that included child, maternal and family risk factors measured at 4 years. The study sample comprised 3,847 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Multivariate logistic regression was used to investigate risks for low receptive vocabulary ability from 4-8 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. In the multivariate model, substantial risk factors for receptive vocabulary delay from 4-8 years, in order of descending magnitude, were low receptive vocabulary ability at 4 years, low maternal education, and low school readiness. Moderate risk factors, in order of descending magnitude, were low maternal parenting consistency, socio-economic area disadvantage, low temperamental persistence, and NESB status. The following risk factors were not significant: One or more siblings, low family income, not reading to the child, high maternal work hours, and Aboriginal or Torres Strait Islander ethnicity. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude does not do particularly well in predicting low receptive vocabulary ability from 4-8 years.

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.

Association of BRAFV600E Mutation and MicroRNA Expression with Central Lymph Node Metastases in Papillary Thyroid Cancer: A Prospective Study from Four Endocrine Surgery Centers

PubMed Central

Aragon Han, Patricia; Kim, Hyun-seok; Cho, Soonweng; Fazeli, Roghayeh; Najafian, Alireza; Khawaja, Hunain; McAlexander, Melissa; Dy, Benzon; Sorensen, Meredith; Aronova, Anna; Sebo, Thomas J.; Giordano, Thomas J.; Fahey, Thomas J.; Thompson, Geoffrey B.; Gauger, Paul G.; Somervell, Helina; Bishop, Justin A.; Eshleman, James R.; Schneider, Eric B.; Witwer, Kenneth W.; Umbricht, Christopher B.

2016-01-01

Background: Studies have demonstrated an association of the BRAFV600E mutation and microRNA (miR) expression with aggressive clinicopathologic features in papillary thyroid cancer (PTC). Analysis of BRAFV600E mutations with miR expression data may improve perioperative decision making for patients with PTC, specifically in identifying patients harboring central lymph node metastases (CLNM). Methods: Between January 2012 and June 2013, 237 consecutive patients underwent total thyroidectomy and prophylactic central lymph node dissection (CLND) at four endocrine surgery centers. All tumors were tested for the presence of the BRAFV600E mutation and miR-21, miR-146b-3p, miR-146b-5p, miR-204, miR-221, miR-222, and miR-375 expression. Bivariate and multivariable analyses were performed to examine associations between molecular markers and aggressive clinicopathologic features of PTC. Results: Multivariable logistic regression analysis of all clinicopathologic features found miR-146b-3p and miR-146b-5p to be independent predictors of CLNM, while the presence of BRAFV600E almost reached significance. Multivariable logistic regression analysis limited to only predictors available preoperatively (molecular markers, age, sex, and tumor size) found miR-146b-3p, miR-146b-5p, miR-222, and BRAFV600E mutation to predict CLNM independently. While BRAFV600E was found to be associated with CLNM (48% mutated in node-positive cases vs. 28% mutated in node-negative cases), its positive and negative predictive values (48% and 72%, respectively) limit its clinical utility as a stand-alone marker. In the subgroup analysis focusing on only classical variant of PTC cases (CVPTC), undergoing prophylactic lymph node dissection, multivariable logistic regression analysis found only miR-146b-5p and miR-222 to be independent predictors of CLNM, while BRAFV600E was not significantly associated with CLNM. Conclusion: In the patients undergoing prophylactic CLNDs, miR-146b-3p, miR-146b-5p, and miR-222 were found to be predictive of CLNM preoperatively. However, there was significant overlap in expression of these miRs in the two outcome groups. The BRAFV600E mutation, while being a marker of CLNM when considering only preoperative variables among all histological subtypes, is likely not a useful stand-alone marker clinically because the difference between node-positive and node-negative cases was small. Furthermore, it lost significance when examining only CVPTC. Overall, our results speak to the concept and interpretation of statistical significance versus actual applicability of molecular markers, raising questions about their clinical usefulness as individual prognostic markers. PMID:26950846

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

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

2011-01-01

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

Apolipoprotein E Polymorphism and Left Ventricular Failure in Beta-Thalassemia: A Multivariate Meta-Analysis.

PubMed

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

2017-09-01

Apolipoprotein E (ApoE) is potentially a genetic risk factor for the development of left ventricular failure (LVF), the main cause of death in beta-thalassemia homozygotes. In the present study, we synthesize the results of independent studies examining the effect of ApoE on LVF development in thalassemic patients through a meta-analytic approach. However, all studies report more than one outcome, as patients are classified into three groups according to the severity of the symptoms and the genetic polymorphism. Thus, a multivariate meta-analytic method that addresses simultaneously multiple exposures and multiple comparison groups was developed. Four individual studies were included in the meta-analysis involving 613 beta-thalassemic patients and 664 controls. The proposed method that takes into account the correlation of log odds ratios (log(ORs)), revealed a statistically significant overall association (P-value  =  0.009), mainly attributed to the contrast of E4 versus E3 allele for patients with evidence (OR: 2.32, 95% CI: 1.19, 4.53) or patients with clinical and echocardiographic findings (OR: 3.34, 95% CI: 1.78, 6.26) of LVF. This study suggests that E4 is a genetic risk factor for LVF in beta-thalassemia major. The presented multivariate approach can be applied in several fields of research. © 2017 John Wiley & Sons Ltd/University College London.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

1 H-NMR with Multivariate Analysis for Automobile Lubricant Comparison.

PubMed

Kim, Siwon; Yoon, Dahye; Lee, Dong-Kye; Yoon, Changshin; Kim, Suhkmann

2017-07-01

Identification of suspected automobile-related lubricants could provide valuable information in forensic cases. We examined that automobile lubricants might exhibit the chemometric characteristics to their individual usages. To compare the degree of clustering in the plots, we co-plotted general industrial oils that were highly dissimilar with automobile lubricants in additive compositions. 1 H-NMR spectroscopy was used with multivariate statistics as a tool for grouping, clustering, and identification of automobile lubricants in laboratory conditions. We analyzed automobile lubricants including automobile engine oils, automobile transmission oils, automobile gear oils, and motorcycle oils. In contrast to the general industrial oils, automobile lubricants showed relatively high tendencies of clustering to their usages. Our pilot study demonstrated that the comparison of known and questioned samples to their usages might be possible in forensic fields. © 2017 American Academy of Forensic Sciences.

Expression of ARs in triple negative breast cancer tumors: a potential prognostic factor?

PubMed

Giannos, Aris; Filipits, Martin; Zagouri, Flora; Brandstetter, Anita; Tsigginou, Alexandra; Sotiropoulou, Maria; Papaspyrou, Irene; Sergentanis, Theodoros N; Psaltopoulou, Theodora; Rodolakis, Alexandros; Antsaklis, Aris; Dimopoulos, Meletios-Athanasios; Dimitrakakis, Constantine

2015-01-01

In light of the controversial published literature, this study aims to examine the potential prognostic role of AR immunohistochemical expression in triple negative breast cancer (TNBC). Ninety patients with TNBC were included in this study; the associations between AR expression (Allred score), clinicopathological variables (stage, grade, histological subtype, tumor size, nodal status, age at diagnosis, Ki67 expression, and p53 expression), and overall survival were evaluated. AR expression was not associated with stage, grade, histological subtype, tumor size, nodal status, age at diagnosis, Ki67 expression, and p53 expression. AR immunopositivity was not associated with overall survival either at the univariate or at the multivariate Cox regression analysis (multivariate hazard ratio =0.66, 95% confidence interval: 0.26-1.70, P=0.393). AR expression does not seem to play a prognostic role in TNBC.

A power analysis for multivariate tests of temporal trend in species composition.

PubMed

Irvine, Kathryn M; Dinger, Eric C; Sarr, Daniel

2011-10-01

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that monitor entire multispecies assemblages require a method for determining the power of multivariate statistical models to detect trend. We provide a method to simulate presence-absence species assemblage data that are consistent with increasing or decreasing directional change in species composition within multiple sites. This step is the foundation for using Monte Carlo methods to approximate the power of any multivariate method for detecting temporal trends. We focus on comparing the power of the Mantel test, permutational multivariate analysis of variance, and constrained analysis of principal coordinates. We find that the power of the various methods we investigate is sensitive to the number of species in the community, univariate species patterns, and the number of sites sampled over time. For increasing directional change scenarios, constrained analysis of principal coordinates was as or more powerful than permutational multivariate analysis of variance, the Mantel test was the least powerful. However, in our investigation of decreasing directional change, the Mantel test was typically as or more powerful than the other models.

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

PubMed Central

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

2013-01-01

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

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

PubMed Central

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

2012-01-01

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

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Cartilage degradation biomarkers predict efficacy of a novel, highly selective matrix metalloproteinase 13 inhibitor in a dog model of osteoarthritis: confirmation by multivariate analysis that modulation of type II collagen and aggrecan degradation peptides parallels pathologic changes.

PubMed

Settle, Steven; Vickery, Lillian; Nemirovskiy, Olga; Vidmar, Tom; Bendele, Alison; Messing, Dean; Ruminski, Peter; Schnute, Mark; Sunyer, Teresa

2010-10-01

To demonstrate that the novel highly selective matrix metalloproteinase 13 (MMP-13) inhibitor PF152 reduces joint lesions in adult dogs with osteoarthritis (OA) and decreases biomarkers of cartilage degradation. The potency and selectivity of PF152 were evaluated in vitro using 16 MMPs, TACE, and ADAMTS-4 and ADAMTS-5, as well as ex vivo in human cartilage explants. In vivo effects were evaluated at 3 concentrations in mature beagles with partial medial meniscectomy. Gross and histologic changes in the femorotibial joints were evaluated using various measures of cartilage degeneration. Biomarkers of cartilage turnover were examined in serum, urine, or synovial fluid. Results were analyzed individually and in combination using multivariate analysis. The potent and selective MMP-13 inhibitor PF152 decreased human cartilage degradation ex vivo in a dose-dependent manner. PF152 treatment of dogs with OA reduced cartilage lesions and decreased biomarkers of type II collagen (type II collagen neoepitope) and aggrecan (peptides ending in ARGN or AGEG) degradation. The dose required for significant inhibition varied with the measure used, but multivariate analysis of 6 gross and histologic measures indicated that all doses differed significantly from vehicle but not from each other. Combined analysis of cartilage degradation markers showed similar results. This highly selective MMP-13 inhibitor exhibits chondroprotective effects in mature animals. Biomarkers of cartilage degradation, when evaluated in combination, parallel the joint structural changes induced by the MMP-13 inhibitor. These data support the potential therapeutic value of selective MMP-13 inhibitors and the use of a set of appropriate biomarkers to predict efficacy in OA clinical trials.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

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

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

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

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

PubMed

Thulin, M

2016-09-10

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

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

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

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

Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study.

PubMed

Mokhtari, Mohammadreza; Narayanan, Balaji; Hamm, Jordan P; Soh, Pauline; Calhoun, Vince D; Ruaño, Gualberto; Kocherla, Mohan; Windemuth, Andreas; Clementz, Brett A; Tamminga, Carol A; Sweeney, John A; Keshavan, Matcheri S; Pearlson, Godfrey D

2016-05-01

The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Elimination of chromatographic and mass spectrometric problems in GC-MS analysis of Lavender essential oil by multivariate curve resolution techniques: Improving the peak purity assessment by variable size moving window-evolving factor analysis.

PubMed

Jalali-Heravi, Mehdi; Moazeni-Pourasil, Roudabeh Sadat; Sereshti, Hassan

2015-03-01

In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined. The proposed methodology was applied to the GC-MS analysis of Iranian Lavender essential oil, which resulted in extending the number of identified constituents from 56 to 143 components. It was found that the most abundant constituents of the Iranian Lavender essential oil are α-pinene (16.51%), camphor (10.20%), 1,8-cineole (9.50%), bornyl acetate (8.11%) and camphene (6.50%). This indicates that the Iranian type Lavender contains a relatively high percentage of α-pinene. Comparison of different types of Lavender essential oils showed the composition similarity between Iranian and Italian (Sardinia Island) Lavenders. Published by Elsevier B.V.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

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

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

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

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

Delayed onset of lactogenesis among first-time mothers is related to maternal obesity and factors associated with ineffective breastfeeding.

PubMed

Nommsen-Rivers, Laurie A; Chantry, Caroline J; Peerson, Janet M; Cohen, Roberta J; Dewey, Kathryn G

2010-09-01

Delayed onset of lactogenesis (OL) is most common in primiparas and increases the risk of excess neonatal weight loss, formula supplementation, and early weaning. We examined variables associated with delayed OL among first-time mothers who delivered at term and initiated breastfeeding (n = 431). We conducted in-person interviews during pregnancy and at days 0, 3, and 7 postpartum and extracted obstetric and newborn information from medical records. We defined OL as delayed if it occurred after 72 h and used chi-square analysis to examine its association with potential risk factors across 6 dimensions: 1) prenatal characteristics, 2) maternal anthropometric characteristics, 3) labor and delivery experience, 4) newborn characteristics, 5) maternal postpartum factors, and 6) infant feeding variables. We examined independent associations by using multivariable logistic regression analysis. Median OL was 68.9 h postpartum; 44% of mothers experienced delayed OL. We observed significant bivariate associations between delayed OL and variables in all 6 dimensions (P < 0.05). In a multivariate model adjusted for prenatal feeding intentions, independent risk factors for delayed OL were maternal age > or =30 y, body mass index in the overweight or obese range, birth weight >3600 g, absence of nipple discomfort between 0-3 d postpartum, and infant failing to "breastfeed well" > or =2 times in the first 24 h. Postpartum edema was significant in an alternate model excluding body mass index (P < 0.05). The risk factors for delayed OL are multidimensional. Public health and obstetric and maternity care interventions are needed to address what has become an alarmingly common problem among primiparas.

Quantifying asymmetry: ratios and alternatives.

PubMed

Franks, Erin M; Cabo, Luis L

2014-08-01

Traditionally, the study of metric skeletal asymmetry has relied largely on univariate analyses, utilizing ratio transformations when the goal is comparing asymmetries in skeletal elements or populations of dissimilar dimensions. Under this approach, raw asymmetries are divided by a size marker, such as a bilateral average, in an attempt to produce size-free asymmetry indices. Henceforth, this will be referred to as "controlling for size" (see Smith: Curr Anthropol 46 (2005) 249-273). Ratios obtained in this manner often require further transformations to interpret the meaning and sources of asymmetry. This model frequently ignores the fundamental assumption of ratios: the relationship between the variables entered in the ratio must be isometric. Violations of this assumption can obscure existing asymmetries and render spurious results. In this study, we examined the performance of the classic indices in detecting and portraying the asymmetry patterns in four human appendicular bones and explored potential methodological alternatives. Examination of the ratio model revealed that it does not fulfill its intended goals in the bones examined, as the numerator and denominator are independent in all cases. The ratios also introduced strong biases in the comparisons between different elements and variables, generating spurious asymmetry patterns. Multivariate analyses strongly suggest that any transformation to control for overall size or variable range must be conducted before, rather than after, calculating the asymmetries. A combination of exploratory multivariate techniques, such as Principal Components Analysis, and confirmatory linear methods, such as regression and analysis of covariance, appear as a promising and powerful alternative to the use of ratios. © 2014 Wiley Periodicals, Inc.

Conflicting Role of Sarcopenia and Obesity in Male Patients with Chronic Obstructive Pulmonary Disease: Korean National Health and Nutrition Examination Survey

PubMed Central

Koo, Hyeon-Kyoung; Park, Joo-Hyun; Park, Hye Kyeong; Jung, Hoon; Lee, Sung-Soon

2014-01-01

Objective To determine the impact of sarcopenia and obesity on pulmonary function and quality of life (QOL) in chronic obstructive pulmonary disease (COPD) patients. Research Design and Methods Data were obtained from the Korea National Health and Nutrition Examination Survey, including data from health interviews, health examinations, nutritional questionnaires, and laboratory findings. Laboratory data included pulmonary function assessment and dual energy X-ray absorptiometry results. Sarcopenia was measured by dual energy X-ray absorptiometry, and obesity was defined by body mass index. Male COPD patients were then classified into 4 groups according to the presence of sarcopenia and obesity. Results In male patients with COPD, the prevalence of sarcopenia was found to be 29.3%, and that of sarcopenic obesity was 14.2%. Furthermore, 22.5% of the patients observed in this study had impaired QOL. Following multivariable statistical analysis, both sarcopenia and obesity were independent risk factors for worsening lung function. Adjusted values of forced vital capacity and forced expiratory volume in 1 second were the lowest in the sarcopenic obesity group. Sarcopenia was also associated with more subjective activity limitation and poorer QOL; however obesity was related to less subjective limitation and better QOL after multivariable analysis. Adjusted value of QOL was the lowest in sarcopenic subjects without obesity, and the highest in obese subject without sarcopenia. Conclusions Both sarcopenia and obesity were found to be associated with worsening lung function in male COPD patients. However, obesity was positively correlated with improved QOL while sarcopenia was negatively correlated with QQL. PMID:25353344

Evaluation and simplification of the occupational slip, trip and fall risk-assessment test

PubMed Central

NAKAMURA, Takehiro; OYAMA, Ichiro; FUJINO, Yoshihisa; KUBO, Tatsuhiko; KADOWAKI, Koji; KUNIMOTO, Masamizu; ODOI, Haruka; TABATA, Hidetoshi; MATSUDA, Shinya

2016-01-01

Objective: The purpose of this investigation is to evaluate the efficacy of the occupational slip, trip and fall (STF) risk assessment test developed by the Japan Industrial Safety and Health Association (JISHA). We further intended to simplify the test to improve efficiency. Methods: A previous cohort study was performed using 540 employees aged ≥50 years who took the JISHA’s STF risk assessment test. We conducted multivariate analysis using these previous results as baseline values and answers to questionnaire items or score on physical fitness tests as variables. The screening efficiency of each model was evaluated based on the obtained receiver operating characteristic (ROC) curve. Results: The area under the ROC obtained in multivariate analysis was 0.79 when using all items. Six of the 25 questionnaire items were selected for stepwise analysis, giving an area under the ROC curve of 0.77. Conclusion: Based on the results of follow-up performed one year after the initial examination, we successfully determined the usefulness of the STF risk assessment test. Administering a questionnaire alone is sufficient for screening subjects at risk of STF during the subsequent one-year period. PMID:27021057

Multivariate analysis of subsurface radiometric data in Rongsohkham area, East Khasi Hills district, Meghalaya (India): implication on uranium exploration.

PubMed

Kukreti, B M; Pandey, Pradeep; Singh, R V

2012-08-01

Non-coring based exploratory drilling was under taken in the sedimentary environment of Rangsohkham block, East Khasi Hills district to examine the eastern extension of existing uranium resources located at Domiasiat and Wakhyn in the Mahadek basin of Meghalaya (India). Although radiometric survey and radiometric analysis of surface grab/channel samples in the block indicate high uranium content but the gamma ray logging results of exploratory boreholes in the block, did not obtain the expected results. To understand this abrupt discontinuity between the two sets of data (surface and subsurface) multivariate statistical analysis of primordial radioactive elements (K(40), U(238) and Th(232)) was performed using the concept of representative subsurface samples, drawn from the randomly selected 11 boreholes of this block. The study was performed to a high confidence level (99%), and results are discussed for assessing the U and Th behavior in the block. Results not only confirm the continuation of three distinct geological formations in the area but also the uranium bearing potential in the Mahadek sandstone of the eastern part of Mahadek Basin. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effects of Lacunar Infarctions on Cognitive Impairment in Patients with Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy

PubMed Central

Choi, Jay Chol; Kang, Sa-Yoon; Kang, Ji-Hoon; Na, Hae Ri; Park, Ji-Kang

2011-01-01

Background and Purpose Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited microangiopathy caused by mutations in the Notch3 gene. Although previous studies have shown an association between lacunar infarction and cognitive impairment, the relationship between MRI parameters and cognition remains unclear. In this study we investigated the influence of MRI parameters on cognitive impairment in CADASIL. Methods We applied a prospective protocol to 40 patients. MRI analysis included the normalized volume of white-matter hyperintensities (nWMHs), number of lacunes, and number of cerebral microbleeds. Cognition was assessed with the aid of psychometric tests [Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-cognition (ADAS-cog), Trail-Making Test, and Stroop interference (Stroop IF)]. Results A multivariate regression analysis revealed that the total number of lacunes influenced the performance in the MMSE, ADAS-cog, and Stroop IF, while nWMHs had a strong univariate association with ADAS-cog and Stroop IF scores. However, this association disappeared in the multivariate analysis. Conclusions These findings demonstrate that the number of lacunes is the main predictive factor of cognitive impairment in CADASIL. PMID:22259617

The effect of heavy metal contamination on the bacterial community structure at Jiaozhou Bay, China.

PubMed

Yao, Xie-Feng; Zhang, Jiu-Ming; Tian, Li; Guo, Jian-Hua

In this study, determination of heavy metal parameters and microbiological characterization of marine sediments obtained from two heavily polluted sites and one low-grade contaminated reference station at Jiaozhou Bay in China were carried out. The microbial communities found in the sampled marine sediments were studied using PCR-DGGE (denaturing gradient gel electrophoresis) fingerprinting profiles in combination with multivariate analysis. Clustering analysis of DGGE and matrix of heavy metals displayed similar occurrence patterns. On this basis, 17 samples were classified into two clusters depending on the presence or absence of the high level contamination. Moreover, the cluster of highly contaminated samples was further classified into two sub-groups based on the stations of their origin. These results showed that the composition of the bacterial community is strongly influenced by heavy metal variables present in the sediments found in the Jiaozhou Bay. This study also suggested that metagenomic techniques such as PCR-DGGE fingerprinting in combination with multivariate analysis is an efficient method to examine the effect of metal contamination on the bacterial community structure. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

A systems theoretic approach to analysis and control of mammalian circadian dynamics

PubMed Central

Abel, John H.; Doyle, Francis J.

2016-01-01

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

Conflicting relationship between age-dependent disorders, valvular heart disease and coronary artery disease by covariance structure analysis: Possible contribution of natriuretic peptide.

PubMed

Fukumoto, Risa; Kawai, Makoto; Minai, Kosuke; Ogawa, Kazuo; Yoshida, Jun; Inoue, Yasunori; Morimoto, Satoshi; Tanaka, Toshikazu; Nagoshi, Tomohisa; Ogawa, Takayuki; Yoshimura, Michihiro

2017-01-01

It is conceivable that contemporary valvular heart disease (VHD) is affected largely by an age-dependent atherosclerotic process, which is similar to that observed in coronary artery disease (CAD). However, a comorbid condition of VHD and CAD has not been precisely examined. The first objective of this study was to examine a possible comorbid condition. Provided that there is no comorbidity, the second objective was to search for the possible reasons by using conventional risk factors and plasma B-type natriuretic peptide (BNP) because BNP has a potentiality to suppress atherosclerotic development. The study population consisted of 3,457 patients consecutively admitted to our institution. The possible comorbid condition of VHD and CAD and the factors that influence the comorbidity were examined by covariance structure analysis and multivariate analysis. The distribution of the patients with VHD and those with CAD in the histograms showed that the incidence of VHD and the severity of CAD rose with seniority in appearance. The real statistical analysis was planned by covariance structure analysis. The current path model revealed that aging was associated with VHD and CAD severity (P < 0.001 for each); however, as a notable result, there was an inverse association regarding the comorbid condition between VHD and CAD (Correlation coefficient [β]: -0.121, P < 0.001). As the second objective, to clarify the factors leading to this inverse association, the contribution of conventional risk factors, such as age, gender, hypertension, smoking, diabetes, obesity and dyslipidemia, to VHD and CAD were examined by multivariate analysis. However, these factors did not exert an opposing effect on VHD and CAD, and the inverse association defied explanation. Since different pathological mechanisms may contribute to the formation of VHD and CAD, a differentially proposed path model using plasma BNP revealed that an increase in plasma BNP being drawn by VHD suppressed the progression of CAD (β: -0.465, P < 0.001). The incidence of VHD and CAD showed a significant conflicting relationship. This result supported the likely presence of unknown diverse mechanisms on top of the common cascade of atherosclerosis. Among them, the continuous elevation of plasma BNP due to VHD might be one of the explicable factors suppressing the progression of CAD.

THE AFRICAN DESCENT AND GLAUCOMA EVALUATION STUDY (ADAGES): PREDICTORS OF VISUAL FIELD DAMAGE IN GLAUCOMA SUSPECTS

PubMed Central

Khachatryan, Naira; Medeiros, Felipe A.; Sharpsten, Lucie; Bowd, Christopher; Sample, Pamela A.; Liebmann, Jeffrey M.; Girkin, Christopher A.; Weinreb, Robert N.; Miki, Atsuya; Hammel, Na’ama; Zangwill, Linda M.

2015-01-01

Purpose To evaluate racial differences in the development of visual field (VF) damage in glaucoma suspects. Design Prospective, observational cohort study. Methods Six hundred thirty six eyes from 357 glaucoma suspects with normal VF at baseline were included from the multicenter African Descent and Glaucoma Evaluation Study (ADAGES). Racial differences in the development of VF damage were examined using multivariable Cox Proportional Hazard models. Results Thirty one (25.4%) of 122 African descent participants and 47 (20.0%) of 235 European descent participants developed VF damage (p=0.078). In multivariable analysis, worse baseline VF mean deviation, higher mean arterial pressure during follow up, and a race *mean intraocular pressure (IOP) interaction term were significantly associated with the development of VF damage suggesting that racial differences in the risk of VF damage varied by IOP. At higher mean IOP levels, race was predictive of the development of VF damage even after adjusting for potentially confounding factors. At mean IOPs during follow-up of 22, 24 and 26 mmHg, multivariable hazard ratios (95%CI) for the development of VF damage in African descent compared to European descent subjects were 2.03 (1.15–3.57), 2.71 (1.39–5.29), and 3.61 (1.61–8.08), respectively. However, at lower mean IOP levels (below 22 mmHg) during follow-up, African descent was not predictive of the development of VF damage. Conclusion In this cohort of glaucoma suspects with similar access to treatment, multivariate analysis revealed that at higher mean IOP during follow-up, individuals of African descent were more likely to develop VF damage than individuals of European descent. PMID:25597839

Sociodemographic and lifestyle factors affecting the self-perception period of lower urinary tract symptoms of international prostate symptom score items.

PubMed

Kim, J H; Shim, S R; Lee, W J; Kim, H J; Kwon, S-S; Bae, J H

2012-12-01

This study investigated the influence of sociodemographic and lifestyle factors on the lower urinary tract symptom (LUTS) self-perception period and International Prostate Symptom Score. This cross-sectional study examined 209 men aged ≥ 40 years with non-treated LUTS who participated in a prostate examination survey. Questions included International Prostate Symptom Score (IPSS) items with self-perception periods for each item. Sociodemographic and lifestyle factors were also assessed. Participants were divided by mild LUTS (IPSS less than 8) and moderate-to-severe LUTS (IPSS 8 or higher). Self-perception period of the moderate-to-severe LUTS (n = 110) was affected by BMI; the self-perception period of the mild LUTS (n = 90) was affected by age, income, occupation and concomitant disease. Moderate-to-severe LUTS were affected by self-perception period (p = 0.03). Self-perception period was affected by concern for health (p = 0.005) by multivariate analysis, and self-perception period of mild LUTS was affected by BMI (p = 0.012). Moderate-to-severe LUTS were affected by age, number of family members, concern for health and drinking (p < 0.05, respectively) by multivariate analysis. Lower urinary tract symptom was affected by self-perception period. In moderate-to-severe LUTS, age, concern for health and drinking were affecting factors of self-perception period. © 2012 Blackwell Publishing Ltd.

Dental erosion and its association with diet in Libyan schoolchildren.

PubMed

Huew, R; Waterhouse, P J; Moynihan, P J; Kometa, S; Maguire, A

2011-10-01

To investigate any association between dental erosion and its potential dietary risk factors in a group of schoolchildren in Benghazi, Libya. A cross-sectional observational study. A random sample of 12-year-old schoolchildren in 36 randomly selected schools completed a questionnaire to provide dietary data and underwent dental examination. Dental erosion was assessed using UK National Diet and Nutrition Survey (2000) criteria. Associations between erosion and dietary variables under study were investigated through processes of bivariate and multivariate analyses. Of 791 schoolchildren dentally examined, 40.8% had dental erosion; erosion into enamel affecting 32.5%, into dentine affecting 8% and into pulp affecting 0.3% of subjects. Bivariate analysis showed frequency of fruit-based sugary drink intake was statistically significantly and positively associated with erosion (p=0.006, Odds Ratio; 1.498, 95% CI; 1.124, 1.996) as was the length of time taken to consume acidic drinks (p≠0.005, Odds Ratio; 1.593, 95%CI; 1.161, 2.186). Additionally, multivariate analysis showed frequency of consumption of fruit other than bananas, sugared tea with milk and flavoured milk to also be positively associated with erosion (p=<0.05). In this group of Libyan 12-year-olds, frequency of consumption of fruit-based sugary drinks and length of time taken to consume acidic drinks were the primary statistically significant positive risk factors for dental erosion.

Hair sterol signatures coupled to multivariate data analysis reveal an increased 7β-hydroxycholesterol production in cognitive impairment.

PubMed

Son, Hyun-Hwa; Lee, Do-Yup; Seo, Hong Seog; Jeong, Jihyeon; Moon, Ju-Yeon; Lee, Jung-Eun; Chung, Bong Chul; Kim, Eosu; Choi, Man Ho

2016-01-01

Altered cholesterol metabolism could be associated with cognitive impairment. The quantitative profiling of 19 hair sterols was developed using gas chromatography-mass spectrometry coupled to multivariate data analysis. The limit of quantification of all sterols ranged from 5 to 20 ng/g, while the calibration linearity was higher than 0.98. The precision (% CV) and accuracy (% bias) ranged from 3.2% to 9.8% and from 83.2% to 119.4%, respectively. Among the sterols examined, 8 were quantitatively detected from two strands of 3-cm-long scalp hair samples of female participants, including mild cognitive impairment (MCI, n=15), Alzheimer's disease (AD, n=31), and healthy controls (HC, n=36). The cognitive impairment (MCI or AD) was correlated with a higher metabolic rate than that of HCs based on 7β-hydroxycholesterol (P<0.005). Significant negative correlations (r=-0.822) were detected between Mini-Mental State Examination (MMSE) scores and hair sample metabolic ratios of 7β-hydroxycholesterol to cholesterol, which is an accepted, sensitive, and specific tool for discriminating HCs from individuals with MCI or AD. In conclusion, improved diagnostic values can be obtained using hair sterol signatures coupled with MMSE scores. This method may prove useful for predictive diagnosis in population screening of cognitive impairment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

DTIC Science & Technology

1993-06-18

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

[Multivariate ordinal logistic regression analysis on the association between consumption of fried food and both esophageal cancer and precancerous lesions].

PubMed

Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

2017-12-10

Objective: To investigate the effect of fried food intake on the pathogenesis of esophageal cancer and precancerous lesions. Methods: From 2005 to 2013, all the residents aged 40-69 years from 11 counties (cities) where cancer screening of upper gastrointestinal cancer had been conducted in rural areas of Henan province, were recruited as the subjects of study. Information on demography and lifestyle was collected. The residents under study were screened with iodine staining endoscopic examination and biopsy samples were diagnosed pathologically, under standardized criteria. Subjects with high risk were divided into the groups based on their different pathological degrees. Multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and esophageal cancer and precancerous lesions. Results: A total number of 8 792 cases with normal esophagus, 3 680 with mild hyperplasia, 972 with moderate hyperplasia, 413 with severe hyperplasia carcinoma in situ, and 336 cases of esophageal cancer were recruited. Results from multivariate logistic regression analysis showed that, when compared with those who did not eat fried food, the intake of fried food (<2 times/week: OR =1.60, 95% CI : 1.40-1.83; ≥2 times/week: OR =2.58, 95% CI : 1.98-3.37) appeared a risk factor for both esophageal cancer or precancerous lesions after adjustment for age, sex, marital status, educational level, body mass index, smoking and alcohol intake. Conclusion: The intake of fried food appeared a risk factor for both esophageal cancer and precancerous lesions.

Effect of membrane flux and dialyzer biocompatibility on survival in end-stage diabetic nephropathy.

PubMed

Götz, Angela K; Böger, Carsten A; Popal, Massoud; Banas, Bernhard; Krämer, Bernhard K

2008-01-01

We examined the effects of dialyzer membrane flux and biocompatibility on mortality in diabetic dialysis patients. We enrolled 402 prevalent chronic hemodialysis patients from 30 centers in Germany in 1999 for a prospective observational study until 2003. We compared 2 groups in post hoc analysis: high-flux (HF, n = 166) versus low-flux (LF, n = 236) membrane, and high biocompatibility (HB, n = 300) versus low biocompatibility (LB, n = 102). All-cause mortality (ACM) was the primary endpoint. Death causes were the secondary endpoints. Multivariate Cox regression analysis showed no significant difference in risk for ACM with respect to flux (hazard ratio, HR, 0.79; p = 0.08; ACM 63% in HF vs. 70% in LF dialysis) and biocompatibility level (HR 1.00; p = 0.98; ACM 67% for HB vs. 66% for LB). The multivariate analysis of different causes of death did not reveal any outcome differences dependent on flux and biocompatibility level apart from a slightly better cumulative survival regarding the death cause 'infectious' in our HF dialysis group (HR 0.48; p = 0.07, Kaplan-Meier analysis p = 0.03). Our data indicate that mortality of hemodialysis patients with type-2 diabetic nephropathy is influenced neither by dialyzer flux level nor by biocompatibility. Copyright 2008 S. Karger AG, Basel.

Targeted metabolomic profiling in rat tissues reveals sex differences.

PubMed

Ruoppolo, Margherita; Caterino, Marianna; Albano, Lucia; Pecce, Rita; Di Girolamo, Maria Grazia; Crisci, Daniela; Costanzo, Michele; Milella, Luigi; Franconi, Flavia; Campesi, Ilaria

2018-03-16

Sex differences affect several diseases and are organ-and parameter-specific. In humans and animals, sex differences also influence the metabolism and homeostasis of amino acids and fatty acids, which are linked to the onset of diseases. Thus, the use of targeted metabolite profiles in tissues represents a powerful approach to examine the intermediary metabolism and evidence for any sex differences. To clarify the sex-specific activities of liver, heart and kidney tissues, we used targeted metabolomics, linear discriminant analysis (LDA), principal component analysis (PCA), cluster analysis and linear correlation models to evaluate sex and organ-specific differences in amino acids, free carnitine and acylcarnitine levels in male and female Sprague-Dawley rats. Several intra-sex differences affect tissues, indicating that metabolite profiles in rat hearts, livers and kidneys are organ-dependent. Amino acids and carnitine levels in rat hearts, livers and kidneys are affected by sex: male and female hearts show the greatest sexual dimorphism, both qualitatively and quantitatively. Finally, multivariate analysis confirmed the influence of sex on the metabolomics profiling. Our data demonstrate that the metabolomics approach together with a multivariate approach can capture the dynamics of physiological and pathological states, which are essential for explaining the basis of the sex differences observed in physiological and pathological conditions.

Multivariate Analysis as a Method for Evaluating the Conceptual Perceptions of Korean Medicine Students regarding Phlegm Pattern

PubMed Central

Kim, Hyungsuk; Park, Young-Jae; Park, Young-Bae

2013-01-01

Individuals may perceive the concepts in Korean medicine pattern classification differently because it is performed according to the integration of a variety of information. Therefore, analysis about individual perspective is very important for examining the cross-sectional perspective state of Korean medicine concepts and developing both the clinical guideline including diagnosis and the curriculum of Korean medicine colleges. Moreover, because this conceptual difference is thought to begin with college education, it is worthwhile to observe students' viewpoints. So, we suggested multivariate analysis to explore the dimensional structure of Korean medicine students' conceptual perceptions regarding phlegm pattern. We surveyed 326 students divided into 5 groups based on their year of study. Data were analyzed using multidimensional scaling and factor analysis. Within-group difference was the smallest for third-year students, who have received Korean medicine education in full for the first time. With the exception of first-year students, the conceptual map revealed that each group's mean perceptions of phlegm pattern were distributed in almost linear fashion. To determine the effect of education, we investigated the preference rankings and scores of each symptom. We also extracted factors to identify latent variables and to compare the between-group conceptual characteristics regarding phlegm pattern. PMID:24062789

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

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

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.

Psoriasis and Sexual Behavior in Men: examination of the National Health and Nutrition Examination Survey (NHANES) in the United States.

PubMed

Armstrong, April W; Harskamp, Caitlin T; Schupp, Clayton W

2014-02-01

Epidemiologic data on sexual behavior in psoriasis patients are lacking. We aim to examine and compare the sexual behaviors between men with and without psoriasis in the United States. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2006 and 2009 to 2010. Responses from male participants to the dermatology and sexual behavior questionnaires of the NHANES were collated and analyzed. Outcome measures included sexual orientation, age of first sexual encounter, number of oral and non-oral sexual partners, and frequency of unprotected sex. Among 6,444 U.S. men that responded to the psoriasis question, 170 (2.6%) reported a physician-given diagnosis of psoriasis. Heterosexual men accounted for 95.5% and nonheterosexual men 4.5% of the overall study population. On multivariate analysis, psoriasis was not associated with differences in sexual orientation (odds ratio 1.78, 95% confidence interval [CI] 0.75-4.15). Heterosexual men with psoriasis experienced first sexual encounter at an earlier age than those without psoriasis (weighted difference -0.9 years, P = 0.002). Heterosexual men with psoriasis had significantly fewer female oral sexual partners compared with heterosexual men without psoriasis on multivariate analysis (lifetime partner number: rate ratio [RR] 0.65, 95% CI 0.45-0.95; past-year partner number: RR 0.64, 95% CI 0.42-0.97). No significant differences existed between heterosexual men with and without psoriasis regarding frequency of unprotected sex (RR 0.96, 95% CI 0.85-1.09). Among nonheterosexual men with and without psoriasis, no significant differences existed in age first had sex, number of sexual partners, or frequency of unprotected sex. Heterosexual men with psoriasis have significantly fewer lifetime female oral sexual partners compared with those without psoriasis. Dermatologists and other healthcare providers need to examine the genital region routinely and initiate appropriate therapy to improve patients' sexual health. © 2013 International Society for Sexual Medicine.

The Influence of Total Nodes Examined, Number of Positive Nodes, and Lymph Node Ratio on Survival After Surgical Resection and Adjuvant Chemoradiation for Pancreatic Cancer: A Secondary Analysis of RTOG 9704

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

Showalter, Timothy N.; Winter, Kathryn A.; Berger, Adam C., E-mail: adam.berger@jefferson.edu

2011-12-01

Purpose: Lymph node status is an important predictor of survival in pancreatic cancer. We performed a secondary analysis of Radiation Therapy Oncology Group (RTOG) 9704, an adjuvant chemotherapy and chemoradiation trial, to determine the influence of lymph node factors-number of positive nodes (NPN), total nodes examined (TNE), and lymph node ratio (LNR ratio of NPN to TNE)-on OS and disease-free survival (DFS). Patient and Methods: Eligible patients from RTOG 9704 form the basis of this secondary analysis of lymph node parameters. Actuarial estimates for OS and DFS were calculated using Kaplan-Meier methods. Cox proportional hazards models were performed to evaluatemore » associations of NPN, TNE, and LNR with OS and DFS. Multivariate Cox proportional hazards models were also performed. Results: There were 538 patients enrolled in the RTOG 9704 trial. Of these, 445 patients were eligible with lymph nodes removed. Overall median NPN was 1 (min-max, 0-18). Increased NPN was associated with worse OS (HR = 1.06, p = 0.001) and DFS (HR = 1.05, p = 0.01). In multivariate analyses, both NPN and TNE were associated with OS and DFS. TNE > 12, and >15 were associated with increased OS for all patients, but not for node-negative patients (n = 142). Increased LNR was associated with worse OS (HR = 1.01, p < 0.0001) and DFS (HR = 1.006, p = 0.002). Conclusion: In patients who undergo surgical resection followed by adjuvant chemoradiation, TNE, NPN, and LNR are associated with OS and DFS. This secondary analysis of a prospective, cooperative group trial supports the influence of these lymph node parameters on outcomes after surgery and adjuvant therapy using contemporary techniques.« less

Asian Versus Non-Asian Outcomes in Nasopharyngeal Carcinoma: A North American Population-based Analysis.

PubMed

Hamilton, Sarah N; Ho, Cheryl; Laskin, Janessa; Zhai, Yongliang; Mak, Paul; Wu, Jonn

2016-12-01

The effect of ethnicity on nasopharyngeal cancer (NPC) outcomes is unclear. This retrospective analysis examines survival and the impact of concurrent chemoradiation (chemoRT) among Asian and non-Asian patients. Subjects included 380 consecutive patients with NPC treated at a Canadian institution from 2000 to 2009. Five-year Kaplan-Meier progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) were compared between Asian (n=279) and non-Asian (n=101) subjects. Multivariable analysis was performed using Cox regression modeling. Two-variable interaction terms with concurrent chemoRT were used to examine whether concurrent chemoRT conferred different effects among subgroups. Asian subjects presented with earlier stage (P=0.005), were younger, had better performance status, and were less likely smokers (all P<0.001). Survival among Asian versus non-Asian subjects with stage I/II NPC were: PFS 68% versus 59% (P=0.04), DSS 87% versus 77% (P=0.08), and OS 84% versus 74% (P=0.003). Corresponding rates with stage III/IVA/IVB disease were PFS 49% versus 42% (P=0.12), DSS 72% versus 46% (P=0.001), and OS 70% versus 44% (P<0.001). On multivariable analysis, Asian ethnicity, age below 65 years, ECOG performance status 0-1, early stage, staging MRI use, and concurrent chemoRT were associated with improved DSS and OS (P<0.05). On testing interactions with concurrent chemoRT, Asian versus non-Asian ethnicity was significant (hazard ratio 3.9), suggesting that concurrent chemoRT conferred more benefit among non-Asian compared with Asian subjects. In this population-based study, Asian ethnicity was associated with improved DSS and OS. Concurrent chemoRT conferred more benefit among non-Asian compared with Asian subjects.

Visual Impairment Is Associated With Depressive Symptoms-Results From the Nationwide German DEGS1 Study.

PubMed

Schuster, Alexander K; Tesarz, Jonas; Rezapour, Jasmin; Beutel, Manfred E; Bertram, Bernd; Pfeiffer, Norbert

2018-01-01

Visual impairment (VI) is associated with a variety of comorbidities including physical and mental health in industrial countries. Our aim is to examine associations between self-reported impairment and depressive symptoms in the German population. The point prevalence of self-reported VI in Germany was computed using data from the German Health Interview and Examination Survey for adults from 2008 to 2011 ( N  = 7.783, 50.5% female, age range 18-79 years). VI was surveyed by two questions, one for seeing faces at a distance of 4 m and one for reading newspapers. Depressive symptoms were evaluated with the Patient Health Questionnaire-9 questionnaire and 2-week prevalence was computed with weighted data. Depressive symptoms were defined by a value of ≥10. Logistic regression analysis was performed to analyze an association between self-reported VI and depressive symptoms. Multivariable analysis including adjustment for age, gender, socioeconomic status, and chronic diseases were carried out with weighted data. The 2-week prevalence of depressive symptoms was 20.8% (95% CI: 16.6-25.7%) for some difficulties in distance vision and 14.4% (95% CI: 7.5-25.9%) for severe difficulties in distance vision, while 17.0% (95% CI: 13.3-21.4%), respectively, 16.7% (95% CI: 10.7-25.1%) for near vision. Analysis revealed that depressive symptoms were associated with self-reported VI for reading, respectively, with low VI for distance vision. Multivariable regression analysis including potential confounders confirmed these findings. Depressive symptoms are a frequent finding in subjects with difficulties in distance and near vision with a prevalence of up to 24%. Depressive comorbidity should therefore be evaluated in subjects reporting VI.

Prolonged Instability Prior to a Regime Shift | Science ...

EPA Pesticide Factsheets

Regime shifts are generally defined as the point of ‘abrupt’ change in the state of a system. However, a seemingly abrupt transition can be the product of a system reorganization that has been ongoing much longer than is evident in statistical analysis of a single component of the system. Using both univariate and multivariate statistical methods, we tested a long-term high-resolution paleoecological dataset with a known change in species assemblage for a regime shift. Analysis of this dataset with Fisher Information and multivariate time series modeling showed that there was a∼2000 year period of instability prior to the regime shift. This period of instability and the subsequent regime shift coincide with regional climate change, indicating that the system is undergoing extrinsic forcing. Paleoecological records offer a unique opportunity to test tools for the detection of thresholds and stable-states, and thus to examine the long-term stability of ecosystems over periods of multiple millennia. This manuscript explores various methods of assessing the transition between alternative states in an ecological system described by a long-term high-resolution paleoecological dataset.

Comparative multivariate analysis of biometric traits of West African Dwarf and Red Sokoto goats.

PubMed

Yakubu, Abdulmojeed; Salako, Adebowale E; Imumorin, Ikhide G

2011-03-01

The population structure of 302 randomly selected West African Dwarf (WAD) and Red Sokoto (RS) goats was examined using multivariate morphometric analyses. This was to make the case for conservation, rational management and genetic improvement of these two most important Nigerian goat breeds. Fifteen morphometric measurements were made on each individual animal. RS goats were superior (P<0.05) to the WAD for the body size and skeletal proportions investigated. The phenotypic variability between the two breeds was revealed by their mutual responses in the principal components. While four principal components were extracted for WAD goats, three components were obtained for their RS counterparts with variation in the loading traits of each component for each breed. The Mahalanobis distance of 72.28 indicated a high degree of spatial racial separation in morphology between the genotypes. The Ward's option of the cluster analysis consolidated the morphometric distinctness of the two breeds. Application of selective breeding to genetic improvement would benefit from the detected phenotypic differentiation. Other implications for management and conservation of the goats are highlighted.

An examination on the influence of small and medium enterprise (SME) stakeholder on green supply chain management practices

NASA Astrophysics Data System (ADS)

Shahlan, M. Z.; Sidek, A. A.; Suffian, S. A.; Hazza, M. H. F. A.; Daud, M. R. C.

2018-01-01

In this paper, climate change and global warming are the biggest current issues in the industrial sectors. The green supply chain managements (GSCM) is one of the crucial input to these issues. Effective GSCM can potentially secure the organization’s competitive advantage and improve the environmental performance of the network activities. In this study, the aim is to investigate and examine how a small and medium enterprises (SMEs) stakeholder pressure and top management influence green supply chain management practices. The study is further advance green supply chain management research in Malaysia focusing on SMEs manufacturing sector using structural equation modelling. Structural equation modelling is a multivariate statistical analysis technique used to examine structural relationship. It is the combination of factor analysis and multi regression analysis and used to analyse structural relationship between measure variable and latent factor. This research found that top management support and stakeholder pressure is the major influence for SMEs to adopt green supply chain management. The research also found that top management is fully mediate with the relationship between stakeholder pressure and monitoring supplier environmental performance.

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

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

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

Post-traumatic stress disorder status in a rescue group after the Wenchuan earthquake relief

PubMed Central

Huang, Junhua; Liu, Qunying; Li, Jinliang; Li, Xuejiang; You, Jin; Zhang, Liang; Tian, Changfu; Luan, Rongsheng

2013-01-01

Previous studies have suggested that the incidence of post-traumatic stress disorder in earthquake rescue workers is relatively high. Risk factors for this disorder include demographic characteristics, earthquake-related high-risk factors, risk factors in the rescue process, personality, social support and coping style. This study examined the current status of a unit of 1 040 rescue workers who participated in earthquake relief for the Wenchuan earthquake that occurred on May 12th, 2008. Post-traumatic stress disorder was diagnosed primarily using the Clinician-Administered Post-traumatic Stress Disorder Scale during structured interviews. Univariate and multivariate statistical analyses were used to examine major risk factors that contributed to the incidence of post-traumatic stress disorder. Results revealed that the incidence of this disorder in the rescue group was 5.96%. The impact factors in univariate analysis included death of family members, contact with corpses or witnessing of the deceased or seriously injured, near-death experience, severe injury or mental trauma in the rescue process and working at the epicenter of the earthquake. Correlation analysis suggested that post-traumatic stress disorder was positively correlated with psychotic and neurotic personalities, negative coping and low social support. Impact factors in multivariate logistic regression analysis included near-death experience, severe injury or mental trauma, working in the epicenter of the rescue, neurotic personality, negative coping and low social support, among which low social support had the largest odds ratio of 20.42. Findings showed that the occurrence of post-traumatic stress disorder was the result of the interaction of multiple factors. PMID:25206499

Self-Esteem and HIV Risk Practices among Young Adult “Ecstasy” Users

PubMed Central

Klein, Hugh; Elifson, Kirk W.; Sterk, Claire E.

2013-01-01

In this paper, we examine the role that self-esteem plays in HIV-related risk taking among users of the drug, ecstasy. The first part of the analysis focuses on the relationship of self-esteem to HIV risk-taking. The second part of the analysis examines predictors of self-esteem in this population. The research is based on a sample of 283 young adult ecstasy users. The study took place between August 2002 and August 2004 and entailed face-to-face interviews that were completed with the use of computer-assisted structured interviews. Study participants were recruited in the Atlanta, Georgia metropolitan area using a targeted sampling and ethnographic mapping approach. Interviews took approximately two hours to complete. Results of multivariate analyses indicated that self-esteem is associated with a variety of risky practices, including: the number of sex partners that people reported having, individuals’ likelihood of having multiple sex partners, the number of different types of illegal drugs that people reported using, and their condom use self-efficacy. The multivariate analysis conducted to ascertain the factors that impact young adult ecstasy users’ levels of self-esteem yielded six such factors: educational attainment (positive), coming from a family-of-origin whose members got along well (positive), the extent of alcohol problems experienced recently (negative), the number of positive effects experienced recently as a result of ecstasy use (positive), the number of negative effects experienced recently as a result of ecstasy use (negative), and the extent of experiencing symptoms of post-traumatic stress disorder (negative). PMID:21305909

Does shear wave ultrasound independently predict axillary lymph node metastasis in women with invasive breast cancer?

PubMed

Evans, Andrew; Rauchhaus, Petra; Whelehan, Patsy; Thomson, Kim; Purdie, Colin A; Jordan, Lee B; Michie, Caroline O; Thompson, Alastair; Vinnicombe, Sarah

2014-01-01

Shear wave elastography (SWE) shows promise as an adjunct to greyscale ultrasound examination in assessing breast masses. In breast cancer, higher lesion stiffness on SWE has been shown to be associated with features of poor prognosis. The purpose of this study was to assess whether lesion stiffness at SWE is an independent predictor of lymph node involvement. Patients with invasive breast cancer treated by primary surgery, who had undergone SWE examination were eligible. Data were retrospectively analysed from 396 consecutive patients. The mean stiffness values were obtained using the Aixplorer® ultrasound machine from SuperSonic Imagine Ltd. Measurements were taken from a region of interest positioned over the stiffest part of the abnormality. The average of the mean stiffness value obtained from each of two orthogonal image planes was used for analysis. Associations between lymph node involvement and mean lesion stiffness, invasive cancer size, histologic grade, tumour type, ER expression, HER-2 status and vascular invasion were assessed using univariate and multivariate logistic regression. At univariate analysis, invasive size, histologic grade, HER-2 status, vascular invasion, tumour type and mean stiffness were significantly associated with nodal involvement. Nodal involvement rates ranged from 7 % for tumours with mean stiffness <50 kPa to 41 % for tumours with a mean stiffness of >150 kPa. At multivariate analysis, invasive size, tumour type, vascular invasion, and mean stiffness maintained independent significance. Mean stiffness at SWE is an independent predictor of lymph node metastasis and thus can confer prognostic information additional to that provided by conventional preoperative tumour assessment and staging.

Prognostic relevance of lymph node ratio and total lymph node count for small bowel adenocarcinoma.

PubMed

Tran, Thuy B; Qadan, Motaz; Dua, Monica M; Norton, Jeffrey A; Poultsides, George A; Visser, Brendan C

2015-08-01

Nodal metastasis is a known prognostic factor for small bowel adenocarcinoma. The goals of this study were to evaluate the number of lymph nodes (LNs) that should be retrieved and the impact of lymph node ratio (LNR) on survival. Surveillance, Epidemiology, and End Results was queried to identify patients with small bowel adenocarcinoma who underwent resection from 1988 to 2010. Survival was calculated with the Kaplan-Meier method. Multivariate analysis identified predictors of survival. A total of 2,772 patients underwent resection with at least one node retrieved, and this sample included equal numbers of duodenal (n = 1,387) and jejunoileal (n = 1,386) adenocarcinomas. There were 1,371 patients with no nodal metastasis (N0, 49.4%), 928 N1 (33.5%), and 474 N2 (17.1%). The median numbers of LNs examined for duodenal and jejunoileal cancers were 9 and 8, respectively. Cut-point analysis demonstrated that harvesting at least 9 for jejunoileal and 5 LN for duodenal cancers resulted in the greatest survival difference. Increasing LNR at both sites was associated with decreased overall median survival (LNR = 0, 71 months; LNR 0-0.02, 35 months; LNR 0.21-0.4, 25 months; and LNR >0.4, 16 months; P < .001). Multivariate analysis confirmed number of LNs examined, T-stage, LN positivity, and LNR were independent predictors of survival. LNR has a profound impact on survival in patients with small bowel adenocarcinoma. To achieve adequate staging, we recommend retrieving a minimum of 5 LN for duodenal and 9 LN for jejunoileal adenocarcinomas. Copyright © 2015 Elsevier Inc. All rights reserved.

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

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

2004-06-01

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

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

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

2015-01-01

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

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

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

2014-10-01

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

Motivations for genetic testing for lung cancer risk among young smokers.

PubMed

O'Neill, Suzanne C; Lipkus, Isaac M; Sanderson, Saskia C; Shepperd, James; Docherty, Sharron; McBride, Colleen M

2013-11-01

To examine why young people might want to undergo genetic susceptibility testing for lung cancer despite knowing that tested gene variants are associated with small increases in disease risk. The authors used a mixed-method approach to evaluate motives for and against genetic testing and the association between these motivations and testing intentions in 128 college students who smoke. Exploratory factor analysis yielded four reliable factors: Test Scepticism, Test Optimism, Knowledge Enhancement and Smoking Optimism. Test Optimism and Knowledge Enhancement correlated positively with intentions to test in bivariate and multivariate analyses (ps<0.001). Test Scepticism correlated negatively with testing intentions in multivariate analyses (p<0.05). Open-ended questions assessing testing motivations generally replicated themes of the quantitative survey. In addition to learning about health risks, young people may be motivated to seek genetic testing for reasons, such as gaining knowledge about new genetic technologies more broadly.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Analysis of fatty acid composition of sea cucumber Apostichopus japonicus using multivariate statistics

NASA Astrophysics Data System (ADS)

Xu, Qinzeng; Gao, Fei; Xu, Qiang; Yang, Hongsheng

2014-11-01

Fatty acids (FAs) provide energy and also can be used to trace trophic relationships among organisms. Sea cucumber Apostichopus japonicus goes into a state of aestivation during warm summer months. We examined fatty acid profiles in aestivated and non-aestivated A. japonicus using multivariate analyses (PERMANOVA, MDS, ANOSIM, and SIMPER). The results indicate that the fatty acid profiles of aestivated and non-aestivated sea cucumbers differed significantly. The FAs that were produced by bacteria and brown kelp contributed the most to the differences in the fatty acid composition of aestivated and nonaestivated sea cucumbers. Aestivated sea cucumbers may synthesize FAs from heterotrophic bacteria during early aestivation, and long chain FAs such as eicosapentaenoic (EPA) and docosahexaenoic acid (DHA) that produced from intestinal degradation, are digested during deep aestivation. Specific changes in the fatty acid composition of A. japonicus during aestivation needs more detailed study in the future.

Compulsive buying: Earlier illicit drug use, impulse buying, depression, and adult ADHD symptoms.

PubMed

Brook, Judith S; Zhang, Chenshu; Brook, David W; Leukefeld, Carl G

2015-08-30

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant's earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Compulsive Buying: Earlier Illicit Drug Use, Impulse Buying, Depression, and Adult ADHD Symptoms

PubMed Central

Brook, Judith S.; Zhang, Chenshu; Brook, David W.; Leukefeld, Carl G.

2015-01-01

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant’s earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. PMID:26165963

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

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

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

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

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

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

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

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

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

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

Childhood adversities and first onset of psychiatric disorders in a national sample of adolescents

PubMed Central

McLaughlin, Katie A.; Green, Jennifer Greif; Gruber, Michael J.; Sampson, Nancy A.; Zaslavsky, Alan M.; Kessler, Ronald C.

2012-01-01

Context Although childhood adversities (CAs) are known to be highly co-occurring, most research examines their associations with mental disorders one at a time. Recent evidence from adult studies suggests, though, that the associations of multiple CAs with mental disorders are non-additive, arguing for the importance of multivariate analysis of multiple CAs. No attempt has yet been made to carry out a similar kind of analysis among children or adolescents. Objective To examine the multivariate associations of 12 CAs with first onset of mental disorders in a national sample of US adolescents. Design US national survey of adolescents (ages 13–17) assessing DSM-IV anxiety, mood, behavior, and substance disorders and CAs. The CAs include parental loss (death, divorce, other separations), maltreatment (physical, sexual, and emotional abuse, neglect), parental maladjustment (psychopathology, substance abuse, criminality, violence) and economic adversity. Setting Dual-frame household-school samples. Participants 6,483 adolescents-parent pairs. Main outcome measure Lifetime DSM-IV disorders assessed with the WHO Composite International Diagnostic Interview. Results 58.3% of adolescents reported at least one CA, among whom 59.7% reported multiple CAs. CAs reflecting maladaptive family functioning (MFF) were more strongly associated than other CAs with disorder onsets. The best-fitting model included terms for type and number of CAs and distinguished between MFF and Other CAs. CAs predicted behavior disorders most strongly and fear disorders least strongly. The joint associations of multiple CAs were sub-additive. The population-attributable risk proportions for disorder classes ranged from 15.7% for fear disorders to 40.7% for behavior disorders. CAs were associated with 28.2% of all onsets. Conclusions CAs are common, highly co-occurring, and strongly associated with onset of mental disorders among US adolescents. The sub-additive multivariate associations of CAs with disorder onsets have implications for targeting interventions to reduce exposure to CAs and to mitigate the harmful effects of CAs to improve population mental health. PMID:23117636

Self-referent information processing in individuals with bipolar spectrum disorders.

PubMed

Molz Adams, Ashleigh; Shapero, Benjamin G; Pendergast, Laura H; Alloy, Lauren B; Abramson, Lyn Y

2014-01-01

Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M=19.65, SD=1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. © 2013 Elsevier B.V. All rights reserved.

Self-referent information processing in individuals with bipolar spectrum disorders

PubMed Central

Molz Adams, Ashleigh; Shapero, Benjamin G.; Pendergast, Laura H.; Alloy, Lauren B.; Abramson, Lyn Y.

2014-01-01

Background Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. Methods This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M = 19.65, SD = 1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Results Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Limitations Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. Conclusions This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. PMID:24074480

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

PubMed Central

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

2013-01-01

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

Automated Classification and Analysis of Non-metallic Inclusion Data Sets

NASA Astrophysics Data System (ADS)

Abdulsalam, Mohammad; Zhang, Tongsheng; Tan, Jia; Webler, Bryan A.

2018-05-01

The aim of this study is to utilize principal component analysis (PCA), clustering methods, and correlation analysis to condense and examine large, multivariate data sets produced from automated analysis of non-metallic inclusions. Non-metallic inclusions play a major role in defining the properties of steel and their examination has been greatly aided by automated analysis in scanning electron microscopes equipped with energy dispersive X-ray spectroscopy. The methods were applied to analyze inclusions on two sets of samples: two laboratory-scale samples and four industrial samples from a near-finished 4140 alloy steel components with varying machinability. The laboratory samples had well-defined inclusions chemistries, composed of MgO-Al2O3-CaO, spinel (MgO-Al2O3), and calcium aluminate inclusions. The industrial samples contained MnS inclusions as well as (Ca,Mn)S + calcium aluminate oxide inclusions. PCA could be used to reduce inclusion chemistry variables to a 2D plot, which revealed inclusion chemistry groupings in the samples. Clustering methods were used to automatically classify inclusion chemistry measurements into groups, i.e., no user-defined rules were required.

[The relationship between academic self-efficacy and academic burnout in medical students].

PubMed

Lee, Su Hyun; Jeon, Woo Taek

2015-03-01

The purpose of this study was to examine the correlation between academic burnout and academic self-efficacy in medical students. The study group comprised 446 students in years 1 to 4 of medical school. They were asked to rate their academic burnout and academic self-efficacy on a scale. The data were analyzed by multivariate analysis of variance and regression analysis. Academic self-efficacy was correlated negatively with academic burnout explaining 37% of academic burnout. Academic self-efficacy (especially self-confidence) had the greatest effect on academic burnout. The implications of these results are discussed in terms of an evaluation and support system for students.

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

High rates of Unintended Pregnancies among Young Women Sex Workers in Conflict-affected Northern Uganda: The Social Contexts of Brothels/Lodges and Substance Use.

PubMed

Duff, Putu; Muzaaya, Godfrey; Muldoon, Katherine; Dobrer, Sabina; Akello, Monika; Birungi, Josephine; Shannon, Kate

2017-06-01

This study aimed to examine the correlates of unintended pregnancies among young women sex workers in conflict-affected northern Uganda. Data were drawn from the Gulu Sexual Health Study, a cross-sectional study of young women engaged in sex work. Bivariable and multivariable logistic regression was used to examine the correlates of ever having an unintended pregnancy. Among 400 sex workers (median age=20 years; IQR 19-25), 175 (43.8%) reported at least one unintended pregnancy. In multivariable analysis, primarily servicing clients in lodges/brothels [Adjusted Odds Ratio (AOR= 2.24; 95% Confidence Interval: 1.03-4.84)], hormonal contraceptive usage [AOR=1.68; 95%CI 1.11-2.59] and drug/alcohol use while working [AOR= 1.64; 95%CI 1.04-2.60] were positively correlated with previous unintended pregnancy. Given that unintended pregnancy is an indicator of unmet reproductive health need, these findings highlight a need for improved access to integrated reproductive health and HIV services, catered to sex workers' needs. Sex work-led strategies (e.g., peer outreach) should be considered, alongside structural strategies and education targeting brothel/lodge owners and managers.

Beyond Reading Alone: The Relationship Between Aural Literacy And Asthma Management

PubMed Central

Rosenfeld, Lindsay; Rudd, Rima; Emmons, Karen M.; Acevedo-García, Dolores; Martin, Laurie; Buka, Stephen

2010-01-01

Objectives To examine the relationship between literacy and asthma management with a focus on the oral exchange. Methods Study participants, all of whom reported asthma, were drawn from the New England Family Study (NEFS), an examination of links between education and health. NEFS data included reading, oral (speaking), and aural (listening) literacy measures. An additional survey was conducted with this group of study participants related to asthma issues, particularly asthma management. Data analysis focused on bivariate and multivariable logistic regression. Results In bivariate logistic regression models exploring aural literacy, there was a statistically significant association between those participants with lower aural literacy skills and less successful asthma management (OR:4.37, 95%CI:1.11, 17.32). In multivariable logistic regression analyses, controlling for gender, income, and race in separate models (one-at-a-time), there remained a statistically significant association between those participants with lower aural literacy skills and less successful asthma management. Conclusion Lower aural literacy skills seem to complicate asthma management capabilities. Practice Implications Greater attention to the oral exchange, in particular the listening skills highlighted by aural literacy, as well as other related literacy skills may help us develop strategies for clear communication related to asthma management. PMID:20399060

Clinical implications of the BRAF mutation in papillary thyroid carcinoma and chronic lymphocytic thyroiditis.

PubMed

Kim, Woon Won; Ha, Tae Kwun; Bae, Sung Kwon

2018-01-09

The purpose of this study was to examine the possible prognostics and clinicopathologic characteristics underlying the BRAFV600E mutation and papillary thyroid carcinoma (PTC) coexisting or in absence of chronic lymphocytic thyroiditis (CLT). This study was conducted on 172 patients who had undergone total thyroidectomy or unilateral total thyroidectomy for PTC; the patients were then examined for the BRAFV600E mutation using specimens obtained after their surgery from January 2013 to August 2015. BRAF mutations were found in 130 of 172 patients (75.6%). CLT was present in 27.9% of patients (48/172). The incidence of the BRAFV600E mutation was significantly increased in the group with no CLT (P = 0.001). The findings of the multivariate analysis pertaining to the coexistence of CLT and PTC showed no significant correlation other than the BRAFV600E mutation. No significant difference was noted in the clinicopathologic factors between the two groups based on the coexistence of CLT in univariate and multivariate analyses. The BRAFV600E mutation is less frequent in PTC coexisting with CLT presumably because CLT and the BRAFV600E mutation operate independently in the formation and progression of thyroid cancer.

The Effectiveness of Cigarette Price and Smoke-Free Homes on Low-Income Smokers in the United States

PubMed Central

Vijayaraghavan, Maya; Messer, Karen; White, Martha M.

2013-01-01

Objectives. We examined the effectiveness of state cigarette price and smoke-free homes on smoking behaviors of low-income and high-income populations in the United States. Methods. We used the 2006–2007 Tobacco Use Supplement to the Current Population Survey. The primary outcomes were average daily cigarette consumption and successful quitting. We used multivariable regression to examine the association of cigarette price and smoke-free home policies on these outcomes. Results. High state cigarette price (pack price ≥ $4.50) was associated with lower consumption across all income levels. Although low-income individuals were least likely to adopt smoke-free homes, those who adopted them had consumption levels and successful quit rates that were similar to those among higher-income individuals. In multivariable analysis, both policies were independently associated with lower consumption, but only smoke-free homes were associated with sustained cessation at 90 days. Conclusions. High cigarette prices and especially smoke-free homes have the potential to reduce smoking behaviors among low-income individuals. Interventions are needed to increase adoption of smoke-free homes among low-income populations to increase cessation rates and prevent relapse. PMID:24134354

Low Bone Density and Bisphosphonate Use and the Risk of Kidney Stones.

PubMed

Prochaska, Megan; Taylor, Eric; Vaidya, Anand; Curhan, Gary

2017-08-07

Previous studies have demonstrated lower bone density in patients with kidney stones, but no longitudinal studies have evaluated kidney stone risk in individuals with low bone density. Small studies with short follow-up reported reduced 24-hour urine calcium excretion with bisphosphonate use. We examined history of low bone density and bisphosphonate use and the risk of incident kidney stone as well as the association with 24-hour calcium excretion. We conducted a prospective analysis of 96,092 women in the Nurses' Health Study II. We used Cox proportional hazards models to adjust for age, body mass index, thiazide use, fluid intake, supplemental calcium use, and dietary factors. We also conducted a cross-sectional analysis of 2294 participants using multivariable linear regression to compare 24-hour urinary calcium excretion between participants with and without a history of low bone density, and among 458 participants with low bone density, with and without bisphosphonate use. We identified 2564 incident stones during 1,179,860 person-years of follow-up. The multivariable adjusted relative risk for an incident kidney stone for participants with history of low bone density compared with participants without was 1.39 (95% confidence interval [95% CI], 1.20 to 1.62). Among participants with low bone density, the multivariable adjusted relative risk for an incident kidney stone for bisphosphonate users was 0.68 (95% CI, 0.48 to 0.98). In the cross-sectional analysis of 24-hour urine calcium excretion, the multivariable adjusted mean difference in 24-hour calcium was 10 mg/d (95% CI, 1 to 19) higher for participants with history of low bone density. However, among participants with history of low bone density, there was no association between bisphosphonate use and 24-hour calcium with multivariable adjusted mean difference in 24-hour calcium of -2 mg/d (95% CI, -25 to 20). Low bone density is an independent risk factor for incident kidney stone and is associated with higher 24-hour urine calcium excretion. Among participants with low bone density, bisphosphonate use was associated with lower risk of incident kidney stone but was not independently associated with 24-hour urine calcium excretion. Copyright © 2017 by the American Society of Nephrology.

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

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

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

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

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

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

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

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

PubMed

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

2015-01-01

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

Racial differences in circulating natriuretic peptide levels: the atherosclerosis risk in communities study.

PubMed

Gupta, Deepak K; Claggett, Brian; Wells, Quinn; Cheng, Susan; Li, Man; Maruthur, Nisa; Selvin, Elizabeth; Coresh, Josef; Konety, Suma; Butler, Kenneth R; Mosley, Thomas; Boerwinkle, Eric; Hoogeveen, Ron; Ballantyne, Christie M; Solomon, Scott D

2015-05-21

Natriuretic peptides promote natriuresis, diuresis, and vasodilation. Experimental deficiency of natriuretic peptides leads to hypertension (HTN) and cardiac hypertrophy, conditions more common among African Americans. Hospital-based studies suggest that African Americans may have reduced circulating natriuretic peptides, as compared to Caucasians, but definitive data from community-based cohorts are lacking. We examined plasma N-terminal pro B-type natriuretic peptide (NTproBNP) levels according to race in 9137 Atherosclerosis Risk in Communities (ARIC) Study participants (22% African American) without prevalent cardiovascular disease at visit 4 (1996-1998). Multivariable linear and logistic regression analyses were performed adjusting for clinical covariates. Among African Americans, percent European ancestry was determined from genetic ancestry informative markers and then examined in relation to NTproBNP levels in multivariable linear regression analysis. NTproBNP levels were significantly lower in African Americans (median, 43 pg/mL; interquartile range [IQR], 18, 88) than Caucasians (median, 68 pg/mL; IQR, 36, 124; P<0.0001). In multivariable models, adjusted log NTproBNP levels were 40% lower (95% confidence interval [CI], -43, -36) in African Americans, compared to Caucasians, which was consistent across subgroups of age, gender, HTN, diabetes, insulin resistance, and obesity. African-American race was also significantly associated with having nondetectable NTproBNP (adjusted OR, 5.74; 95% CI, 4.22, 7.80). In multivariable analyses in African Americans, a 10% increase in genetic European ancestry was associated with a 7% (95% CI, 1, 13) increase in adjusted log NTproBNP. African Americans have lower levels of plasma NTproBNP than Caucasians, which may be partially owing to genetic variation. Low natriuretic peptide levels in African Americans may contribute to the greater risk for HTN and its sequalae in this population. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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 ...

Impact of distance to a urologist on early diagnosis of prostate cancer among black and white patients.

PubMed

Holmes, Jordan A; Carpenter, William R; Wu, Yang; Hendrix, Laura H; Peacock, Sharon; Massing, Mark; Schenck, Anna P; Meyer, Anne-Marie; Diao, Kevin; Wheeler, Stephanie B; Godley, Paul A; Stitzenberg, Karyn B; Chen, Ronald C

2012-03-01

We examined whether an increased distance to a urologist is associated with a delayed diagnosis of prostate cancer among black and white patients, as manifested by higher risk disease at diagnosis. North Carolina Central Cancer Registry data were linked to Medicare claims for patients with incident prostate cancer diagnosed in 2004 to 2005. Straight-line distances were calculated from the patient home to the nearest urologist. Race stratified multivariate ordinal logistic regression was used to examine the association between distance to a urologist and prostate cancer risk group (low, intermediate, high or very high/metastasis) at diagnosis for black and white patients while accounting for age, comorbidity, marital status and diagnosis year. An overall model was then used to examine the distance × race interaction effect. Included in analysis were 1,720 white and 531 black men. In the overall cohort the high risk cancer rate increased monotonically with distance to a urologist, including 40% for 0 to 10, 45% for 11 to 20 and 57% for greater than 20 miles. Correspondingly the low risk cancer rate decreased with longer distance. On race stratified multivariate analysis longer distance was associated with higher risk prostate cancer for white and black patients (p = 0.04 and <0.01, respectively) but the effect was larger in the latter group. The distance × race interaction term was significant in the overall model (p = 0.03). Longer distance to a urologist may disproportionally impact black patients. Decreasing modifiable barriers to health care access, such as distance to care, may decrease racial disparities in prostate cancer. Copyright © 2012 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

The preventive effects of lifestyle intervention on the occurrence of diabetes mellitus and acute myocardial infarction in metabolic syndrome.

PubMed

Kim, D; Yoon, S-J; Lim, D-S; Gong, Y-H; Ko, S; Lee, Y-H; Lee, H S; Park, M-S; Kim, K-H; Kim, Y A

2016-10-01

Metabolic syndrome (MS), as a precursor of diabetes mellitus (DM) and cardiovascular disease, is increasing steadily worldwide. We examined the preventive effects of lifestyle intervention on the occurrence of DM and acute myocardial infarction (AMI) in MS. Observational study on disease occurrence after lifestyle intervention. The lifestyle intervention was administered to subjects with MS participating in a metropolitan lifestyle intervention program for 1 year. The same numbers of non-participating age- and sex-matched subjects with MS were randomly extracted from national health examination data. After intervention or examination, new occurrences of hypertension, DM, and AMI were identified through the national health insurance claims data during 1 year. For DM and AMI, multivariate logistic regression analysis for the factors affecting each disease was performed. In the intervention group and the control group (14,918 in each group), the occurrence of hypertension was 555 (6.07%) and 751 (8.33%), the occurrence of DM was 324 (2.55%) and 488 (3.89%), the occurrence of dyslipidemia was 321 (2.59%) and 373 (2.72%), and the occurrence of AMI was 13 (0.09%) and 26 (0.17%), respectively. In multivariate logistic regression analysis, adjusted odds ratios for intervention were 0.752 (95% confidence interval [CI]: 0.644-0.879) and 0.499 (95% CI: 0.251-0.992) for DM and AMI, respectively, indicating that lifestyle intervention has a preventive effect. Lifestyle intervention in MS has preventive effects on the occurrence of DM and AMI, and long-term follow-up is needed to evaluate these preventive effects in more detail. Copyright © 2016. Published by Elsevier Ltd.

Why are our children wasting: Determinants of wasting among under 5s in Ghana.

PubMed

Darteh, Eugene Kofuor Maafo; Acquah, Evelyn; Darteh, Florie

2017-09-01

Wasting is one of the indicators of malnutrition known to contribute to the deaths occurring from childhood malnutrition. It is the measure of body mass in relation to body length used to explain recent nutritional status. This paper examines the determinants of wasting among under 5s in Ghana. Data were drawn from the 2014 Ghana Demographic and Health Survey children's records file to examine the determinants of wasting among children. A total of 2720 children under 5 years with valid anthropometric data were used. Data on wasting were collected by measuring the weight and height of all children under 5 years of age. Bi-variate and multi-variate statistics are used to examine the determinants of wasting. The bi-variate analysis showed significant differences ( p < 0.001) in the prevalence of wasting among under 5s according to age of the child, region, and wealth status. On the other hand, the multi-variate analysis revealed that the odds of wasting were lower among children aged 24-35 months (Odds ratio (OR) = 0.37; p < 0.001), those from households of the middle wealth quintile (OR = 0.49, p < 0.05) and with health insurance (OR = 0.70; p < 0.10). Programmes and policies aimed at ensuring the survival of children during the first 24 months of life should be strengthened to reduce the risk of wasting among under 5s. Also, efforts should be made by the relevant government agencies and other stakeholders to strengthen the socio-economic status of mothers to enable them to provide adequate nutrition and improve access to health insurance for their children in order to reduce the incidence of wasting among these children.

Added sugar intake and metabolic syndrome in US adolescents: cross-sectional analysis of the National Health and Nutrition Examination Survey 2005-2012.

PubMed

Rodríguez, Luis A; Madsen, Kristine A; Cotterman, Carolyn; Lustig, Robert H

2016-09-01

To examine the association between added sugar intake and metabolic syndrome among adolescents. Dietary, serum biomarker, anthropometric and physical activity data from the US National Health and Nutrition Examination Survey cycles between 2005 and 2012 were analysed using multivariate logistic regression models. Added sugar intake in grams per day was estimated from two 24 h standardized dietary recalls and then separated into quintiles from lowest to highest consumption. Multivariate logistic regression analyses were adjusted for physical activity, age, BMI Z-score and energy intake, and their interactions with race were included. Nationally representative sample, USA. US adolescents aged 12-19 years (n 1623). Added sugar was significantly associated with metabolic syndrome. The adjusted prevalence odds ratios for having metabolic syndrome comparing adolescents in the third, fourth and fifth quintiles v. those in the lowest quintile of added sugar were 5·3 (95 % CI 1·4, 20·6), 9·9 (95 % CI 1·9, 50·9) and 8·7 (95 % CI 1·4, 54·9), respectively. Our findings suggest that higher added sugar intake, independent of total energy intake, physical activity or BMI Z-score, is associated with increased prevalence of metabolic syndrome in US adolescents. Further studies are needed to determine if reducing intake of added sugar may help US adolescents prevent or reverse metabolic syndrome.

Association between Patient History and Physical Examination and Osteoarthritis after Ankle Sprain.

PubMed

van Ochten, John M; de Vries, Anja D; van Putte, Nienke; Oei, Edwin H G; Bindels, Patrick J E; Bierma-Zeinstra, Sita M A; van Middelkoop, Marienke

2017-09-01

Structural abnormalities on MRI are frequent after an ankle sprain. To determine the association between patient history, physical examination and early osteoarthritis (OA) in patients after a previous ankle sprain, 98 patients with persistent complaints were selected from a cross-sectional study. Patient history taking and physical examination were applied and MRI was taken. Univariate and multivariable analyses were used to test possible associations. Signs of OA (cartilage loss, osteophytes and bone marrow edema) were seen in the talocrural joint (TCJ) in 40% and the talonavicular joint (TNJ) in 49%. Multivariable analysis showed a significant positive association between swelling (OR 3.58, 95%CI 1.13;11.4), a difference in ROM of passive plantar flexion (OR 1.09, 95%CI 1.01;1.18) and bone edema in the TCJ. A difference in ROM of passive plantar flexion (OR 1.07, 95%CI 1.00;1.15) and pain at the end range of dorsiflexion/plantar flexion (OR 5.23, 95%CI 1.88;14.58) were associated with osteophytes in the TNJ. Pain at the end of dorsiflexion/plantar flexion, a difference in ROM of passive plantar flexion and swelling seem to be associated with features of OA (bone marrow edema, osteophytes) in the TCJ and TNJ. Our findings may guide physicians to predict structural joint abnormalities as signs of osteoarthritis. 1b. © Georg Thieme Verlag KG Stuttgart · New York.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Stigma towards mental illness among medical and nursing students in Singapore: a cross-sectional study

PubMed Central

Chang, Sherilyn; Ong, Hui Lin; Seow, Esmond; Chua, Boon Yiang; Abdin, Edimansyah; Samari, Ellaisha; Chong, Siow Ann; Subramaniam, Mythily

2017-01-01

Objectives To assess stigma towards people with mental illness among Singapore medical and nursing students using the Opening Minds Stigma Scale for Health Care Providers (OMS-HC), and to examine the relationship of students’ stigmatising attitudes with sociodemographic and education factors. Design and setting Cross-sectional study conducted in Singapore Participants The study was conducted among 1002 healthcare (502 medical and 500 nursing) students during April to September 2016. Students had to be Singapore citizens or permanent residents and enrolled in public educational institutions to be included in the study. The mean (SD) age of the participants was 21.3 (3.3) years, with the majority being females (71.1%). 75.2% of the participants were Chinese, 14.1% were Malays, and 10.7% were either Indians or of other ethnicity. Methods Factor analysis was conducted to validate the OMS-HC scale in the study sample and to examine its factor structure. Descriptive statistics and multivariate linear regression were used to examine sociodemographic and education correlates. Results Factor analysis revealed a three-factor structure with 14 items. The factors were labelled as attitudes towards help-seeking and people with mental illness, social distance and disclosure. Multivariable linear regression analysis showed that medical students were found to be associated with lower total OMS-HC scores (P<0.05), less negative attitudes (P<0.001) and greater disclosure (P<0.05) than nursing students. Students who had a monthly household income of below S$4000 had more unfavourable attitudes than those with an income of SGD$10 000 and above (P<0.05). Having attended clinical placement was associated with more negative attitudes (P<0.05) among the students. Conclusion Healthcare students generally possessed positive attitudes towards help-seeking and persons with mental illness, though they preferred not to disclose their own mental health condition. Academic curriculum may need to enhance the component of mental health training, particularly on reducing stigma in certain groups of students. PMID:29208617

Vascular endothelial growth factor-C (VEGF-C) expression predicts lymph node metastasis of transitional cell carcinoma of the bladder.

PubMed

Suzuki, Kazumi; Morita, Tatsuo; Tokue, Akihiko

2005-02-01

It has been found that expression of vascular endothelial growth factor-C (VEGF-C) in several carcinomas is significantly associated with angiogenesis, lymphangiogenesis and regional lymph node metastasis. However, VEGF-C expression in bladder transitional cell carcinoma (TCC) has not yet been reported. To elucidate the role of VEGF-C in bladder TCC, we examined VEGF-C expression in bladder TCC and pelvic lymph node metastasis specimens obtained from patients who underwent radical cystectomy. Eighty-seven patients who underwent radical cystectomy for clinically organ-confined TCC of the bladder were enrolled in the present study. No neoadjuvant treatments, except transurethral resection of the tumor, were given to these patients. The VEGF-C expressions of 87 bladder tumors and 20 pelvic lymph node metastasis specimens were examined immunohistochemically and the association between VEGF-C expression and clinicopathological factors, including angiogenesis as evaluated by microvessel density (MVD), was also examined. Vascular endothelial growth factor-C expression was found in the cytoplasm of tumor cells, but not in the normal transitional epithelium. Vascular endothelial growth factor-C expression was significantly associated with the pathological T stage (P = 0.0289), pelvic lymph node metastasis (P < 0.0001), lymphatic involvement (P = 0.0008), venous involvement (P = 0.0002) and high MVD (P = 0.0043). The multivariate analysis demonstrated that VEGF-C expression and high MVD in bladder TCC were independent risk factors influencing the pelvic lymph node metastasis. Moreover, the patients with VEGF-C-positive tumors had significantly poorer prognoses than those with the VEGF-C-negative tumors (P = 0.0087) in the univariate analysis. The multivariate analysis based on Cox proportional hazard model showed that the independent prognostic factors were patient age (P = 0.0132) and pelvic lymph node metastasis (P = 0.0333). The present study suggests that VEGF-C expression is an important predictive factor of pelvic lymph node metastasis in bladder cancer patients.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Racial and ethnic disparities in maternal morbidity and obstetric care.

PubMed

Grobman, William A; Bailit, Jennifer L; Rice, Madeline Murguia; Wapner, Ronald J; Reddy, Uma M; Varner, Michael W; Thorp, John M; Leveno, Kenneth J; Caritis, Steve N; Iams, Jay D; Tita, Alan T N; Saade, George; Rouse, Dwight J; Blackwell, Sean C; Tolosa, Jorge E; VanDorsten, J Peter

2015-06-01

To evaluate whether racial and ethnic disparities exist in obstetric care and adverse outcomes. We analyzed data from a cohort of women who delivered at 25 hospitals across the United States over a 3-year period. Race and ethnicity was categorized as non-Hispanic white, non-Hispanic black, Hispanic, or Asian. Associations between race and ethnicity and severe postpartum hemorrhage, peripartum infection, and severe perineal laceration at spontaneous vaginal delivery as well as between race and ethnicity and obstetric care (eg, episiotomy) relevant to the adverse outcomes were estimated by univariable analysis and multivariable logistic regression. Of 115,502 studied women, 95% were classified by one of the race and ethnicity categories. Non-Hispanic white women were significantly less likely to experience severe postpartum hemorrhage (1.6% non-Hispanic white compared with 3.0% non-Hispanic black compared with 3.1% Hispanic compared with 2.2% Asian) and peripartum infection (4.1% non-Hispanic white compared with 4.9% non-Hispanic black compared with 6.4% Hispanic compared with 6.2% Asian) than others (P<.001 for both). Severe perineal laceration at spontaneous vaginal delivery was significantly more likely in Asian women (2.5% non-Hispanic white compared with 1.2% non-Hispanic black compared with 1.5% Hispanic compared with 5.5% Asian; P<.001). These disparities persisted in multivariable analysis. Many types of obstetric care examined also were significantly different according to race and ethnicity in both univariable and multivariable analysis. There were no significant interactions between race and ethnicity and hospital of delivery. Racial and ethnic disparities exist for multiple adverse obstetric outcomes and types of obstetric care and do not appear to be explained by differences in patient characteristics or by delivery hospital. II.

Racial and Ethnic Disparities in Maternal Morbidity and Obstetric Care

PubMed Central

Grobman, William A.; Bailit, Jennifer L.; Rice, Madeline Murguia; Wapner, Ronald J.; Reddy, Uma M.; Varner, Michael W.; Thorp, John M.; Leveno, Kenneth J.; Caritis, Steve N.; Iams, Jay D.; Tita, Alan T. N.; Saade, George; Rouse, Dwight J.; Blackwell, Sean C.; Tolosa, Jorge E.; VanDorsten, J. Peter

2015-01-01

Objective To evaluate whether racial and ethnic disparities exist in obstetric care and adverse outcomes. Methods We analyzed data from a cohort of women who delivered at 25 hospitals across the United States over a 3-year period. Race and ethnicity was categorized as Non-Hispanic white, Non-Hispanic black, Hispanic, or Asian. Associations between race and ethnicity and severe postpartum hemorrhage (PPH), peripartum infection, and severe perineal laceration at spontaneous vaginal delivery, as well as between race and ethnicity and obstetric care (eg, episiotomy) relevant to the adverse outcomes, were estimated by univariable analysis and multivariable logistic regression. Results Of 115,502 studied women, 95% were classified by one of the race and ethnicity categories. Non-Hispanic white women were significantly less likely to experience severe PPH (1.6% non-Hispanic white vs. 3.0% Non-Hispanic black vs. 3.1% Hispanic vs. 2.2%Asian) and peripartum infection (4.1% non-Hispanic white vs. 4.9% Non-Hispanic black vs. 6.4% Hispanic vs. 6.2% Asian) than others (P < 0.001 for both). Severe perineal laceration at spontaneous vaginal delivery was significantly more likely in Asian women (2.5% non-Hispanic white vs. 1.2% Non-Hispanic black vs. 1.5% Hispanic vs. 5.5% Asian) P< 0.001). These disparities persisted in multivariable analysis. Many types of obstetric care examined also were significantly different according to race and ethnicity in both univariable and multivariable analysis. There were no significant interactions between race and ethnicity and hospital of delivery. Conclusion Racial and ethnic disparities exist for multiple adverse obstetric outcomes and types of obstetric care, and do not appear to be explained by differences in patient characteristics or by delivery hospital. PMID:26000518

[Multivariate analysis of the association between consumption of fried food and gastric cancer and precancerous lesions].

PubMed

Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

2018-02-06

Objective: To investigate the effect of fried food intake on the pathogenesis of gastric cancer and precancerous lesions. Methods: From 2005 to 2013, the residents aged 40-69 years from 11 counties/cities where cancer screening of upper gastrointestinal cancer were conducted in rural areas of Henan province as the subjects (82 367 cases). The information such as demography and lifestyle was collected. The residents were screened with endoscopic examination. The biopsy sampleswere diagnosed pathologically, according to pathological diagnosis criteria, the subjects with high risk were divided into the groups with different pathological degrees. The multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and gastric cancer and precancerous lesions. Results: The study coverd 46 425 males and 35 942 females, with a age of (53.46±8.07)years. The study collected 6 707 cases of normal stomach, 2 325 cases of low grade intraepithelial neoplasia, 226 cases of high grade intraepithelial neoplasia and 331 cases of gastric cancer. Multivariate logistic regression analysis showed that, compared with those whoeat fried food less than one time per week, fried foods intake (<2 times/week: OR= 1.89, 95 %CI: 1.57-2.28; ≥ 2 times/week: OR= 1.91, 95 %CI: 1.66-2.20) were a risk factor for gastric cancer and precancerous lesions after adjustment for age, sex, marital status, educational level, body mass index (BMI), smoking and drinking status. Conclusion: The intake of fried food is a risk factor for gastric cancer and precancerous lesions. Therefore, reducing the intake of fried food can prevent the occurrence of gastric carcinoma and precancerous lesions.

Socioeconomic disparities in the utilization of mechanical thrombectomy for acute ischemic stroke in US hospitals.

PubMed

Brinjikji, W; Rabinstein, A A; McDonald, J S; Cloft, H J

2014-03-01

Previous studies have demonstrated that socioeconomic disparities in the treatment of cerebrovascular diseases exist. We studied a large administrative data base to study disparities in the utilization of mechanical thrombectomy for acute ischemic stroke. With the utilization of the Perspective data base, we studied disparities in mechanical thrombectomy utilization between patient race and insurance status in 1) all patients presenting with acute ischemic stroke and 2) patients presenting with acute ischemic stroke at centers that performed mechanical thrombectomy. We examined utilization rates of mechanical thrombectomy by race/ethnicity (white, black, and Hispanic) and insurance status (Medicare, Medicaid, self-pay, and private). Multivariate logistic regression analysis adjusting for potential confounding variables was performed to study the association between race/insurance status and mechanical thrombectomy utilization. The overall mechanical thrombectomy utilization rate was 0.15% (371/249,336); utilization rate at centers that performed mechanical thrombectomy was 1.0% (371/35,376). In the sample of all patients with acute ischemic stroke, multivariate logistic regression analysis demonstrated that uninsured patients had significantly lower odds of mechanical thrombectomy utilization compared with privately insured patients (OR = 0.52, 95% CI = 0.25-0.95, P = .03), as did Medicare patients (OR = 0.53, 95% CI = 0.41-0.70, P < .0001). Blacks had significantly lower odds of mechanical thrombectomy utilization compared with whites (OR = 0.35, 95% CI = 0.23-0.51, P < .0001). When considering only patients treated at centers performing mechanical thrombectomy, multivariate logistic regression analysis demonstrated that insurance was not associated with significant disparities in mechanical thrombectomy utilization; however, black patients had significantly lower odds of mechanical thrombectomy utilization compared with whites (OR = 0.41, 95% CI = 0.27-0.60, P < .0001). Significant socioeconomic disparities exist in the utilization of mechanical thrombectomy in the United States.

Association between thoracic aortic disease and inguinal hernia.

PubMed

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

2014-08-21

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

A lengthy look at the daily grind: time series analysis of events, mood, stress, and satisfaction.

PubMed

Fuller, Julie A; Stanton, Jeffrey M; Fisher, Gwenith G; Spitzmuller, Christiane; Russell, Steven S; Smith, Patricia C

2003-12-01

The present study investigated processes by which job stress and satisfaction unfold over time by examining the relations between daily stressful events, mood, and these variables. Using a Web-based daily survey of stressor events, perceived strain, mood, and job satisfaction completed by 14 university workers, 1,060 occasions of data were collected. Transfer function analysis, a multivariate version of time series analysis, was used to examine the data for relationships among the measured variables after factoring out the contaminating influences of serial dependency. Results revealed a contrast effect in which a stressful event associated positively with higher strain on the same day and associated negatively with strain on the following day. Perceived strain increased over the course of a semester for a majority of participants, suggesting that effects of stress build over time. Finally, the data were consistent with the notion that job satisfaction is a distal outcome that is mediated by perceived strain. ((c) 2003 APA, all rights reserved)

Relationship between body image and breast self-examination intentions and behavior among female university students in Malaysia.

PubMed

Samah, Asnarulkhadi Abu; Ahmadian, Maryam

2014-01-01

This study aimed to examine the relationship between body image satisfaction and breast self-screening behavior and intentions. The sample for this cross-sectional study consisted of 842 female university students who were recruited from a number of public and private universities. Data were obtained between the months of November and December, 2013, using multistage random cluster sampling. Main research variables were breast cancer screening behavior and intentions, demographic factors, and the total scores on each of the Multidimensional Body-Self Relations Questionnaire (MBSRQ-Appearance Scales) subscales. Results of multivariate analysis showed that having higher satisfaction and more positive evaluation of appearance were related to having performed breast self-examination more frequently in the last year and intending to perform breast self-examination more frequently in the next year. Longitudinal research can potentially provide detailed information about overall body image satisfaction and breast cancer screening behavior among various communities.

A Multivariate Model of Parent-Adolescent Relationship Variables in Early Adolescence

ERIC Educational Resources Information Center

McKinney, Cliff; Renk, Kimberly

2011-01-01

Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle…

MULTIVARIATE CURVE RESOLUTION OF NMR SPECTROSCOPY METABONOMIC DATA

EPA Science Inventory

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

Pastoral Care Use among Post-9/11 Veterans who Screen Positive for Mental Health Problems

PubMed Central

Nieuwsma, Jason A.; Fortune-Greeley, Alice K.; Jackson, George L.; Meador, Keith G.; Beckham, Jean C.; Elbogen, Eric B.

2014-01-01

As a result of their military experience, veterans with mental health problems may have unique motivations for seeking help from clergy. Patterns and correlates of seeking pastoral care were examined using a nationwide representative survey that was conducted among veterans of post-9/11 conflicts (adjusted N = 1,068; 56% response rate). Separate multivariate logistic regression models were used to examine veteran characteristics associated with seeking pastoral care and seeking mental health services. Among post-9/11 veterans with a probable mental disorder (n = 461) – defined as a positive screen for posttraumatic stress disorder, major depressive disorder, or alcohol misuse – 20.2% reported talking to a “pastoral counselor” in the preceding year, 44.7% reported talking to a mental health professional, and 46.6% reported talking to neither. In a multivariate analysis for veterans with a probable mental disorder, seeing a pastoral counselor was associated with an increased likelihood of seeing a mental health professional in the past year (OR: 2.16; 95% CI: [1.28, 3.65]). In a separate bivariate analysis, pastoral counselors were more likely to be seen by veterans who indicated concerns about stigma or distrust of mental health care. These results suggest that pastoral and mental health care services may complement one another and underscore the importance of enhancing understanding and collaboration between these disciplines so as to meet the needs of the veterans they serve. PMID:24933105

Incidence and timing of presentation of necrotizing enterocolitis in preterm infants.

PubMed

Yee, Wendy H; Soraisham, Amuchou Singh; Shah, Vibhuti S; Aziz, Khalid; Yoon, Woojin; Lee, Shoo K

2012-02-01

To examine the variation in the incidence and to identify the timing of the presentation of necrotizing enterocolitis (NEC) in a cohort of preterm infants within the Canadian Neonatal Network (CNN). This was a population-based cohort of 16 669 infants with gestational age (GA) <33 weeks, admitted to 25 NICUs participating in the CNN between January 1, 2003, and December 31(,) 2008. Variations in NEC incidence among the participating NICUs for the study period were examined. We categorized early-onset NEC as occurring at <14 days of age and late-onset NEC occurring at ≥14 days. Multivariate logistic regression analysis was performed to identify risk factors for early-onset NEC. The overall incidence of NEC was 5.1%, with significant variation in the risk adjusted incidence among the participating NICUs in the CNN. Early-onset NEC occurred at a mean of 7 days compared with 32 days for late-onset NEC. Early-onset NEC infants had lower incidence of respiratory distress syndrome, patent ductus treated with indomethacin, less use of postnatal steroids, and shorter duration of ventilation days. Multivariate logistic regression analysis identified that greater GA and vaginal delivery were associated with increased risk of early-onset NEC. Among infants <33 weeks' gestation, NEC appears to present at mean age of 7 days in more mature infants, whereas onset of NEC is delayed to 32 days of age in smaller, lower GA infants. Further studies are required to understand the etiology of this disease process.

[Eye symptoms in office employees working at computer stations].

PubMed

Kowalska, Małgorzata; Zejda, Jan E; Bugajska, Joanna; Braczkowska, Bogumiła; Brozek, Grzegorz; Malińska, Marzena

2011-01-01

The aim of the study was to measure the prevalence and intensity of eye symptoms in office workers who use computers on a regular basis, and to find out if the symptoms depend on the duration of computer use and other work-related factors. Office workers employed at large social services companies in two cities (Warszawa and Katowice) were invited to fill in a questionnaire (cross-sectional study). The questions included work history and history of last-week eye symptoms and eye-related complains. Altogether 477 men and women returned the completed questionnaires. Between-group symptom differences were tested by the chi-square test and verified by the results of multivariate logistic analysis. The examined effects included the role of daily computer use and lighting conditions at work stations. The examined persons complained of such eye symptoms as eye strain, visual acuity impairment and mucosal dryness or eye burning. The following values of symptom prevalence were found in women and men, respectively: eye strain 50.7% and 32.6%, disturbed visual acuity 38.3% and 21.2%, mucosal dryness and eye burning 46.5% and 24.2%. The results of multivariate analysis confirmed the statistically significant effects of lighting intensity and screen flickering on the occurrence of symptoms. Frequent occurrence of eye symptoms and their associatation with some characteristics of the work environment point to the need of observing ergonomic standards of work stations and of the usage of computers at work.

Proton magnetic resonance spectroscopy predicts proliferative activity in diffuse low-grade gliomas.

PubMed

Guillevin, Remy; Menuel, Carole; Duffau, Hugues; Kujas, Michel; Capelle, Laurent; Aubert, Agnès; Taillibert, Sophie; Idbaih, Ahmed; Pallud, Joan; Demarco, Giovanni; Costalat, Robert; Hoang-Xuan, Khê; Chiras, Jacques; Vallée, Jean-Noel

2008-04-01

The aim of the study was to investigate the ability of (1)HMRS to reflect proliferative activity of diffuse low-grade gliomas (WHO grade II). Between November 2002 and March 2007, a prospective study was performed on consecutive patients with suspected supratentorial hemispheric diffuse low-grade tumors. All the patients underwent MR examination using uniform procedures, and then surgical resection or biopsy within 2 weeks of the MR examination. Proliferative activity of the tumors was assessed by Ki-67 immunochemistry (Mb-1) on paraffin embedded tumor sections. Spectroscopic data was compared with Ki-67 labeling index and other histologic data such as histological subtype, cellular atypia, cellular density using univariate and multivariate analysis. 82 of 97 consecutive patients had histologically confirmed WHO grade 2 gliomas. Ki-67 proliferation index (PI) was correlated with specific spectral patterns: (1) low PI (<4%) was associated with increased Cho/Cr and absence of both free lipids or lactates; (2) intermediate PI (4-8%) was associated with resonance of lactates; and (3) high PI (>8%) was characterized by a resonance of free lipids. On multivariate analysis, resonance of lactates and resonance of free lipids appeared as independent predictors of intermediate PI (P < 0.001) and high PI (P < 0.001), respectively; moreover, free lipids resonance was correlated with cellular atypia (P < 0.05). This study suggests that (1)HMRS is a reliable tool to evaluate the proliferation activity of WHO grade 2 glioma and to identify potentially more aggressive clinical behavior.

Youth, violence and non-injection drug use: nexus of vulnerabilities among lesbian and bisexual sex workers.

PubMed

Lyons, Tara; Kerr, Thomas; Duff, Putu; Feng, Cindy; Shannon, Kate

2014-01-01

Despite increasing evidence of enhanced HIV risk among sexual minority populations, and sex workers (SWs) in particular, there remains a paucity of epidemiological data on the risk environments of SWs who identify as lesbian or bisexual. Therefore, this short report describes a study that examined the individual, interpersonal and structural associations with lesbian or bisexual identity among SWs in Vancouver, Canada. Analysis drew on data from an open prospective cohort of street and hidden off-street SWs in Vancouver. Bivariate and multivariable logistic regressions were used to examine the independent relationships between individual, interpersonal, work environment and structural factors and lesbian or bisexual identity. Of the 510 individuals in our sample, 95 (18.6%) identified as lesbian or bisexual. In multivariable analysis, reporting non-injection drug use in the last six months (adjusted odds ratio [AOR] = 2.89; 95% confidence intervals [CI] = 1.42, 5.75), youth ≤24 years of age (AOR = 2.43; 95% CI = 1.24, 4.73) and experiencing client-perpetrated verbal, physical and/or sexual violence in the last six months (AOR = 1.85; 95% CI = 1.15, 2.98) remained independently associated with lesbian/bisexual identity, after adjusting for potential confounders. The findings demonstrate an urgent need for evidence-based social and structural HIV prevention interventions. In particular, policies and programmes tailored to lesbian and bisexual youth and women working in sex work, including those that prevent violence and address issues of non-injection stimulant use are required.

Racial differences in colorectal cancer survival at a safety net hospital.

PubMed

Tapan, Umit; Lee, Shin Yin; Weinberg, Janice; Kolachalama, Vijaya B; Francis, Jean; Charlot, Marjory; Hartshorn, Kevan; Chitalia, Vipul

2017-08-01

While racial disparity in colorectal cancer survival have previously been studied, whether this disparity exists in patients with metastatic colorectal cancer receiving care at safety net hospitals (and therefore of similar socioeconomic status) is poorly understood. We examined racial differences in survival in a cohort of patients with stage IV colorectal cancer treated at the largest safety net hospital in the New England region, which serves a population with a majority (65%) of non-Caucasian patients. Data was extracted from the hospital's electronic medical record. Survival differences among different racial and ethnic groups were examined graphically using Kaplan-Meier analysis. A univariate cox proportional hazards model and a multivariable adjusted model were generated. Black patients had significantly lower overall survival compared to White patients, with median overall survival of 1.9 years and 2.5 years respectively. In a multivariate analysis, Black race posed a significant hazard (HR 1.70, CI 1.01-2.90, p=0.0467) for death. Though response to therapy emerged as a strong predictor of survival (HR=0.4, CI=0.2-0.7, p=0.0021), it was comparable between Blacks and Whites. Despite presumed equal access to healthcare and socioeconomic status within a safety-net hospital system, our results reinforce findings from previous studies showing lower colorectal cancer survival in Black patients, and also point to the importance of investigating other factors such as genetic and pathologic differences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

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

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

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

Analysis of some metallic elements and metalloids composition and relationships in parasol mushroom Macrolepiota procera.

PubMed

Falandysz, Jerzy; Sapkota, Atindra; Dryżałowska, Anna; Mędyk, Małgorzata; Feng, Xinbin

2017-06-01

The aim of the study was to characterise the multi-elemental composition and associations between a group of 32 elements and 16 rare earth elements collected by mycelium from growing substrates and accumulated in fruiting bodies of Macrolepiota procera from 16 sites from the lowland areas of Poland. The elements were quantified by inductively coupled plasma quadrupole mass spectrometry using validated method. The correlation matrix obtained from a possible 48 × 16 data matrix has been used to examine if any association exits between 48 elements in mushrooms foraged from 16 sampling localizations by multivariate approach using principal component (PC) analysis. The model could explain up to 93% variability by eight factors for which an eigenvalue value was ≥1. Absolute values of the correlation coefficient were above 0.72 (significance at p < 0.05) for 43 elements. From a point of view by consumer, the absolute content of Cd, Hg, Pb in caps of M. procera collected from background (unpolluted) areas could be considered elevated while sporadic/occasional ingestion of this mushroom is considered safe. The multivariate functional analysis revealed on associated accumulation of many elements in this mushroom. M. procera seem to possess some features of a bio-indicative species for anthropogenic Pb but also for some geogenic metals.

Factors associated with sealant outcome in 2 pediatric dental clinics: a multivariate hierarchical analysis.

PubMed

West, Nathan G; Ilief-Ala, Melina A; Douglass, Joanna M; Hagadorn, James I

2011-01-01

This study's purpose was to determine whether one-time sealants placed by pediatric dental residents vs dental students have different outcomes. The effect of isolation technique, behavior, duration of follow-up, and caries history was also examined. Records from 2 inner-city pediatric dental clinics were audited for 6- to 10-year-old patients with a permanent first molar sealant with at least 2 years of follow-up. A successful sealant was a one-time sealant that received no further treatment and was sealed or unsealed but not carious or restored at the final audit. Charts from 203 children with 481 sealants were audited. Of these, 281 sealants were failures. Univariate analysis revealed longer follow-up and younger age were associated with sealant failure. Operator type, child behavior, and isolation technique were not associated with sealant failure. After adjusting for follow-up duration, increased age at treatment reduced the odds of sealant failure while a history of caries reduced the protective effect of increased age. After adjusting for these factors, practitioner type, behavior, and type of isolation were not associated with sealant outcome in multivariate analysis. Age at sealant placement, history of caries prior to placement, and longer duration of follow-up are associated with sealant failure.

Correlation between ultrafiltration rate and phase angle measured by BIA in chronic kidney disease patients on regular hemodialysis

NASA Astrophysics Data System (ADS)

Nasution, B. R.; Lubis, A. R.

2018-03-01

Chronic Kidney Disease (CKD) patients with regular hemodialysis have high rates of morbidity and mortality that may be related to the hemodynamic effects of rapid UFR and low PhA value. In this study, we investigated whether high UFR is associated with a low value of PhA thus indirectly affect the risk of morbidity and mortality. UFR and Bioelectrical Impedance Analysis (BIA) examination on 92 subjects were recorded shortly after HD and analyzed by using Pearson correlation test. Multivariate analysis was also conducted to identify several factors that can affect the value of Phase angle. The number of HD regular CKD patients with PhA<4 based on the division of the UFR (cc/kg/h) <10, 10-13, ≥ 13, respectively were3, 10 and 6, whereas patients with ≥ 4 PhA <10, 10-13, ≥ 13respectively were 60, 11, and 2. The results showed a significant relationship between UFR with PhA. In CKD patients with regular HD, UFR has aninverse relationship with the value of PhA. After multivariate analysis, the UFR and the etiology of HD are still significantly affect the value of PhA. UFR optimal value in patients with CKD with regular HD is <10 cc/kg/h.

Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

PubMed

Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

Palliative interventions for hepatocellular carcinoma patients: analysis of the National Cancer Database.

PubMed

Hammad, Abdulrahman Y; Robbins, Jared R; Turaga, Kiran K; Christians, Kathleen K; Gamblin, T Clark; Johnston, Fabian M

2017-01-01

Palliative therapies are provided to a subset of hepatocellular carcinoma (HCC) patients with the aim of providing symptomatic relief, better quality of life and improved survival. The present study sought to assess and compare the efficacy of different palliative therapies for HCC. The National Cancer Database (NCDB), a retrospective national database that captures approximately 70% of all patients treated for cancer in the US, was queried for patients with HCC who were deemed unresectable from 1998-2011. Patients were stratified by receipt of palliative therapy. Survival analysis was examined by log-rank test and Kaplan Meier curves, and a multivariate proportional hazards model was utilized to identify the predictors of survival. A total of 3,267 patients were identified; 287 (8.7%) received surgical palliation, 827 (25.3%) received radiotherapy (RT), 877 (26.8%) received chemotherapy, 1,067 (32.6%) received pain management therapy, while 209 (6.4%) received a combination of the previous three modalities. On multivariate analysis palliative RT was identified as a positive predictor of survival [hazards ratio (HR) 0.65; 95% CI, 0.50-0.83]. Stratifying by disease stage, palliative RT provided a significant survival benefit for patients with stage IV disease. Palliative RT appears to extend survival and should be considered for patients presenting with late stage HCC.

Nationwide analysis of adrenocortical carcinoma reveals higher perioperative morbidity in functional tumors.

PubMed

Parikh, Punam P; Rubio, Gustavo A; Farra, Josefina C; Lew, John I

2017-08-25

Current adrenalectomy outcomes for functional adrenocortical carcinoma (ACC) remain unclear. This study examines nationwide in-hospital post-adrenalectomy outcomes for ACC. A retrospective analysis of the Nationwide Inpatient Sample database (2006-2011) to identify unilateral adrenalectomy patients for functional or nonfunctional ACC was performed. Patient demographics, comorbidities and postoperative outcomes were evaluated by t-test, Chi-square and multivariate regression. Of 2199 patients who underwent adrenalectomy, 87% had nonfunctional and 13% had functional ACC (86% hypercortisolism, 16% hyperaldosteronism, 4% hyperandrogenism). Functional ACC patients had significantly more comorbidities, and experienced certain postoperative complications more frequently including wound issues, adrenocortical insufficiency and acute kidney injury with longer hospital stay compared to nonfunctional ACC (P < 0.01). On multivariate analysis, functional ACC was an independent prognosticator for wound complications (28.1, 95%CI 4.59-176.6). Patients with functional ACC manifest significant comorbidities with certain in-hospital complications. Such high-risk patients require appropriate preoperative medical optimization prior to adrenalectomy. Patients with functional adrenocortical carcinoma (ACC) have significant preoperative comorbidities and experience higher rates of certain postoperative complications including wound complications, hematoma formation, adrenal insufficiency, pulmonary embolism and acute kidney injury. Functional ACC patients also necessitate longer hospitalizations. These patients should undergo appropriate preoperative counseling in preparation for adrenalectomy. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2015-12-30

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

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

PubMed Central

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

2015-01-01

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

Social cohesion and self-rated health among adults in South Africa: The moderating role of race.

PubMed

Olamijuwon, Emmanuel O; Odimegwu, Clifford O; De Wet, Nicole

2018-05-01

In African countries including South Africa, the nexus between social cohesion and health remains under-researched. Using data from the 2012 South African social attitudes survey with a sample of 1988 adults in South Africa aged 18 years or older, we used the collective efficacy theory by Sampson and colleagues to examine the relationship between social cohesion and self-rated health in an African sample. We also examined how this relationship differed by race. Results from the multivariate analysis after adjusting for covariates suggested that adults in the highest tertile of social cohesion were more likely to report moderate or good health compared to those in the lowest tertile. Sub-group analysis provided no evidence that the relationship was moderated by race. These findings corroborate prior evidence that social cohesion is important for improving the health of adults. Copyright © 2018 Elsevier Ltd. All rights reserved.

Indicating spinal joint mobilisations or manipulations in patients with neck or low-back pain: protocol of an inter-examiner reliability study among manual therapists.

PubMed

van Trijffel, Emiel; Lindeboom, Robert; Bossuyt, Patrick Mm; Schmitt, Maarten A; Lucas, Cees; Koes, Bart W; Oostendorp, Rob Ab

2014-01-01

Manual spinal joint mobilisations and manipulations are widely used treatments in patients with neck and low-back pain. Inter-examiner reliability of passive intervertebral motion assessment of the cervical and lumbar spine, perceived as important for indicating these interventions, is poor within a univariable approach. The diagnostic process as a whole in daily practice in manual therapy has a multivariable character, however, in which the use and interpretation of passive intervertebral motion assessment depend on earlier results from the diagnostic process. To date, the inter-examiner reliability among manual therapists of a multivariable diagnostic decision-making process in patients with neck or low-back pain is unknown. This study will be conducted as a repeated-measures design in which 14 pairs of manual therapists independently examine a consecutive series of a planned total of 165 patients with neck or low-back pain presenting in primary care physiotherapy. Primary outcome measure is therapists' decision about whether or not manual spinal joint mobilisations or manipulations, or both, are indicated in each patient, alone or as part of a multimodal treatment. Therapists will largely be free to conduct the full diagnostic process based on their formulated examination objectives. For each pair of therapists, 2×2 tables will be constructed and reliability for the dichotomous decision will be expressed using Cohen's kappa. In addition, observed agreement, prevalence of positive decisions, prevalence index, bias index, and specific agreement in positive and negative decisions will be calculated. Univariable logistic regression analysis of concordant decisions will be performed to explore which demographic, professional, or clinical factors contributed to reliability. This study will provide an estimate of the inter-examiner reliability among manual therapists of indicating spinal joint mobilisations or manipulations in patients with neck or low-back pain based on a multivariable diagnostic reasoning and decision-making process, as opposed to reliability of individual tests. As such, it is proposed as an initial step toward the development of an alternative approach to current classification systems and prediction rules for identifying those patients with spinal disorders that may show a better response to manual therapy which can be incorporated in randomised clinical trials. Potential methodological limitations of this study are discussed.

Indicating spinal joint mobilisations or manipulations in patients with neck or low-back pain: protocol of an inter-examiner reliability study among manual therapists

PubMed Central

2014-01-01

Background Manual spinal joint mobilisations and manipulations are widely used treatments in patients with neck and low-back pain. Inter-examiner reliability of passive intervertebral motion assessment of the cervical and lumbar spine, perceived as important for indicating these interventions, is poor within a univariable approach. The diagnostic process as a whole in daily practice in manual therapy has a multivariable character, however, in which the use and interpretation of passive intervertebral motion assessment depend on earlier results from the diagnostic process. To date, the inter-examiner reliability among manual therapists of a multivariable diagnostic decision-making process in patients with neck or low-back pain is unknown. Methods This study will be conducted as a repeated-measures design in which 14 pairs of manual therapists independently examine a consecutive series of a planned total of 165 patients with neck or low-back pain presenting in primary care physiotherapy. Primary outcome measure is therapists’ decision about whether or not manual spinal joint mobilisations or manipulations, or both, are indicated in each patient, alone or as part of a multimodal treatment. Therapists will largely be free to conduct the full diagnostic process based on their formulated examination objectives. For each pair of therapists, 2×2 tables will be constructed and reliability for the dichotomous decision will be expressed using Cohen’s kappa. In addition, observed agreement, prevalence of positive decisions, prevalence index, bias index, and specific agreement in positive and negative decisions will be calculated. Univariable logistic regression analysis of concordant decisions will be performed to explore which demographic, professional, or clinical factors contributed to reliability. Discussion This study will provide an estimate of the inter-examiner reliability among manual therapists of indicating spinal joint mobilisations or manipulations in patients with neck or low-back pain based on a multivariable diagnostic reasoning and decision-making process, as opposed to reliability of individual tests. As such, it is proposed as an initial step toward the development of an alternative approach to current classification systems and prediction rules for identifying those patients with spinal disorders that may show a better response to manual therapy which can be incorporated in randomised clinical trials. Potential methodological limitations of this study are discussed. PMID:24982754

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

PubMed

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

2007-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Link between perceived smoking behaviour at school and students smoking status: a large survey among Italian adolescents.

PubMed

Backhaus, I; D'Egidio, V; Grassucci, D; Gelardini, M; Ardizzone, C; La Torre, G

2017-10-01

To investigate a possible link between sociodemographic factors, the perception of smoking habits at school and smoking status of Italian adolescents attending secondary school. The study was a cross-sectional study. An anonymous online survey was employed to gather information on age, gender, smoking status and to examine the perception of smoking behaviour on the school premises. Chi-squared and Kruskal-Wallis tests were performed for the univariate analysis and logistic and multinomial regressions for the multivariate analysis. The statistical analyses included 1889 students. Univariate analysis showed significant differences concerning knowledge between smoker and non-smoker concerning the harmfulness of smoking (P < 0.001). According to the multivariate analysis smokers had a higher perception of teacher, principal or janitor smoking at school (odds ratio: 1.54 [95% confidence interval 1.26-1.89]). Students older than 19 years most often begin smoking because their friends smoke compared with younger students (adjusted odds ratio: 1.18 [95% confidence interval 0.48-2.89]). School environment and behaviour of role models play a crucial part in student smoking. To prevent and reduce youth tobacco smoking, not merely the presence of preventive measures is important but greater attention needs to be placed on the enforcement of smoking policies. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis.

PubMed

Zhang, Sheng; Hu, Sien; Sinha, Rajita; Potenza, Marc N; Malison, Robert T; Li, Chiang-Shan R

2016-01-01

Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions in cocaine dependence. To address this issue, we used multivariate pattern analysis (MVPA) to examine how functional connectivity of the thalamus distinguishes 100 cocaine-dependent participants (CD) from 100 demographically matched healthy control individuals (HC). We characterized six task-related networks with independent component analysis of fMRI data of a stop signal task and employed MVPA to distinguish CD from HC on the basis of voxel-wise thalamic connectivity to the six independent components. In an unbiased model of distinct training and testing data, the analysis correctly classified 72% of subjects with leave-one-out cross-validation (p < 0.001), superior to comparison brain regions with similar voxel counts (p < 0.004, two-sample t test). Thalamic voxels that form the basis of classification aggregate in distinct subclusters, suggesting that connectivities of thalamic subnuclei distinguish CD from HC. Further, linear regressions provided suggestive evidence for a correlation of the thalamic connectivities with clinical variables and performance measures on the stop signal task. Together, these findings support thalamic circuit dysfunction in cognitive control as an important neural marker of cocaine dependence.

Patterns and Predictors of Language and Literacy Abilities 4-10 Years in the Longitudinal Study of Australian Children.

PubMed

Zubrick, Stephen R; Taylor, Catherine L; Christensen, Daniel

2015-01-01

Oral language is the foundation of literacy. Naturally, policies and practices to promote children's literacy begin in early childhood and have a strong focus on developing children's oral language, especially for children with known risk factors for low language ability. The underlying assumption is that children's progress along the oral to literate continuum is stable and predictable, such that low language ability foretells low literacy ability. This study investigated patterns and predictors of children's oral language and literacy abilities at 4, 6, 8 and 10 years. The study sample comprised 2,316 to 2,792 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Six developmental patterns were observed, a stable middle-high pattern, a stable low pattern, an improving pattern, a declining pattern, a fluctuating low pattern, and a fluctuating middle-high pattern. Most children (69%) fit a stable middle-high pattern. By contrast, less than 1% of children fit a stable low pattern. These results challenged the view that children's progress along the oral to literate continuum is stable and predictable. Multivariate logistic regression was used to investigate risks for low literacy ability at 10 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. Predictors were modelled as risk variables with the lowest level of risk as the reference category. In the multivariate model, substantial risks for low literacy ability at 10 years, in order of descending magnitude, were: low school readiness, Aboriginal and/or Torres Strait Islander status and low language ability at 8 years. Moderate risks were high temperamental reactivity, low language ability at 4 years, and low language ability at 6 years. The following risk factors were not statistically significant in the multivariate model: Low maternal consistency, low family income, health care card, child not read to at home, maternal smoking, maternal education, family structure, temperamental persistence, and socio-economic area disadvantage. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude did not do particularly well in predicting low literacy ability at 10 years.

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

PubMed

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

2015-04-01

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

Multivariate meta-analysis using individual participant data

PubMed Central

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

2016-01-01

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

Effectiveness of water fluoridation in the prevention of dental caries across adult age groups.

PubMed

Do, Loc; Ha, Diep; Peres, Marco A; Skinner, John; Byun, Roy; Spencer, A John

2017-06-01

Lifetime access to fluoridated water (FW) is associated with lower caries experience. However, assessing this association in adults is likely affected by age. Cohort stratification and categorization of per cent lifetime access to fluoridated water (% LAFW) within cohorts are current approaches to this assessment. These approaches require an examination of the % LAFW and caries experience variation within and across age groups and their association to inform future analyses. This secondary analysis aimed to examine the age group variation in % LAFW and caries experience; and the association of % LAFW with caries within and across age groups of adults. A secondary analysis was undertaken using the Australian National Survey of Adult Oral Health 2004-2006 data on 4090 persons aged 15-91 years randomly sampled by a stratified, multistage probability method. Study participants underwent an interview, an oral examination by trained and standardized dentists to determine decayed, missing or filled tooth surfaces (DMFS) and a mailed self-complete questionnaire which collected residential history to calculate % LAFW. Variations in % LAFW and DMFS across age groups (15-34; 35-44; 45-54; 55+) were examined. Multivariable regression log-link models were generated for DMFS score within each age group. The age groups varied in values and distribution of % LAFW. Caries experience was strongly associated with age. % LAFW was significantly associated with DMFS score in the two younger age groups, but not in the others. Multivariable regression models showed that the highest % LAFW quartile had significantly lower DMFS count than the lowest quartile in the two younger age groups (mean ratios: 0.67 and 0.78, respectively), controlling for other covariates. Access to FW was associated with caries experience in Australian adults. The magnitude of associations varied between age groups, dependent on the natural history of caries and its measurement by DMFS. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

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

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

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

Deeper Insights into the Circumgalactic Medium using Multivariate Analysis Methods

NASA Astrophysics Data System (ADS)

Lewis, James; Churchill, Christopher W.; Nielsen, Nikole M.; Kacprzak, Glenn

2017-01-01

Drawing from a database of galaxies whose surrounding gas has absorption from MgII, called the MgII-Absorbing Galaxy Catalog (MAGIICAT, Neilsen et al 2013), we studied the circumgalactic medium (CGM) for a sample of 47 galaxies. Using multivariate analysis, in particular the k-means clustering algorithm, we determined that simultaneously examining column density (N), rest-frame B-K color, virial mass, and azimuthal angle (the projected angle between the galaxy major axis and the quasar line of sight) yields two distinct populations: (1) bluer, lower mass galaxies with higher column density along the minor axis, and (2) redder, higher mass galaxies with lower column density along the major axis. We support this grouping by running (i) two-sample, two-dimensional Kolmogorov-Smirnov (KS) tests on each of the six bivariate planes and (ii) two-sample KS tests on each of the four variables to show that the galaxies significantly cluster into two independent populations. To account for the fact that 16 of our 47 galaxies have upper limits on N, we performed Monte-Carlo tests whereby we replaced upper limits with random deviates drawn from a Schechter distribution fit, f(N). These tests strengthen the results of the KS tests. We examined the behavior of the MgII λ2796 absorption line equivalent width and velocity width for each galaxy population. We find that equivalent width and velocity width do not show similar characteristic distinctions between the two galaxy populations. We discuss the k-means clustering algorithm for optimizing the analysis of populations within datasets as opposed to using arbitrary bivariate subsample cuts. We also discuss the power of the k-means clustering algorithm in extracting deeper physical insight into the CGM in relationship to host galaxies.

Employment situation and risk of death among middle-aged Japanese women.

PubMed

Honjo, Kaori; Iso, Hiroyasu; Ikeda, Ai; Fujino, Yoshihisa; Tamakoshi, Akiko

2015-10-01

Few studies have examined the health effects of employment situation among women, taking social and economic conditions into consideration. The objective of this research was to investigate the association of employment situation (full-time or part-time employee and self-employed) with mortality risk in women over a 20-year follow-up period. Additionally, we examined whether the association between employment situation and mortality in women differed by education level and marital status. We investigated the association of employment situation with mortality among 16,692 women aged 40-59 years enrolled in the Japan Collaborative Cohort Study. Multivariate HRs and 95% CIs for total deaths by employment situation were calculated after adjustment for age, disease history, residential area, education level, marital status and number of children. We also conducted subgroup analysis by education level and marital status. Multivariate HRs for mortality of part-time employees and self-employed workers were 1.48 (95% CI, 1.25 to 1.75) and 1.44 (95% CI, 1.21 to 1.72), respectively, with reference to women working full-time. Subgroup analysis by education level indicated that health effects in women according to employment situation were likely to be more evident in the low education-level group. Subgroup analysis by marital status indicated that this factor also affected the association between employment situation and risk of death. Among middle-aged Japanese women, employment situation was associated with mortality risk. Health effects were likely to differ by household structure and socioeconomic conditions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Is coffee consumption associated with a lower risk of hyperuricaemia or gout? A systematic review and meta-analysis

PubMed Central

Zhang, Yi; Yang, Tuo; Zeng, Chao; Wei, Jie; Li, Hui; Xiong, Yi-lin; Yang, Ye; Ding, Xiang; Lei, Guanghua

2016-01-01

Objectives To examine the associations of coffee consumption with the serum uric acid (SUA) level, hyperuricaemia (HU) and gout. Design Systematic review and meta-analysis. Data sources and study eligibility criteria A comprehensive literature search up to April 2015, using PubMed and EMBASE databases, was conducted to identify the observational researches that examined the associations of coffee consumption with the SUA level, HU and gout. The standard mean difference (SMD), OR, relative risk (RR) and their corresponding 95% CIs for the highest and the lowest categories of coffee intake were determined. Results A total of 11 observational studies (6 cross-sectional, 3 cohort and 2 case–control studies) were included in this systematic review and meta-analysis. The combined SMD suggested that there was no significant difference between the highest and the lowest coffee intake categories in terms of the SUA level (SMD=−0.09, 95% CI −0.23 to 0.05; p=0.21). Meanwhile, the overall multivariable adjusted OR for HU showed no significant difference between the highest and the lowest coffee intake categories (OR=0.84, 95% CI 0.65 to 1.09; p=0.20). However, the overall multivariable adjusted RR for gout showed a significant inverse association between coffee consumption and the incidence of gout (RR=0.43, 95% CI 0.31 to 0.59, p<0.001). Conclusions Current evidences are insufficient to validate the association between coffee consumption and a lower risk of HU. Owing to the limited number of studies, the available data show that coffee consumption may be associated with a lower risk of incident gout. Further well-designed prospective researches and randomised controlled trials are therefore needed to elaborate on these issues. PMID:27401353

Colorectal Specialization Increases Lymph Node Yield: Evidence from a National Database.

PubMed

Jeganathan, Arjun N; Shanmugan, Skandan; Bleier, Joshua I S; Hall, Glenn M; Paulson, Emily C

2016-07-01

Current guidelines recommend the evaluation of at least 12 lymph nodes (LNs) in the pathologic specimen following surgery for colorectal cancer (CRC). We sought to examine the role of colorectal specialization on nodal identification. We conducted a retrospective cohort study using SEER-Medicare data to examine the association between colorectal specialization and LN identification following surgery for colon and rectal adenocarcinoma between 2001 and 2009. Our dataset included patients >65 years who underwent surgical resection for CRC. We excluded patients with rectal cancer who had received neoadjuvant therapy. The primary outcome measure was the number of LNs identified in the pathologic specimen following surgery for CRC. Multivariate analysis was used to identify the association between surgical specialization and LN identification in the pathologic specimen. In multivariate analysis, odds of an adequate lymphadenectomy following surgery with a colorectal specialist were 1.32 and 1.41 times greater for colon and rectal cancer, respectively, than following surgery by a general surgeon (p < 0.001). These odds increased to 1.36 and 1.58, respectively, when analysis was limited to board-certified colorectal surgeons. Hospital factors associated with ≥12 LNs identified included high-volume CRC surgery (colon OR 1.84, p < 0.001; rectal OR 1.78, p < 0.001) and NCI-designated Cancer Centers (colon OR 1.75, p < 0.001; rectal OR 1.64; p = 0.007). Colorectal specialization and, in particular, board-certification in colorectal surgery, is significantly associated with increased LN identification following surgery for colon and rectal adenocarcinoma since the adoption of the 12-LN guideline in 2001.

Impact of social capital on psychological distress and interaction with house destruction and displacement after the Great East Japan Earthquake of 2011.

PubMed

Tsuchiya, Naho; Nakaya, Naoki; Nakamura, Tomohiro; Narita, Akira; Kogure, Mana; Aida, Jun; Tsuji, Ichiro; Hozawa, Atsushi; Tomita, Hiroaki

2017-01-01

Social capital has been considered an important factor affecting mental-health outcomes, such as psychological distress in post-disaster settings. Although disaster-related house condition and displacement could affect both social capital and psychological distress, limited studies have investigated interactions. This study aimed to examine the association between social capital and psychological distress, taking into consideration the interaction of disaster-related house condition after the Great East Japan Earthquake of 2011. Using data from 3793 adults living in Shichigahama, Miyagi Prefecture, Japan, we examined the association between social capital measured by generalized trust and psychological distress measured by the Kessler 6 scale. We conducted stratified analysis to investigate an interaction of house destruction and displacement. Multivariate analyses taking into consideration the interaction were performed. In the crude analysis, low social capital (odds ratio [OR] 4.46; 95% confidence interval [CI], 3.27-6.07) and large-scale house destruction (OR 1.96; 95%CI, 1.47-2.62) were significantly associated with psychological distress. Stratified analyses detected an interaction with house destruction and displacement (P for interaction = 0.04). Multivariate analysis with interaction term revealed that individuals with low social capital, large-scale house damage, and displacement were at greater risk of psychological distress, corresponding to adjusted OR of 5.78 (95%CI, 3.48-9.60). In the post-disaster setting, low social capital increased the risk of psychological distress, especially among individuals who had large-scale house destruction. Among the participants with severe disaster damage, high social capital would play an important role in protecting mental health. © 2016 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.

Metabolite profiling in Trigonella seeds via UPLC-MS and GC-MS analyzed using multivariate data analyses.

PubMed

Farag, Mohamed A; Rasheed, Dalia M; Kropf, Matthias; Heiss, Andreas G

2016-11-01

Trigonella foenum-graecum is a plant of considerable value for its nutritive composition as well as medicinal effects. This study aims to examine Trigonella seeds using a metabolome-based ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) in parallel to gas chromatography-mass spectrometry (GC-MS) coupled with multivariate data analyses. The metabolomic differences of seeds derived from three Trigonella species, i.e., T. caerulea, T. corniculata, and T. foenum-graecum, were assessed. Under specified conditions, we were able to identify 93 metabolites including 5 peptides, 2 phenolic acids, 22 C/O-flavonoid conjugates, 26 saponins, and 9 fatty acids using UPLC-MS. Several novel dipeptides, saponins, and flavonoids were found in Trigonella herein for the first time. Samples were classified via unsupervised principal component analysis (PCA) followed by supervised orthogonal projection to latent structures-discriminant analysis (OPLS-DA). A distinct separation among the investigated Trigonella species was revealed, with T. foenum-graecum samples found most enriched in apigenin-C-glycosides, viz. vicenins 1/3 and 2, compared to the other two species. In contrast to UPLC-MS, GC-MS was less efficient to classify specimens, with differences among specimens mostly attributed to fatty acyl esters. GC-MS analysis of Trigonella seed extracts led to the identification of 91 metabolites belonging mostly to fatty acyl esters, free fatty acids followed by organic acids, sugars, and amino acids. This study presents the first report on primary and secondary metabolite compositional differences among Trigonella seeds via a metabolomics approach and reveals that, among the species examined, the official T. foenum-graecum presents a better source of Trigonella secondary bioactive metabolites.

Association Between Severe Hypoglycemia and Cardiovascular Disease Risk in Japanese Patients With Type 2 Diabetes.

PubMed

Goto, Atsushi; Goto, Maki; Terauchi, Yasuo; Yamaguchi, Naohito; Noda, Mitsuhiko

2016-03-09

It remains unclear whether severe hypoglycemia is associated with cardiovascular disease (CVD) in Asian populations with type 2 diabetes (T2D). Furthermore, no study in Japan, where the prescription patterns differ from those in other countries, has examined this association. We retrospectively included 58 223 patients (18-74 years old) with T2D. First, we examined the potential predictors of severe hypoglycemia. Then, we investigated the association between severe hypoglycemia and CVD risk. Finally, we performed an updated systematic review and meta-analysis to incorporate our findings and recently published studies into the previous systematic review and meta-analysis. During 134 597 person-years from cumulative observation periods, 128 persons experienced severe hypoglycemia and 550 developed CVD events. In a multivariate Cox proportional hazard model, severe hypoglycemia was strongly and positively associated with the risk of CVD (multivariate-adjusted adjusted hazard ratio, 3.39; 95% CI, 1.25-9.18). In a propensity score-matched cohort that had similar baseline characteristics for patients with severe hypoglycemia and those without, severe hypoglycemia was more strongly associated with the risk of CVD. An updated systematic review and meta-analysis that included 10 studies found that severe hypoglycemia was associated with an ≈2-fold increased risk of CVD (pooled relative risk, 1.91; 95% CI, 1.69-2.15). Our results suggest that severe hypoglycemia is strongly associated with an increased risk of CVD in Japanese patients with T2D, further supporting the notion that avoiding severe hypoglycemia may be important in preventing CVD in this patient population. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

A first insight into high prevalence of undiagnosed smear-negative pulmonary tuberculosis in Northern Ethiopian prisons: implications for greater investment and quality control.

PubMed

Biadglegne, Fantahun; Rodloff, Arne C; Sack, Ulrich

2014-01-01

Tuberculosis (TB) transmission in prisons poses significant risks to inmates as well as the general population. Currently, there are no data on smear-negative pulmonary TB cases in prisons and by extension no data on the impact such cases have on TB incidence. This study was designed to obtain initial data on the prevalence of smear-negative cases of TB in prisons as well as preliminary risk factor analysis for such TB cases. This cross-sectional survey was conducted in November 2013 at eight main prisons located in the state of Amhara, Ethiopia. Interviews using a structured and pretested questionnaire were done first to identify symptomatic prisoners. Three consecutive sputum samples were collected and examined using acid fast bacilli (AFB) microscopy at the point of care. All smear-negative sputum samples were taken for culture and Xpert testing. Descriptive and multivariate analysis was done using SPSS version 16. Overall the prevalence of smear-negative pulmonary TB cases in the study prisons was 8% (16/200). Using multivariate analysis, a contact history to TB patients in prison, educational level, cough and night sweating were found to be predictors of TB positivity among smear-negative pulmonary TB cases (p ≤ 0.05). In the studied prisons, high prevalence of undiagnosed TB cases using AFB microscopy was documented, which is an important public health concern that urgently needs to be addressed. Furthermore, patients with night sweating, non-productive cough, a contact history with TB patients and who are illiterate merit special attention, larger studies are warranted in the future to assess the associations more precisely. Further studies are also needed to examine TB transmission dynamics by patients with smear-negative pulmonary TB in a prison setting.

Rhabdomyolysis among critically ill combat casualties: Associations with acute kidney injury and mortality.

PubMed

Stewart, Ian J; Faulk, Tarra I; Sosnov, Jonathan A; Clemens, Michael S; Elterman, Joel; Ross, James D; Howard, Jeffrey T; Fang, Raymond; Zonies, David H; Chung, Kevin K

2016-03-01

Rhabdomyolysis has been associated with poor outcomes in patients with traumatic injury, especially in the setting of acute kidney injury (AKI). However, rhabdomyolysis has not been systematically examined in a large cohort of combat casualties injured in the wars in Iraq and Afghanistan. We conducted a retrospective study of casualties injured during combat operations in Iraq and Afghanistan who were initially admitted to the intensive care unit from February 1, 2002, to February 1, 2011. Information on age, sex, Abbreviated Injury Scale (AIS) score, Injury Severity Score (ISS), mechanism of injury, shock index, creatine kinase, and serum creatinine were collected. These variables were examined via multivariate logistic and Cox regression analyses to determine factors independently associated with rhabdomyolysis, AKI, and death. Of 6,011 admissions identified, a total of 2,109 patients met inclusion criteria and were included for analysis. Rhabdomyolysis, defined as creatine kinase greater than 5,000 U/L, was present in 656 subjects (31.1%). Risk factors for rhabdomyolysis identified on multivariable analysis included injuries to the abdomen and extremities, increased ISS, male sex, explosive mechanism of injury, and shock index greater than 0.9. After adjustment, patients with rhabdomyolysis had a greater than twofold increase in the odds of AKI. In the analysis for mortality, rhabdomyolysis was significantly associated with death until AKI was added, at which point it lost statistical significance. We found that rhabdomyolysis is associated with the development of AKI in combat casualties. While rhabdomyolysis was strongly associated with mortality on the univariate model and in conjunction with both ISS and age, it was not associated with mortality after the inclusion of AKI. This suggests that the effect of rhabdomyolysis on mortality may be mediated by AKI. Prognostic and epidemiologic study, level III.

Stochastic univariate and multivariate time series analysis of PM2.5 and PM10 air pollution: A comparative case study for Plovdiv and Asenovgrad, Bulgaria

NASA Astrophysics Data System (ADS)

Gocheva-Ilieva, S.; Stoimenova, M.; Ivanov, A.; Voynikova, D.; Iliev, I.

2016-10-01

Fine particulate matter PM2.5 and PM10 air pollutants are a serious problem in many urban areas affecting both the health of the population and the environment as a whole. The availability of large data arrays for the levels of these pollutants makes it possible to perform statistical analysis, to obtain relevant information, and to find patterns within the data. Research in this field is particularly topical for a number of Bulgarian cities, European country, where in recent years regulatory air pollution health limits are constantly being exceeded. This paper examines average daily data for air pollution with PM2.5 and PM10, collected by 3 monitoring stations in the cities of Plovdiv and Asenovgrad between 2011 and 2016. The goal is to find and analyze actual relationships in data time series, to build adequate mathematical models, and to develop short-term forecasts. Modeling is carried out by stochastic univariate and multivariate time series analysis, based on Box-Jenkins methodology. The best models are selected following initial transformation of the data and using a set of standard and robust statistical criteria. The Mathematica and SPSS software were used to perform calculations. This examination showed measured concentrations of PM2.5 and PM10 in the region of Plovdiv and Asenovgrad regularly exceed permissible European and national health and safety thresholds. We obtained adequate stochastic models with high statistical fit with the data and good quality forecasting when compared against actual measurements. The mathematical approach applied provides an independent alternative to standard official monitoring and control means for air pollution in urban areas.

Power analysis for multivariate and repeated measures designs: a flexible approach using the SPSS MANOVA procedure.

PubMed

D'Amico, E J; Neilands, T B; Zambarano, R

2001-11-01

Although power analysis is an important component in the planning and implementation of research designs, it is often ignored. Computer programs for performing power analysis are available, but most have limitations, particularly for complex multivariate designs. An SPSS procedure is presented that can be used for calculating power for univariate, multivariate, and repeated measures models with and without time-varying and time-constant covariates. Three examples provide a framework for calculating power via this method: an ANCOVA, a MANOVA, and a repeated measures ANOVA with two or more groups. The benefits and limitations of this procedure are discussed.

Comparison of a clinical gait analysis method using videography and temporal-distance measures with 16-mm cinematography.

PubMed

Stuberg, W A; Colerick, V L; Blanke, D J; Bruce, W

1988-08-01

The purpose of this study was to compare a clinical gait analysis method using videography and temporal-distance measures with 16-mm cinematography in a gait analysis laboratory. Ten children with a diagnosis of cerebral palsy (means age = 8.8 +/- 2.7 years) and 9 healthy children (means age = 8.9 +/- 2.4 years) participated in the study. Stride length, walking velocity, and goniometric measurements of the hip, knee, and ankle were recorded using the two gait analysis methods. A multivariate analysis of variance was used to determine significant differences between the data collected using the two methods. Pearson product-moment correlation coefficients were determined to examine the relationship between the measurements recorded by the two methods. The consistency of performance of the subjects during walking was examined by intraclass correlation coefficients. No significant differences were found between the methods for the variables studied. Pearson product-moment correlation coefficients ranged from .79 to .95, and intraclass coefficients ranged from .89 to .97. The clinical gait analysis method was found to be a valid tool in comparison with 16-mm cinematography for the variables that were studied.

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

DTIC Science & Technology

1982-12-20

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

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

NASA Astrophysics Data System (ADS)

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

2008-05-01

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

SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

EPA Science Inventory

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

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

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

2015-01-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-10-15

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

Interactions and accumulation differences of metal(loid)s in three sea cucumber species collected from the Northern Mediterranean Sea.

PubMed

Tunca, Evren; Aydın, Mehmet; Şahin, ÜlküAlver

2016-10-01

This study was conducted on Holothuria polii, Holothuria tubulosa, and Holothuria mammata collected from five stations with different depths in the Northern Mediterranean Sea. The body walls and guts of these holothurians were examined in terms of interactions of 10 metals (iron (Fe), copper (Cu), manganese (Mn), zinc (Zn), chromium (Cr), cobalt (Co), vanadium (V), nickel (Ni), cadmium (Cd), and lead (Pb)) and one metalloid (arsenic (As)) using a multivariate analysis, and interspecies differences were determined. The multivariate analysis of variance (MANOVA) revealed significant differences between the species in terms of metal(loid) accumulations. The principal component analysis (PCA) showed a more association between H. tubulosa and H. polii with regard to the accumulation. The cluster analysis (CA) located Pb concentrations of the guts to the farthest place from all elements regardless of the species. A correlation analysis displayed that the element concentrations of the guts were more closely related to each other compared with those of the walls. The most inconsistent element in terms of correlations was the gut Fe contents. Accordingly, while Fe concentrations of H. mammata and H. tubulosa were correlated with all elements (except Pb) in divalent metal transporter 1 (DMT1) (divalent cation transporter 1 (DCT1) or natural resistance-associated macrophage protein 2 (NRAMP2)) belonging to the NRAM protein family, this was not the case in H. polii. Consequently, significant relationships between accumulated metal(loid)s that changed by tissues and sea cucumber species were observed.

Seasonal and habitat abundance and distribution of some forensically important blow flies (Diptera: Calliphoridae) in Central California.

PubMed

Brundage, Adrienne; Bros, Shannon; Honda, Jeffrey Y

2011-10-10

Seasonal and habitat calliphorid abundance and distribution were examined weekly for two years (2001-2003) in Santa Clara County, California, using sentinel traps baited with bovine liver. Of the 34,389 flies examined in three defined habitats (rural, urban, and riparian), 38% of the total catch represented Compsomyiops callipes (Bigot) and 23% represented Phormia regina (Meigen). Other flies collected in this survey included Calliphora vomitoria (Linnaeus), Calliphora latifrons (Hough), Lucilia sericata (Meigen), Lucilia cuprina (Wiedemann), and Lucilia mexicana (Macquart), which is a new record for the area. Multivariate MANOVA and ANOVA (P ≤ 0.05) analysis indicate significant seasonal habitat preference for all fly species examined. This information may be used to identify potentially forensically impo rtant fly species within Santa Clara County, California. Published by Elsevier Ireland Ltd.

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

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

Loveday, D.L.; Craggs, C.

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

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

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

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

Loneliness in Men 60 Years and Over: The Association With Purpose in Life.

PubMed

Neville, Stephen; Adams, Jeffery; Montayre, Jed; Larmer, Peter; Garrett, Nick; Stephens, Christine; Alpass, Fiona

2018-07-01

Loneliness as a consequence of getting older negatively impacts on the health and well-being of men as they age. Having a purpose in life may mitigate loneliness and therefore positively impact on health and well-being. Limited research into loneliness and purpose in life has been undertaken in older men. This study seeks to understand the relationship between loneliness and purpose in life in a group of older men. Using data from a cross-sectional survey of 614 men aged 60 years and over living in New Zealand, bivariate and multivariate analyses were undertaken to examine the relationship between loneliness and purpose in life using a range of demographic, health, and social connection variables. Bivariate analysis revealed that being unpartnered and having low socioeconomic status, limited social networks, low levels of participation, and mental health issues were associated with loneliness. Multivariate analysis showed that having poor mental health and lower purpose in life were indicators of loneliness. Consequently, improving mental health and purpose in life are likely to reduce loneliness in at-risk older men. As older men are a heterogeneous group from a variety of sociocultural and ethnic backgrounds, a multidimensional approach to any intervention initiatives needs to occur.

Trends in Fatalities From Distracted Driving in the United States, 1999 to 2008

PubMed Central

Stimpson, Jim P.

2010-01-01

Objectives. We examined trends in distracted driving fatalities and their relation to cell phone use and texting volume. Methods. The Fatality Analysis Reporting System (FARS) records data on all road fatalities that occurred on public roads in the United States from 1999 to 2008. We studied trends in distracted driving fatalities, driver and crash characteristics, and trends in cell phone use and texting volume. We used multivariate regression analysis to estimate the relation between state-level distracted driving fatalities and texting volumes. Results. After declining from 1999 to 2005, fatalities from distracted driving increased 28% after 2005, rising from 4572 fatalities to 5870 in 2008. Crashes increasingly involved male drivers driving alone in collisions with roadside obstructions in urban areas. By use of multivariate analyses, we predicted that increasing texting volumes resulted in more than 16 000 additional road fatalities from 2001 to 2007. Conclusions. Distracted driving is a growing public safety hazard. Specifically, the dramatic rise in texting volume since 2005 appeared to be contributing to an alarming rise in distracted driving fatalities. Legislation enacting texting bans should be paired with effective enforcement to deter drivers from using cell phones while driving. PMID:20864709

Trends in fatalities from distracted driving in the United States, 1999 to 2008.

PubMed

Wilson, Fernando A; Stimpson, Jim P

2010-11-01

We examined trends in distracted driving fatalities and their relation to cell phone use and texting volume. The Fatality Analysis Reporting System (FARS) records data on all road fatalities that occurred on public roads in the United States from 1999 to 2008. We studied trends in distracted driving fatalities, driver and crash characteristics, and trends in cell phone use and texting volume. We used multivariate regression analysis to estimate the relation between state-level distracted driving fatalities and texting volumes. After declining from 1999 to 2005, fatalities from distracted driving increased 28% after 2005, rising from 4572 fatalities to 5870 in 2008. Crashes increasingly involved male drivers driving alone in collisions with roadside obstructions in urban areas. By use of multivariate analyses, we predicted that increasing texting volumes resulted in more than 16,000 additional road fatalities from 2001 to 2007. Distracted driving is a growing public safety hazard. Specifically, the dramatic rise in texting volume since 2005 appeared to be contributing to an alarming rise in distracted driving fatalities. Legislation enacting texting bans should be paired with effective enforcement to deter drivers from using cell phones while driving.

Multiscale entropy analysis of biological signals: a fundamental bi-scaling law

PubMed Central

Gao, Jianbo; Hu, Jing; Liu, Feiyan; Cao, Yinhe

2015-01-01

Since introduced in early 2000, multiscale entropy (MSE) has found many applications in biosignal analysis, and been extended to multivariate MSE. So far, however, no analytic results for MSE or multivariate MSE have been reported. This has severely limited our basic understanding of MSE. For example, it has not been studied whether MSE estimated using default parameter values and short data set is meaningful or not. Nor is it known whether MSE has any relation with other complexity measures, such as the Hurst parameter, which characterizes the correlation structure of the data. To overcome this limitation, and more importantly, to guide more fruitful applications of MSE in various areas of life sciences, we derive a fundamental bi-scaling law for fractal time series, one for the scale in phase space, the other for the block size used for smoothing. We illustrate the usefulness of the approach by examining two types of physiological data. One is heart rate variability (HRV) data, for the purpose of distinguishing healthy subjects from patients with congestive heart failure, a life-threatening condition. The other is electroencephalogram (EEG) data, for the purpose of distinguishing epileptic seizure EEG from normal healthy EEG. PMID:26082711

A multivariate analysis of prognostic factors for melanoma patients with lesions greater than or equal to 3.65 mm in thickness. The importance of revealing alternative Cox models.

PubMed Central

Day, C L; Lew, R A; Mihm, M C; Sober, A J; Harris, M N; Kopf, A W; Fitzpatrick, T B; Harrist, T J; Golomb, F M; Postel, A; Hennessey, P; Gumport, S L; Raker, J W; Malt, R A; Cosimi, A B; Wood, W C; Roses, D F; Gorstein, F; Rigel, D; Friedman, R J; Mintzis, M M; Grier, R W

1982-01-01

Fourteen prognostic factors were examined in 79 patients with clinical Stage I melanoma greater than or equal to 3.65 mm in thickness. All nine patients with melanoma of the hands or feet died of melanoma. A Cox proportional hazards (multivariate) analysis of the remaining 70 patients showed that a combination of the following four variables best predicted bony or visceral metastases: 1) a nearly absent or minimal lymphocyte response at the base of the tumor, 2) histologic type other than superficial spreading melanoma, 3) location on the trunk, and 4) positive nodes or no initial node dissection. Ulceration and/or ulceration width were not useful in predicting outcome either singly or in combination with other variables. Patients with negative lymph nodes and primary tumors of the trunk, hands, and feet did not do better than patients with positive nodes at those sites. Conversely, non of 16 patients with negative lymph nodes and extremity melanomas (excluding the hands and feet) or head and neck melanomas developed visceral or bony metastases (i.e., five-year disease-free survival rate 100%). PMID:7055383

Impact of interleukin-10 polymorphisms (-1082 and -3575) on the survival of patients with lymphoid neoplasms.

PubMed

Domingo-Domènech, Eva; Benavente, Yolanda; González-Barca, Eva; Montalban, Carlos; Gumà, Josep; Bosch, Ramón; Wang, Sophia S; Lan, Qing; Whitby, Denise; Fernández de Sevilla, Alberto; Rothman, Nathaniel; de Sanjosé, Sílvia

2007-11-01

Single-nucleotide polymorphisms (SNP) in interleukin-10 (IL-10) genes can influence immune responses, which may affect the outcome of patients with lymphoid neoplasms. The aim of this study was to explore the association between polymorphisms of IL-10-(1082A>G) and IL-10-(3575T>A) with the overall survival in patients with lymphoid neoplasms. We analyzed two IL-10 SNP (-1082 and -3575) in 472 consecutive cases with lymphoid neoplasms. Genotypes were tested for association with overall survival and classical prognostic factors by multivariate analysis. Haplotype analysis was carried out using the haplostats package implemented in R software. The implications for survival of patients with lymphoma were evaluated using multivariate analysis. Lymphoma patients with the IL-10-(3575T>A) genotype had a better overall survival (p= 0.002), as did the subgroup with non-Hodgkin's lymphoma (NHL) (p=0.05). Patients with the IL10(-1082GG) genotype had a better median overall survival (p=0.05). When both genotypes were included in a multivariate analysis, IL-10(-3575AA) genotype was the only independent prognostic factor for survival (HR=0.20, 95%CI 0.05-0.92). Patients with the IL-10(-1082) and (-3575) G-A/G-A diplotype had a longer overall survival (p=0.003) and this combination appeared to be an independent prognostic factor for survival (HR:0.26; 95%CI 0.08-0.83). The IL-10(-3575A/A) genotype was identified as a marker of favorable survival. Because the IL-10(-1082) and (-3575) G-A/G-A diplotype was also identified as an indicator of longer survival, we cannot exclude the potential additive role of the IL-10(-1082GG) genotype. These results need to be replicated in larger series and examined in different NHL subtypes.

Regular sugar-sweetened beverage consumption between meals increases risk of overweight among preschool-aged children.

PubMed

Dubois, Lise; Farmer, Anna; Girard, Manon; Peterson, Kelly

2007-06-01

To examine the relationship between consumption of sugar-sweetened beverages (eg, nondiet carbonated drinks and fruit drinks) and the prevalence of overweight among preschool-aged children living in Canada. Data come from the Longitudinal Study of Child Development in Québec (1998-2002). A representative sample (n=2,103) of children born in 1998 in Québec, Canada. A total of 1,944 children (still representative of the same-age children in this population) remaining at 4 to 5 years in 2002 participated in the nutrition study. Data were collected via 24-hour dietary recall interview. Frequency of sugar-sweetened beverage consumption between meals at age 2.5, 3.5, and 4.5 years was recorded and children's height and weight were measured. Multivariate regression analysis was done with Statistical Analysis System software. Weighted data were adjusted for within-child variability and significance level was set at 5%. Overall, 6.9% of children who were nonconsumers of sugar-sweetened beverages between meals between the ages of 2.5 to 4.5 years were overweight at 4.5 years, compared to 15.4% of regular consumers (four to six times or more per week) at ages 2.5 years, 3.5 years, and 4.5 years. According to multivariate analysis, sugar-sweetened beverage consumption between meals more than doubles the odds of being overweight when other important factors are considered in multivariate analysis. Children from families with insufficient income who consume sugar-sweetened beverages regularly between the ages of 2.5 and 4.5 years are more than three times more likely to be overweight at age 4.5 years compared to nonconsuming children from sufficient income households. Regular sugar-sweetened beverage consumption between meals may put some young children at a greater risk for overweight. Parents should limit the quantity of sweetened beverages consumed during preschool years because it may increase propensity to gain weight.

Stereotactic Body Radiation Therapy and the Influence of Chemotherapy on Overall Survival for Large (≥5 Centimeter) Non-Small Cell Lung Cancer

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

Verma, Vivek; McMillan, Matthew T.; Grover, Surbhi

2017-01-01

Purpose: Stereotactic body radiation therapy (SBRT) for ≥5 cm lesions is poorly defined, largely owing to the low sample sizes in existing studies. The present analysis examined the SBRT outcomes and assessed the effect of chemotherapy in this population. Methods and Materials: The National Cancer Data Base was queried for primary non-small cell lung cancer ≥5 cm treated with SBRT (≤10 fractions). Patient, tumor, and treatment parameters were extracted. The primary outcome was overall survival (OS). Statistical methods involved Kaplan-Meier analysis and multivariable Cox proportional hazards modeling. Results: From 2004 to 2012, data from 201 patients were analyzed. The median follow-upmore » was 41.1 months. The median tumor size was 5.5 cm (interquartile range 5.0-6.0), with cT2a, cT2b, and cT3 disease in 24.9%, 53.2%, and 21.9%, respectively. The median total SBRT dose and fractionation was 50 Gy in 4 fractions, and 92.5% of the patients underwent SBRT with ≤5 fractions. The median OS was 25.1 months. Of the 201 patients, 15% received chemotherapy. The receipt of chemotherapy was associated with longer OS (median 30.6 vs 23.4 months; P=.027). On multivariable analysis, worse OS was seen with increasing age (hazard ratio [HR] 1.03; P=.012), poorly differentiated tumors (HR 2.06; P=.049), and T3 classification (HR 2.13; P=.005). On multivariable analysis, chemotherapy remained independently associated with improved OS (HR 0.57; P=.039). Conclusions: SBRT has utility in the setting of tumors ≥5 cm, with chemotherapy associated with improved OS in this subset. These hypothesis-generating data now raise the necessity of performing prospective analyses to determine whether chemotherapy confers outcome benefits after SBRT.« less

Syringe Disposal Among Injection Drug Users in San Francisco

PubMed Central

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

2011-01-01

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

Exploring the effects of tape-recording on personality assessment.

PubMed

Lichton, A I; Waehler, C A

1999-06-01

This study examined the possible influence of audio and video recording of personality assessment measures on anxiety. Undergraduate students in psychology were randomly assigned to Audiotape, Videotape, or Control conditions and given the State-Trait Anxiety Inventory and Rorschach Inkblot Method. A one-way multivariate analysis of variance indicated no significant differences among these conditions on the Spielberger, et al. State-Trait Anxiety Inventory, A-State scale, and five Rorschach measures of situational anxiety. Tape-recording itself did not seem to affect the anxiety indices of these frequently used personality assessments.

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

PubMed

Miah, M M

1993-01-01

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

Horabagrus melanosoma: a junior synonym of Horabagrus brachysoma (Teleostei: Horabagridae).

PubMed

Ali, Anvar; Katwate, Unmesh; Philip, Siby; Dhaneesh, K V; Bijukumar, A; Raghavan, Rajeev; Dahanukar, Neelesh

2014-11-06

Horabagrus melanosoma was described from West Venpala in the lower reaches of the Manimala River, in the state of Kerala, India. It was distinguished from its nearest congener, H. brachysoma based on a combination of characters including darker body colour, shorter pelvic fin and greater number of anal fin rays. Examination of the type material revealed significant morphometric and meristic discrepancies with the original description. Based on multivariate morphometric, and genetic analysis of topotypical specimens, we propose that H. melanosoma should be treated as a junior synonym of H. brachysoma.

Calibrating the ChemCam LIBS for Carbonate Minerals on Mars

DOE R&D Accomplishments Database

Wiens, Roger C.; Clegg, Samuel M.; Ollila, Ann M.; Barefield, James E.; Lanza, Nina; Newsom, Horton E.

2009-01-01

The ChemCam instrument suite on board the NASA Mars Science Laboratory (MSL) rover includes the first LIBS instrument for extraterrestrial applications. Here we examine carbonate minerals in a simulated martian environment using the LIDS technique in order to better understand the in situ signature of these materials on Mars. Both chemical composition and rock type are determined using multivariate analysis (MVA) techniques. Composition is confirmed using scanning electron microscopy (SEM) techniques. Our initial results suggest that ChemCam can recognize and differentiate between carbonate materials on Mars.

IMPACT OF PHYSICIAN COMMUNICATION ON DIABETIC EYE EXAMINATION ADHERENCE: Results From a Retrospective Cohort Analysis.

PubMed

Storey, Philip P; Murchison, Ann P; Pizzi, Laura T; Hark, Lisa A; Dai, Yang; Leiby, Benjamin E; Haller, Julia A

2016-01-01

To evaluate the effect of written communication between an ophthalmologist and a primary care physician (PCP) on patient adherence to diabetic eye examination recommendations. In a retrospective cohort study of a multiethnic population at an urban ophthalmology center, records of all patients with diabetes and clinic visits between 2007 and 2010 were reviewed. Data collected included patient demographics, insurance status, hemoglobin A1C, severity of diabetic retinopathy, follow-up examinations, and written communication between a patient's ophthalmologist and PCP. Statistical analyses were performed to examine the relationship between physician communication and adherence to diabetic eye examination based on the American Academy of Ophthalmology-published recommendations. A total of 1,968 people with diabetes were included. Written communication from an ophthalmologist to a PCP was associated with increased adherence to follow-up eye examination recommendations (Odds Ratio: 1.49; 95% Confidence Interval: 1.16-1.92; P = 0.0018). Communication from a PCP to an ophthalmologist was also associated with increased adherence (Odds Ratio: 1.94; 95% Confidence Interval: 1.37-2.77; P = 0.0002). Multivariable analysis controlling for other factors associated with examination adherence confirmed that communication both to and from an ophthalmologist was independently and significantly associated with increased follow-up adherence. Patients with communication between ophthalmologists and PCPs are more likely to adhere to diabetic eye examinations.

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

PubMed

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

2015-11-04

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

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

ERIC Educational Resources Information Center

Bejar, Isaac I.

1981-01-01

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

A Multivariate Descriptive Model of Motivation for Orthodontic Treatment.

ERIC Educational Resources Information Center

Hackett, Paul M. W.; And Others

1993-01-01

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

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

ERIC Educational Resources Information Center

Grundmann, Matthias

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

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

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

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

Evaluation of Meterorite Amono Acid Analysis Data Using Multivariate Techniques

NASA Technical Reports Server (NTRS)

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

1999-01-01

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

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

EPA Science Inventory

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

Informing Federal Policy on Firearm Restrictions for Veterans with Fiduciaries: Risk Indicators in the Post-Deployment Mental Health Study.

PubMed

Swanson, Jeffrey; Easter, Michele; Brancu, Mira; Fairbank, John A

2018-05-24

This article examines the public safety rationale for a federal policy of prohibiting gun sales to veterans with psychiatric disabilities who are assigned a fiduciary to manage their benefits from the Department of Veterans Affairs. The policy was evaluated using data on 3200 post-deployment veterans from the Iraq and Afghanistan war era. Three proxy measures of fiduciary need-based on intellectual disability, drug abuse, or acute psychopathology-were associated in bivariate analysis with interpersonal violence and suicidality. In multivariate analysis, statistical significance remained only for the measure based on acute psychopathology. Implications for reforms to the fiduciary firearm restriction policy are discussed.

Characteristics associated with low self-esteem among US adolescents.

PubMed

McClure, Auden C; Tanski, Susanne E; Kingsbury, John; Gerrard, Meg; Sargent, James D

2010-01-01

Low self-esteem in adolescents has been associated with a number of risk and protective factors in previous studies, but results have been mixed. Our objective was to examine characteristics associated with low self-esteem in a large national sample of young adolescents. We conducted a population-based correlational study. A sample of 6522 adolescents aged 12 to 16 years was surveyed by phone as part of a national study of media and substance use. Self-esteem was measured with 3 questions that assessed global self-worth and physical appearance. Multivariate logistic regression was used to examine the relationship between self-esteem and sociodemographics, child personality characteristics,weight status, daily TV time, parenting style, school performance,and team sports participation. Interactions among gender, race, and weight status were examined. In multivariate analysis, female gender, Hispanic race, overweight and obesity, sensation seeking, rebelliousness, and daily TV time were each independently associated with lower self-esteem. Teens of black race, with higher parental responsiveness and demandingness, better school performance, or involvement in team sports were less likely to report low self-esteem. Black females were at lower risk and Hispanic males were at higher risk for low esteem than peers of similar gender of other races. Low self-esteem was associated with a number of modifiable risk factors, including obesity, TV time, team sports participation, school performance, and parenting style, that should be discussed with teens and parents at health supervision visits. Further research examining race and gender-specific factors that serve to moderate risk for poor self-esteem in adolescents is warranted.

Characteristics Associated with Low Self-esteem among U.S. Adolescents

PubMed Central

McClure, Auden C.; Tanski, Susanne E.; Kingsbury, John; Gerrard, Meg; Sargent, James D.

2010-01-01

Objective Low self-esteem in adolescents has been associated with a number of risk and protective factors in previous studies, but results have been mixed. Our objective was to examine characteristics associated with low self-esteem in a large national sample of young adolescents. Design/Methods Population-based correlational study. A sample of 6522 adolescents, aged 12-16 years, was surveyed by phone as part of a national study of media and substance use. Self-esteem was measured with three questions that assessed global self worth and physical appearance. Multivariate logistic regression was used to examine the relation between self-esteem and socio-demographics, child personality characteristics, weight status, daily TV time, parenting style, school performance and team sports participation. Interactions among gender, race, and weight status were examined. Results In multivariate analysis, female gender, Hispanic race, overweight and obesity, sensation seeking, rebelliousness, and daily TV time were each independently associated with lower self-esteem. Teens of Black race, with higher parental responsiveness and demandingness, better school performance or involvement in team sports were less likely to report low self-esteem. Black females were at lower risk and Hispanic males were at higher risk for low esteem than peers of similar gender of other races. Conclusions Low self-esteem was associated with a number of modifiable risk factors including obesity, television time, team sports participation, school performance and parenting style that should be discussed with teens and parents at health supervision visits. Further research examining race and gender-specific factors that serve to moderate risk for poor self-esteem in adolescents is warranted. PMID:20605547

Proteinuria is associated with neurocognitive impairment in antiretroviral therapy treated HIV-infected individuals.

PubMed

Kalayjian, Robert C; Wu, Kunling; Evans, Scott; Clifford, David B; Pallaki, Muraldihar; Currier, Judith S; Smryzynski, Marlene

2014-09-01

Proteinuria is a marker of vascular dysfunction that predicted increased cardiovascular mortality and is associated with neurocognitive impairment (NCI) in population-based studies. We examined associations between proteinuria and HIV-associated NCI. Multivariable logistic regression was used to examine associations between NCI at the first neurocognitive assessment (baseline) and simultaneous, clinically significant proteinuria [as random spot urine protein-to-creatinine ratios (UP/Cr) ≥200 mg/g] in a prospective multicenter observational cohort study. Generalized estimating equations were used to examine associations between baseline proteinuria and subsequent NCI among subjects without NCI at baseline. NCI was defined as a Z-score, derived from the combination of normalized scores from the Trailmaking A and B and the Wechsler Adult Intelligence Scale-Revised Digit Symbol tests. A total of 1972 subjects were included in this analysis. Baseline proteinuria was associated with increased odds of NCI [odds ratio (OR): 1.41, 95% confidence interval (CI): 1.08 to 1.85; P = 0.01] and with subsequent NCI among subjects without NCI at baseline (OR: 1.39, 95% CI: 1.01 to 1.93; P = 0.046) in multivariable models adjusted for risk factors and potential confounders. Similar associations were evident when these analyses were limited to visits at which time study subjects maintained plasma HIV RNA levels <200 copies per milliliter. The association between proteinuria and NCI observed in this study adds to a growing body of evidence implicating contributions by vascular disease to NCI in antiretroviral treated individuals. Studies examining interventions that improve vascular function are warranted.

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.

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals

PubMed Central

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-01-01

Abstract Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals. To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors. A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis. The application rates of Kaplan–Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate, misleading of the reported results, or difficult to interpret. There are gaps in the conduct and reporting of survival analysis in studies published in Chinese oncology journals, severe deficiencies were noted. More endorsement by journals of the report guideline for survival analysis may improve articles quality, and the dissemination of reliable evidence to oncology clinicians. We recommend authors, readers, reviewers, and editors to consider survival analysis more carefully and cooperate more closely with statisticians and epidemiologists. PMID:29390340

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

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

Mouse allergen, lung function, and atopy in Puerto Rican children.

PubMed

Forno, Erick; Cloutier, Michelle M; Datta, Soma; Paul, Kathryn; Sylvia, Jody; Calvert, Deanna; Thornton-Thompson, Sherell; Wakefield, Dorothy B; Brehm, John; Hamilton, Robert G; Alvarez, María; Colón-Semidey, Angel; Acosta-Pérez, Edna; Canino, Glorisa; Celedón, Juan C

2012-01-01

To examine the relation between mouse allergen exposure and asthma in Puerto Rican children. Mus m 1, Der p 1, Bla g 2, and Fel d 1 allergens were measured in dust samples from homes of Puerto Rican children with (cases) and without (controls) asthma in Hartford, CT (n = 449) and San Juan (SJ), Puerto Rico (n = 678). Linear or logistic regression was used for the multivariate analysis of mouse allergen (Mus m 1) and lung function (FEV(1) and FEV(1)/FVC) and allergy (total IgE and skin test reactivity (STR) to ≥1 allergen) measures. Homes in SJ had lower mouse allergen levels than those in Hartford. In multivariate analyses, mouse allergen was associated with higher FEV(1) in cases in Hartford (+70.6 ml, 95% confidence interval (CI) = 8.6-132.7 ml, P = 0.03) and SJ (+45.1 ml, 95% CI =  -0.5 to 90.6 ml, P = 0.05). In multivariate analyses of controls, mouse allergen was inversely associated with STR to ≥1 allergen in non-sensitized children (odds ratio [OR] for each log-unit increment in Mus m 1 = 0.7, 95% CI = 0.5-0.9, P<0.01). In a multivariate analysis including all children at both study sites, each log-increment in mouse allergen was positively associated with FEV(1) (+28.3 ml, 95% CI = 1.4-55.2 ml, P = 0.04) and inversely associated with STR to ≥1 allergen (OR for each log-unit increment in Mus m 1 = 0.8, 95% CI = 0.6-0.9, P<0.01). Mouse allergen is associated with a higher FEV(1) and lower odds of STR to ≥1 allergen in Puerto Rican children. This may be explained by the allergen itself or correlated microbial exposures.

Mouse Allergen, Lung Function, and Atopy in Puerto Rican Children

PubMed Central

Forno, Erick; Cloutier, Michelle M.; Datta, Soma; Paul, Kathryn; Sylvia, Jody; Calvert, Deanna; Thornton-Thompson, Sherell; Wakefield, Dorothy B.; Brehm, John; Hamilton, Robert G.; Alvarez, María; Colón-Semidey, Angel; Acosta-Pérez, Edna; Canino, Glorisa; Celedón, Juan C.

2012-01-01

Objective To examine the relation between mouse allergen exposure and asthma in Puerto Rican children. Methods Mus m 1, Der p 1, Bla g 2, and Fel d 1 allergens were measured in dust samples from homes of Puerto Rican children with (cases) and without (controls) asthma in Hartford, CT (n = 449) and San Juan (SJ), Puerto Rico (n = 678). Linear or logistic regression was used for the multivariate analysis of mouse allergen (Mus m 1) and lung function (FEV1 and FEV1/FVC) and allergy (total IgE and skin test reactivity (STR) to ≥1 allergen) measures. Results Homes in SJ had lower mouse allergen levels than those in Hartford. In multivariate analyses, mouse allergen was associated with higher FEV1 in cases in Hartford (+70.6 ml, 95% confidence interval (CI) = 8.6–132.7 ml, P = 0.03) and SJ (+45.1 ml, 95% CI =  −0.5 to 90.6 ml, P = 0.05). In multivariate analyses of controls, mouse allergen was inversely associated with STR to ≥1 allergen in non-sensitized children (odds ratio [OR] for each log-unit increment in Mus m 1 = 0.7, 95% CI = 0.5–0.9, P<0.01). In a multivariate analysis including all children at both study sites, each log-increment in mouse allergen was positively associated with FEV1 (+28.3 ml, 95% CI = 1.4–55.2 ml, P = 0.04) and inversely associated with STR to ≥1 allergen (OR for each log-unit increment in Mus m 1 = 0.8, 95% CI = 0.6–0.9, P<0.01). Conclusions Mouse allergen is associated with a higher FEV1 and lower odds of STR to ≥1 allergen in Puerto Rican children. This may be explained by the allergen itself or correlated microbial exposures. PMID:22815744

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.

Exploring Radiotherapy Targeting Strategy and Dose: A Pooled Analysis of Cooperative Group Trials of Combined Modality Therapy for Stage III Non-Small Cell Lung Cancer.

PubMed

Schild, Steven E; Fan, Wen; Stinchcombe, Thomas E; Vokes, Everett E; Ramalingam, Suresh S; Bradley, Jeffrey D; Kelly, Karen; Pang, Herbert H; Wang, Xiaofei

2018-04-21

Concurrent chemoradiotherapy(CRT) is standard therapy for locally-advanced non-small-cell lung cancer(LA-NSCLC)patients. This study was performed to examine thoracic radiotherapy(TRT) parameters and their impact on patient survival. We collected Individual patient data(IPD) from 3600LA-NSCLC patients participating in 16 cooperative group trials of concurrent CRT. The primary TRT parameters examined included field design strategy(elective nodal irradiation(ENI) compared to involved field TRT(IF-TRT)), total dose, and biologically effective dose(BED). Hazard ratios(HRs) for overall survival were calculated with univariable and multivariable Cox models. TRT doses ranged from 60 to 74 Gy with most treatments administered once-daily. ENI was associated with poorer survival than IF-TRT(univariable HR,1.37;95%CI,1.24-1.51,p<0.0001;multivariable HR,1.31;95%CI,1.08-1.59,p=0.002). The median survival of the IF and ENI patients were 24 and 16 months, respectively. Patients were divided into 3 dose groups: low total dose(60 Gy), medium total dose(>60Gy-66Gy) and high total dose(>66Gy-74 Gy). With reference to the low dose group, the multivariable HR's were 1.08 for the medium dose group(95%CI=0.93-1.25) and 1.12 for the high dose group(CI=0.97-1.30).The univariate p=0.054 and multivariable p=0.17. BED was grouped as follows: low(<55.5Gy 10 ), medium(=55.5 Gy 10) , or high(>55.5 Gy 10 ). With reference to the low BED group, the HR was 1.00(95%CI=0.85-1.18) for the medium BED group and 1.10(95%CI=0.93-1.31) for the high BED group. The univariable p=0.076 and multivariable p=0.16. For LA-NSCLC patients treated with concurrent CRT, IF-TRT was associated with significantly better survival than ENI-TRT. TRT total and BED dose levels were not significantly associated with patient survival. Future progress will require research focusing on better systemic therapy and TRT. Copyright © 2018. Published by Elsevier Inc.

The influence of television and video game use on attention and school problems: a multivariate analysis with other risk factors controlled.

PubMed

Ferguson, Christopher J

2011-06-01

Research on youth mental health has increasingly indicated the importance of multivariate analyses of multiple risk factors for negative outcomes. Television and video game use have often been posited as potential contributors to attention problems, but previous studies have not always been well-controlled or used well-validated outcome measures. The current study examines the multivariate nature of risk factors for attention problems symptomatic of attention deficit hyperactivity disorder and poor school performance. A predominantly Hispanic population of 603 children (ages 10-14) and their parents/guardians responded to multiple behavioral measures. Outcome measures included parent and child reported attention problem behaviors on the Child Behavior Checklist (CBCL) as well as poor school performance as measured by grade point average (GPA). Results found that internal factors such as male gender, antisocial traits, family environment and anxiety best predicted attention problems. School performance was best predicted by family income. Television and video game use, whether total time spent using, or exposure to violent content specifically, did not predict attention problems or GPA. Television and video game use do not appear to be significant predictors of childhood attention problems. Intervention and prevention efforts may be better spent on other risk factors. Copyright © 2010 Elsevier Ltd. All rights reserved.

Intake of Fiber and Nuts during Adolescence and Incidence of Proliferative Benign Breast Disease

PubMed Central

Su, Xuefen; Tamimi, Rulla M.; Collins, Laura C.; Baer, Heather J.; Cho, Eunyoung; Sampson, Laura; Willett, Walter C.; Schnitt, Stuart J.; Connolly, James L.; Rosner, Bernard A.; Colditz, Graham A.

2011-01-01

Objective We examined the association between adolescent fiber intake and proliferative BBD, a marker of increased breast cancer risk, in the Nurses’ Health Study II. Methods Among 29,480 women who completed a high school diet questionnaire in 1998, 682 proliferative BBD cases were identified and confirmed by centralized pathology review between 1991 and 2001. Multivariate-adjusted Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results Women in the highest quintile of adolescent fiber intake had a 25% lower risk of proliferative BBD (multivariate HR (95% CI): 0.75 (0.59, 0.96), p-trend = 0.01) than women in the lowest quintile. High school intake of nuts and apples was also related to significantly reduced BBD risk. Women consuming ≥2 servings of nuts/week had a 36% lower risk (multivariate HR (95% CI): 0.64 (0.48, 0.85), p-trend < 0.01) than women consuming <1 serving/month. Results were essentially the same when the analysis was restricted to prospective cases (n = 142) diagnosed after return of the high school diet questionnaire. Conclusions These findings support the hypothesis that dietary intake of fiber and nuts during adolescence influence subsequent risk of breast disease and may suggest a viable means for breast cancer prevention. PMID:20229245

Multivariate Profiles of Selected versus Non-Selected Elite Youth Brazilian Soccer Players

PubMed Central

Alves, Isabella S.; Padilha, Maickel B.; Casanova, Filipe; Puggina, Enrico F.; Maia, José

2017-01-01

Abstract This study determined whether a multivariate profile more effectively discriminated selected than non-selected elite youth Brazilian soccer players. This examination was carried out on 66 youth soccer players (selected, n = 28, mean age 16.3 ± 0.1; non-selected, n = 38, mean age 16.7 ± 0.4) using objective instruments. Multivariate profiles were assessed through anthropometric characteristics, biological maturation, tactical-technical skills, and motor performance. The Student’s t-test identified that selected players exhibited significantly higher values for height (t = 2.331, p = 0.02), lean body mass (t = 2.441, p = 0.01), and maturity offset (t = 4.559, p < 0.001), as well as performed better in declarative tactical knowledge (t = 10.484, p < 0.001), shooting (t = 2.188, p = 0.03), dribbling (t = 5.914, p < 0.001), speed – 30 m (t = 8.304, p < 0.001), countermovement jump (t = 2.718, p = 0.008), and peak power tests (t = 2.454, p = 0.01). Forward stepwise discriminant function analysis showed that declarative tactical knowledge, running speed –30 m, maturity offset, dribbling, height, and peak power correctly classified 97% of the selected players. These findings may have implications for a highly efficient selection process with objective measures of youth players in soccer clubs. PMID:29339991

Determinants of Paramedic Response Readiness for CBRNE Threats

PubMed Central

Jones, Alison; Smith, George; Nelson, Jenny; Agho, Kingsley; Taylor, Melanie; Raphael, Beverley

2010-01-01

Paramedics play a pivotal role in the response to major emergencies. Recent evidence indicates that their confidence and willingness to respond to chemical, biological, radiological, nuclear, and explosives-related (CBRNE) incidents differs from that relating to their “routine” emergency work. To further investigate the factors underpinning their readiness to respond to CBRNE incidents, paramedics in New South Wales (NSW), Australia, were asked to complete a validated online survey instrument. Univariate and multivariate analyses were performed to examine associated factors determining readiness. The sample of 663 respondents was weighted to reflect the NSW paramedic population as a whole. The univariate analysis indicated that gender, length of service, deployment concern, perceived personal resilience, CBRNE training, and incident experience were significantly associated with perceived CBRNE response readiness. In the initial multivariate analysis, significantly higher response readiness was associated with male gender, university education, and greater length of service (10-15 years). In the final multivariate model, the combined effect of training/incident experience negated the significant effects observed in the initial model and, importantly, showed that those with recent training reported higher readiness, irrespective of incident experience. Those with lower concern regarding CBRNE deployment and those with higher personal resilience were significantly more likely to report higher readiness (Adjusted Relative Risk [ARR] = 0.91, 95% CI: 0.84-0.99; ARR = 1.40, 95% CI: 1.11-1.72, respectively). These findings will assist emergency medical planners in recognizing occupational and dispositional factors associated with enhanced CBRNE readiness and highlight the important role of training in redressing potential readiness differences associated with these factors. PMID:20569060

An integrated phenomic approach to multivariate allelic association

PubMed Central

Medland, Sarah Elizabeth; Neale, Michael Churton

2010-01-01

The increased feasibility of genome-wide association has resulted in association becoming the primary method used to localize genetic variants that cause phenotypic variation. Much attention has been focused on the vast multiple testing problems arising from analyzing large numbers of single nucleotide polymorphisms. However, the inflation of experiment-wise type I error rates through testing numerous phenotypes has received less attention. Multivariate analyses can be used to detect both pleiotropic effects that influence a latent common factor, and monotropic effects that operate at a variable-specific levels, whilst controlling for non-independence between phenotypes. In this study, we present a maximum likelihood approach, which combines both latent and variable-specific tests and which may be used with either individual or family data. Simulation results indicate that in the presence of factor-level association, the combined multivariate (CMV) analysis approach performs well with a minimal loss of power as compared with a univariate analysis of a factor or sum score (SS). As the deviation between the pattern of allelic effects and the factor loadings increases, the power of univariate analyses of both factor and SSs decreases dramatically, whereas the power of the CMV approach is maintained. We show the utility of the approach by examining the association between dopamine receptor D2 TaqIA and the initiation of marijuana, tranquilizers and stimulants in data from the Add Health Study. Perl scripts that takes ped and dat files as input and produces Mx scripts and data for running the CMV approach can be downloaded from www.vipbg.vcu.edu/~sarahme/WriteMx. PMID:19707246

Sex hormones and quantitative ultrasound parameters at the heel in men and women from the general population.

PubMed

Pätzug, Konrad; Friedrich, Nele; Kische, Hanna; Hannemann, Anke; Völzke, Henry; Nauck, Matthias; Keevil, Brian G; Haring, Robin

2017-12-01

The present study investigates potential associations between liquid chromatography-mass spectrometry (LC-MS) measured sex hormones, dehydroepiandrosterone sulphate, sex hormone-binding globulin (SHBG) and bone ultrasound parameters at the heel in men and women from the general population. Data from 502 women and 425 men from the population-based Study of Health in Pomerania (SHIP-TREND) were used. Cross-sectional associations of sex hormones including testosterone (TT), calculated free testosterone (FT), dehydroepiandrosterone sulphate (DHEAS), androstenedione (ASD), estrone (E1) and SHBG with quantitative ultrasound (QUS) parameters at the heel, including broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (SI) were examined by analysis of variance (ANOVA) and multivariable quantile regression models. Multivariable regression analysis showed a sex-specific inverse association of DHEAS with SI in men (Beta per SI unit = - 3.08, standard error (SE) = 0.88), but not in women (Beta = - 0.01, SE = 2.09). Furthermore, FT was positively associated with BUA in men (Beta per BUA unit = 29.0, SE = 10.1). None of the other sex hormones (ASD, E1) or SHBG was associated with QUS parameters after multivariable adjustment. This cross-sectional population-based study revealed independent associations of DHEAS and FT with QUS parameters in men, suggesting a potential influence on male bone metabolism. The predictive role of DHEAS and FT as a marker for osteoporosis in men warrants further investigation in clinical trials and large-scale observational studies.

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

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

Genomic Analysis of Complex Microbial Communities in Wounds

DTIC Science & Technology

2012-01-01

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

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

PubMed

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

2013-01-01

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

Forensic analysis of dyed textile fibers.

PubMed

Goodpaster, John V; Liszewski, Elisa A

2009-08-01

Textile fibers are a key form of trace evidence, and the ability to reliably associate or discriminate them is crucial for forensic scientists worldwide. While microscopic and instrumental analysis can be used to determine the composition of the fiber itself, additional specificity is gained by examining fiber color. This is particularly important when the bulk composition of the fiber is relatively uninformative, as it is with cotton, wool, or other natural fibers. Such analyses pose several problems, including extremely small sample sizes, the desire for nondestructive techniques, and the vast complexity of modern dye compositions. This review will focus on more recent methods for comparing fiber color by using chromatography, spectroscopy, and mass spectrometry. The increasing use of multivariate statistics and other data analysis techniques for the differentiation of spectra from dyed fibers will also be discussed.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

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

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

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

ERIC Educational Resources Information Center

Sun, Anji; Valiga, Michael J.

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

Morphometric discrimination of early life stage Lampetra tridentata and L richardsoni (Petromyzonidae) from the Columbia river basin

USGS Publications Warehouse

Meeuwig, M.H.; Bayer, J.M.; Reiche, R.A.

2006-01-01

The effectiveness of morphometric and meristic characteristics for taxonomic discrimination of Lampetra tridentata and L. richardsoni (Petromyzonidae) during embryological, prolarval, and early larval stages (i.e., age class 1) were examined. Mean chorion diameter increased with time from fertilization to hatch and was significantly greater for L. tridentata than for L. richardsoni at 1, 8, and 15 days postfertilization. Lampetra tridentata larvae had significantly more trunk myomeres than L. richardsoni; however, trunk myomere numbers were highly variable within species and deviated from previously published data. Multivariate examinations of prolarval and larval L. tridentata (7.2-11.0 mm; standard length) and L. richardsoni (6.6-10.8 mm) were conducted based on standard length and truss element lengths established from eight homologous landmarks. Principal components analysis indicated allometric relationships among the morphometric characteristics examined. Changes in body shape were indicated by groupings of morphometric characteristics associated with body regions (e.g., oral hood, branchial region, trunk region, and tail region). Discriminant function analysis using morphometric characteristics was successful in classifying a large proportion (>94.7%) of the lampreys sampled. 

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.

A multivariate model exploring the predictive value of demographic, adolescent, and family factors on glycemic control in adolescents with type 1 diabetes.

PubMed

Agarwal, Shivani; Jawad, Abbas F; Miller, Victoria A

2016-11-01

The current study examined how a comprehensive set of variables from multiple domains, including at the adolescent and family level, were predictive of glycemic control in adolescents with type 1 diabetes (T1D). Participants included 100 adolescents with T1D ages 10-16 yrs and their parents. Participants were enrolled in a longitudinal study about youth decision-making involvement in chronic illness management of which the baseline data were available for analysis. Bivariate associations with glycemic control (HbA1C) were tested. Hierarchical linear regression was implemented to inform the predictive model. In bivariate analyses, race, family structure, household income, insulin regimen, adolescent-reported adherence to diabetes self-management, cognitive development, adolescent responsibility for T1D management, and parent behavior during the illness management discussion were associated with HbA1c. In the multivariate model, the only significant predictors of HbA1c were race and insulin regimen, accounting for 17% of the variance. Caucasians had better glycemic control than other racial groups. Participants using pre-mixed insulin therapy and basal-bolus insulin had worse glycemic control than those on insulin pumps. This study shows that despite associations of adolescent and family-level variables with glycemic control at the bivariate level, only race and insulin regimen are predictive of glycemic control in hierarchical multivariate analyses. This model offers an alternative way to examine the relationship of demographic and psychosocial factors on glycemic control in adolescents with T1D. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Race and Region Are Associated with Nutrient Intakes among Black and White Men in the United States12

PubMed Central

Newby, P. K.; Noel, Sabrina E.; Grant, Rachael; Judd, Suzanne; Shikany, James M.; Ard, Jamy

2011-01-01

Stroke mortality rates and prevalence of several chronic diseases are higher in Southern populations and blacks in the US. This study examined the relationships of race (black, white) and region (Stroke Belt, Stroke Buckle, other) with selected nutrient intakes among black and white American men (n = 9229). The Block 98 FFQ assessed dietary intakes and multivariable linear regression analysis was used to examine whether race and region were associated with intakes of fiber, saturated fat, trans fat, sodium, potassium, magnesium, calcium, and cholesterol. Race and region were significant predictors of most nutrient intakes. Black men consumed 1.00% lower energy from saturated fat compared with white men [multivariable-adjusted β: 1.00% (95% CI = −0.88, −1.13)]. A significant interaction between race and region was detected for trans fat (P < 0.0001), where intake was significantly lower among black men compared with white men only in the Stroke Belt [multivariable-adjusted β: −0.21 (95% CI = −0.11, −0.31)]. Among black men, intakes of sodium, potassium, magnesium, and calcium were lower, whereas cholesterol was higher, compared with white men (P < 0.05 for all). Comparing regions, men in the Stroke Buckle had the lowest intakes of fiber, potassium, magnesium, and calcium compared with those in the Stroke Belt and other regions; men in both the Stroke Buckle and Stroke Belt had higher intakes of cholesterol compared with those in other regions (P < 0.005 for all). Given these observed differences in dietary intakes, more research is needed to understand if and how they play a role in the health disparities and chronic disease risks observed among racial groups and regions in the US. PMID:21178088

Impact of specialized inpatient IBD care on outcomes of IBD hospitalizations: A cohort study

PubMed Central

Law, Cindy CY; Sasidharan, Saranya; Rodrigues, Rodrigo; Nguyen, Deanna D; Sauk, Jenny; Garber, John; Giallourakis, Cosmas; Xavier, Ramnik; Khalili, Hamed; Yajnik, Vijay; Ananthakrishnan, Ashwin N

2016-01-01

Background The management of inflammatory bowel diseases (IBD; Crohn’s disease (CD), ulcerative colitis (UC)) is increasingly complex. Specialized care has been associated with improved ambulatory IBD outcomes. Aims To examine if the implementation of specialized inpatient IBD care modified short and long-term clinical outcomes in IBD-related hospitalizations. Methods This retrospective cohort study included IBD patients hospitalized between July 2013 and April 2015 at a single tertiary referral center where a specialized inpatient IBD care model was implemented in July 2014. In-hospital medical and surgical outcomes as well as post-discharge outcomes at 30 and 90 days were analyzed along with measures of quality of in-hospital care. Effect of specialist IBD care was examined on multivariate analysis. Results A total of 408 IBD-related admissions were included. With implementation of specialized IBD inpatient care, we observed increased frequency of use of high-dose biologic therapy for induction (26% vs. 9%, odds ratio (OR) 5.50, 95% CI 1.30 – 23.17) and higher proportion of patients in remission at 90 days after discharge (multivariate OR 1.60, 95% CI 0.99 – 2.69). While there was no difference in surgery by 90 days, among those who underwent surgery, early surgery defined as in-hospital or within 30 days of discharge, was more common in the study period (71%) compared to the control period (46%, multivariate OR 2.73, 95% CI 1.22 – 6.12). There was no difference in length of stay between the two years. Conclusions Implementation of specialized inpatient IBD care beneficially impacted remission and facilitated early surgical treatment. PMID:27482978

NIH disease funding levels and burden of disease.

PubMed

Gillum, Leslie A; Gouveia, Christopher; Dorsey, E Ray; Pletcher, Mark; Mathers, Colin D; McCulloch, Charles E; Johnston, S Claiborne

2011-02-24

An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time. We analyzed public data on 2006 NIH funding for 29 common conditions. Measures of US disease burden in 2004 were obtained from the World Health Organization's Global Burden of Disease study and national databases. We assessed the relationship between disease burden and NIH funding dollars in univariate and multivariable log-linear models that evaluated all measures of disease burden. Sensitivity analyses examined associations with future US burden, current and future measures of world disease burden, and a newly standardized NIH accounting method. In univariate and multivariable analyses, disease-specific NIH funding levels increased with burden of disease measured in DALYs (p = 0.001), which accounted for 33% of funding level variation. No other factor predicted funding in multivariable models. Conditions receiving the most funding greater than expected based on disease burden were AIDS ($2474 M), diabetes mellitus ($390 M), and perinatal conditions ($297 M). Depression ($719 M), injuries ($691 M), and chronic obstructive pulmonary disease ($613 M) were the most underfunded. Results were similar using estimates of future US burden, current and future world disease burden, and alternate NIH accounting methods. Current levels of NIH disease-specific research funding correlate modestly with US disease burden, and correlation has not improved in the last decade.

Gender Differences in Antipsychotics Prescribed to Veterans with Serious Mental Illness

PubMed Central

Schwartz, Elana; Charlotte, Melanie; Slade, Eric; Medoff, Deborah; Li, Lan; Dixon, Lisa; Kilbourne, Amy; Kreyenbuhl, Julie

2017-01-01

Objective To examine gender differences in prescribing of antipsychotic medications (APMs) according to their liability for weight gain and other metabolic side effects. Method We identified 4,510 patients with schizophrenia or bipolar disorders receiving usual care in a VA healthcare network in the U.S. mid-Atlantic region who initiated treatment with an APM between 10/2006 and 9/2011. We used multivariable logistic regression to examine gender differences in the likelihood of incident prescription of APMs with low versus medium/high metabolic risk, adjusting for fiscal year of prescribing and selected Veteran demographic, mental health, and physical health characteristics. Results Overall, 58% of women were prescribed an APM with a low risk of metabolic side effects compared to 45% of men (p < 0.001). In multivariable analysis, women Veterans were 1.47 times as likely as men to be prescribed a low metabolic risk APM (95% CI: 1.26–1.73, p<0.001). Several demographic and clinical covariates were also independently related to prescribing of APMs by level of metabolic risk. Conclusions The results may suggest that prescribing choices for APMs by VA mental health prescribers and female Veterans reflect a growing awareness of the potential adverse health consequences of these treatments in women. PMID:25936673

Gender differences in antipsychotics prescribed to veterans with serious mental illness.

PubMed

Schwartz, Elana; Charlotte, Melanie; Slade, Eric; Medoff, Deborah; Li, Lan; Dixon, Lisa; Kilbourne, Amy; Kreyenbuhl, Julie

2015-01-01

To examine gender differences in prescribing of antipsychotic medications (APMs) according to their liability for weight gain and other metabolic side effects. We identified 4510 patients with schizophrenia or bipolar disorders receiving usual care in a Veterans Affairs (VA) health care network in the U.S. mid-Atlantic region who initiated treatment with an APM between October 2006 and September 2011. We used multivariable logistic regression to examine gender differences in the likelihood of incident prescription of APMs with low versus medium/high metabolic risk, adjusting for fiscal year of prescribing and selected Veteran demographic, mental health and physical health characteristics. Overall, 58% of women were prescribed an APM with a low risk of metabolic side effects compared to 45% of men (P<.001). In multivariable analysis, women Veterans were 1.47 times as likely as men to be prescribed a low-metabolic-risk APM (95% confidence interval: 1.26-1.73, P<.001). Several demographic and clinical covariates were also independently related to prescribing of APMs by level of metabolic risk. The results may suggest that prescribing choices for APMs by VA mental health prescribers and female Veterans reflect a growing awareness of the potential adverse health consequences of these treatments in women. Published by Elsevier Inc.

Factors Associated With Caregivers' Resilience in a Terminal Cancer Care Setting.

PubMed

Hwang, In Cheol; Kim, Young Sung; Lee, Yong Joo; Choi, Youn Seon; Hwang, Sun Wook; Kim, Hyo Min; Koh, Su-Jin

2018-04-01

Resilience implies characteristics such as self-efficacy, adaptability to change, optimism, and the ability to recover from traumatic stress. Studies on resilience in family caregivers (FCs) of patients with terminal cancer are rare. This study aims to examine the factors associated with FCs' resilience in a terminal cancer care setting. This is a cross-sectional study of 273 FCs from 7 hospice and palliative care units in Korea. Resilience was categorized as high and low, and factors associated with resilience were grouped or categorized into subscales. A multivariate logistic regression analysis was used to examine relevant factors. High FCs' resilience was significantly associated with FCs' health status, depression, and social support. In a multivariate regression model, FCs' perception of good health (adjusted odds ratio [aOR] = 2.26, 95% confidence interval [CI] = 1.16-4.40), positive social support (aOR = 3.70, 95% CI = 1.07-12.87), and absence of depression (aOR = 3.12, 95% CI = 1.59-6.13) remained significantly associated with high FCs' resilience. Lack of family support is associated with and may be a cause of diminished resilience. And more concern should be paid to FCs to improve FCs' health and emotional status. Education programs might be effective for improving caregivers' resilience. Further research with supportive interventions is indicated.

Correlates of Suicidality: Investigation of a Representative Sample of Manitoba First Nations Adolescents

PubMed Central

Mota, Natalie; Elias, Brenda; Tefft, Bruce; Medved, Maria; Munro, Garry

2012-01-01

Objectives. We examined individual, friend or family, and community or tribe correlates of suicidality in a representative on-reserve sample of First Nations adolescents. Methods. Data came from the 2002–2003 Manitoba First Nations Regional Longitudinal Health Survey of Youth. Interviews were conducted with adolescents aged 12 to 17 years (n = 1125) from 23 First Nations communities in Manitoba. We used bivariate logistic regression analyses to examine the relationships between a range of factors and lifetime suicidality. We conducted sex-by-correlate interactions for each significant correlate at the bivariate level. A multivariate logistic regression analysis identified those correlates most strongly related to suicidality. Results. We found several variables to be associated with an increased likelihood of suicidality in the multivariate model, including being female, depressed mood, abuse or fear of abuse, a hospital stay, and substance use (adjusted odds ratio range = 2.43–11.73). Perceived community caring was protective against suicidality (adjusted odds ratio = 0.93; 95% confidence interval = 0.88, 0.97) in the same model. Conclusions. Results of this study may be important in informing First Nations and government policy related to the implementation of suicide prevention strategies in First Nations communities. PMID:22676500

Examining the impacts of increased corn production on ...

EPA Pesticide Factsheets

This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirectional and Environmental Policy Integrated Climate modeling system incorporates agricultural management practices and N exchange processes between the soil and atmosphere to estimate levels of N that may volatilize into the atmosphere, re-deposit, and seep or flow into surface and groundwater. Simulated values from this modeling system were used in a land-use regression model to examine associations between groundwater nitrate-N measurements and a suite of factors related to N fertilizer and groundwater nitrate contamination. Multi-variable modeling analysis revealed that the N-fertilizer rate (versus total) applied to irrigated (versus rainfed) grain corn (versus other crops) was the strongest N-related predictor variable of groundwater nitrate-N concentrations. Application of this multi-variable model considered groundwater nitrate-N concentration responses under two corn production scenarios. Findings suggest that increased corn production between 2002 and 2022 could result in 56% to 79% increase in areas vulnerable to groundwater nitrate-N concentrations ≥ 5 mg/L. These above-threshold areas occur on soils with a hydraulic conductivity 13% higher than the rest of the domain. Additio

Homelessness among a cohort of women in street-based sex work: the need for safer environment interventions.

PubMed

Duff, Putu; Deering, Kathleen; Gibson, Kate; Tyndall, Mark; Shannon, Kate

2011-08-12

Drawing on data from a community-based prospective cohort study in Vancouver, Canada, we examined the prevalence and individual, interpersonal and work environment correlates of homelessness among 252 women in street-based sex work. Bivariate and multivariate logistic regression using generalized estimating equations (GEE) was used to examine the individual, interpersonal and work environment factors that were associated with homelessness among street-based sex workers. Among 252 women, 43.3% reported homelessness over an 18-month follow-up period. In the multivariable GEE logistic regression analysis, younger age (adjusted odds ratio [aOR] = 0.93; 95%confidence interval [95%CI] 0.93-0.98), sexual violence by non-commercial partners (aOR = 2.14; 95%CI 1.06-4.34), servicing a higher number of clients (10+ per week vs < 10) (aOR = 1.68; 95%CI 1.05-2.69), intensive, daily crack use (aOR = 1.65; 95%CI 1.11-2.45), and servicing clients in public spaces (aOR = 1.52; CI 1.00-2.31) were independently associated with sleeping on the street. These findings indicate a critical need for safer environment interventions that mitigate the social and physical risks faced by homeless FSWs and increase access to safe, secure housing for women.

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

Treesearch

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

1996-01-01

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

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

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

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

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

PubMed Central

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

2003-01-01

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

Multivariate meta-analysis using individual participant data.

PubMed

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

2015-06-01

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

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

PubMed

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

2017-01-01

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

Multivariate analysis of longitudinal rates of change.

PubMed

Bryan, Matthew; Heagerty, Patrick J

2016-12-10

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

Characterizing backcountry camping impacts in Great Smoky Mountains National Park

USGS Publications Warehouse

Leung, Y.-F.; Marion, J.L.

1999-01-01

This investigates resource impacts on backcounty campsites in the Great Smoky Mountains National Park, USA. Study objectives were to enhance our understanding of camping impacts and to improve campsite impact assessment procedures by means of multivariate techniques. Three-hundred and eight campsites at designated backcountry campgrounds, and 69 additional unofficial campsites were assessed. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: area disturbance, soil and groundcover damage, and tree-related damage. Four distinctive backcountry campsite types were identified, three of which were derived from cluster analyses of factor scores. These four backcountry campsite types characterize the intensity and areal extent of resource impacts, and they vary in locational and environmental attributes. At an aggregate level, different campsite types contributed unequally to the cumulative level of impact. The dimensional structure and typology developed in this study demonstrates that campsite impacts can be viewed and examined holistically with the use of multivariate methods. Implications for assessment procedures, management and further research are discussed.

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method.

PubMed

Liu, Siwei; Molenaar, Peter

2016-01-01

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.

Business closure and relocation: a comparative analysis of the Loma Prieta earthquake and Hurricane Andrew.

PubMed

Wasileski, Gabriela; Rodríguez, Havidán; Diaz, Walter

2011-01-01

The occurrence of a number of large-scale disasters or catastrophes in recent years, including the Indian Ocean tsunami (2004), the Kashmir earthquake (2005), Hurricane Katrina (2005) and Hurricane Ike (2008), have raised our awareness regarding the devastating effects of disasters on human populations and the importance of developing mitigation and preparedness strategies to limit the consequences of such events. However, there is still a dearth of social science research focusing on the socio-economic impact of disasters on businesses in the United States. This paper contributes to this research literature by focusing on the impact of disasters on business closure and relocation through the use of multivariate logistic regression models, specifically focusing on the Loma Prieta earthquake (1989) and Hurricane Andrew (1992). Using a multivariate model, we examine how physical damage to the infrastructure, lifeline disruption and business characteristics, among others, impact business closure and relocation following major disasters. © 2011 The Author(s). Disasters © Overseas Development Institute, 2011.

A multivariate analysis of youth violence and aggression: the influence of family, peers, depression, and media violence.

PubMed

Ferguson, Christopher J; San Miguel, Claudia; Hartley, Richard D

2009-12-01

To examine the multivariate nature of risk factors for youth violence including delinquent peer associations, exposure to domestic violence in the home, family conflict, neighborhood stress, antisocial personality traits, depression level, and exposure to television and video game violence. A population of 603 predominantly Hispanic children (ages 10-14 years) and their parents or guardians responded to multiple behavioral measures. Outcomes included aggression and rule-breaking behavior on the Child Behavior Checklist (CBCL), as well as violent and nonviolent criminal activity and bullying behavior. Delinquent peer influences, antisocial personality traits, depression, and parents/guardians who use psychological abuse in intimate relationships were consistent risk factors for youth violence and aggression. Neighborhood quality, parental use of domestic violence in intimate relationships, and exposure to violent television or video games were not predictive of youth violence and aggression. Childhood depression, delinquent peer association, and parental use of psychological abuse may be particularly fruitful avenues for future prevention or intervention efforts.

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

PubMed

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

2018-02-01

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

Admixture analysis of age of onset in generalized anxiety disorder.

PubMed

Rhebergen, Didi; Aderka, Idan M; van der Steenstraten, Ira M; van Balkom, Anton J L M; van Oppen, Patricia; Stek, Max L; Comijs, Hannie C; Batelaan, Neeltje M

2017-08-01

Age of onset is a marker of clinically relevant subtypes in various medical and psychiatric disorders. Past research has also reported that age of onset in generalized anxiety disorder (GAD) is clinically significant; but, in research to date, arbitrary cut-off ages have been used. In the present study, admixture analysis was used to determine the best fitting model for age of onset distribution in GAD. Data were derived from 459 adults with a diagnosis of GAD who took part in the Netherlands Study of Depression and Anxiety (NESDA). Associations between age of onset subtypes, identified by admixture analysis, and sociodemographic, clinical, and vulnerability factors were examined using univariate tests and multivariate logistic regression analyses. Two age of onset distributions were identified: an early-onset group (24 years of age and younger) and a late-onset group (greater than 24 years of age). Multivariate analysis revealed that early-onset GAD was associated with female gender (OR 2.1 (95%CI 1.4-3.2)), higher education (OR 1.1 (95%CI 1.0-1.2)), and higher neuroticism (OR 1.4 (95%CI 1.1-1.7)), while late-onset GAD was associated with physical illnesses (OR 1.3 (95%CI 1.1-1.7)). Study limitations include the possibility of recall bias given that age of onset was assessed retrospectively, and an inability to detect a possible very-late-onset GAD subtype. Collectively, the results of the study indicate that GAD is characterized by a bimodal age of onset distribution with an objectively determined early cut-off at 24 years of age. Early-onset GAD is associated with unique factors that may contribute to its aetiology; but, it does not constitute a more severe subtype compared to late-onset GAD. Future research should use 24 years of age as the cut-off for early-onset GAD to when examining the clinical relevance of age of onset for treatment efficacy and illness course. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

DTIC Science & Technology

1980-07-08

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

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

DTIC Science & Technology

2015-01-01

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

Multivariate optimum interpolation of surface pressure and winds over oceans

NASA Technical Reports Server (NTRS)

Bloom, S. C.

1984-01-01

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

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

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

Work factors are associated with workplace activity limitations in systemic lupus erythematosus.

PubMed

Al Dhanhani, Ali M; Gignac, Monique A M; Beaton, Dorcas E; Su, Jiandong; Fortin, Paul R

2014-11-01

The objective of this study was to examine the extent of workplace activity limitations among persons with lupus and to identify factors associated with activity limitations among those employed. We conducted a cross-sectional study using a mailed survey and clinical data of persons with lupus who attended a large lupus outpatient clinic. Data were collected on demographics, health, work factors and psychosocial measures. The workplace activity limitations scale (WALS) was used to measure difficulty related to different activities at work. Multivariable analysis examined the association of health, work context, psychosocial and demographic variables with workplace activity limitations. We received 362 responses from 604 (60%) mailed surveys. Among those not employed, 52% reported not working because of lupus. A range of physical and mental tasks were reported as difficult. Each of the physical, cognitive and energy work activities was cited as difficult by more than one-third of participants. Among employed participants, 40% had medium to high WALS difficulty scores. In the multivariable analysis, factors significantly associated with workplace activity limitations were older age, greater disease activity, fatigue, poorer health status measured by the 36-item Short Form Health Survey, lower job control, greater job strain and working more than 40 h/week. People with lupus experience limitations and difficulty at work. Determinants of workplace activity limitations are mainly those related to workplace and health factors. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Factors associated with inability to access addiction treatment among people who inject drugs in Vancouver, Canada.

PubMed

Prangnell, Amy; Daly-Grafstein, Ben; Dong, Huiru; Nolan, Seonaid; Milloy, M-J; Wood, Evan; Kerr, Thomas; Hayashi, Kanna

2016-02-25

Addiction treatment is an effective strategy used to reduce drug-related harm. In the wake of recent developments in novel addiction treatment modalities, we conducted a longitudinal data analysis to examine factors associated with inability to access addiction treatment among a prospective cohort of persons who inject drugs (PWID). Data were derived from two prospective cohorts of PWID in Vancouver, Canada, between December 2005 and November 2013. Using multivariate generalized estimating equations, we examined factors associated with reporting an inability to access addiction treatment. In total, 1142 PWID who had not accessed any addiction treatment during the six months prior to interview were eligible for this study, including 364 women (31.9 %). Overall, 188 (16.5 %) reported having sought but were ultimately unsuccessful in accessing addiction treatment at least once during the study period. In multivariate analysis, factors independently and positively associated with reporting inability to access addiction treatment included: binge drug use (Adjusted Odds Ratio [AOR] = 1.65), being a victim of violence (AOR = 1.77), homelessness (AOR = 1.99), and having ever accessed addiction treatment (AOR = 2.33); while length of time injecting was negatively and independently associated (AOR = 0.98) (all p < 0.05). These findings suggest that sub-populations of PWID were more likely to report experiencing difficulty accessing addiction treatment, including those who may be entrenched in severe drug addiction and vulnerable to violence. It is imperative that additional resources go into ensuring treatment options are readily available when requested for these target populations.

The impact of childhood emotional abuse on violence among people who inject drugs.

PubMed

Lake, Stephanie; Wood, Evan; Dong, Huiru; Dobrer, Sabina; Montaner, Julio; Kerr, Thomas

2015-01-01

Childhood emotional abuse is a known risk factor for various poor social and health outcomes. While people who inject drugs (IDU) report high levels of violence, in addition to high rates of childhood maltreatment, the relationship between childhood emotional abuse and later life violence within this population has not been examined. Cross-sectional data were derived from an open prospective cohort of IDU in Vancouver, Canada. Childhood emotional abuse was measured using the Childhood Trauma Questionnaire. We used multivariate logistic regression to examine potential associations between childhood emotional abuse and being a recent victim or perpetrator of violence. Between December 2005 and May 2013, 1437 IDU were eligible for inclusion in this analysis, including 465 (32.4%) women. In total, 689 (48.0%) reported moderate to severe history of childhood emotional abuse, whereas 333 (23.2%) reported being a recent victim of violence and 173 (12.0%) reported being a recent perpetrator of violence. In multivariate analysis, being a victim of violence (adjusted odds ratio = 1.49, 95% confidence interval 1.15-1.94) and being a perpetrator of violence (adjusted odds ratio = 1.58, 95% confidence interval 1.12-2.24) remained independently associated with childhood emotional abuse. We found high rates of childhood emotional abuse and subsequent adult violence among this sample of IDU. Emotional abuse was associated with both victimisation and perpetration of violence. These findings highlight the need for policies and programmes that address both child abuse and historical emotional abuse among adult IDU. © 2014 Australasian Professional Society on Alcohol and other Drugs.

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

Placebo group improvement in trials of pharmacotherapies for alcohol use disorders: a multivariate meta-analysis examining change over time.

PubMed

Del Re, A C; Maisel, Natalya; Blodgett, Janet C; Wilbourne, Paula; Finney, John W

2013-10-01

Placebo group improvement in pharmacotherapy trials has been increasing over time across several pharmacological treatment areas. However, it is unknown to what degree increasing improvement has occurred in pharmacotherapy trials for alcohol use disorders or what factors may account for placebo group improvement. This meta-analysis of 47 alcohol pharmacotherapy trials evaluated (1) the magnitude of placebo group improvement, (2) the extent to which placebo group improvement has been increasing over time, and (3) several potential moderators that might account for variation in placebo group improvement. Random-effects univariate and multivariate analyses were conducted that examined the magnitude of placebo group improvement in the 47 studies and several potential moderators of improvement: (a) publication year, (b) country in which the study was conducted, (c) outcome data source/type, (d) number of placebo administrations, (e) overall severity of study participants, and (f) additional psychosocial treatment. Substantial placebo group improvement was found overall and improvement was larger in more recent studies. Greater improvement was found on moderately subjective outcomes, with more frequent administrations of the placebo, and in studies with greater participant severity of illness. However, even after controlling for these moderators, placebo group improvement remained significant, as did placebo group improvement over time. Similar to previous pharmacotherapy placebo research, substantial pretest to posttest placebo group improvement has occurred in alcohol pharmacotherapy trials, an effect that has been increasing over time. However, several plausible moderator variables were not able to explain why placebo group improvement has been increasing over time.

The Perceived Socioeconomic Status Is an Important Factor of Health Recovery for Victims of Occupational Accidents in Korea.

PubMed

Seok, Hongdeok; Yoon, Jin-Ha; Lee, Wanhyung; Lee, June-Hee; Jung, Pil Kyun; Roh, Jaehoon; Won, Jong-Uk

2016-02-01

We aimed to examine whether there is a correlation between the health recovery of industrial accident victims and their perceived socioeconomic status. Data were obtained from the first Panel Study of Worker's Compensation Insurance, which included 2,000 participants. We performed multivariate regression analysis and determined the odds ratios for participants with a subjectively lower socioeconomic status and for those with a subjectively lower middle socioeconomic status using 95% confidence intervals. An additional multivariate regression analysis yielded the odds ratios for participants with a subjectively lower socioeconomic status and those with a subjectively upper middle socioeconomic class using 95% confidence intervals. Of all participants, 299 reported a full recovery, whereas 1,701 did not. We examined the odds ratio (95% confidence intervals) for participants' health recovery according to their subjective socioeconomic status while controlling for sex, age, education, tobacco use, alcohol use, subjective state of health prior to the accident, chronic disease, employment duration, recovery period, accident type, disability status, disability rating, and economic participation. The odds of recovery in participants with a subjectively lower middle socioeconomic status were 1.707 times greater (1.264-2.305) than that of those with a subjectively lower socioeconomic status. Similarly, the odds of recovery in participants with a subjectively upper middle socioeconomic status were 3.124 times greater (1.795-5.438) than that of those with a subjectively lower socioeconomic status. Our findings indicate that participants' perceived socioeconomic disparities extend to disparities in their health status. The reinforcement of welfare measures is greatly needed to temper these disparities.

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

PubMed

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

2009-05-30

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

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

PubMed

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

2009-01-01

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

PYCHEM: a multivariate analysis package for python.

PubMed

Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston

2006-10-15

We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Multivariate longitudinal data analysis with censored and intermittent missing responses.

PubMed

Lin, Tsung-I; Lachos, Victor H; Wang, Wan-Lun

2018-05-08

The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach. Copyright © 2018 John Wiley & Sons, Ltd.

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

Periodontal inflamed surface area as a novel numerical variable describing periodontal conditions

PubMed Central

2017-01-01

Purpose A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis (P. gingivalis) expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation. PMID:29093989

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

PubMed

Hirai, Hiroshi; Kondo, Katsunori

2008-01-01

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

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.

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

PubMed

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

2010-12-24

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

A framework for multivariate data-based at-site flood frequency analysis: Essentiality of the conjugal application of parametric and nonparametric approaches

NASA Astrophysics Data System (ADS)

Vittal, H.; Singh, Jitendra; Kumar, Pankaj; Karmakar, Subhankar

2015-06-01

In watershed management, flood frequency analysis (FFA) is performed to quantify the risk of flooding at different spatial locations and also to provide guidelines for determining the design periods of flood control structures. The traditional FFA was extensively performed by considering univariate scenario for both at-site and regional estimation of return periods. However, due to inherent mutual dependence of the flood variables or characteristics [i.e., peak flow (P), flood volume (V) and flood duration (D), which are random in nature], analysis has been further extended to multivariate scenario, with some restrictive assumptions. To overcome the assumption of same family of marginal density function for all flood variables, the concept of copula has been introduced. Although, the advancement from univariate to multivariate analyses drew formidable attention to the FFA research community, the basic limitation was that the analyses were performed with the implementation of only parametric family of distributions. The aim of the current study is to emphasize the importance of nonparametric approaches in the field of multivariate FFA; however, the nonparametric distribution may not always be a good-fit and capable of replacing well-implemented multivariate parametric and multivariate copula-based applications. Nevertheless, the potential of obtaining best-fit using nonparametric distributions might be improved because such distributions reproduce the sample's characteristics, resulting in more accurate estimations of the multivariate return period. Hence, the current study shows the importance of conjugating multivariate nonparametric approach with multivariate parametric and copula-based approaches, thereby results in a comprehensive framework for complete at-site FFA. Although the proposed framework is designed for at-site FFA, this approach can also be applied to regional FFA because regional estimations ideally include at-site estimations. The framework is based on the following steps: (i) comprehensive trend analysis to assess nonstationarity in the observed data; (ii) selection of the best-fit univariate marginal distribution with a comprehensive set of parametric and nonparametric distributions for the flood variables; (iii) multivariate frequency analyses with parametric, copula-based and nonparametric approaches; and (iv) estimation of joint and various conditional return periods. The proposed framework for frequency analysis is demonstrated using 110 years of observed data from Allegheny River at Salamanca, New York, USA. The results show that for both univariate and multivariate cases, the nonparametric Gaussian kernel provides the best estimate. Further, we perform FFA for twenty major rivers over continental USA, which shows for seven rivers, all the flood variables followed nonparametric Gaussian kernel; whereas for other rivers, parametric distributions provide the best-fit either for one or two flood variables. Thus the summary of results shows that the nonparametric method cannot substitute the parametric and copula-based approaches, but should be considered during any at-site FFA to provide the broadest choices for best estimation of the flood return periods.

"Heart trouble" and religious involvement among older white men and women.

PubMed

Thompson, Edward H; Killgore, Leslie; Connors, Heather

2009-09-01

Objective Few studies examine how older adults' health status affects spiritual and religious involvement. This study examined the effects of gender and poor cardiac health on older adults' ends, means, and quest religious motivations and frequency of private devotion. Method Longitudinal data (12 months between the T1 and T2 interviews) with 182 older adults sampled from a Northeast city were used to examine in a multivariate analysis of covariance whether gender and the existence of cardiac health problems at T1 affected older adults' spiritual and religious involvement at T2. Findings A gender and cardiac health condition interaction showed older men with heart trouble had more changes in religious involvement-they engaged in more religious doubt, prayed less, and were not as intrinsically oriented at T2. Discussion The findings strongly suggest that older men with heart trouble may maintain a masculine style and shun seeking divine help.

The prognostic role of CD68 and FoxP3 expression in patients with primary central nervous system lymphoma.

PubMed

Cho, Hyunsoo; Kim, Se Hoon; Kim, Soo-Jeong; Chang, Jong Hee; Yang, Woo Ick; Suh, Chang-Ok; Cheong, June-Won; Kim, Yu Ri; Lee, Jung Yeon; Jang, Ji Eun; Kim, Yundeok; Min, Yoo Hong; Kim, Jin Seok

2017-07-01

The prognostic role of CD68 and FoxP3 in primary central nervous system lymphoma (PCNSL) has not been evaluated. Thus, we examined the prognostic significance of CD68 and FoxP3 expression in tumor samples of 76 newly diagnosed immunocompetent PCNSL patients. All patients were treated initially with high-dose methotrexate (HD-MTX)-based chemotherapy, and 16 (21.1%) patients received upfront autologous stem cell transplantation (ASCT) consolidation. High expression of CD68 (>55 cells/high-power field) or FoxP3 (>15 cells/high-power field) was observed in 10 patients, respectively. High CD68 expression was associated with inferior overall survival (OS) and progression-free survival (PFS) in multivariate analysis (P = 0.023 and P = 0.021, respectively). In addition, we performed subgroup analysis based on upfront ASCT. High CD68 expression was also associated with inferior OS and PFS in multivariate analysis (P = 0.013 and P < 0.001, respectively) among patients who did not receive upfront ASCT (n = 60), but not in patients who received upfront ASCT. The expression of FoxP3 was not significantly associated with survival. Therefore, we identified a prognostic significance of high CD68 expression in PCNSL, which suggests a need for further clinical trials and biological studies on the role of PCNSL tumor microenvironment.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Risk models for post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP): smoking and chronic liver disease are predictors of protection against PEP.

PubMed

DiMagno, Matthew J; Spaete, Joshua P; Ballard, Darren D; Wamsteker, Erik-Jan; Saini, Sameer D

2013-08-01

We investigated which variables independently associated with protection against or development of postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) and severity of PEP. Subsequently, we derived predictive risk models for PEP. In a case-control design, 6505 patients had 8264 ERCPs, 211 patients had PEP, and 22 patients had severe PEP. We randomly selected 348 non-PEP controls. We examined 7 established- and 9 investigational variables. In univariate analysis, 7 variables predicted PEP: younger age, female sex, suspected sphincter of Oddi dysfunction (SOD), pancreatic sphincterotomy, moderate-difficult cannulation (MDC), pancreatic stent placement, and lower Charlson score. Protective variables were current smoking, former drinking, diabetes, and chronic liver disease (CLD, biliary/transplant complications). Multivariate analysis identified seven independent variables for PEP, three protective (current smoking, CLD-biliary, CLD-transplant/hepatectomy complications) and 4 predictive (younger age, suspected SOD, pancreatic sphincterotomy, MDC). Pre- and post-ERCP risk models of 7 variables have a C-statistic of 0.74. Removing age (seventh variable) did not significantly affect the predictive value (C-statistic of 0.73) and reduced model complexity. Severity of PEP did not associate with any variables by multivariate analysis. By using the newly identified protective variables with 3 predictive variables, we derived 2 risk models with a higher predictive value for PEP compared to prior studies.

Gastroduodenal Ulcers and ABO Blood Group: the Japan Nurses' Health Study (JNHS).

PubMed

Alkebsi, Lobna; Ideno, Yuki; Lee, Jung-Su; Suzuki, Shosuke; Nakajima-Shimada, Junko; Ohnishi, Hiroshi; Sato, Yasunori; Hayashi, Kunihiko

2018-01-05

Although several studies have shown that blood type O is associated with increased risk of peptic ulcer, few studies have investigated these associations in Japan. We sought to investigate the association between the ABO blood group and risk of gastroduodenal ulcers (GDU) using combined analysis of both retrospective and prospective data from a large cohort study of Japanese women, the Japan Nurses' Health Study (JNHS; n = 15,019). The impact of the ABO blood group on GDU risk was examined using Cox regression analysis to estimate hazard ratios (HRs) and 95% confidence intervals (CI), with adjustment for potential confounders. Compared with women with non-O blood types (A, B, and AB), women with blood type O had a significantly increased risk of GDU from birth (multivariable-adjusted HR 1.18; 95% CI, 1.04-1.34). Moreover, the highest cumulative incidence of GDU was observed in women born pre-1956 with blood type O. In a subgroup analysis stratified by birth year (pre-1956 or post-1955), the multivariable-adjusted HR of women with blood type O was 1.22 (95% CI, 1.00-1.49) and 1.15 (95% CI, 0.98-1.35) in the pre-1956 and post-1955 groups, respectively. In this large, combined, ambispective cohort study of Japanese women, older women with blood type O had a higher risk of developing GDU than those with other blood types.

Factors Influencing the Appearance of Oxaliplatin-Induced Allergy.

PubMed

Nishihara, Masayuki; Nishikura, Kyoko; Morikawa, Norimichi; Yokoyama, Shota

2017-01-01

Several studies reported that the administration of oxaliplatin often induced allergy, but few studies have analyzed the pathogenesis. In this study, we examined the relationship between the incidence of allergy and status of oxaliplatin administration, patient background, laboratory data, or combined drugs. The subjects were 144 patients with colorectal or gastric cancer in whom oxaliplatin administration was started and completed between 2010 and 2016. They were divided into 2 groups: allergy and non-allergy groups. We extracted important factors influencing its appearance using multivariate analysis, and analyzed items of which the influence was suggested, using receiver operating characteristic (ROC) analysis. In 11 patients (7.6%), allergy appeared. The median frequency of appearance was 9 times (range: 5-13), being similar to that previously reported. On multivariate analysis, albumin (Alb) was extracted as an important factor. The cut-off value of Alb for the risk of allergy was 4.1 g/dL. An increase in the number of protein conjugates may have increased the risk of functioning as a hapten. Furthermore, the results suggested that the more frequency of oxaliplatin administration might increase the incidence of allergy, although it was not extracted as an important factor. In addition to young and female patients, as previously indicated, careful follow-up may be necessary for those with an Alb level of ≥4.1 g/dL especially after the 6th course.

Investigating the sex-related geometric variation of the human cranium.

PubMed

Bertsatos, Andreas; Papageorgopoulou, Christina; Valakos, Efstratios; Chovalopoulou, Maria-Eleni

2018-01-29

Accurate sexing methods are of great importance in forensic anthropology since sex assessment is among the principal tasks when examining human skeletal remains. The present study explores a novel approach in assessing the most accurate metric traits of the human cranium for sex estimation based on 80 ectocranial landmarks from 176 modern individuals of known age and sex from the Athens Collection. The purpose of the study is to identify those distance and angle measurements that can be most effectively used in sex assessment. Three-dimensional landmark coordinates were digitized with a Microscribe 3DX and analyzed in GNU Octave. An iterative linear discriminant analysis of all possible combinations of landmarks was performed for each unique set of the 3160 distances and 246,480 angles. Cross-validated correct classification as well as multivariate DFA on top performing variables reported 13 craniometric distances with over 85% classification accuracy, 7 angles over 78%, as well as certain multivariate combinations yielding over 95%. Linear regression of these variables with the centroid size was used to assess their relation to the size of the cranium. In contrast to the use of generalized procrustes analysis (GPA) and principal component analysis (PCA), which constitute the common analytical work flow for such data, our method, although computational intensive, produced easily applicable discriminant functions of high accuracy, while at the same time explored the maximum of cranial variability.

Risk factors in laparoscopic cholecystectomy: a multivariate analysis.

PubMed

Kanakala, Venkatesh; Borowski, David W; Pellen, Michael G C; Dronamraju, Shridhar S; Woodcock, Sean A A; Seymour, Keith; Attwood, Stephen E A; Horgan, Liam F

2011-01-01

Laparoscopic cholecystectomy (LC) is the operation of choice in the treatment of symptomatic gallstone disease. The aim of this study is to identify risk factors for LC, outcomes include operating time, length of stay, conversion rate, morbidity and mortality. All patients undergoing LC between 1998 and 2007 in a single district general hospital. Risk factors were examined using uni- and multivariate analysis. 2117 patients underwent LC, with 1706 (80.6%) patients operated on electively. Male patients were older, had more co-morbidity and more emergency surgery than females. The median post-operative hospital stay was one day, and was positively correlated with the complexity of surgery. Conversion rates were higher in male patients (OR 1.47, p = 0.047) than in females, and increased with co-morbidity. Emergency surgery (OR 1.75, p = 0.005), male gender (OR 1.68, p = 0.005), increasing co-morbidity and complexity of surgery were all positively associated with the incidence of complications (153/2117 [7.2%]), whereas only male gender was significantly associated with mortality (OR 5.71, p = 0.025). Adverse outcome from LC is particularly associated with male gender, but also the patient's co-morbidity, complexity and urgency of surgery. Risk-adjusted outcome analysis is desirable to ensure an informed consent process. Copyright © 2011 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Nailfold capillaroscopy abnormalities as predictors of mortality in patients with systemic sclerosis.

PubMed

Kayser, Cristiane; Sekiyama, Juliana Y; Próspero, Lucas C; Camargo, Cintia Z; Andrade, Luis E C

2013-01-01

Peripheral microangiopathy is a hallmark of systemic sclerosis (SSc) and can be early detected by nailfold capillaroscopy (NFC). This study aimed to examine whether more severe peripheral microangiopathy at NFC are predictive factor for death in SSc patients. 135 SSc patients who performed NFC between June 2001 and July 2009 were included. The following NFC parameters were evaluated: number of capillary loops/mm, avascular score (scored from 0 to 3), and number of enlarged and giant capillary loops. Univariate and multivariate regression models were used to analyse the association of mortality with NFC and clinical parameters. At the time of the analysis (August 2010), 123 patients were alive, and 12 were dead. By univariate analysis, male gender, forced vital capacity <75% predicted, higher number of giant capillary loops, and an avascular score >1.5 on NFC were associated with a significantly increase risk of death. By multivariate analysis, an avascular score >1.5 was the only independent predictor of death (hazard ratio 2.265). Survival rates from diagnosis at 1, 5 and 10 years were lower in patients with avascular score >1.5 (97%, 86%, and 59%, respectively) compared with those with avascular score ≤1.5 (97%, 97%, and 91% respectively) (p=0.009 by log rank test). Avascular scores higher than 1.5 at NFC was an independent predictor of death in SSc, suggesting that NFC can be useful for predicting SSc outcome.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Multivariate geometry as an approach to algal community analysis

USGS Publications Warehouse

Allen, T.F.H.; Skagen, S.

1973-01-01

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1984-01-01

The objective of this investigation is to develop a state-of-the-art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies. A three-dimensional multivariate O/I analysis scheme has been developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

The development of a state of the art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies was investigated. A three dimensional multivariate O/I analysis scheme was developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Functional Path Analysis as a Multivariate Technique in Developing a Theory of Participation in Adult Education.

ERIC Educational Resources Information Center

Martin, James L.

This paper reports on attempts by the author to construct a theoretical framework of adult education participation using a theory development process and the corresponding multivariate statistical techniques. Two problems are identified: the lack of theoretical framework in studying problems, and the limiting of statistical analysis to univariate…

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Web-Based Tools for Modelling and Analysis of Multivariate Data: California Ozone Pollution Activity

ERIC Educational Resources Information Center

Dinov, Ivo D.; Christou, Nicolas

2011-01-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting…

Multivariate analysis of climate along the southern coast of Alaska—some forestry implications.

Treesearch

Wilbur A. Farr; John S. Hard

1987-01-01

A multivariate analysis of climate was used to delineate 10 significantly different groups of climatic stations along the southern coast of Alaska based on latitude, longitude, seasonal temperatures and precipitation, frost-free periods, and total number of growing degree days. The climatic stations were too few to delineate this rugged, mountainous region into...

A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Treesearch

Xuan Chi; Barry Goodwin

2012-01-01

Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and...

Myopia and personality: the genes in myopia (GEM) personality study.

PubMed

van de Berg, Robert; Dirani, Mohamed; Chen, Christine Y; Haslam, Nicholas; Baird, Paul N

2008-03-01

A long-held view among the medical and broader community is that people who are short-sighted (myopic persons) have distinctive personality characteristics such as introversion and conscientiousness. However, existing research on this question is flawed, and its findings are inconsistent. The authors therefore aimed to determine whether myopia and personality are associated. The authors examined twins recruited through the Australian Twin Registry and a clinical-based family sample through a proband from a Melbourne Excimer Laser Clinic. There was no relation between family members and twins recruited in our study. Each individual underwent a full eye examination, completed a standard medical and general questionnaire, and was administered a five-factor model International Personality Item Pool (IPIP) inventory (Openness, Conscientiousness, Extroversion, Agreeableness, Neuroticism). Myopia was defined as worse than or equal to -0.50 (DS) spherical equivalent in the eye with the least refractive error. Data from 633 individual twins aged 18 to 83 years (mean, 53.04 years) and 278 family members aged 11 to 90 years (mean, 49.84 years) were analyzed. Prevalence of myopia was 35.7% for twins and 47.6% for family members. Mean spherical equivalent was +0.13 DS (95% CI, +/-0.16) for twins and -1.13 DS (95% CI, +/-0.25) for family members. Correlation and regression results for personality for both sample cohorts after multivariate analysis did not support the view that myopic persons are introverted or conscientious; however, there was a significant but small association between myopia and Agreeableness (r = 0.08, P < 0.05). In multivariate analysis with age, sex, education, and the five personality factors entered as predictors, Openness was the only significant personality predictor of myopia in both samples. This is the first multivariate study to assess links between personality and myopia using the IPIP. The long-held view that myopic persons are introverted and conscientious may reflect intelligence-related stereotypes rather than real correlations. Furthermore, the predictive characteristic of intellect, subsumed in Openness, appeared to be representative of a previously reported link between intellective abilities (IQ) and myopia rather than personality and myopia.

Ovarian Conservation and Overall Survival in Young Women With Early-Stage Low-Grade Endometrial Cancer.

PubMed

Matsuo, Koji; Machida, Hiroko; Shoupe, Donna; Melamed, Alexander; Muderspach, Laila I; Roman, Lynda D; Wright, Jason D

2016-10-01

To characterize contributing factors for ovarian conservation during surgical treatment for endometrial cancer and to examine the association of ovarian conservation on survival of young women with early-stage, low-grade tumors. This was a population-based study using the Surveillance, Epidemiology, and End Results program to identify surgically treated stage I type I (grade 1-2 endometrioid histology) endometrial cancer cases diagnosed between 1983 and 2012 (N=86,005). Multivariable models were used to identify independent factors for ovarian conservation. Survival outcomes and cause of death were examined for women aged younger than 50 with stage I type I endometrial cancer who underwent ovarian conservation (1,242 among 12,860 women [9.7%]). On multivariable analysis, age younger than 50 years, grade 1 endometrioid histology, and tumor size 2.0 cm or less were noted to be independent factors for ovarian conservation (all, P<.001). For 9,110 women aged younger than 50 years with stage I grade 1 tumors, cause-specific survival was similar between ovarian conservation and oophorectomy cases (20-year rates 98.9% compared with 97.7%, P=.31), whereas overall survival was significantly higher in ovarian conservation cases than oophorectomy cases (88.8% compared with 82.0%, P=.011). On multivariable analysis, ovarian conservation remained an independent prognostic factor for improved overall survival (adjusted hazard ratio 0.73, 95% confidence interval [CI] 0.54-0.98, P=.036) and was independently associated with a lower cumulative risk of death resulting from cardiovascular disease compared with oophorectomy (20-year rates, 2.3% compared with 3.7%, adjusted hazard ratio 0.40, 95% CI 0.17-0.91, P=.029). Contrary, cause-specific survival (20-year rates 94.6% compared with 96.1%, P=.68) and overall survival (81.0% compared with 80.6%, P=.91) were similar between ovarian conservation and oophorectomy among 3,750 women aged younger than 50 years with stage I grade 2 tumors. Ovarian conservation is performed in less than 10% of young women with stage I type I endometrial cancer. Ovarian conservation is associated with decreased mortality in young women with stage I grade 1 tumors.

Global health inequalities and breast cancer: an impending public health problem for developing countries.

PubMed

Igene, Helen

2008-01-01

The aim of the study was to provide information on the global health inequality pattern produced by the increasing incidence of breast cancer and its relationship with the health expenditure of developing countries with emphasis on sub-Saharan Africa. It examines the difference between the health expenditure of developed and developing countries, and how this affects breast cancer incidence and mortality. The data collected from the World Health Organization and World Bank were examined, using bivariate analysis, through scatter-plots and Pearson's product moment correlation coefficient. Multivariate analysis was carried out by multiple regression analysis. National income, health expenditure affects breast cancer incidence, particularly between the developed and developing countries. However, these factors do not adequately explain variations in mortality rates. The study reveals the risk posed to developing countries to solving the present and predicted burden of breast cancer, currently characterized by late presentation, inadequate health care systems, and high mortality. Findings from this study contribute to the knowledge of the burden of disease in developing countries, especially sub-Saharan Africa, and how that is related to globalization and health inequalities.

Multivariate statistical analysis of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Caramelo, Liliana; Pereira, Mário

2013-04-01

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

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

MULTIVARIATE ANALYSES (CONONICAL CORRELATION AND PARTIAL LEAST SQUARE, PLS) TO MODEL AND ASSESS THE ASSOCIATION OF LANDSCAPE METRICS TO SURFACE WATER CHEMICAL AND BIOLOGICAL PROPERTIES USING SAVANNAH RIVER BASIN DATA.

EPA Science Inventory

Many multivariate methods are used in describing and predicting relation; each has its unique usage of categorical and non-categorical data. In multivariate analysis of variance (MANOVA), many response variables (y's) are related to many independent variables that are categorical...

Multivariate Density Estimation and Remote Sensing

NASA Technical Reports Server (NTRS)

Scott, D. W.

1983-01-01

Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Effect of Contact Damage on the Strength of Ceramic Materials.

DTIC Science & Technology

1982-10-01

variables that are important to erosion, and a multivariate , linear regression analysis is used to fit the data to the dimensional analysis. The...of Equations 7 and 8 by a multivariable regression analysis (room tem- perature data) Exponent Regression Standard error Computed coefficient of...1980) 593. WEAVER, Proc. Brit. Ceram. Soc. 22 (1973) 125. 39. P. W. BRIDGMAN, "Dimensional Analaysis ", (Yale 18. R. W. RICE, S. W. FREIMAN and P. F