Meta- and statistical analysis of single-case intervention research data: quantitative gifts and a wish list.

PubMed

Kratochwill, Thomas R; Levin, Joel R

2014-04-01

In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Efficiency Analysis: Enhancing the Statistical and Evaluative Power of the Regression-Discontinuity Design.

ERIC Educational Resources Information Center

Madhere, Serge

An analytic procedure, efficiency analysis, is proposed for improving the utility of quantitative program evaluation for decision making. The three features of the procedure are explained: (1) for statistical control, it adopts and extends the regression-discontinuity design; (2) for statistical inferences, it de-emphasizes hypothesis testing in…

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

Analysis of defect structure in silicon. Characterization of samples from UCP ingot 5848-13C

NASA Technical Reports Server (NTRS)

Natesh, R.; Guyer, T.; Stringfellow, G. B.

1982-01-01

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13 C. Important trends were noticed between the measured data, cell efficiency, and diffusion length. Grain boundary substructure appears to have an important effect on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements give statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for QTM analysis was perfected.

Radiomic analysis in prediction of Human Papilloma Virus status.

PubMed

Yu, Kaixian; Zhang, Youyi; Yu, Yang; Huang, Chao; Liu, Rongjie; Li, Tengfei; Yang, Liuqing; Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Zhu, Hongtu

2017-12-01

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.

Integration of Research Studies: Meta-Analysis of Research. Methods of Integrative Analysis; Final Report.

ERIC Educational Resources Information Center

Glass, Gene V.; And Others

Integrative analysis, or what is coming to be known as meta-analysis, is the integration of the findings of many empirical research studies of a topic. Meta-analysis differs from traditional narrative forms of research reviewing in that it is more quantitative and statistical. Thus, the methods of meta-analysis are merely statistical methods,…

The other half of the story: effect size analysis in quantitative research.

PubMed

Maher, Jessica Middlemis; Markey, Jonathan C; Ebert-May, Diane

2013-01-01

Statistical significance testing is the cornerstone of quantitative research, but studies that fail to report measures of effect size are potentially missing a robust part of the analysis. We provide a rationale for why effect size measures should be included in quantitative discipline-based education research. Examples from both biological and educational research demonstrate the utility of effect size for evaluating practical significance. We also provide details about some effect size indices that are paired with common statistical significance tests used in educational research and offer general suggestions for interpreting effect size measures. Finally, we discuss some inherent limitations of effect size measures and provide further recommendations about reporting confidence intervals.

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2014 CFR

2014-07-01

... are highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2013 CFR

2013-07-01

... highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

40 CFR 796.2750 - Sediment and soil adsorption isotherm.

Code of Federal Regulations, 2012 CFR

2012-07-01

... highly reproducible. The test provides excellent quantitative data readily amenable to statistical... combination of methods suitable for the identification and quantitative detection of the parent test chemical... quantitative analysis of the parent chemical. (3) Amount of parent test chemical applied, the amount recovered...

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

Evaluating and Reporting Statistical Power in Counseling Research

ERIC Educational Resources Information Center

Balkin, Richard S.; Sheperis, Carl J.

2011-01-01

Despite recommendations from the "Publication Manual of the American Psychological Association" (6th ed.) to include information on statistical power when publishing quantitative results, authors seldom include analysis or discussion of statistical power. The rationale for discussing statistical power is addressed, approaches to using "G*Power" to…

Characterizing microstructural features of biomedical samples by statistical analysis of Mueller matrix images

NASA Astrophysics Data System (ADS)

He, Honghui; Dong, Yang; Zhou, Jialing; Ma, Hui

2017-03-01

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

DAnTE: a statistical tool for quantitative analysis of –omics data

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

Polpitiya, Ashoka D.; Qian, Weijun; Jaitly, Navdeep

2008-05-03

DAnTE (Data Analysis Tool Extension) is a statistical tool designed to address challenges unique to quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide to protein rollup methods, an extensive array of plotting functions, and a comprehensive ANOVA scheme that can handle unbalanced data and random effects. The Graphical User Interface (GUI) is designed to be very intuitive and user friendly.

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

PubMed

Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

2015-11-03

We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

A new strategy for statistical analysis-based fingerprint establishment: Application to quality assessment of Semen sojae praeparatum.

PubMed

Guo, Hui; Zhang, Zhen; Yao, Yuan; Liu, Jialin; Chang, Ruirui; Liu, Zhao; Hao, Hongyuan; Huang, Taohong; Wen, Jun; Zhou, Tingting

2018-08-30

Semen sojae praeparatum with homology of medicine and food is a famous traditional Chinese medicine. A simple and effective quality fingerprint analysis, coupled with chemometrics methods, was developed for quality assessment of Semen sojae praeparatum. First, similarity analysis (SA) and hierarchical clusting analysis (HCA) were applied to select the qualitative markers, which obviously influence the quality of Semen sojae praeparatum. 21 chemicals were selected and characterized by high resolution ion trap/time-of-flight mass spectrometry (LC-IT-TOF-MS). Subsequently, principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to select the quantitative markers of Semen sojae praeparatum samples from different origins. Moreover, 11 compounds with statistical significance were determined quantitatively, which provided an accurate and informative data for quality evaluation. This study proposes a new strategy for "statistic analysis-based fingerprint establishment", which would be a valuable reference for further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Secondary Analysis of Qualitative Data.

ERIC Educational Resources Information Center

Turner, Paul D.

The reanalysis of data to answer the original research question with better statistical techniques or to answer new questions with old data is not uncommon in quantitative studies. Meta analysis and research syntheses have increased with the increase in research using similar statistical analyses, refinements of analytical techniques, and the…

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

An Investigation of Civilians Preparedness to Compete with Individuals with Military Experience for Army Board Select Acquisition Positions

DTIC Science & Technology

2017-05-25

37 Research Design ... research employed a mixed research methodology – quantitative with descriptive statistical analysis and qualitative with a thematic analysis approach...mixed research methodology – quantitative and qualitative, using interviews to collect the data. The interviews included demographic and open-ended

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

A review of empirical research related to the use of small quantitative samples in clinical outcome scale development.

PubMed

Houts, Carrie R; Edwards, Michael C; Wirth, R J; Deal, Linda S

2016-11-01

There has been a notable increase in the advocacy of using small-sample designs as an initial quantitative assessment of item and scale performance during the scale development process. This is particularly true in the development of clinical outcome assessments (COAs), where Rasch analysis has been advanced as an appropriate statistical tool for evaluating the developing COAs using a small sample. We review the benefits such methods are purported to offer from both a practical and statistical standpoint and detail several problematic areas, including both practical and statistical theory concerns, with respect to the use of quantitative methods, including Rasch-consistent methods, with small samples. The feasibility of obtaining accurate information and the potential negative impacts of misusing large-sample statistical methods with small samples during COA development are discussed.

Analysis of defect structure in silicon. Characterization of SEMIX material. Silicon sheet growth development for the large area silicon sheet task of the low-cost solar array project

NASA Technical Reports Server (NTRS)

Natesh, R.; Stringfellow, G. B.; Virkar, A. V.; Dunn, J.; Guyer, T.

1983-01-01

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13C. Important correlation was obtained between defect densities, cell efficiency, and diffusion length. Grain boundary substructure displayed a strong influence on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements gave statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for quantimet quantitative image analyzer (QTM) analysis was perfected and is used routinely. The relationships between hole mobility and grain boundary density was determined. Mobility was measured using the van der Pauw technique, and grain boundary density was measured using quantitative microscopy technique. Mobility was found to decrease with increasing grain boundary density.

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data.

PubMed

Vu, Trung N; Valkenborg, Dirk; Smets, Koen; Verwaest, Kim A; Dommisse, Roger; Lemière, Filip; Verschoren, Alain; Goethals, Bart; Laukens, Kris

2011-10-20

Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline. We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data. The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from http://code.google.com/p/speaq/.

Challenge in Enhancing the Teaching and Learning of Variable Measurements in Quantitative Research

ERIC Educational Resources Information Center

Kee, Chang Peng; Osman, Kamisah; Ahmad, Fauziah

2013-01-01

Statistical analysis is one component that cannot be avoided in a quantitative research. Initial observations noted that students in higher education institution faced difficulty analysing quantitative data which were attributed to the confusions of various variable measurements. This paper aims to compare the outcomes of two approaches applied in…

Multivariate analysis, mass balance techniques, and statistical tests as tools in igneous petrology: application to the Sierra de las Cruces volcanic range (Mexican Volcanic Belt).

PubMed

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures).

A Quantitative Features Analysis of Recommended No- and Low-Cost Preschool E-Books

ERIC Educational Resources Information Center

Parette, Howard P.; Blum, Craig; Luthin, Katie

2015-01-01

In recent years, recommended e-books have drawn increasing attention from early childhood education professionals. This study applied a quantitative descriptive features analysis of cost (n = 70) and no-cost (n = 60) e-books recommended by the Texas Computer Education Association. While t tests revealed no statistically significant differences…

Quantitative Analysis of the Interdisciplinarity of Applied Mathematics.

PubMed

Xie, Zheng; Duan, Xiaojun; Ouyang, Zhenzheng; Zhang, Pengyuan

2015-01-01

The increasing use of mathematical techniques in scientific research leads to the interdisciplinarity of applied mathematics. This viewpoint is validated quantitatively here by statistical and network analysis on the corpus PNAS 1999-2013. A network describing the interdisciplinary relationships between disciplines in a panoramic view is built based on the corpus. Specific network indicators show the hub role of applied mathematics in interdisciplinary research. The statistical analysis on the corpus content finds that algorithms, a primary topic of applied mathematics, positively correlates, increasingly co-occurs, and has an equilibrium relationship in the long-run with certain typical research paradigms and methodologies. The finding can be understood as an intrinsic cause of the interdisciplinarity of applied mathematics.

[Confidence interval or p-value--similarities and differences between two important methods of statistical inference of quantitative studies].

PubMed

Harari, Gil

2014-01-01

Statistic significance, also known as p-value, and CI (Confidence Interval) are common statistics measures and are essential for the statistical analysis of studies in medicine and life sciences. These measures provide complementary information about the statistical probability and conclusions regarding the clinical significance of study findings. This article is intended to describe the methodologies, compare between the methods, assert their suitability for the different needs of study results analysis and to explain situations in which each method should be used.

[A comparison of convenience sampling and purposive sampling].

PubMed

Suen, Lee-Jen Wu; Huang, Hui-Man; Lee, Hao-Hsien

2014-06-01

Convenience sampling and purposive sampling are two different sampling methods. This article first explains sampling terms such as target population, accessible population, simple random sampling, intended sample, actual sample, and statistical power analysis. These terms are then used to explain the difference between "convenience sampling" and purposive sampling." Convenience sampling is a non-probabilistic sampling technique applicable to qualitative or quantitative studies, although it is most frequently used in quantitative studies. In convenience samples, subjects more readily accessible to the researcher are more likely to be included. Thus, in quantitative studies, opportunity to participate is not equal for all qualified individuals in the target population and study results are not necessarily generalizable to this population. As in all quantitative studies, increasing the sample size increases the statistical power of the convenience sample. In contrast, purposive sampling is typically used in qualitative studies. Researchers who use this technique carefully select subjects based on study purpose with the expectation that each participant will provide unique and rich information of value to the study. As a result, members of the accessible population are not interchangeable and sample size is determined by data saturation not by statistical power analysis.

Diagnostic value of (99m)Tc-3PRGD2 scintimammography for differentiation of malignant from benign breast lesions: Comparison of visual and semi-quantitative analysis.

PubMed

Chen, Qianqian; Xie, Qian; Zhao, Min; Chen, Bin; Gao, Shi; Zhang, Haishan; Xing, Hua; Ma, Qingjie

2015-01-01

To compare the diagnostic value of visual and semi-quantitative analysis of technetium-99m-poly-ethylene glycol, 4-arginine-glycine-aspartic acid ((99m)Tc-3PRGD2) scintimammography (SMG) for better differentiation of benign from malignant breast masses, and also investigate the incremental role of semi-quantitative index of SMG. A total of 72 patients with breast lesions were included in the study. Technetium-99m-3PRGD2 SMG was performed with single photon emission computed tomography (SPET) at 60 min after intravenous injection of 749 ± 86MBq of the radiotracer. Images were evaluated by visual interpretation and semi-quantitative indices of tumor to non-tumor (T/N) ratios, which were compared with pathology results. Receiver operating characteristics (ROC) curve analyses were performed to determine the optimal visual grade, to calculate cut-off values of semi-quantitative indices, and to compare visual and semi-quantitative diagnostic values. Among the 72 patients, 89 lesions were confirmed by histopathology after fine needle aspiration biopsy or surgery, 48 malignant and 41 benign lesions. The mean T/N ratio of (99m)Tc-3PRGD2 SMG in malignant lesions was significantly higher than that in benign lesions (P<0.05). When grade 2 of the disease was used as cut-off value for the detection of primary breast cancer, the sensitivity, specificity and accuracy were 81.3%, 70.7%, and 76.4%, respectively. When a T/N ratio of 2.01 was used as cut-off value, the sensitivity, specificity and accuracy were 79.2%, 75.6%, and 77.5%, respectively. According to ROC analysis, the area under the curve for semi-quantitative analysis was higher than that for visual analysis, but the statistical difference was not significant (P=0.372). Compared with visual analysis or semi-quantitative analysis alone, the sensitivity, specificity and accuracy of visual analysis combined with semi-quantitative analysis in diagnosing primary breast cancer were higher, being: 87.5%, 82.9%, and 85.4%, respectively. The area under the curve was 0.891. Results of the present study suggest that the semi-quantitative and visual analysis statistically showed similar results. The semi-quantitative analysis provided incremental value additive to visual analysis of (99m)Tc-3PRGD2 SMG for the detection of breast cancer. It seems from our results that, when the tumor was located in the medial part of the breast, the semi-quantitative analysis gave better diagnostic results.

Clinical applications of a quantitative analysis of regional lift ventricular wall motion

NASA Technical Reports Server (NTRS)

Leighton, R. F.; Rich, J. M.; Pollack, M. E.; Altieri, P. I.

1975-01-01

Observations were summarized which may have clinical application. These were obtained from a quantitative analysis of wall motion that was used to detect both hypokinesis and tardokinesis in left ventricular cineangiograms. The method was based on statistical comparisons with normal values for regional wall motion derived from the cineangiograms of patients who were found not to have heart disease.

Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain

PubMed Central

Quinkert, Amy Wells; Vimal, Vivek; Weil, Zachary M.; Reeke, George N.; Schiff, Nicholas D.; Banavar, Jayanth R.; Pfaff, Donald W.

2011-01-01

We review a concept of the most primitive, fundamental function of the vertebrate CNS, generalized arousal (GA). Three independent lines of evidence indicate the existence of GA: statistical, genetic, and mechanistic. Here we ask, is this concept amenable to quantitative analysis? Answering in the affirmative, four quantitative approaches have proven useful: (i) factor analysis, (ii) information theory, (iii) deterministic chaos, and (iv) application of a Gaussian equation. It strikes us that, to date, not just one but at least four different quantitative approaches seem necessary for describing different aspects of scientific work on GA. PMID:21555568

Stable Isotope Quantitative N-Glycan Analysis by Liquid Separation Techniques and Mass Spectrometry.

PubMed

Mittermayr, Stefan; Albrecht, Simone; Váradi, Csaba; Millán-Martín, Silvia; Bones, Jonathan

2017-01-01

Liquid phase separation analysis and subsequent quantitation remains a challenging task for protein-derived oligosaccharides due to their inherent structural complexity and diversity. Incomplete resolution or co-detection of multiple glycan species complicates peak area-based quantitation and associated statistical analysis when optical detection methods are used. The approach outlined herein describes the utilization of stable isotope variants of commonly used fluorescent tags that allow for mass-based glycan identification and relative quantitation following separation by liquid chromatography (LC) or capillary electrophoresis (CE). Comparability assessment of glycoprotein-derived oligosaccharides is performed by derivatization with commercially available isotope variants of 2-aminobenzoic acid or aniline and analysis by LC- and CE-mass spectrometry. Quantitative information is attained from the extracted ion chromatogram/electropherogram ratios generated from the light and heavy isotope clusters.

Ketamine as a novel treatment for major depressive disorder and bipolar depression: a systematic review and quantitative meta-analysis.

PubMed

Lee, Ellen E; Della Selva, Megan P; Liu, Anson; Himelhoch, Seth

2015-01-01

Given the significant disability, morbidity and mortality associated with depression, the promising recent trials of ketamine highlight a novel intervention. A meta-analysis was conducted to assess the efficacy of ketamine in comparison with placebo for the reduction of depressive symptoms in patients who meet criteria for a major depressive episode. Two electronic databases were searched in September 2013 for English-language studies that were randomized placebo-controlled trials of ketamine treatment for patients with major depressive disorder or bipolar depression and utilized a standardized rating scale. Studies including participants receiving electroconvulsive therapy and adolescent/child participants were excluded. Five studies were included in the quantitative meta-analysis. The quantitative meta-analysis showed that ketamine significantly reduced depressive symptoms. The overall effect size at day 1 was large and statistically significant with an overall standardized mean difference of 1.01 (95% confidence interval 0.69-1.34) (P<.001), with the effects sustained at 7 days postinfusion. The heterogeneity of the studies was low and not statistically significant, and the funnel plot showed no publication bias. The large and statistically significant effect of ketamine on depressive symptoms supports a promising, new and effective pharmacotherapy with rapid onset, high efficacy and good tolerability. Copyright © 2015. Published by Elsevier Inc.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

LANDSCAPE STRUCTURE AND ESTUARINE CONDITION IN THE MID-ATLANTIC REGION OF THE UNITED STATES: I. DEVELOPING QUANTITATIVE RELATIONSHIPS

EPA Science Inventory

In a previously published study, quantitative relationships were developed between landscape metrics and sediment contamination for 25 small estuarine systems within Chesapeake Bay. Nonparametric statistical analysis (rank transformation) was used to develop an empirical relation...

Multivariate Analysis, Mass Balance Techniques, and Statistical Tests as Tools in Igneous Petrology: Application to the Sierra de las Cruces Volcanic Range (Mexican Volcanic Belt)

PubMed Central

Velasco-Tapia, Fernando

2014-01-01

Magmatic processes have usually been identified and evaluated using qualitative or semiquantitative geochemical or isotopic tools based on a restricted number of variables. However, a more complete and quantitative view could be reached applying multivariate analysis, mass balance techniques, and statistical tests. As an example, in this work a statistical and quantitative scheme is applied to analyze the geochemical features for the Sierra de las Cruces (SC) volcanic range (Mexican Volcanic Belt). In this locality, the volcanic activity (3.7 to 0.5 Ma) was dominantly dacitic, but the presence of spheroidal andesitic enclaves and/or diverse disequilibrium features in majority of lavas confirms the operation of magma mixing/mingling. New discriminant-function-based multidimensional diagrams were used to discriminate tectonic setting. Statistical tests of discordancy and significance were applied to evaluate the influence of the subducting Cocos plate, which seems to be rather negligible for the SC magmas in relation to several major and trace elements. A cluster analysis following Ward's linkage rule was carried out to classify the SC volcanic rocks geochemical groups. Finally, two mass-balance schemes were applied for the quantitative evaluation of the proportion of the end-member components (dacitic and andesitic magmas) in the comingled lavas (binary mixtures). PMID:24737994

Distribution of lod scores in oligogenic linkage analysis.

PubMed

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

How to Perform a Systematic Review and Meta-analysis of Diagnostic Imaging Studies.

PubMed

Cronin, Paul; Kelly, Aine Marie; Altaee, Duaa; Foerster, Bradley; Petrou, Myria; Dwamena, Ben A

2018-05-01

A systematic review is a comprehensive search, critical evaluation, and synthesis of all the relevant studies on a specific (clinical) topic that can be applied to the evaluation of diagnostic and screening imaging studies. It can be a qualitative or a quantitative (meta-analysis) review of available literature. A meta-analysis uses statistical methods to combine and summarize the results of several studies. In this review, a 12-step approach to performing a systematic review (and meta-analysis) is outlined under the four domains: (1) Problem Formulation and Data Acquisition, (2) Quality Appraisal of Eligible Studies, (3) Statistical Analysis of Quantitative Data, and (4) Clinical Interpretation of the Evidence. This review is specifically geared toward the performance of a systematic review and meta-analysis of diagnostic test accuracy (imaging) studies. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

PubMed

Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

2015-02-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra.

PubMed

Shin, S M; Kim, Y-I; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. The sample included 24 female and 19 male patients with hand-wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

PubMed Central

Shin, S M; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand–wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index. PMID:25411713

Some Epistemological Considerations Concerning Quantitative Analysis

ERIC Educational Resources Information Center

Dobrescu, Emilian

2008-01-01

This article presents the author's address at the 2007 "Journal of Applied Quantitative Methods" ("JAQM") prize awarding festivity. The festivity was included in the opening of the 4th International Conference on Applied Statistics, November 22, 2008, Bucharest, Romania. In the address, the author reflects on three theses that…

Statistical significance of trace evidence matches using independent physicochemical measurements

NASA Astrophysics Data System (ADS)

Almirall, Jose R.; Cole, Michael; Furton, Kenneth G.; Gettinby, George

1997-02-01

A statistical approach to the significance of glass evidence is proposed using independent physicochemical measurements and chemometrics. Traditional interpretation of the significance of trace evidence matches or exclusions relies on qualitative descriptors such as 'indistinguishable from,' 'consistent with,' 'similar to' etc. By performing physical and chemical measurements with are independent of one another, the significance of object exclusions or matches can be evaluated statistically. One of the problems with this approach is that the human brain is excellent at recognizing and classifying patterns and shapes but performs less well when that object is represented by a numerical list of attributes. Chemometrics can be employed to group similar objects using clustering algorithms and provide statistical significance in a quantitative manner. This approach is enhanced when population databases exist or can be created and the data in question can be evaluated given these databases. Since the selection of the variables used and their pre-processing can greatly influence the outcome, several different methods could be employed in order to obtain a more complete picture of the information contained in the data. Presently, we report on the analysis of glass samples using refractive index measurements and the quantitative analysis of the concentrations of the metals: Mg, Al, Ca, Fe, Mn, Ba, Sr, Ti and Zr. The extension of this general approach to fiber and paint comparisons also is discussed. This statistical approach should not replace the current interpretative approaches to trace evidence matches or exclusions but rather yields an additional quantitative measure. The lack of sufficient general population databases containing the needed physicochemical measurements and the potential for confusion arising from statistical analysis currently hamper this approach and ways of overcoming these obstacles are presented.

QTest: Quantitative Testing of Theories of Binary Choice.

PubMed

Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

An Automated System for Chromosome Analysis

NASA Technical Reports Server (NTRS)

Castleman, K. R.; Melnyk, J. H.

1976-01-01

The design, construction, and testing of a complete system to produce karyotypes and chromosome measurement data from human blood samples, and to provide a basis for statistical analysis of quantitative chromosome measurement data are described.

Quantitative research.

PubMed

Watson, Roger

2015-04-01

This article describes the basic tenets of quantitative research. The concepts of dependent and independent variables are addressed and the concept of measurement and its associated issues, such as error, reliability and validity, are explored. Experiments and surveys – the principal research designs in quantitative research – are described and key features explained. The importance of the double-blind randomised controlled trial is emphasised, alongside the importance of longitudinal surveys, as opposed to cross-sectional surveys. Essential features of data storage are covered, with an emphasis on safe, anonymous storage. Finally, the article explores the analysis of quantitative data, considering what may be analysed and the main uses of statistics in analysis.

A simple approach to quantitative analysis using three-dimensional spectra based on selected Zernike moments.

PubMed

Zhai, Hong Lin; Zhai, Yue Yuan; Li, Pei Zhen; Tian, Yue Li

2013-01-21

A very simple approach to quantitative analysis is proposed based on the technology of digital image processing using three-dimensional (3D) spectra obtained by high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD). As the region-based shape features of a grayscale image, Zernike moments with inherently invariance property were employed to establish the linear quantitative models. This approach was applied to the quantitative analysis of three compounds in mixed samples using 3D HPLC-DAD spectra, and three linear models were obtained, respectively. The correlation coefficients (R(2)) for training and test sets were more than 0.999, and the statistical parameters and strict validation supported the reliability of established models. The analytical results suggest that the Zernike moment selected by stepwise regression can be used in the quantitative analysis of target compounds. Our study provides a new idea for quantitative analysis using 3D spectra, which can be extended to the analysis of other 3D spectra obtained by different methods or instruments.

Engaging Business Students in Quantitative Skills Development

ERIC Educational Resources Information Center

Cronin, Anthony; Carroll, Paula

2015-01-01

In this paper the complex problems of developing quantitative and analytical skills in undergraduate first year, first semester business students are addressed. An action research project, detailing how first year business students perceive the relevance of data analysis and inferential statistics in light of the economic downturn and the…

Improving Student Retention and Performance in Quantitative Courses Using Clickers

ERIC Educational Resources Information Center

Liu, Wallace C.; Stengel, Donald N.

2011-01-01

Clickers offer instructors of mathematics-related courses an opportunity to involve students actively in class sessions while diminishing the embarrassment of being wrong. This paper reports on the use of clickers in two university-level courses in quantitative analysis and business statistics. Results for student retention and examination…

mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry.

PubMed

Teo, Guoshou; Kim, Sinae; Tsou, Chih-Chiang; Collins, Ben; Gingras, Anne-Claude; Nesvizhskii, Alexey I; Choi, Hyungwon

2015-11-03

Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome. The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparative study of contrast-enhanced ultrasound qualitative and quantitative analysis for identifying benign and malignant breast tumor lumps.

PubMed

Liu, Jian; Gao, Yun-Hua; Li, Ding-Dong; Gao, Yan-Chun; Hou, Ling-Mi; Xie, Ting

2014-01-01

To compare the value of contrast-enhanced ultrasound (CEUS) qualitative and quantitative analysis in the identification of breast tumor lumps. Qualitative and quantitative indicators of CEUS for 73 cases of breast tumor lumps were retrospectively analyzed by univariate and multivariate approaches. Logistic regression was applied and ROC curves were drawn for evaluation and comparison. The CEUS qualitative indicator-generated regression equation contained three indicators, namely enhanced homogeneity, diameter line expansion and peak intensity grading, which demonstrated prediction accuracy for benign and malignant breast tumor lumps of 91.8%; the quantitative indicator-generated regression equation only contained one indicator, namely the relative peak intensity, and its prediction accuracy was 61.5%. The corresponding areas under the ROC curve for qualitative and quantitative analyses were 91.3% and 75.7%, respectively, which exhibited a statistically significant difference by the Z test (P<0.05). The ability of CEUS qualitative analysis to identify breast tumor lumps is better than with quantitative analysis.

Final Report for Dynamic Models for Causal Analysis of Panel Data. Models for Change in Quantitative Variables, Part II Scholastic Models. Part II, Chapter 4.

ERIC Educational Resources Information Center

Hannan, Michael T.

This document is part of a series of chapters described in SO 011 759. Stochastic models for the sociological analysis of change and the change process in quantitative variables are presented. The author lays groundwork for the statistical treatment of simple stochastic differential equations (SDEs) and discusses some of the continuities of…

Quantitative 3D analysis of bone in hip osteoarthritis using clinical computed tomography.

PubMed

Turmezei, Tom D; Treece, Graham M; Gee, Andrew H; Fotiadou, Anastasia F; Poole, Kenneth E S

2016-07-01

To assess the relationship between proximal femoral cortical bone thickness and radiological hip osteoarthritis using quantitative 3D analysis of clinical computed tomography (CT) data. Image analysis was performed on clinical CT imaging data from 203 female volunteers with a technique called cortical bone mapping (CBM). Colour thickness maps were created for each proximal femur. Statistical parametric mapping was performed to identify statistically significant differences in cortical bone thickness that corresponded with the severity of radiological hip osteoarthritis. Kellgren and Lawrence (K&L) grade, minimum joint space width (JSW) and a novel CT-based osteophyte score were also blindly assessed from the CT data. For each increase in K&L grade, cortical thickness increased by up to 25 % in distinct areas of the superolateral femoral head-neck junction and superior subchondral bone plate. For increasing severity of CT osteophytes, the increase in cortical thickness was more circumferential, involving a wider portion of the head-neck junction, with up to a 7 % increase in cortical thickness per increment in score. Results were not significant for minimum JSW. These findings indicate that quantitative 3D analysis of the proximal femur can identify changes in cortical bone thickness relevant to structural hip osteoarthritis. • CT is being increasingly used to assess bony involvement in osteoarthritis • CBM provides accurate and reliable quantitative analysis of cortical bone thickness • Cortical bone is thicker at the superior femoral head-neck with worse osteoarthritis • Regions of increased thickness co-locate with impingement and osteophyte formation • Quantitative 3D bone analysis could enable clinical disease prediction and therapy development.

Global scaling for semi-quantitative analysis in FP-CIT SPECT.

PubMed

Kupitz, D; Apostolova, I; Lange, C; Ulrich, G; Amthauer, H; Brenner, W; Buchert, R

2014-01-01

Semi-quantitative characterization of dopamine transporter availability from single photon emission computed tomography (SPECT) with 123I-ioflupane (FP-CIT) is based on uptake ratios relative to a reference region. The aim of this study was to evaluate the whole brain as reference region for semi-quantitative analysis of FP-CIT SPECT. The rationale was that this might reduce statistical noise associated with the estimation of non-displaceable FP-CIT uptake. 150 FP-CIT SPECTs were categorized as neurodegenerative or non-neurodegenerative by an expert. Semi-quantitative analysis of specific binding ratios (SBR) was performed with a custom-made tool based on the Statistical Parametric Mapping software package using predefined regions of interest (ROIs) in the anatomical space of the Montreal Neurological Institute. The following reference regions were compared: predefined ROIs for frontal and occipital lobe and whole brain (without striata, thalamus and brainstem). Tracer uptake in the reference region was characterized by the mean, median or 75th percentile of its voxel intensities. The area (AUC) under the receiver operating characteristic curve was used as performance measure. The highest AUC of 0.973 was achieved by the SBR of the putamen with the 75th percentile in the whole brain as reference. The lowest AUC for the putamen SBR of 0.937 was obtained with the mean in the frontal lobe as reference. We recommend the 75th percentile in the whole brain as reference for semi-quantitative analysis in FP-CIT SPECT. This combination provided the best agreement of the semi-quantitative analysis with visual evaluation of the SPECT images by an expert and, therefore, is appropriate to support less experienced physicians.

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software.

PubMed

Moon, Andres; Smith, Geoffrey H; Kong, Jun; Rogers, Thomas E; Ellis, Carla L; Farris, Alton B Brad

2018-02-01

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm 2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling "maxima" criteria for CD3 expression (custom CD3+ cells/mm 2 ). Based on visual inspections of "markup" images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide "flow cytometry" that can facilitate additional diagnostic accuracy in tissue-based assessments.

Econophysical visualization of Adam Smith’s invisible hand

NASA Astrophysics Data System (ADS)

Cohen, Morrel H.; Eliazar, Iddo I.

2013-02-01

Consider a complex system whose macrostate is statistically observable, but yet whose operating mechanism is an unknown black-box. In this paper we address the problem of inferring, from the system’s macrostate statistics, the system’s intrinsic force yielding the observed statistics. The inference is established via two diametrically opposite approaches which result in the very same intrinsic force: a top-down approach based on the notion of entropy, and a bottom-up approach based on the notion of Langevin dynamics. The general results established are applied to the problem of visualizing the intrinsic socioeconomic force-Adam Smith’s invisible hand-shaping the distribution of wealth in human societies. Our analysis yields quantitative econophysical representations of figurative socioeconomic forces, quantitative definitions of “poor” and “rich”, and a quantitative characterization of the “poor-get-poorer” and the “rich-get-richer” phenomena.

STATISTICAL ANALYSIS OF SPECTROPHOTOMETRIC DETERMINATIONS OF BORON; Estudo Estatistico de Determinacoes Espectrofotometricas de Boro

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

Lima, F.W.; Pagano, C.; Schneiderman, B.

1959-07-01

Boron can be determined quantitatively by absorption spectrophotometry of solutions of the red compound formed by the reaction of boric acid with curcumin. This reaction is affected by various factors, some of which can be detected easily in the data interpretation. Others, however, provide more difficulty. The application of modern statistical method to the study of the influence of these factors on the quantitative determination of boron is presented. These methods provide objective ways of establishing significant effects of the factors involved. (auth)

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales

Treesearch

Lisa A. Schulte; David J. Mladenoff; Erik V. Nordheim

2002-01-01

We developed a quantitative and replicable classification system to improve understanding of historical composition and structure within northern Wisconsin's forests. The classification system was based on statistical cluster analysis and two forest metrics, relative dominance (% basal area) and relative importance (mean of relative dominance and relative density...

Analysis of the sleep quality of elderly people using biomedical signals.

PubMed

Moreno-Alsasua, L; Garcia-Zapirain, B; Mendez-Zorrilla, A

2015-01-01

This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the level of a person's rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

PubMed

Ulgen, Ayse; Han, Zhihua; Li, Wentian

2003-12-31

We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

The cutting edge - Micro-CT for quantitative toolmark analysis of sharp force trauma to bone.

PubMed

Norman, D G; Watson, D G; Burnett, B; Fenne, P M; Williams, M A

2018-02-01

Toolmark analysis involves examining marks created on an object to identify the likely tool responsible for creating those marks (e.g., a knife). Although a potentially powerful forensic tool, knife mark analysis is still in its infancy and the validation of imaging techniques as well as quantitative approaches is ongoing. This study builds on previous work by simulating real-world stabbings experimentally and statistically exploring quantitative toolmark properties, such as cut mark angle captured by micro-CT imaging, to predict the knife responsible. In Experiment 1 a mechanical stab rig and two knives were used to create 14 knife cut marks on dry pig ribs. The toolmarks were laser and micro-CT scanned to allow for quantitative measurements of numerous toolmark properties. The findings from Experiment 1 demonstrated that both knives produced statistically different cut mark widths, wall angle and shapes. Experiment 2 examined knife marks created on fleshed pig torsos with conditions designed to better simulate real-world stabbings. Eight knives were used to generate 64 incision cut marks that were also micro-CT scanned. Statistical exploration of these cut marks suggested that knife type, serrated or plain, can be predicted from cut mark width and wall angle. Preliminary results suggest that knives type can be predicted from cut mark width, and that knife edge thickness correlates with cut mark width. An additional 16 cut marks walls were imaged for striation marks using scanning electron microscopy with results suggesting that this approach might not be useful for knife mark analysis. Results also indicated that observer judgements of cut mark shape were more consistent when rated from micro-CT images than light microscopy images. The potential to combine micro-CT data, medical grade CT data and photographs to develop highly realistic virtual models for visualisation and 3D printing is also demonstrated. This is the first study to statistically explore simulated real-world knife marks imaged by micro-CT to demonstrate the potential of quantitative approaches in knife mark analysis. Findings and methods presented in this study are relevant to both forensic toolmark researchers as well as practitioners. Limitations of the experimental methodologies and imaging techniques are discussed, and further work is recommended. Copyright © 2017 Elsevier B.V. All rights reserved.

FT. Sam 91 Whiskey Combat Medic Medical Simulation Training Quantitative Integration Enhancement Program

DTIC Science & Technology

2011-07-01

joined the project team in the statistical and research coordination role. Dr. Collin is an employee at the University of Pittsburgh. A successful...3. Submit to Ft. Detrick Completed Milestone: Statistical analysis planning 1. Review planned data metrics and data gathering tools...approach to performance assessment for continuous quality improvement.  Analyzing data with modern statistical techniques to determine the

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets.

PubMed

Sornborger, Andrew; Broder, Josef; Majumder, Anirban; Srinivasamoorthy, Ganesh; Porter, Erika; Reagin, Sean S; Keith, Charles; Lauderdale, James D

2008-09-01

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.

A methodological analysis of chaplaincy research: 2000-2009.

PubMed

Galek, Kathleen; Flannelly, Kevin J; Jankowski, Katherine R B; Handzo, George F

2011-01-01

The present article presents a comprehensive review and analysis of quantitative research conducted in the United States on chaplaincy and closely related topics published between 2000 and 2009. A combined search strategy identified 49 quantitative studies in 13 journals. The analysis focuses on the methodological sophistication of the studies, compared to earlier research on chaplaincy and pastoral care. Cross-sectional surveys of convenience samples still dominate the field, but sample sizes have increased somewhat over the past three decades. Reporting of the validity and reliability of measures continues to be low, although reporting of response rates has improved. Improvements in the use of inferential statistics and statistical controls were also observed, compared to previous research. The authors conclude that more experimental research is needed on chaplaincy, along with an increased use of hypothesis testing, regardless of the research designs that are used.

Advantages of Social Network Analysis in Educational Research

ERIC Educational Resources Information Center

Ushakov, K. M.; Kukso, K. N.

2015-01-01

Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Jennie Jorgenson | NREL

Science.gov Websites

Quantitative and statistical analysis Power grid topology of the Western Interconnection Energy storage for grid applications Research Interests Understanding the implications of high penetrations of renewable

QTest: Quantitative Testing of Theories of Binary Choice

PubMed Central

Regenwetter, Michel; Davis-Stober, Clintin P.; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences. PMID:24999495

Quantification of integrated HIV DNA by repetitive-sampling Alu-HIV PCR on the basis of poisson statistics.

PubMed

De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos

2014-06-01

Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

PubMed

Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Van Dorssaeler, Alain; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

2016-01-30

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

QUANTITATIVE IMAGING AND STATISTICAL ANALYSIS OF FLUORESCENCE IN SITU HYBRIDIZATION (FISH) OF AUREOBASIDIUM PULLULANS. (R823845)

EPA Science Inventory

Abstract

Image and multifactorial statistical analyses were used to evaluate the intensity of fluorescence signal from cells of three strains of A. pullulans and one strain of Rhodosporidium toruloides, as an outgroup, hybridized with either a universal o...

LAKE DATA ANALYSIS AND NUTRIENT BUDGET MODELING

EPA Science Inventory

Several quantitative methods that may be useful for lake trophic quality management planning are discussed and illustrated. An emphasis is placed on scientific methods in research, data analysis, and modeling. Proper use of statistical methods is also stressed, along with conside...

Quantitative Analysis of Venus Radar Backscatter Data in ArcGIS

NASA Technical Reports Server (NTRS)

Long, S. M.; Grosfils, E. B.

2005-01-01

Ongoing mapping of the Ganiki Planitia (V14) quadrangle of Venus and definition of material units has involved an integrated but qualitative analysis of Magellan radar backscatter images and topography using standard geomorphological mapping techniques. However, such analyses do not take full advantage of the quantitative information contained within the images. Analysis of the backscatter coefficient allows a much more rigorous statistical comparison between mapped units, permitting first order selfsimilarity tests of geographically separated materials assigned identical geomorphological labels. Such analyses cannot be performed directly on pixel (DN) values from Magellan backscatter images, because the pixels are scaled to the Muhleman law for radar echoes on Venus and are not corrected for latitudinal variations in incidence angle. Therefore, DN values must be converted based on pixel latitude back to their backscatter coefficient values before accurate statistical analysis can occur. Here we present a method for performing the conversions and analysis of Magellan backscatter data using commonly available ArcGIS software and illustrate the advantages of the process for geological mapping.

Characterization of breast lesion using T1-perfusion magnetic resonance imaging: Qualitative vs. quantitative analysis.

PubMed

Thakran, S; Gupta, P K; Kabra, V; Saha, I; Jain, P; Gupta, R K; Singh, A

2018-06-14

The objective of this study was to quantify the hemodynamic parameters using first pass analysis of T 1 -perfusion magnetic resonance imaging (MRI) data of human breast and to compare these parameters with the existing tracer kinetic parameters, semi-quantitative and qualitative T 1 -perfusion analysis in terms of lesion characterization. MRI of the breast was performed in 50 women (mean age, 44±11 [SD] years; range: 26-75) years with a total of 15 benign and 35 malignant breast lesions. After pre-processing, T 1 -perfusion MRI data was analyzed using qualitative approach by two radiologists (visual inspection of the kinetic curve into types I, II or III), semi-quantitative (characterization of kinetic curve types using empirical parameters), generalized-tracer-kinetic-model (tracer kinetic parameters) and first pass analysis (hemodynamic-parameters). Chi-squared test, t-test, one-way analysis-of-variance (ANOVA) using Bonferroni post-hoc test and receiver-operating-characteristic (ROC) curve were used for statistical analysis. All quantitative parameters except leakage volume (Ve), qualitative (type-I and III) and semi-quantitative curves (type-I and III) provided significant differences (P<0.05) between benign and malignant lesions. Kinetic parameters, particularly volume transfer coefficient (K trans ) provided a significant difference (P<0.05) between all grades except grade-II vs III. The hemodynamic parameter (relative-leakage-corrected-breast-blood-volume [rBBVcorr) provided a statistically significant difference (P<0.05) between all grades. It also provided highest sensitivity and specificity among all parameters in differentiation between different grades of malignant breast lesions. Quantitative parameters, particularly rBBVcorr and K trans provided similar sensitivity and specificity in differentiating benign from malignant breast lesions for this cohort. Moreover, rBBVcorr provided better differentiation between different grades of malignant breast lesions among all the parameters. Copyright © 2018. Published by Elsevier Masson SAS.

Condenser: a statistical aggregation tool for multi-sample quantitative proteomic data from Matrix Science Mascot Distiller™.

PubMed

Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan

2014-05-30

We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

Chen, Yi-Hau

2017-01-01

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

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

PubMed

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

2017-06-01

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

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

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

PubMed

Friedman, David B

2012-01-01

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

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Assessment of statistical uncertainty in the quantitative analysis of solid samples in motion using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Cabalín, L. M.; González, A.; Ruiz, J.; Laserna, J. J.

2010-08-01

Statistical uncertainty in the quantitative analysis of solid samples in motion by laser-induced breakdown spectroscopy (LIBS) has been assessed. For this purpose, a LIBS demonstrator was designed and constructed in our laboratory. The LIBS system consisted of a laboratory-scale conveyor belt, a compact optical module and a Nd:YAG laser operating at 532 nm. The speed of the conveyor belt was variable and could be adjusted up to a maximum speed of 2 m s - 1 . Statistical uncertainty in the analytical measurements was estimated in terms of precision (reproducibility and repeatability) and accuracy. The results obtained by LIBS on shredded scrap samples under real conditions have demonstrated that the analytical precision and accuracy of LIBS is dependent on the sample geometry, position on the conveyor belt and surface cleanliness. Flat, relatively clean scrap samples exhibited acceptable reproducibility and repeatability; by contrast, samples with an irregular shape or a dirty surface exhibited a poor relative standard deviation.

From the Classroom to the Workplace: How Social Science Students Are Learning to Do Data Analysis for Real

ERIC Educational Resources Information Center

Carter, Jackie; Brown, Mark; Simpson, Kathryn

2017-01-01

In British social science degree programmes, methods courses have a bad press, and statistics courses in particular are not well-liked by most students. A nationally-coordinated, strategic investment in quantitative skills training, Q-Step, is an attempt to address the issues affecting the shortage of quantitatively trained humanities and social…

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

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

ERIC Educational Resources Information Center

Brattin, Barbara C.

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

[Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

PubMed

Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu

2014-05-01

The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

Teaching statistics in biology: using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses.

PubMed

Metz, Anneke M

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.

Agro-ecoregionalization of Iowa using multivariate geographical clustering

Treesearch

Carol L. Williams; William W. Hargrove; Matt Leibman; David E. James

2008-01-01

Agro-ecoregionalization is categorization of landscapes for use in crop suitability analysis, strategic agroeconomic development, risk analysis, and other purposes. Past agro-ecoregionalizations have been subjective, expert opinion driven, crop specific, and unsuitable for statistical extrapolation. Use of quantitative analytical methods provides an opportunity for...

Kolmogorov-Smirnov statistical test for analysis of ZAP-70 expression in B-CLL, compared with quantitative PCR and IgV(H) mutation status.

PubMed

Van Bockstaele, Femke; Janssens, Ann; Piette, Anne; Callewaert, Filip; Pede, Valerie; Offner, Fritz; Verhasselt, Bruno; Philippé, Jan

2006-07-15

ZAP-70 has been proposed as a surrogate marker for immunoglobulin heavy-chain variable region (IgV(H)) mutation status, which is known as a prognostic marker in B-cell chronic lymphocytic leukemia (CLL). The flow cytometric analysis of ZAP-70 suffers from difficulties in standardization and interpretation. We applied the Kolmogorov-Smirnov (KS) statistical test to make analysis more straightforward. We examined ZAP-70 expression by flow cytometry in 53 patients with CLL. Analysis was performed as initially described by Crespo et al. (New England J Med 2003; 348:1764-1775) and alternatively by application of the KS statistical test comparing T cells with B cells. Receiver-operating-characteristics (ROC)-curve analyses were performed to determine the optimal cut-off values for ZAP-70 measured by the two approaches. ZAP-70 protein expression was compared with ZAP-70 mRNA expression measured by a quantitative PCR (qPCR) and with the IgV(H) mutation status. Both flow cytometric analyses correlated well with the molecular technique and proved to be of equal value in predicting the IgV(H) mutation status. Applying the KS test is reproducible, simple, straightforward, and overcomes a number of difficulties encountered in the Crespo-method. The KS statistical test is an essential part of the software delivered with modern routine analytical flow cytometers and is well suited for analysis of ZAP-70 expression in CLL. (c) 2006 International Society for Analytical Cytology.

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

PubMed

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: Guidelines and statistical methodology

PubMed Central

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2017-01-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes. PMID:24872353

A quantitative study of nanoparticle skin penetration with interactive segmentation.

PubMed

Lee, Onseok; Lee, See Hyun; Jeong, Sang Hoon; Kim, Jaeyoung; Ryu, Hwa Jung; Oh, Chilhwan; Son, Sang Wook

2016-10-01

In the last decade, the application of nanotechnology techniques has expanded within diverse areas such as pharmacology, medicine, and optical science. Despite such wide-ranging possibilities for implementation into practice, the mechanisms behind nanoparticle skin absorption remain unknown. Moreover, the main mode of investigation has been qualitative analysis. Using interactive segmentation, this study suggests a method of objectively and quantitatively analyzing the mechanisms underlying the skin absorption of nanoparticles. Silica nanoparticles (SNPs) were assessed using transmission electron microscopy and applied to the human skin equivalent model. Captured fluorescence images of this model were used to evaluate degrees of skin penetration. These images underwent interactive segmentation and image processing in addition to statistical quantitative analyses of calculated image parameters including the mean, integrated density, skewness, kurtosis, and area fraction. In images from both groups, the distribution area and intensity of fluorescent silica gradually increased in proportion to time. Since statistical significance was achieved after 2 days in the negative charge group and after 4 days in the positive charge group, there is a periodic difference. Furthermore, the quantity of silica per unit area showed a dramatic change after 6 days in the negative charge group. Although this quantitative result is identical to results obtained by qualitative assessment, it is meaningful in that it was proven by statistical analysis with quantitation by using image processing. The present study suggests that the surface charge of SNPs could play an important role in the percutaneous absorption of NPs. These findings can help achieve a better understanding of the percutaneous transport of NPs. In addition, these results provide important guidance for the design of NPs for biomedical applications.

Quantitative analysis of diffusion tensor orientation: theoretical framework.

PubMed

Wu, Yu-Chien; Field, Aaron S; Chung, Moo K; Badie, Benham; Alexander, Andrew L

2004-11-01

Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing. (c) 2004 Wiley-Liss, Inc.

Improved sample preparation of glyphosate and methylphosphonic acid by EPA method 6800A and time-of-flight mass spectrometry using novel solid-phase extraction.

PubMed

Wagner, Rebecca; Wetzel, Stephanie J; Kern, John; Kingston, H M Skip

2012-02-01

The employment of chemical weapons by rogue states and/or terrorist organizations is an ongoing concern in the United States. The quantitative analysis of nerve agents must be rapid and reliable for use in the private and public sectors. Current methods describe a tedious and time-consuming derivatization for gas chromatography-mass spectrometry and liquid chromatography in tandem with mass spectrometry. Two solid-phase extraction (SPE) techniques for the analysis of glyphosate and methylphosphonic acid are described with the utilization of isotopically enriched analytes for quantitation via atmospheric pressure chemical ionization-quadrupole time-of-flight mass spectrometry (APCI-Q-TOF-MS) that does not require derivatization. Solid-phase extraction-isotope dilution mass spectrometry (SPE-IDMS) involves pre-equilibration of a naturally occurring sample with an isotopically enriched standard. The second extraction method, i-Spike, involves loading an isotopically enriched standard onto the SPE column before the naturally occurring sample. The sample and the spike are then co-eluted from the column enabling precise and accurate quantitation via IDMS. The SPE methods in conjunction with IDMS eliminate concerns of incomplete elution, matrix and sorbent effects, and MS drift. For accurate quantitation with IDMS, the isotopic contribution of all atoms in the target molecule must be statistically taken into account. This paper describes two newly developed sample preparation techniques for the analysis of nerve agent surrogates in drinking water as well as statistical probability analysis for proper molecular IDMS. The methods described in this paper demonstrate accurate molecular IDMS using APCI-Q-TOF-MS with limits of quantitation as low as 0.400 mg/kg for glyphosate and 0.031 mg/kg for methylphosphonic acid. Copyright © 2012 John Wiley & Sons, Ltd.

Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.

PubMed

Counsell, Alyssa; Harlow, Lisa L

2017-05-01

With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t -tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.

A Generalized Approach for the Interpretation of Geophysical Well Logs in Ground-Water Studies - Theory and Application

USGS Publications Warehouse

Paillet, Frederick L.; Crowder, R.E.

1996-01-01

Quantitative analysis of geophysical logs in ground-water studies often involves at least as broad a range of applications and variation in lithology as is typically encountered in petroleum exploration, making such logs difficult to calibrate and complicating inversion problem formulation. At the same time, data inversion and analysis depend on inversion model formulation and refinement, so that log interpretation cannot be deferred to a geophysical log specialist unless active involvement with interpretation can be maintained by such an expert over the lifetime of the project. We propose a generalized log-interpretation procedure designed to guide hydrogeologists in the interpretation of geophysical logs, and in the integration of log data into ground-water models that may be systematically refined and improved in an iterative way. The procedure is designed to maximize the effective use of three primary contributions from geophysical logs: (1) The continuous depth scale of the measurements along the well bore; (2) The in situ measurement of lithologic properties and the correlation with hydraulic properties of the formations over a finite sample volume; and (3) Multiple independent measurements that can potentially be inverted for multiple physical or hydraulic properties of interest. The approach is formulated in the context of geophysical inversion theory, and is designed to be interfaced with surface geophysical soundings and conventional hydraulic testing. The step-by-step procedures given in our generalized interpretation and inversion technique are based on both qualitative analysis designed to assist formulation of the interpretation model, and quantitative analysis used to assign numerical values to model parameters. The approach bases a decision as to whether quantitative inversion is statistically warranted by formulating an over-determined inversion. If no such inversion is consistent with the inversion model, quantitative inversion is judged not possible with the given data set. Additional statistical criteria such as the statistical significance of regressions are used to guide the subsequent calibration of geophysical data in terms of hydraulic variables in those situations where quantitative data inversion is considered appropriate.

A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products*

PubMed Central

auf dem Keller, Ulrich; Prudova, Anna; Gioia, Magda; Butler, Georgina S.; Overall, Christopher M.

2010-01-01

Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed. PMID:20305283

Quantitative determination and validation of octreotide acetate using 1 H-NMR spectroscopy with internal standard method.

PubMed

Yu, Chen; Zhang, Qian; Xu, Peng-Yao; Bai, Yin; Shen, Wen-Bin; Di, Bin; Su, Meng-Xiang

2018-01-01

Quantitative nuclear magnetic resonance (qNMR) is a well-established technique in quantitative analysis. We presented a validated 1 H-qNMR method for assay of octreotide acetate, a kind of cyclic octopeptide. Deuterium oxide was used to remove the undesired exchangeable peaks, which was referred to as proton exchange, in order to make the quantitative signals isolated in the crowded spectrum of the peptide and ensure precise quantitative analysis. Gemcitabine hydrochloride was chosen as the suitable internal standard. Experimental conditions, including relaxation delay time, the numbers of scans, and pulse angle, were optimized first. Then method validation was carried out in terms of selectivity, stability, linearity, precision, and robustness. The assay result was compared with that by means of high performance liquid chromatography, which is provided by Chinese Pharmacopoeia. The statistical F test, Student's t test, and nonparametric test at 95% confidence level indicate that there was no significant difference between these two methods. qNMR is a simple and accurate quantitative tool with no need for specific corresponding reference standards. It has the potential of the quantitative analysis of other peptide drugs and standardization of the corresponding reference standards. Copyright © 2017 John Wiley & Sons, Ltd.

Quantitative analysis of domain texture in polycrystalline barium titanate by polarized Raman microprobe spectroscopy

NASA Astrophysics Data System (ADS)

Sakashita, Tatsuo; Chazono, Hirokazu; Pezzotti, Giuseppe

2007-12-01

A quantitative determination of domain distribution in polycrystalline barium titanate (BaTiO3, henceforth BT) ceramics has been pursued with the aid of a microprobe polarized Raman spectrometer. The crystallographic texture and domain orientation distribution of BT ceramics, which switched upon applying stress according to ferroelasticity principles, were determined from the relative intensity of selected phonon modes, taking into consideration a theoretical analysis of the angular dependence of phonon mode intensity for the tetragonal BT phase. Furthermore, the angular dependence of Raman intensity measured in polycrystalline BT depended on the statistical distribution of domain angles in the laser microprobe, which was explicitly taken into account in this work for obtaining a quantitative analysis of domain orientation for in-plane textured BT polycrystalline materials.

[Evaluation on methodological problems in reports concerning quantitative analysis of syndrome differentiation of diabetes mellitus].

PubMed

Chen, Bi-Cang; Wu, Qiu-Ying; Xiang, Cheng-Bin; Zhou, Yi; Guo, Ling-Xiang; Zhao, Neng-Jiang; Yang, Shu-Yu

2006-01-01

To evaluate the quality of reports published in recent 10 years in China about quantitative analysis of syndrome differentiation for diabetes mellitus (DM) in order to explore the methodological problems in these reports and find possible solutions. The main medical literature databases in China were searched. Thirty-one articles were included and evaluated by the principles of clinical epidemiology. There were many mistakes and deficiencies in these articles, such as clinical trial designs, diagnosis criteria for DM, standards of syndrome differentiation of DM, case inclusive and exclusive criteria, sample size and estimation, data comparability and statistical methods. It is necessary and important to improve the quality of reports concerning quantitative analysis of syndrome differentiation of DM in light of the principles of clinical epidemiology.

Sedimentological analysis and bed thickness statistics from a Carboniferous deep-water channel-levee complex: Myall Trough, SE Australia

NASA Astrophysics Data System (ADS)

Palozzi, Jason; Pantopoulos, George; Maravelis, Angelos G.; Nordsvan, Adam; Zelilidis, Avraam

2018-02-01

This investigation presents an outcrop-based integrated study of internal division analysis and statistical treatment of turbidite bed thickness applied to a Carboniferous deep-water channel-levee complex in the Myall Trough, southeast Australia. Turbidite beds of the studied succession are characterized by a range of sedimentary structures grouped into two main associations, a thick-bedded and a thin-bedded one, that reflect channel-fill and overbank/levee deposits, respectively. Three vertically stacked channel-levee cycles have been identified. Results of statistical analysis of bed thickness, grain-size and internal division patterns applied on the studied channel-levee succession, indicate that turbidite bed thickness data seem to be well characterized by a bimodal lognormal distribution, which is possibly reflecting the difference between deposition from lower-density flows (in a levee/overbank setting) and very high-density flows (in a channel fill setting). Power law and exponential distributions were observed to hold only for the thick-bedded parts of the succession and cannot characterize the whole bed thickness range of the studied sediments. The succession also exhibits non-random clustering of bed thickness and grain-size measurements. The studied sediments are also characterized by the presence of statistically detected fining-upward sandstone packets. A novel quantitative approach (change-point analysis) is proposed for the detection of those packets. Markov permutation statistics also revealed the existence of order in the alternation of internal divisions in the succession expressed by an optimal internal division cycle reflecting two main types of gravity flow events deposited within both thick-bedded conglomeratic and thin-bedded sandstone associations. The analytical methods presented in this study can be used as additional tools for quantitative analysis and recognition of depositional environments in hydrocarbon-bearing research of ancient deep-water channel-levee settings.

Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals.

PubMed

Lipiäinen, Tiina; Pessi, Jenni; Movahedi, Parisa; Koivistoinen, Juha; Kurki, Lauri; Tenhunen, Mari; Yliruusi, Jouko; Juppo, Anne M; Heikkonen, Jukka; Pahikkala, Tapio; Strachan, Clare J

2018-04-03

Raman spectroscopy is widely used for quantitative pharmaceutical analysis, but a common obstacle to its use is sample fluorescence masking the Raman signal. Time-gating provides an instrument-based method for rejecting fluorescence through temporal resolution of the spectral signal and allows Raman spectra of fluorescent materials to be obtained. An additional practical advantage is that analysis is possible in ambient lighting. This study assesses the efficacy of time-gated Raman spectroscopy for the quantitative measurement of fluorescent pharmaceuticals. Time-gated Raman spectroscopy with a 128 × (2) × 4 CMOS SPAD detector was applied for quantitative analysis of ternary mixtures of solid-state forms of the model drug, piroxicam (PRX). Partial least-squares (PLS) regression allowed quantification, with Raman-active time domain selection (based on visual inspection) improving performance. Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Overall, time-gated Raman spectroscopy, especially with optimized data analysis in both the spectral and time dimensions, shows potential for sensitive and relatively routine quantitative analysis of photoluminescent pharmaceuticals during drug development and manufacturing.

Statistics used in current nursing research.

PubMed

Zellner, Kathleen; Boerst, Connie J; Tabb, Wil

2007-02-01

Undergraduate nursing research courses should emphasize the statistics most commonly used in the nursing literature to strengthen students' and beginning researchers' understanding of them. To determine the most commonly used statistics, we reviewed all quantitative research articles published in 13 nursing journals in 2000. The findings supported Beitz's categorization of kinds of statistics. Ten primary statistics used in 80% of nursing research published in 2000 were identified. We recommend that the appropriate use of those top 10 statistics be emphasized in undergraduate nursing education and that the nursing profession continue to advocate for the use of methods (e.g., power analysis, odds ratio) that may contribute to the advancement of nursing research.

78 FR 70059 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-22

... (as opposed to quantitative statistical methods). In consultation with research experts, we have... qualitative interviews (as opposed to quantitative statistical methods). In consultation with research experts... utilization of qualitative interviews (as opposed to quantitative statistical methods). In consultation with...

An automated system for chromosome analysis. Volume 1: Goals, system design, and performance

NASA Technical Reports Server (NTRS)

Castleman, K. R.; Melnyk, J. H.

1975-01-01

The design, construction, and testing of a complete system to produce karyotypes and chromosome measurement data from human blood samples, and a basis for statistical analysis of quantitative chromosome measurement data is described. The prototype was assembled, tested, and evaluated on clinical material and thoroughly documented.

Regression Commonality Analysis: A Technique for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…

Alaska national hydrography dataset positional accuracy assessment study

USGS Publications Warehouse

Arundel, Samantha; Yamamoto, Kristina H.; Constance, Eric; Mantey, Kim; Vinyard-Houx, Jeremy

2013-01-01

Initial visual assessments Wide range in the quality of fit between features in NHD and these new image sources. No statistical analysis has been performed to actually quantify accuracy Determining absolute accuracy is cost prohibitive (must collect independent, well defined test points) Quantitative analysis of relative positional error is feasible.

The Use of Modelling for Theory Building in Qualitative Analysis

ERIC Educational Resources Information Center

Briggs, Ann R. J.

2007-01-01

The purpose of this article is to exemplify and enhance the place of modelling as a qualitative process in educational research. Modelling is widely used in quantitative research as a tool for analysis, theory building and prediction. Statistical data lend themselves to graphical representation of values, interrelationships and operational…

Putting the "But" Back in Meta-Analysis: Issues Affecting the Validity of Quantitative Reviews.

ERIC Educational Resources Information Center

L'Hommedieu, Randi; And Others

Some of the frustrations inherent in trying to incorporate qualifications of statistical results into meta-analysis are reviewed, and some solutions are proposed to prevent the loss of information in meta-analytic reports. The validity of a meta-analysis depends on several factors, including the: thoroughness of the literature search; selection of…

Statistical innovations in the medical device world sparked by the FDA.

PubMed

Campbell, Gregory; Yue, Lilly Q

2016-01-01

The world of medical devices while highly diverse is extremely innovative, and this facilitates the adoption of innovative statistical techniques. Statisticians in the Center for Devices and Radiological Health (CDRH) at the Food and Drug Administration (FDA) have provided leadership in implementing statistical innovations. The innovations discussed include: the incorporation of Bayesian methods in clinical trials, adaptive designs, the use and development of propensity score methodology in the design and analysis of non-randomized observational studies, the use of tipping-point analysis for missing data, techniques for diagnostic test evaluation, bridging studies for companion diagnostic tests, quantitative benefit-risk decisions, and patient preference studies.

Teaching Statistics in Biology: Using Inquiry-based Learning to Strengthen Understanding of Statistical Analysis in Biology Laboratory Courses

PubMed Central

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754

Qualitative and quantitative evaluation of some vocal function parameters following fitting of a prosthesis.

PubMed

Cavalot, A L; Palonta, F; Preti, G; Nazionale, G; Ricci, E; Vione, N; Albera, R; Cortesina, G

2001-12-01

The insertion of a prosthesis and restoration with pectoralis major myocutaneous flaps for patients subjected to total pharyngolaryngectomy is a technique now universally accepted; however the literature on the subject is lacking. Our study considers 10 patients subjected to total pharyngolaryngectomy and restoration with pectoralis major myocutaneous flaps who were fitted with vocal function prostheses and a control group of 50 subjects treated with a total laryngectomy without pectoralis major myocutaneous flaps and who were fitted with vocal function prostheses. Specific qualitative and quantitative parameters were compared. The quantitative measurement of the levels of voice intensity and the evaluation of the harmonics-to-noise ratio were not statistically significant (p > 0.05) between the two study groups at either high- or low-volume speech. On the contrary, statistically significant differences were found (p < 0.05) for the basic frequency of both the low and the high volume voice. For the qualitative analysis seven parameters were established for evaluation by trained and untrained listeners: on the basis of these parameters the control group had statistically better voices.

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

Quantitative analysis of aircraft multispectral-scanner data and mapping of water-quality parameters in the James River in Virginia

NASA Technical Reports Server (NTRS)

Johnson, R. W.; Bahn, G. S.

1977-01-01

Statistical analysis techniques were applied to develop quantitative relationships between in situ river measurements and the remotely sensed data that were obtained over the James River in Virginia on 28 May 1974. The remotely sensed data were collected with a multispectral scanner and with photographs taken from an aircraft platform. Concentration differences among water quality parameters such as suspended sediment, chlorophyll a, and nutrients indicated significant spectral variations. Calibrated equations from the multiple regression analysis were used to develop maps that indicated the quantitative distributions of water quality parameters and the dispersion characteristics of a pollutant plume entering the turbid river system. Results from further analyses that use only three preselected multispectral scanner bands of data indicated that regression coefficients and standard errors of estimate were not appreciably degraded compared with results from the 10-band analysis.

Developing statistical wildlife habitat relationships for assessing cumulative effects of fuels treatments: Final Report for Joint Fire Science Program Project

Treesearch

Samuel A. Cushman; Kevin S. McKelvey

2006-01-01

The primary weakness in our current ability to evaluate future landscapes in terms of wildlife lies in the lack of quantitative models linking wildlife to forest stand conditions, including fuels treatments. This project focuses on 1) developing statistical wildlife habitat relationships models (WHR) utilizing Forest Inventory and Analysis (FIA) and National Vegetation...

An analysis of a large dataset on immigrant integration in Spain. The Statistical Mechanics perspective on Social Action

NASA Astrophysics Data System (ADS)

Barra, Adriano; Contucci, Pierluigi; Sandell, Rickard; Vernia, Cecilia

2014-02-01

How does immigrant integration in a country change with immigration density? Guided by a statistical mechanics perspective we propose a novel approach to this problem. The analysis focuses on classical integration quantifiers such as the percentage of jobs (temporary and permanent) given to immigrants, mixed marriages, and newborns with parents of mixed origin. We find that the average values of different quantifiers may exhibit either linear or non-linear growth on immigrant density and we suggest that social action, a concept identified by Max Weber, causes the observed non-linearity. Using the statistical mechanics notion of interaction to quantitatively emulate social action, a unified mathematical model for integration is proposed and it is shown to explain both growth behaviors observed. The linear theory instead, ignoring the possibility of interaction effects would underestimate the quantifiers up to 30% when immigrant densities are low, and overestimate them as much when densities are high. The capacity to quantitatively isolate different types of integration mechanisms makes our framework a suitable tool in the quest for more efficient integration policies.

Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

NASA Astrophysics Data System (ADS)

Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

2017-03-01

A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

Relationship between self-reported upper limb disability and quantitative tests in hand-arm vibration syndrome.

PubMed

Poole, Kerry; Mason, Howard

2007-03-15

To establish the relationship between quantitative tests of hand function and upper limb disability, as measured by the Disability of the Arm, Shoulder and Hand (DASH) questionnaire, in hand-arm vibration syndrome (HAVS). A total of 228 individuals with HAVS were included in this study. Each had undergone a full HAVS assessment by an experienced physician, including quantitative tests of vibrotactile and thermal perception thresholds, maximal hand-grip strength (HG) and the Purdue pegboard (PP) test. Individuals were also asked to complete a DASH questionnaire. PP and HG of the quantitative tests gave the best and statistically significant individual correlations with the DASH disability score (r2 = 0.168 and 0.096). Stepwise linear regression analysis revealed that only PP and HG measurements were statistically significant predictors of upper limb disability (r2 = 0.178). Overall a combination of the PP and HG measurements, rather than each alone, gave slightly better discrimination, although not statistically significant, between normal and abnormal DASH scores with a sensitivity of 73.1% and specificity of 64.3%. Measurements of manual dexterity and hand-grip strength using PP and HG may be useful in helping to confirm lack of upper limb function and 'perceived' disability in HAVS.

A quantitative approach to evolution of music and philosophy

NASA Astrophysics Data System (ADS)

Vieira, Vilson; Fabbri, Renato; Travieso, Gonzalo; Oliveira, Osvaldo N., Jr.; da Fontoura Costa, Luciano

2012-08-01

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master-apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

The Quantitative Preparation of Future Geoscience Graduate Students

NASA Astrophysics Data System (ADS)

Manduca, C. A.; Hancock, G. S.

2006-12-01

Modern geoscience is a highly quantitative science. In February, a small group of faculty and graduate students from across the country met to discuss the quantitative preparation of geoscience majors for graduate school. The group included ten faculty supervising graduate students in quantitative areas spanning the earth, atmosphere, and ocean sciences; five current graduate students in these areas; and five faculty teaching undergraduate students in the spectrum of institutions preparing students for graduate work. Discussion focused in four key ares: Are incoming graduate students adequately prepared for the quantitative aspects of graduate geoscience programs? What are the essential quantitative skills are that are required for success in graduate school? What are perceived as the important courses to prepare students for the quantitative aspects of graduate school? What programs/resources would be valuable in helping faculty/departments improve the quantitative preparation of students? The participants concluded that strengthening the quantitative preparation of undergraduate geoscience majors would increase their opportunities in graduate school. While specifics differed amongst disciplines, a special importance was placed on developing the ability to use quantitative skills to solve geoscience problems. This requires the ability to pose problems so they can be addressed quantitatively, understand the relationship between quantitative concepts and physical representations, visualize mathematics, test the reasonableness of quantitative results, creatively move forward from existing models/techniques/approaches, and move between quantitative and verbal descriptions. A list of important quantitative competencies desirable in incoming graduate students includes mechanical skills in basic mathematics, functions, multi-variate analysis, statistics and calculus, as well as skills in logical analysis and the ability to learn independently in quantitative ways. Calculus, calculus-based physics, chemistry, statistics, programming and linear algebra were viewed as important course preparation for a successful graduate experience. A set of recommendations for departments and for new community resources includes ideas for infusing quantitative reasoning throughout the undergraduate experience and mechanisms for learning from successful experiments in both geoscience and mathematics. A full list of participants, summaries of the meeting discussion and recommendations are available at http://serc.carleton.edu/quantskills/winter06/index.html. These documents, crafted by a small but diverse group can serve as a starting point for broader community discussion of the quantitative preparation of future geoscience graduate students.

The Effects of Ability Grouping: A Meta-Analysis of Research Findings.

ERIC Educational Resources Information Center

Noland, Theresa Koontz; Taylor, Bob L.

The study reported in this paper quantitatively integrated the recent research findings on ability grouping in order to generalize about these effects on student achievement and student self-concept. Meta-analysis was used to statistically integrate the empirical data. The relationships among various experimental variables including grade level,…

Teaching for Art Criticism: Incorporating Feldman's Critical Analysis Learning Model in Students' Studio Practice

ERIC Educational Resources Information Center

Subramaniam, Maithreyi; Hanafi, Jaffri; Putih, Abu Talib

2016-01-01

This study adopted 30 first year graphic design students' artwork, with critical analysis using Feldman's model of art criticism. Data were analyzed quantitatively; descriptive statistical techniques were employed. The scores were viewed in the form of mean score and frequencies to determine students' performances in their critical ability.…

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

NASA Technical Reports Server (NTRS)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

A twelve-year profile of students' SAT scores, GPAs, and MCAT scores from a small university's premedical program.

PubMed

Montague, J R; Frei, J K

1993-04-01

To determine whether significant correlations existed among quantitative and qualitative predictors of students' academic success and quantitative outcomes of such success over a 12-year period in a small university's premedical program. A database was assembled from information on the 199 graduates who earned BS degrees in biology from Barry University's School of Natural and Health Sciences from 1980 through 1991. The quantitative variables were year of BS degree, total score on the Scholastic Aptitude Test (SAT), various measures of undergraduate grade-point averages (GPAs), and total score on the Medical College Admission Test (MCAT); and the qualitative variables were minority (54% of the students) or majority status and transfer (about one-third of the students) or nontransfer status. The statistical methods were multiple analysis of variance and stepwise multiple regression. Statistically significant positive correlations were found among SAT total scores, final GPAs, biology GPAs versus nonbiology GPAs, and MCAT total scores. These correlations held for transfer versus nontransfer students and for minority versus majority students. Over the 12-year period there were significant fluctuations in mean MCAT scores. The students' SAT scores and GPAs proved to be statistically reliable predictors of MCAT scores, but the minority or majority status and the transfer or nontransfer status of the students were statistically insignificant.

Conceptual versus Algorithmic Learning in High School Chemistry: The Case of Basic Quantum Chemical Concepts--Part 1. Statistical Analysis of a Quantitative Study

ERIC Educational Resources Information Center

Papaphotis, Georgios; Tsaparlis, Georgios

2008-01-01

Part 1 of the findings are presented of a quantitative study (n = 125) on basic quantum chemical concepts taught in the twelfth grade (age 17-18 years) in Greece. A paper-and-pencil test of fourteen questions was used. The study compared performance in five questions that tested recall of knowledge or application of algorithmic procedures (type-A…

The Quantitative Analysis on the Individual Characteristics of Urban Residents and Their Sport Consumption Motivation

NASA Astrophysics Data System (ADS)

Xianliang, Lei; Hongying, Yu

Using the questionnaire, mathematical statistics and entropy measurement methods, the quantitative relationship between the individual characteristics urban residents and their sports consumption motivation are studied. The results show that the most main sports consumption motivation of urban residents is fitness motivation and social motivation. Urban residents of different gender, age, education and income levels are different in regulating psychological motivation, rational consumption motivation and seeking common motivation.

40 CFR 63.5350 - How do I distinguish between the water-resistant/specialty and nonwater-resistant leather product...

Code of Federal Regulations, 2010 CFR

2010-07-01

... by the Administrator. (1) Statistical analysis of initial water penetration data performed to support ASTM Designation D2099-00 indicates that poor quantitative precision is associated with this testing...

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins. PMID:19181660

SDAR 1.0 a New Quantitative Toolkit for Analyze Stratigraphic Data

NASA Astrophysics Data System (ADS)

Ortiz, John; Moreno, Carlos; Cardenas, Andres; Jaramillo, Carlos

2015-04-01

Since the foundation of stratigraphy geoscientists have recognized that data obtained from stratigraphic columns (SC), two dimensional schemes recording descriptions of both geological and paleontological features (e.g., thickness of rock packages, grain size, fossil and lithological components, and sedimentary structures), are key elements for establishing reliable hypotheses about the distribution in space and time of rock sequences, and ancient sedimentary environmental and paleobiological dynamics. Despite the tremendous advances on the way geoscientists store, plot, and quantitatively analyze sedimentological and paleontological data (e.g., Macrostrat [http://www.macrostrat.org/], Paleobiology Database [http://www.paleodb.org/], respectively), there is still a lack of computational methodologies designed to quantitatively examine data from a highly detailed SCs. Moreover, frequently the stratigraphic information is plotted "manually" using vector graphics editors (e.g., Corel Draw, Illustrator), however, this information although store on a digital format, cannot be used readily for any quantitative analysis. Therefore, any attempt to examine the stratigraphic data in an analytical fashion necessarily takes further steps. Given these issues, we have developed the sofware 'Stratigraphic Data Analysis in R' (SDAR), which stores in a database all sedimentological, stratigraphic, and paleontological information collected from a SC, allowing users to generate high-quality graphic plots (including one or multiple features stored in the database). SDAR also encompasses quantitative analyses helping users to quantify stratigraphic information (e.g. grain size, sorting and rounding, proportion of sand/shale). Finally, given that the SDAR analysis module, has been written in the open-source high-level computer language "R graphics/statistics language" [R Development Core Team, 2014], it is already loaded with many of the crucial features required to accomplish basic and complex tasks of statistical analysis (i.e., R language provide more than hundred spatial libraries that allow users to explore various Geostatistics and spatial analysis). Consequently, SDAR allows a deeper exploration of the stratigraphic data collected in the field, it will allow the geoscientific community in the near future to develop complex analyses related with the distribution in space and time of rock sequences, such as lithofacial correlations, by a multivariate comparison between empirical SCs with quantitative lithofacial models established from modern sedimentary environments.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

PubMed

Matafora, Vittoria; Corno, Andrea; Ciliberto, Andrea; Bachi, Angela

2017-04-07

In global proteomic analysis, it is estimated that proteins span from millions to less than 100 copies per cell. The challenge of protein quantitation by classic shotgun proteomic techniques relies on the presence of missing values in peptides belonging to low-abundance proteins that lowers intraruns reproducibility affecting postdata statistical analysis. Here, we present a new analytical workflow MvM (missing value monitoring) able to recover quantitation of missing values generated by shotgun analysis. In particular, we used confident data-dependent acquisition (DDA) quantitation only for proteins measured in all the runs, while we filled the missing values with data-independent acquisition analysis using the library previously generated in DDA. We analyzed cell cycle regulated proteins, as they are low abundance proteins with highly dynamic expression levels. Indeed, we found that cell cycle related proteins are the major components of the missing values-rich proteome. Using the MvM workflow, we doubled the number of robustly quantified cell cycle related proteins, and we reduced the number of missing values achieving robust quantitation for proteins over ∼50 molecules per cell. MvM allows lower quantification variance among replicates for low abundance proteins with respect to DDA analysis, which demonstrates the potential of this novel workflow to measure low abundance, dynamically regulated proteins.

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.

Analyzing 7000 texts on deep brain stimulation: what do they tell us?

PubMed

Ineichen, Christian; Christen, Markus

2015-01-01

The enormous increase in numbers of scientific publications in the last decades requires quantitative methods for obtaining a better understanding of topics and developments in various fields. In this exploratory study, we investigate the emergence, trends, and connections of topics within the whole text corpus of the deep brain stimulation (DBS) literature based on more than 7000 papers (title and abstracts) published between 1991 to 2014 using a network approach. Taking the co-occurrence of basic terms that represent important topics within DBS as starting point, we outline the statistics of interconnections between DBS indications, anatomical targets, positive, and negative effects, as well as methodological, technological, and economic issues. This quantitative approach confirms known trends within the literature (e.g., regarding the emergence of psychiatric indications). The data also reflect an increased discussion about complex issues such as personality connected tightly to the ethical context, as well as an apparent focus on depression as important DBS indication, where the co-occurrence of terms related to negative effects is low both for the indication as well as the related anatomical targets. We also discuss consequences of the analysis from a bioethical perspective, i.e., how such a quantitative analysis could uncover hidden subject matters that have ethical relevance. For example, we find that hardware-related issues in DBS are far more robustly connected to an ethical context compared to impulsivity, concrete side-effects or death/suicide. Our contribution also outlines the methodology of quantitative text analysis that combines statistical approaches with expert knowledge. It thus serves as an example how innovative quantitative tools can be made useful for gaining a better understanding in the field of DBS.

Analyzing 7000 texts on deep brain stimulation: what do they tell us?

PubMed Central

Ineichen, Christian; Christen, Markus

2015-01-01

The enormous increase in numbers of scientific publications in the last decades requires quantitative methods for obtaining a better understanding of topics and developments in various fields. In this exploratory study, we investigate the emergence, trends, and connections of topics within the whole text corpus of the deep brain stimulation (DBS) literature based on more than 7000 papers (title and abstracts) published between 1991 to 2014 using a network approach. Taking the co-occurrence of basic terms that represent important topics within DBS as starting point, we outline the statistics of interconnections between DBS indications, anatomical targets, positive, and negative effects, as well as methodological, technological, and economic issues. This quantitative approach confirms known trends within the literature (e.g., regarding the emergence of psychiatric indications). The data also reflect an increased discussion about complex issues such as personality connected tightly to the ethical context, as well as an apparent focus on depression as important DBS indication, where the co-occurrence of terms related to negative effects is low both for the indication as well as the related anatomical targets. We also discuss consequences of the analysis from a bioethical perspective, i.e., how such a quantitative analysis could uncover hidden subject matters that have ethical relevance. For example, we find that hardware-related issues in DBS are far more robustly connected to an ethical context compared to impulsivity, concrete side-effects or death/suicide. Our contribution also outlines the methodology of quantitative text analysis that combines statistical approaches with expert knowledge. It thus serves as an example how innovative quantitative tools can be made useful for gaining a better understanding in the field of DBS. PMID:26578908

Statistical analysis of sparse infection data and its implications for retroviral treatment trials in primates.

PubMed Central

Spouge, J L

1992-01-01

Reports on retroviral primate trials rarely publish any statistical analysis. Present statistical methodology lacks appropriate tests for these trials and effectively discourages quantitative assessment. This paper describes the theory behind VACMAN, a user-friendly computer program that calculates statistics for in vitro and in vivo infectivity data. VACMAN's analysis applies to many retroviral trials using i.v. challenges and is valid whenever the viral dose-response curve has a particular shape. Statistics from actual i.v. retroviral trials illustrate some unappreciated principles of effective animal use: dilutions other than 1:10 can improve titration accuracy; infecting titration animals at the lowest doses possible can lower challenge doses; and finally, challenging test animals in small trials with more virus than controls safeguards against false successes, "reuses" animals, and strengthens experimental conclusions. The theory presented also explains the important concept of viral saturation, a phenomenon that may cause in vitro and in vivo titrations to agree for some retroviral strains and disagree for others. PMID:1323844

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Do Deregulated Cas Proteins Induce Genomic Instability in Early-Stage Ovarian Cancer

DTIC Science & Technology

2006-12-01

use Western blot analysis of tumor lysates to correlate expression of HEF1, p130Cas, Aurora A, and phospho-Aurora A. This analysis is in progress. In...and importantly, evaluated a number of different detection/image analysis systems to ensure reproducible quantitative results. We have used a pilot...reproducible Interestingly, preliminary statistical analysis using Spearman and Pearson correlation indicates at least one striking correlation

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PubMed

Golder, W

1999-09-01

To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools.

PubMed

Blattmann, Peter; Heusel, Moritz; Aebersold, Ruedi

2016-01-01

SWATH-MS is an acquisition and analysis technique of targeted proteomics that enables measuring several thousand proteins with high reproducibility and accuracy across many samples. OpenSWATH is popular open-source software for peptide identification and quantification from SWATH-MS data. For downstream statistical and quantitative analysis there exist different tools such as MSstats, mapDIA and aLFQ. However, the transfer of data from OpenSWATH to the downstream statistical tools is currently technically challenging. Here we introduce the R/Bioconductor package SWATH2stats, which allows convenient processing of the data into a format directly readable by the downstream analysis tools. In addition, SWATH2stats allows annotation, analyzing the variation and the reproducibility of the measurements, FDR estimation, and advanced filtering before submitting the processed data to downstream tools. These functionalities are important to quickly analyze the quality of the SWATH-MS data. Hence, SWATH2stats is a new open-source tool that summarizes several practical functionalities for analyzing, processing, and converting SWATH-MS data and thus facilitates the efficient analysis of large-scale SWATH/DIA datasets.

The APOSTEL recommendations for reporting quantitative optical coherence tomography studies.

PubMed

Cruz-Herranz, Andrés; Balk, Lisanne J; Oberwahrenbrock, Timm; Saidha, Shiv; Martinez-Lapiscina, Elena H; Lagreze, Wolf A; Schuman, Joel S; Villoslada, Pablo; Calabresi, Peter; Balcer, Laura; Petzold, Axel; Green, Ari J; Paul, Friedemann; Brandt, Alexander U; Albrecht, Philipp

2016-06-14

To develop consensus recommendations for reporting of quantitative optical coherence tomography (OCT) study results. A panel of experienced OCT researchers (including 11 neurologists, 2 ophthalmologists, and 2 neuroscientists) discussed requirements for performing and reporting quantitative analyses of retinal morphology and developed a list of initial recommendations based on experience and previous studies. The list of recommendations was subsequently revised during several meetings of the coordinating group. We provide a 9-point checklist encompassing aspects deemed relevant when reporting quantitative OCT studies. The areas covered are study protocol, acquisition device, acquisition settings, scanning protocol, funduscopic imaging, postacquisition data selection, postacquisition data analysis, recommended nomenclature, and statistical analysis. The Advised Protocol for OCT Study Terminology and Elements recommendations include core items to standardize and improve quality of reporting in quantitative OCT studies. The recommendations will make reporting of quantitative OCT studies more consistent and in line with existing standards for reporting research in other biomedical areas. The recommendations originated from expert consensus and thus represent Class IV evidence. They will need to be regularly adjusted according to new insights and practices. © 2016 American Academy of Neurology.

Analysis of Student Activity in Web-Supported Courses as a Tool for Predicting Dropout

ERIC Educational Resources Information Center

Cohen, Anat

2017-01-01

Persistence in learning processes is perceived as a central value; therefore, dropouts from studies are a prime concern for educators. This study focuses on the quantitative analysis of data accumulated on 362 students in three academic course website log files in the disciplines of mathematics and statistics, in order to examine whether student…

An Overview of ACRL"Metrics", Part II: Using NCES and IPEDs Data

ERIC Educational Resources Information Center

Stewart, Christopher

2012-01-01

This report is the second in a two-part analysis of ACRL"Metrics", an online service that provides access to a range of quantitative data for academic libraries. In this analysis, ACRL"Metrics"' inclusion of data from the National Center for Educational Statistics' Academic Libraries Survey and the Integrated Postsecondary Education Data System is…

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…

Digital Natives, Digital Immigrants: An Analysis of Age and ICT Competency in Teacher Education

ERIC Educational Resources Information Center

Guo, Ruth Xiaoqing; Dobson, Teresa; Petrina, Stephen

2008-01-01

This article examines the intersection of age and ICT (information and communication technology) competency and critiques the "digital natives versus digital immigrants" argument proposed by Prensky (2001a, 2001b). Quantitative analysis was applied to a statistical data set collected in the context of a study with over 2,000 pre-service…

Not the Norm: The Potential of Tree Analysis of Performance Data from Students in a Foundation Mathematics Module

ERIC Educational Resources Information Center

Kirby, Nicola; Dempster, Edith

2015-01-01

Quantitative methods of data analysis usually involve inferential statistics, and are not well known for their ability to reflect the intricacies of a diverse student population. The South African tertiary education sector is characterised by extreme inequality and diversity. Foundation programmes address issues of inequality of access by…

Statistical differences between relative quantitative molecular fingerprints from microbial communities.

PubMed

Portillo, M C; Gonzalez, J M

2008-08-01

Molecular fingerprints of microbial communities are a common method for the analysis and comparison of environmental samples. The significance of differences between microbial community fingerprints was analyzed considering the presence of different phylotypes and their relative abundance. A method is proposed by simulating coverage of the analyzed communities as a function of sampling size applying a Cramér-von Mises statistic. Comparisons were performed by a Monte Carlo testing procedure. As an example, this procedure was used to compare several sediment samples from freshwater ponds using a relative quantitative PCR-DGGE profiling technique. The method was able to discriminate among different samples based on their molecular fingerprints, and confirmed the lack of differences between aliquots from a single sample.

A quantitative link between microplastic instability and macroscopic deformation behaviors in metallic glasses

NASA Astrophysics Data System (ADS)

Wu, Y.; Chen, G. L.; Hui, X. D.; Liu, C. T.; Lin, Y.; Shang, X. C.; Lu, Z. P.

2009-10-01

Based on mechanical instability of individual shear transformation zones (STZs), a quantitative link between the microplastic instability and macroscopic deformation behavior of metallic glasses was proposed. Our analysis confirms that macroscopic metallic glasses comprise a statistical distribution of STZ embryos with distributed values of activation energy, and the microplastic instability of all the individual STZs dictates the macroscopic deformation behavior of amorphous solids. The statistical model presented in this paper can successfully reproduce the macroscopic stress-strain curves determined experimentally and readily be used to predict strain-rate effects on the macroscopic responses with the availability of the material parameters at a certain strain rate, which offer new insights into understanding the actual deformation mechanism in amorphous solids.

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

PubMed

Li, Zitong; Sillanpää, Mikko J

2015-12-01

Advanced platforms have recently become available for automatic and systematic quantification of plant growth and development. These new techniques can efficiently produce multiple measurements of phenotypes over time, and introduce time as an extra dimension to quantitative trait locus (QTL) studies. Functional mapping utilizes a class of statistical models for identifying QTLs associated with the growth characteristics of interest. A major benefit of functional mapping is that it integrates information over multiple timepoints, and therefore could increase the statistical power for QTL detection. We review the current development of computationally efficient functional mapping methods which provide invaluable tools for analyzing large-scale timecourse data that are readily available in our post-genome era. Copyright © 2015 Elsevier Ltd. All rights reserved.

Critically appraising qualitative research: a guide for clinicians more familiar with quantitative techniques.

PubMed

Kisely, Stephen; Kendall, Elizabeth

2011-08-01

Papers using qualitative methods are increasingly common in psychiatric journals. This overview is an introduction to critically appraising a qualitative paper for clinicians who are more familiar with quantitative methods. Qualitative research uses data from interviews (semi-structured or unstructured), focus groups, observations or written materials. Data analysis is inductive, allowing meaning to emerge from the data, rather than the more deductive, hypothesis centred approach of quantitative research. This overview compares and contrasts quantitative and qualitative research methods. Quantitative concepts such as reliability, validity, statistical power, bias and generalisability have qualitative equivalents. These include triangulation, trustworthiness, saturation, reflexivity and applicability. Reflexivity also shares features of transference. Qualitative approaches include: ethnography, action-assessment, grounded theory, case studies and mixed methods. Qualitative research can complement quantitative approaches. An understanding of both is useful in critically appraising the psychiatric literature.

NASA standard: Trend analysis techniques

NASA Technical Reports Server (NTRS)

1990-01-01

Descriptive and analytical techniques for NASA trend analysis applications are presented in this standard. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. This document should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend analysis is neither a precise term nor a circumscribed methodology: it generally connotes quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this document. The basic ideas needed for qualitative and quantitative assessment of trends along with relevant examples are presented.

Application of pedagogy reflective in statistical methods course and practicum statistical methods

NASA Astrophysics Data System (ADS)

Julie, Hongki

2017-08-01

Subject Elementary Statistics, Statistical Methods and Statistical Methods Practicum aimed to equip students of Mathematics Education about descriptive statistics and inferential statistics. The students' understanding about descriptive and inferential statistics were important for students on Mathematics Education Department, especially for those who took the final task associated with quantitative research. In quantitative research, students were required to be able to present and describe the quantitative data in an appropriate manner, to make conclusions from their quantitative data, and to create relationships between independent and dependent variables were defined in their research. In fact, when students made their final project associated with quantitative research, it was not been rare still met the students making mistakes in the steps of making conclusions and error in choosing the hypothetical testing process. As a result, they got incorrect conclusions. This is a very fatal mistake for those who did the quantitative research. There were some things gained from the implementation of reflective pedagogy on teaching learning process in Statistical Methods and Statistical Methods Practicum courses, namely: 1. Twenty two students passed in this course and and one student did not pass in this course. 2. The value of the most accomplished student was A that was achieved by 18 students. 3. According all students, their critical stance could be developed by them, and they could build a caring for each other through a learning process in this course. 4. All students agreed that through a learning process that they undergo in the course, they can build a caring for each other.

Statistical image quantification toward optimal scan fusion and change quantification

NASA Astrophysics Data System (ADS)

Potesil, Vaclav; Zhou, Xiang Sean

2007-03-01

Recent advance of imaging technology has brought new challenges and opportunities for automatic and quantitative analysis of medical images. With broader accessibility of more imaging modalities for more patients, fusion of modalities/scans from one time point and longitudinal analysis of changes across time points have become the two most critical differentiators to support more informed, more reliable and more reproducible diagnosis and therapy decisions. Unfortunately, scan fusion and longitudinal analysis are both inherently plagued with increased levels of statistical errors. A lack of comprehensive analysis by imaging scientists and a lack of full awareness by physicians pose potential risks in clinical practice. In this paper, we discuss several key error factors affecting imaging quantification, studying their interactions, and introducing a simulation strategy to establish general error bounds for change quantification across time. We quantitatively show that image resolution, voxel anisotropy, lesion size, eccentricity, and orientation are all contributing factors to quantification error; and there is an intricate relationship between voxel anisotropy and lesion shape in affecting quantification error. Specifically, when two or more scans are to be fused at feature level, optimal linear fusion analysis reveals that scans with voxel anisotropy aligned with lesion elongation should receive a higher weight than other scans. As a result of such optimal linear fusion, we will achieve a lower variance than naïve averaging. Simulated experiments are used to validate theoretical predictions. Future work based on the proposed simulation methods may lead to general guidelines and error lower bounds for quantitative image analysis and change detection.

Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions

PubMed Central

Ezard, Thomas H.G.; Jørgensen, Peter S.; Zimmerman, Naupaka; Chamberlain, Scott; Salguero-Gómez, Roberto; Curran, Timothy J.; Poisot, Timothée

2014-01-01

Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was “too low” in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice. PMID:24688862

A Pilot Study of the Noninvasive Assessment of the Lung Microbiota as a Potential Tool for the Early Diagnosis of Ventilator-Associated Pneumonia

PubMed Central

Brady, Jacob S.; Romano-Keeler, Joann; Drake, Wonder P.; Norris, Patrick R.; Jenkins, Judith M.; Isaacs, Richard J.; Boczko, Erik M.

2015-01-01

BACKGROUND: Ventilator-associated pneumonia (VAP) remains a common complication in critically ill surgical patients, and its diagnosis remains problematic. Exhaled breath contains aerosolized droplets that reflect the lung microbiota. We hypothesized that exhaled breath condensate fluid (EBCF) in hygroscopic condenser humidifier/heat and moisture exchanger (HCH/HME) filters would contain bacterial DNA that qualitatively and quantitatively correlate with pathogens isolated from quantitative BAL samples obtained for clinical suspicion of pneumonia. METHODS: Forty-eight adult patients who were mechanically ventilated and undergoing quantitative BAL (n = 51) for suspected pneumonia in the surgical ICU were enrolled. Per protocol, patients fulfilling VAP clinical criteria undergo quantitative BAL bacterial culture. Immediately prior to BAL, time-matched HCH/HME filters were collected for study of EBCF by real-time polymerase chain reaction. Additionally, convenience samples of serially collected filters in patients with BAL-diagnosed VAP were analyzed. RESULTS: Forty-nine of 51 time-matched EBCF/BAL fluid samples were fully concordant (concordance > 95% by κ statistic) relative to identified pathogens and strongly correlated with clinical cultures. Regression analysis of quantitative bacterial DNA in paired samples revealed a statistically significant positive correlation (r = 0.85). In a convenience sample, qualitative and quantitative polymerase chain reaction analysis of serial HCH/HME samples for bacterial DNA demonstrated an increase in load that preceded the suspicion of pneumonia. CONCLUSIONS: Bacterial DNA within EBCF demonstrates a high correlation with BAL fluid and clinical cultures. Bacterial DNA within EBCF increases prior to the suspicion of pneumonia. Further study of this novel approach may allow development of a noninvasive tool for the early diagnosis of VAP. PMID:25474571

Mathematical problem solving ability of sport students in the statistical study

NASA Astrophysics Data System (ADS)

Sari, E. F. P.; Zulkardi; Putri, R. I. I.

2017-12-01

This study aims to determine the problem-solving ability of sport students of PGRI Palembang semester V in the statistics course. Subjects in this study were sport students of PGRI Palembang semester V which amounted to 31 people. The research method used is quasi experiment type one case shoot study. Data collection techniques in this study use the test and data analysis used is quantitative descriptive statistics. The conclusion of this study shown that the mathematical problem solving ability of PGRI Palembang sport students of V semester in the statistical course is categorized well with the average of the final test score of 80.3.

Automated Quantitative Analysis of Retinal Microvasculature in Normal Eyes on Optical Coherence Tomography Angiography.

PubMed

Lupidi, Marco; Coscas, Florence; Cagini, Carlo; Fiore, Tito; Spaccini, Elisa; Fruttini, Daniela; Coscas, Gabriel

2016-09-01

To describe a new automated quantitative technique for displaying and analyzing macular vascular perfusion using optical coherence tomography angiography (OCT-A) and to determine a normative data set, which might be used as reference in identifying progressive changes due to different retinal vascular diseases. Reliability study. A retrospective review of 47 eyes of 47 consecutive healthy subjects imaged with a spectral-domain OCT-A device was performed in a single institution. Full-spectrum amplitude-decorrelation angiography generated OCT angiograms of the retinal superficial and deep capillary plexuses. A fully automated custom-built software was used to provide quantitative data on the foveal avascular zone (FAZ) features and the total vascular and avascular surfaces. A comparative analysis between central macular thickness (and volume) and FAZ metrics was performed. Repeatability and reproducibility were also assessed in order to establish the feasibility and reliability of the method. The comparative analysis between the superficial capillary plexus and the deep capillary plexus revealed a statistically significant difference (P < .05) in terms of FAZ perimeter, surface, and major axis and a not statistically significant difference (P > .05) when considering total vascular and avascular surfaces. A linear correlation was demonstrated between central macular thickness (and volume) and the FAZ surface. Coefficients of repeatability and reproducibility were less than 0.4, thus demonstrating high intraobserver repeatability and interobserver reproducibility for all the examined data. A quantitative approach on retinal vascular perfusion, which is visible on Spectralis OCT angiography, may offer an objective and reliable method for monitoring disease progression in several retinal vascular diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Launch commit criteria performance trending analysis, phase 1, revision A. SRM and QA mission services

NASA Technical Reports Server (NTRS)

1989-01-01

An assessment of quantitative methods and measures for measuring launch commit criteria (LCC) performance measurement trends is made. A statistical performance trending analysis pilot study was processed and compared to STS-26 mission data. This study used four selected shuttle measurement types (solid rocket booster, external tank, space shuttle main engine, and range safety switch safe and arm device) from the five missions prior to mission 51-L. After obtaining raw data coordinates, each set of measurements was processed to obtain statistical confidence bounds and mean data profiles for each of the selected measurement types. STS-26 measurements were compared to the statistical data base profiles to verify the statistical capability of assessing occurrences of data trend anomalies and abnormal time-varying operational conditions associated with data amplitude and phase shifts.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

A Framework for Establishing Standard Reference Scale of Texture by Multivariate Statistical Analysis Based on Instrumental Measurement and Sensory Evaluation.

PubMed

Zhi, Ruicong; Zhao, Lei; Xie, Nan; Wang, Houyin; Shi, Bolin; Shi, Jingye

2016-01-13

A framework of establishing standard reference scale (texture) is proposed by multivariate statistical analysis according to instrumental measurement and sensory evaluation. Multivariate statistical analysis is conducted to rapidly select typical reference samples with characteristics of universality, representativeness, stability, substitutability, and traceability. The reasonableness of the framework method is verified by establishing standard reference scale of texture attribute (hardness) with Chinese well-known food. More than 100 food products in 16 categories were tested using instrumental measurement (TPA test), and the result was analyzed with clustering analysis, principal component analysis, relative standard deviation, and analysis of variance. As a result, nine kinds of foods were determined to construct the hardness standard reference scale. The results indicate that the regression coefficient between the estimated sensory value and the instrumentally measured value is significant (R(2) = 0.9765), which fits well with Stevens's theory. The research provides reliable a theoretical basis and practical guide for quantitative standard reference scale establishment on food texture characteristics.

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Infusion of Quantitative and Statistical Concepts into Biology Courses Does Not Improve Quantitative Literacy

ERIC Educational Resources Information Center

Beck, Christopher W.

2018-01-01

Multiple national reports have pushed for the integration of quantitative concepts into the context of disciplinary science courses. The aim of this study was to evaluate the quantitative and statistical literacy of biology students and explore learning gains when those skills were taught implicitly in the context of biology. I examined gains in…

Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

2013-07-01

This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

PubMed

Banerjee, Imon; Malladi, Sadhika; Lee, Daniela; Depeursinge, Adrien; Telli, Melinda; Lipson, Jafi; Golden, Daniel; Rubin, Daniel L

2018-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

PubMed

Gunawardena, Harsha P; O'Brien, Jonathon; Wrobel, John A; Xie, Ling; Davies, Sherri R; Li, Shunqiang; Ellis, Matthew J; Qaqish, Bahjat F; Chen, Xian

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Understanding quantitative research: part 1.

PubMed

Hoe, Juanita; Hoare, Zoë

This article, which is the first in a two-part series, provides an introduction to understanding quantitative research, basic statistics and terminology used in research articles. Critical appraisal of research articles is essential to ensure that nurses remain up to date with evidence-based practice to provide consistent and high-quality nursing care. This article focuses on developing critical appraisal skills and understanding the use and implications of different quantitative approaches to research. Part two of this article will focus on explaining common statistical terms and the presentation of statistical data in quantitative research.

Navigational Traffic Conflict Technique: A Proactive Approach to Quantitative Measurement of Collision Risks in Port Waters

NASA Astrophysics Data System (ADS)

Debnath, Ashim Kumar; Chin, Hoong Chor

Navigational safety analysis relying on collision statistics is often hampered because of the low number of observations. A promising alternative approach that overcomes this problem is proposed in this paper. By analyzing critical vessel interactions this approach proactively measures collision risk in port waters. The proposed method is illustrated for quantitative measurement of collision risks in Singapore port fairways, and validated by examining correlations between the measured risks with those perceived by pilots. This method is an ethically appealing alternative to the collision-based analysis for fast, reliable and effective safety assessment, thus possessing great potential for managing collision risks in port waters.

An Exploration of Bias in Meta-Analysis: The Case of Technology Integration Research in Higher Education

ERIC Educational Resources Information Center

Bernard, Robert M.; Borokhovski, Eugene; Schmid, Richard F.; Tamim, Rana M.

2014-01-01

This article contains a second-order meta-analysis and an exploration of bias in the technology integration literature in higher education. Thirteen meta-analyses, dated from 2000 to 2014 were selected to be included based on the questions asked and the presence of adequate statistical information to conduct a quantitative synthesis. The weighted…

Consequences of Assumption Violations Revisited: A Quantitative Review of Alternatives to the One-Way Analysis of Variance "F" Test.

ERIC Educational Resources Information Center

Lix, Lisa M.; And Others

1996-01-01

Meta-analytic techniques were used to summarize the statistical robustness literature on Type I error properties of alternatives to the one-way analysis of variance "F" test. The James (1951) and Welch (1951) tests performed best under violations of the variance homogeneity assumption, although their use is not always appropriate. (SLD)

Statistics, Structures & Satisfied Customers: Using Web Log Data to Improve Site Performance.

ERIC Educational Resources Information Center

Peacock, Darren

This paper explores some of the ways in which the National Museum of Australia is using Web analysis tools to shape its future directions in the delivery of online services. In particular, it explores the potential of quantitative analysis, based on Web server log data, to convert these ephemeral traces of user experience into a strategic…

Effectiveness of Quantitative Real Time PCR in Long-Term Follow-up of Chronic Myeloid Leukemia Patients.

PubMed

Savasoglu, Kaan; Payzin, Kadriye Bahriye; Ozdemirkiran, Fusun; Berber, Belgin

2015-08-01

To determine the use of the Quantitative Real Time PCR (RQ-PCR) assay follow-up with Chronic Myeloid Leukemia (CML) patients. Cross-sectional observational. Izmir Ataturk Education and Research Hospital, Izmir, Turkey, from 2009 to 2013. Cytogenetic, FISH, RQ-PCR test results from 177 CMLpatients' materials selected between 2009 - 2013 years was set up for comparison analysis. Statistical analysis was performed to compare between FISH, karyotype and RQ-PCR results of the patients. Karyotyping and FISH specificity and sensitivity rates determined by ROC analysis compared with RQ-PCR results. Chi-square test was used to compare test failure rates. Sensitivity and specificity values were determined for karyotyping 17.6 - 98% (p=0.118, p > 0.05) and for FISH 22.5 - 96% (p=0.064, p > 0.05) respectively. FISH sensitivity was slightly higher than karyotyping but there was calculated a strong correlation between them (p < 0.001). RQ-PCR test failure rate did not correlate with other two tests (p > 0.05); however, karyotyping and FISH test failure rate was statistically significant (p < 0.001). Besides, the situation needed for karyotype analysis, RQ-PCR assay can be used alone in the follow-up of CMLdisease.

Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

PubMed Central

Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

2012-01-01

Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

Microscopes and computers combined for analysis of chromosomes

NASA Technical Reports Server (NTRS)

Butler, J. W.; Butler, M. K.; Stroud, A. N.

1969-01-01

Scanning machine CHLOE, developed for photographic use, is combined with a digital computer to obtain quantitative and statistically significant data on chromosome shapes, distribution, density, and pairing. CHLOE permits data acquisition about a chromosome complement to be obtained two times faster than by manual pairing.

Statistical methodology: II. Reliability and validity assessment in study design, Part B.

PubMed

Karras, D J

1997-02-01

Validity measures the correspondence between a test and other purported measures of the same or similar qualities. When a reference standard exists, a criterion-based validity coefficient can be calculated. If no such standard is available, the concepts of content and construct validity may be used, but quantitative analysis may not be possible. The Pearson and Spearman tests of correlation are often used to assess the correspondence between tests, but do not account for measurement biases and may yield misleading results. Techniques that measure interest differences may be more meaningful in validity assessment, and the kappa statistic is useful for analyzing categorical variables. Questionnaires often can be designed to allow quantitative assessment of reliability and validity, although this may be difficult. Inclusion of homogeneous questions is necessary to assess reliability. Analysis is enhanced by using Likert scales or similar techniques that yield ordinal data. Validity assessment of questionnaires requires careful definition of the scope of the test and comparison with previously validated tools.

Characterization of a neutron sensitive MCP/Timepix detector for quantitative image analysis at a pulsed neutron source

NASA Astrophysics Data System (ADS)

Watanabe, Kenichi; Minniti, Triestino; Kockelmann, Winfried; Dalgliesh, Robert; Burca, Genoveva; Tremsin, Anton S.

2017-07-01

The uncertainties and the stability of a neutron sensitive MCP/Timepix detector when operating in the event timing mode for quantitative image analysis at a pulsed neutron source were investigated. The dominant component to the uncertainty arises from the counting statistics. The contribution of the overlap correction to the uncertainty was concluded to be negligible from considerations based on the error propagation even if a pixel occupation probability is more than 50%. We, additionally, have taken into account the multiple counting effect in consideration of the counting statistics. Furthermore, the detection efficiency of this detector system changes under relatively high neutron fluxes due to the ageing effects of current Microchannel Plates. Since this efficiency change is position-dependent, it induces a memory image. The memory effect can be significantly reduced with correction procedures using the rate equations describing the permanent gain degradation and the scrubbing effect on the inner surfaces of the MCP pores.

Ramifications of increased training in quantitative methodology.

PubMed

Zimiles, Herbert

2009-01-01

Comments on the article "Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America" by Aiken, West, and Millsap. The current author asks three questions that are provoked by the comprehensive identification of gaps and deficiencies in the training of quantitative methodology that led Aiken, West, and Millsap to call for expanded graduate instruction resources and programs. This comment calls for greater attention to how advances and expansion in the training of quantitative analysis are influencing who chooses to study psychology and how and what will be studied. PsycINFO Database Record 2009 APA.

Quantitative analysis of sitagliptin using the (19)F-NMR method: a universal technique for fluorinated compound detection.

PubMed

Zhang, Fen-Fen; Jiang, Meng-Hong; Sun, Lin-Lin; Zheng, Feng; Dong, Lei; Shah, Vishva; Shen, Wen-Bin; Ding, Ya

2015-01-07

To expand the application scope of nuclear magnetic resonance (NMR) technology in quantitative analysis of pharmaceutical ingredients, (19)F nuclear magnetic resonance ((19)F-NMR) spectroscopy has been employed as a simple, rapid, and reproducible approach for the detection of a fluorine-containing model drug, sitagliptin phosphate monohydrate (STG). ciprofloxacin (Cipro) has been used as the internal standard (IS). Influential factors, including the relaxation delay time (d1) and pulse angle, impacting the accuracy and precision of spectral data are systematically optimized. Method validation has been carried out in terms of precision and intermediate precision, linearity, limit of detection (LOD) and limit of quantification (LOQ), robustness, and stability. To validate the reliability and feasibility of the (19)F-NMR technology in quantitative analysis of pharmaceutical analytes, the assay result has been compared with that of (1)H-NMR. The statistical F-test and student t-test at 95% confidence level indicate that there is no significant difference between these two methods. Due to the advantages of (19)F-NMR, such as higher resolution and suitability for biological samples, it can be used as a universal technology for the quantitative analysis of other fluorine-containing pharmaceuticals and analytes.

NASA standard: Trend analysis techniques

NASA Technical Reports Server (NTRS)

1988-01-01

This Standard presents descriptive and analytical techniques for NASA trend analysis applications. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. Use of this Standard is not mandatory; however, it should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend Analysis is neither a precise term nor a circumscribed methodology, but rather connotes, generally, quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this Standard. The document presents the basic ideas needed for qualitative and quantitative assessment of trends, together with relevant examples. A list of references provides additional sources of information.

Data article on the effectiveness of entrepreneurship curriculum contents on entrepreneurial interest and knowledge of Nigerian university students.

PubMed

Olokundun, Maxwell; Iyiola, Oluwole; Ibidunni, Stephen; Ogbari, Mercy; Falola, Hezekiah; Salau, Odunayo; Peter, Fred; Borishade, Taiye

2018-06-01

The article presented data on the effectiveness of entrepreneurship curriculum contents on university students' entrepreneurial interest and knowledge. The study focused on the perceptions of Nigerian university students. Emphasis was laid on the first four universities in Nigeria to offer a degree programme in entrepreneurship. The study adopted quantitative approach with a descriptive research design to establish trends related to the objective of the study. Survey was be used as quantitative research method. The population of this study included all students in the selected universities. Data was analyzed with the use of Statistical Package for Social Sciences (SPSS). Mean score was used as statistical tool of analysis. The field data set is made widely accessible to enable critical or a more comprehensive investigation.

Factors influencing students' perceptions of their quantitative skills

NASA Astrophysics Data System (ADS)

Matthews, Kelly E.; Hodgson, Yvonne; Varsavsky, Cristina

2013-09-01

There is international agreement that quantitative skills (QS) are an essential graduate competence in science. QS refer to the application of mathematical and statistical thinking and reasoning in science. This study reports on the use of the Science Students Skills Inventory to capture final year science students' perceptions of their QS across multiple indicators, at two Australian research-intensive universities. Statistical analysis reveals several variables predicting higher levels of self-rated competence in QS: students' grade point average, students' perceptions of inclusion of QS in the science degree programme, their confidence in QS, and their belief that QS will be useful in the future. The findings are discussed in terms of implications for designing science curricula more effectively to build students' QS throughout science degree programmes. Suggestions for further research are offered.

Agriculture, population growth, and statistical analysis of the radiocarbon record.

PubMed

Zahid, H Jabran; Robinson, Erick; Kelly, Robert L

2016-01-26

The human population has grown significantly since the onset of the Holocene about 12,000 y ago. Despite decades of research, the factors determining prehistoric population growth remain uncertain. Here, we examine measurements of the rate of growth of the prehistoric human population based on statistical analysis of the radiocarbon record. We find that, during most of the Holocene, human populations worldwide grew at a long-term annual rate of 0.04%. Statistical analysis of the radiocarbon record shows that transitioning farming societies experienced the same rate of growth as contemporaneous foraging societies. The same rate of growth measured for populations dwelling in a range of environments and practicing a variety of subsistence strategies suggests that the global climate and/or endogenous biological factors, not adaptability to local environment or subsistence practices, regulated the long-term growth of the human population during most of the Holocene. Our results demonstrate that statistical analyses of large ensembles of radiocarbon dates are robust and valuable for quantitatively investigating the demography of prehistoric human populations worldwide.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Meta-analysis is not an exact science: Call for guidance on quantitative synthesis decisions.

PubMed

Haddaway, Neal R; Rytwinski, Trina

2018-05-01

Meta-analysis is becoming increasingly popular in the field of ecology and environmental management. It increases the effective power of analyses relative to single studies, and allows researchers to investigate effect modifiers and sources of heterogeneity that could not be easily examined within single studies. Many systematic reviewers will set out to conduct a meta-analysis as part of their synthesis, but meta-analysis requires a niche set of skills that are not widely held by the environmental research community. Each step in the process of carrying out a meta-analysis requires decisions that have both scientific and statistical implications. Reviewers are likely to be faced with a plethora of decisions over which effect size to choose, how to calculate variances, and how to build statistical models. Some of these decisions may be simple based on appropriateness of the options. At other times, reviewers must choose between equally valid approaches given the information available to them. This presents a significant problem when reviewers are attempting to conduct a reliable synthesis, such as a systematic review, where subjectivity is minimised and all decisions are documented and justified transparently. We propose three urgent, necessary developments within the evidence synthesis community. Firstly, we call on quantitative synthesis experts to improve guidance on how to prepare data for quantitative synthesis, providing explicit detail to support systematic reviewers. Secondly, we call on journal editors and evidence synthesis coordinating bodies (e.g. CEE) to ensure that quantitative synthesis methods are adequately reported in a transparent and repeatable manner in published systematic reviews. Finally, where faced with two or more broadly equally valid alternative methods or actions, reviewers should conduct multiple analyses, presenting all options, and discussing the implications of the different analytical approaches. We believe it is vital to tackle the possible subjectivity in quantitative synthesis described herein to ensure that the extensive efforts expended in producing systematic reviews and other evidence synthesis products is not wasted because of a lack of rigour or reliability in the final synthesis step. Copyright © 2018 Elsevier Ltd. All rights reserved.

Thinking big

NASA Astrophysics Data System (ADS)

Collins, Harry

2008-02-01

Physicists are often quick to discount social research based on qualitative techniques such as ethnography and "deep case studies" - where a researcher draws conclusions about a community based on immersion in the field - thinking that only quantitative research backed up by statistical analysis is sound. The balance is not so clear, however.

Research Analysis on MOOC Course Dropout and Retention Rates

ERIC Educational Resources Information Center

Gomez-Zermeno, Marcela Gerogina; Aleman de La Garza, Lorena

2016-01-01

This research's objective was to identify the terminal efficiency of the Massive Online Open Course "Educational Innovation with Open Resources" offered by a Mexican private university. A quantitative methodology was used, combining descriptive statistics and probabilistic models to analyze the levels of retention, completion, and…

Linguistic Alternatives to Quantitative Research Strategies. Part One: How Linguistic Mechanisms Advance Research Outcomes

ERIC Educational Resources Information Center

Yeager, Joseph; Sommer, Linda

2007-01-01

Combining psycholinguistic technologies and systems analysis created advances in motivational profiling and numerous new behavioral engineering applications. These advances leapfrog many mainstream statistical research methods, producing superior research results via cause-effect language mechanisms. Entire industries explore motives ranging from…

Statistical Issues in Testing Conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Profile Claims.

PubMed

Obuchowski, Nancy A; Buckler, Andrew; Kinahan, Paul; Chen-Mayer, Heather; Petrick, Nicholas; Barboriak, Daniel P; Bullen, Jennifer; Barnhart, Huiman; Sullivan, Daniel C

2016-04-01

A major initiative of the Quantitative Imaging Biomarker Alliance is to develop standards-based documents called "Profiles," which describe one or more technical performance claims for a given imaging modality. The term "actor" denotes any entity (device, software, or person) whose performance must meet certain specifications for the claim to be met. The objective of this paper is to present the statistical issues in testing actors' conformance with the specifications. In particular, we present the general rationale and interpretation of the claims, the minimum requirements for testing whether an actor achieves the performance requirements, the study designs used for testing conformity, and the statistical analysis plan. We use three examples to illustrate the process: apparent diffusion coefficient in solid tumors measured by MRI, change in Perc 15 as a biomarker for the progression of emphysema, and percent change in solid tumor volume by computed tomography as a biomarker for lung cancer progression. Copyright © 2016 The Association of University Radiologists. All rights reserved.

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

PubMed

Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira

2014-08-01

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Topological Cacti: Visualizing Contour-based Statistics

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

Weber, Gunther H.; Bremer, Peer-Timo; Pascucci, Valerio

2011-05-26

Contours, the connected components of level sets, play an important role in understanding the global structure of a scalar field. In particular their nestingbehavior and topology-often represented in form of a contour tree-have been used extensively for visualization and analysis. However, traditional contour trees onlyencode structural properties like number of contours or the nesting of contours, but little quantitative information such as volume or other statistics. Here we use thesegmentation implied by a contour tree to compute a large number of per-contour (interval) based statistics of both the function defining the contour tree as well asother co-located functions. We introducemore » a new visual metaphor for contour trees, called topological cacti, that extends the traditional toporrery display of acontour tree to display additional quantitative information as width of the cactus trunk and length of its spikes. We apply the new technique to scalar fields ofvarying dimension and different measures to demonstrate the effectiveness of the approach.« less

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

PubMed

Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

2017-11-01

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

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

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Immunohistochemical evaluation of inducible nitric oxide synthase in the epithelial lining of odontogenic cysts: A qualitative and quantitative analysis

PubMed Central

Akshatha, B K; Karuppiah, Karpagaselvi; Manjunath, G S; Kumarswamy, Jayalakshmi; Papaiah, Lokesh; Rao, Jyothi

2017-01-01

Introduction: The three common odontogenic cysts include radicular cysts (RCs), dentigerous cysts (DCs), and odontogenic keratocysts (OKCs). Among these 3 cysts, OKC is recently been classified as benign keratocystic odontogenic tumor attributing to its aggressive behavior, recurrence rate, and malignant potential. The present study involved qualitative and quantitative analysis of inducible nitric oxide synthase (iNOS) expression in epithelial lining of RCs, DCs, and OKCs, compare iNOS expression in epithelial linings of all the 3 cysts and determined overexpression of iNOS in OKCs which might contribute to its aggressive behavior and malignant potential. Aims: The present study is to investigate the role of iNOS in the pathogenesis of OKCs, DCs, and RCs by evaluating the iNOS expression in the epithelial lining of these cysts. Subjects and Methods: Analysis of iNOS expression in epithelial lining cells of 20 RCs, 20 DCs, and 20 OKCs using immunohistochemistry done. Statistical Analysis Used: The percentage of positive cells and intensity of stain was assessed and compared among all the 3 cysts using contingency coefficient. Kappa statistics for the two observers were computed for finding interobserver agreement. Results: The percentage of iNOS-positive cells was found to be remarkably high in OKCs (12/20) –57.1% as compared to RCs (6/20) – 28.6% and DCs (3/20) – 14.3%. The interobserver agreement for iNOS-positive percentage cells was arrived with kappa values with OKCs → Statistically significant (P > 0.000), RCs → statistically significant (P > 0.001) with no significant values for DCs. No statistical difference exists among 3 study samples in regard to the intensity of staining with iNOS. Conclusions: Increased iNOS expression in OKCs may contribute to bone resorption and accumulation of wild-type p53, hence, making OKCs more aggressive. PMID:29391711

Rapid Quantitation of Ascorbic and Folic Acids in SRM 3280 Multivitamin/Multielement Tablets using Flow-Injection Tandem Mass Spectrometry

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

Bhandari, Deepak; Kertesz, Vilmos; Van Berkel, Gary J

RATIONALE: Ascorbic acid (AA) and folic acid (FA) are water-soluble vitamins and are usually fortified in food and dietary supplements. For the safety of human health, proper intake of these vitamins is recommended. Improvement in the analysis time required for the quantitative determination of these vitamins in food and nutritional formulations is desired. METHODS: A simple and fast (~5 min) in-tube sample preparation was performed, independently for FA and AA, by mixing extraction solvent with a powdered sample aliquot followed by agitation, centrifugation, and filtration to recover an extract for analysis. Quantitative detection was achieved by flow-injection (1 L injectionmore » volume) electrospray ionization tandem mass spectrometry (ESI-MS/MS) in negative ion mode using the method of standard addition. RESULTS: Method of standard addition was employed for the quantitative estimation of each vitamin in a sample extract. At least 2 spiked and 1 non-spiked sample extract were injected in triplicate for each quantitative analysis. Given an injection-to-injection interval of approximately 2 min, about 18 min was required to complete the quantitative estimation of each vitamin. The concentration values obtained for the respective vitamins in the standard reference material (SRM) 3280 using this approach were within the statistical range of the certified values provided in the NIST Certificate of Analysis. The estimated limit of detections of FA and AA were 13 and 5.9 ng/g, respectively. CONCLUSIONS: Flow-injection ESI-MS/MS was successfully applied for the rapid quantitation of FA and AA in SRM 3280 multivitamin/multielement tablets.« less

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

NASA Technical Reports Server (NTRS)

Tamayo, Tak Chai

1987-01-01

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy.

PubMed

Biglands, John D; Ibraheem, Montasir; Magee, Derek R; Radjenovic, Aleksandra; Plein, Sven; Greenwood, John P

2018-05-01

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial blood flow values to generate a myocardial perfusion reserve did not significantly increase the quantitative analysis area under the curve (p = 0.79). Quantitative perfusion has a high diagnostic accuracy for detecting coronary artery disease but is not superior to visual analysis. The incorporation of rest perfusion imaging does not improve diagnostic accuracy in quantitative perfusion analysis. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Selecting the most appropriate inferential statistical test for your quantitative research study.

PubMed

Bettany-Saltikov, Josette; Whittaker, Victoria Jane

2014-06-01

To discuss the issues and processes relating to the selection of the most appropriate statistical test. A review of the basic research concepts together with a number of clinical scenarios is used to illustrate this. Quantitative nursing research generally features the use of empirical data which necessitates the selection of both descriptive and statistical tests. Different types of research questions can be answered by different types of research designs, which in turn need to be matched to a specific statistical test(s). Discursive paper. This paper discusses the issues relating to the selection of the most appropriate statistical test and makes some recommendations as to how these might be dealt with. When conducting empirical quantitative studies, a number of key issues need to be considered. Considerations for selecting the most appropriate statistical tests are discussed and flow charts provided to facilitate this process. When nursing clinicians and researchers conduct quantitative research studies, it is crucial that the most appropriate statistical test is selected to enable valid conclusions to be made. © 2013 John Wiley & Sons Ltd.

Not so Fast My Friend: The Rush to R and the Need for Rigorous Evaluation of Data Analysis and Software in Education

ERIC Educational Resources Information Center

Harwell, Michael

2014-01-01

Commercial data analysis software has been a fixture of quantitative analyses in education for more than three decades. Despite its apparent widespread use there is no formal evidence cataloging what software is used in educational research and educational statistics classes, by whom and for what purpose, and whether some programs should be…

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

A quantitative analysis of factors influencing the professional longevity of high school science teachers in Florida

NASA Astrophysics Data System (ADS)

Ridgley, James Alexander, Jr.

This dissertation is an exploratory quantitative analysis of various independent variables to determine their effect on the professional longevity (years of service) of high school science teachers in the state of Florida for the academic years 2011-2012 to 2013-2014. Data are collected from the Florida Department of Education, National Center for Education Statistics, and the National Assessment of Educational Progress databases. The following research hypotheses are examined: H1 - There are statistically significant differences in Level 1 (teacher variables) that influence the professional longevity of a high school science teacher in Florida. H2 - There are statistically significant differences in Level 2 (school variables) that influence the professional longevity of a high school science teacher in Florida. H3 - There are statistically significant differences in Level 3 (district variables) that influence the professional longevity of a high school science teacher in Florida. H4 - When tested in a hierarchical multiple regression, there are statistically significant differences in Level 1, Level 2, or Level 3 that influence the professional longevity of a high school science teacher in Florida. The professional longevity of a Floridian high school science teacher is the dependent variable. The independent variables are: (Level 1) a teacher's sex, age, ethnicity, earned degree, salary, number of schools taught in, migration count, and various years of service in different areas of education; (Level 2) a school's geographic location, residential population density, average class size, charter status, and SES; and (Level 3) a school district's average SES and average spending per pupil. Statistical analyses of exploratory MLRs and a HMR are used to support the research hypotheses. The final results of the HMR analysis show a teacher's age, salary, earned degree (unknown, associate, and doctorate), and ethnicity (Hispanic and Native Hawaiian/Pacific Islander); a school's charter status; and a school district's average SES are all significant predictors of a Florida high school science teacher's professional longevity. Although statistically significant in the initial exploratory MLR analyses, a teacher's ethnicity (Asian and Black), a school's geographic location (city and rural), and a school's SES are not statistically significant in the final HMR model.

Objective research of auscultation signals in Traditional Chinese Medicine based on wavelet packet energy and support vector machine.

PubMed

Yan, Jianjun; Shen, Xiaojing; Wang, Yiqin; Li, Fufeng; Xia, Chunming; Guo, Rui; Chen, Chunfeng; Shen, Qingwei

2010-01-01

This study aims at utilising Wavelet Packet Transform (WPT) and Support Vector Machine (SVM) algorithm to make objective analysis and quantitative research for the auscultation in Traditional Chinese Medicine (TCM) diagnosis. First, Wavelet Packet Decomposition (WPD) at level 6 was employed to split more elaborate frequency bands of the auscultation signals. Then statistic analysis was made based on the extracted Wavelet Packet Energy (WPE) features from WPD coefficients. Furthermore, the pattern recognition was used to distinguish mixed subjects' statistical feature values of sample groups through SVM. Finally, the experimental results showed that the classification accuracies were at a high level.

Counting Better? An Examination of the Impact of Quantitative Method Teaching on Statistical Anxiety and Confidence

ERIC Educational Resources Information Center

Chamberlain, John Martyn; Hillier, John; Signoretta, Paola

2015-01-01

This article reports the results of research concerned with students' statistical anxiety and confidence to both complete and learn to complete statistical tasks. Data were collected at the beginning and end of a quantitative method statistics module. Students recognised the value of numeracy skills but felt they were not necessarily relevant for…

Which statistics should tropical biologists learn?

PubMed

Loaiza Velásquez, Natalia; González Lutz, María Isabel; Monge-Nájera, Julián

2011-09-01

Tropical biologists study the richest and most endangered biodiversity in the planet, and in these times of climate change and mega-extinctions, the need for efficient, good quality research is more pressing than in the past. However, the statistical component in research published by tropical authors sometimes suffers from poor quality in data collection; mediocre or bad experimental design and a rigid and outdated view of data analysis. To suggest improvements in their statistical education, we listed all the statistical tests and other quantitative analyses used in two leading tropical journals, the Revista de Biología Tropical and Biotropica, during a year. The 12 most frequent tests in the articles were: Analysis of Variance (ANOVA), Chi-Square Test, Student's T Test, Linear Regression, Pearson's Correlation Coefficient, Mann-Whitney U Test, Kruskal-Wallis Test, Shannon's Diversity Index, Tukey's Test, Cluster Analysis, Spearman's Rank Correlation Test and Principal Component Analysis. We conclude that statistical education for tropical biologists must abandon the old syllabus based on the mathematical side of statistics and concentrate on the correct selection of these and other procedures and tests, on their biological interpretation and on the use of reliable and friendly freeware. We think that their time will be better spent understanding and protecting tropical ecosystems than trying to learn the mathematical foundations of statistics: in most cases, a well designed one-semester course should be enough for their basic requirements.

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

The Effectiveness of Edgenuity When Used for Credit Recovery

ERIC Educational Resources Information Center

Eddy, Carri

2013-01-01

This quantitative study used descriptive statistics, logistic regression, and chi-square analysis to determine the impact of using Edgenuity (formerly Education 2020 Virtual Classroom) to assist students in the recovery of lost credits. The sample included a North Texas school district. The Skyward student management system provided archived…

Quantitative Microbial Risk Assessment Tutorial: Publishing a Microbial Density Time Series as a Txt File

EPA Science Inventory

A SARA Timeseries Utility supports analysis and management of time-varying environmental data including listing, graphing, computing statistics, computing meteorological data and saving in a WDM or text file. File formats supported include WDM, HSPF Binary (.hbn), USGS RDB, and T...

Developing and Assessing E-Learning Techniques for Teaching Forecasting

ERIC Educational Resources Information Center

Gel, Yulia R.; O'Hara Hines, R. Jeanette; Chen, He; Noguchi, Kimihiro; Schoner, Vivian

2014-01-01

In the modern business environment, managers are increasingly required to perform decision making and evaluate related risks based on quantitative information in the face of uncertainty, which in turn increases demand for business professionals with sound skills and hands-on experience with statistical data analysis. Computer-based training…

Predictors of Science Subject Discipline Identities: A Statistical Analysis

ERIC Educational Resources Information Center

Nieswandt, Martina; Barrett, Sarah E.; McEneaney, Elizabeth H.

2013-01-01

This quantitative study (n = 247) explores whether preservice science teachers express science-specific identities that reflect multiple areas of their beliefs (e.g., purpose for science teaching, inclusion of science-technology-society-environment issues into science teaching, and nature of science) as well as other individual characteristics…

Investigation of Millennial Students' Responses to a Shelter-in-Place Experience

ERIC Educational Resources Information Center

Johnson, Thomas C.; Frick, Melodie H.

2016-01-01

This study investigated millennial students' responses to an armed gunman threat and shelter-in-place warnings that occurred on a university campus. Using descriptive statistics and quantitative analysis, several significant differences were found for students' responses for sheltering-in-place and engaging in protective behaviors. Baxter Magolda'…

Predicting Teacher Job Satisfaction Based on Principals' Instructional Supervision Behaviours: A Study of Turkish Teachers

ERIC Educational Resources Information Center

Ilgan, Abdurrahman; Parylo, Oksana; Sungu, Hilmi

2015-01-01

This quantitative research examined instructional supervision behaviours of school principals as a predictor of teacher job satisfaction through the analysis of Turkish teachers' perceptions of principals' instructional supervision behaviours. There was a statistically significant difference found between the teachers' job satisfaction level and…

High-coverage quantitative proteomics using amine-specific isotopic labeling.

PubMed

Melanson, Jeremy E; Avery, Steven L; Pinto, Devanand M

2006-08-01

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.

Food Consumption and Handling Survey for Quantitative Microbiological Consumer Phase Risk Assessments.

PubMed

Chardon, Jurgen; Swart, Arno

2016-07-01

In the consumer phase of a typical quantitative microbiological risk assessment (QMRA), mathematical equations identify data gaps. To acquire useful data we designed a food consumption and food handling survey (2,226 respondents) for QMRA applications that is especially aimed at obtaining quantitative data. For a broad spectrum of food products, the survey covered the following topics: processing status at retail, consumer storage, preparation, and consumption. Questions were designed to facilitate distribution fitting. In the statistical analysis, special attention was given to the selection of the most adequate distribution to describe the data. Bootstrap procedures were used to describe uncertainty. The final result was a coherent quantitative consumer phase food survey and parameter estimates for food handling and consumption practices in The Netherlands, including variation over individuals and uncertainty estimates.

Doctoral training in statistics, measurement, and methodology in psychology: replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America.

PubMed

Aiken, Leona S; West, Stephen G; Millsap, Roger E

2008-01-01

In a survey of all PhD programs in psychology in the United States and Canada, the authors documented the quantitative methodology curriculum (statistics, measurement, and research design) to examine the extent to which innovations in quantitative methodology have diffused into the training of PhDs in psychology. In all, 201 psychology PhD programs (86%) participated. This survey replicated and extended a previous survey (L. S. Aiken, S. G. West, L. B. Sechrest, & R. R. Reno, 1990), permitting examination of curriculum development. Most training supported laboratory and not field research. The median of 1.6 years of training in statistics and measurement was mainly devoted to the modally 1-year introductory statistics course, leaving little room for advanced study. Curricular enhancements were noted in statistics and to a minor degree in measurement. Additional coverage of both fundamental and innovative quantitative methodology is needed. The research design curriculum has largely stagnated, a cause for great concern. Elite programs showed no overall advantage in quantitative training. Forces that support curricular innovation are characterized. Human capital challenges to quantitative training, including recruiting and supporting young quantitative faculty, are discussed. Steps must be taken to bring innovations in quantitative methodology into the curriculum of PhD programs in psychology. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Quantitative chromatin pattern description in Feulgen-stained nuclei as a diagnostic tool to characterize the oligodendroglial and astroglial components in mixed oligo-astrocytomas.

PubMed

Decaestecker, C; Lopes, B S; Gordower, L; Camby, I; Cras, P; Martin, J J; Kiss, R; VandenBerg, S R; Salmon, I

1997-04-01

The oligoastrocytoma, as a mixed glioma, represents a nosologic dilemma with respect to precisely defining the oligodendroglial and astroglial phenotypes that constitute the neoplastic cell lineages of these tumors. In this study, cell image analysis with Feulgen-stained nuclei was used to distinguish between oligodendroglial and astrocytic phenotypes in oligodendrogliomas and astrocytomas and then applied to mixed oligoastrocytomas. Quantitative features with respect to chromatin pattern (30 variables) and DNA ploidy (8 variables) were evaluated on Feulgen-stained nuclei in a series of 71 gliomas using computer-assisted microscopy. These included 32 oligodendrogliomas (OLG group: 24 grade II and 8 grade III tumors according to the WHO classification), 32 astrocytomas (AST group: 13 grade II and 19 grade III tumors), and 7 oligoastrocytomas (OLGAST group). Initially, image analysis with multivariate statistical analyses (Discriminant Analysis) could identify each glial tumor group. Highly significant statistical differences were obtained distinguishing the morphonuclear features of oligodendrogliomas from those of astrocytomas, regardless of their histological grade. When compared with the 7 mixed oligoastrocytomas under study, 5 exhibited DNA ploidy and chromatin pattern characteristics similar to grade II oligodendrogliomas, I to grade III oligodendrogliomas, and I to grade II astrocytomas. Using multifactorial statistical analyses (Discriminant Analysis combined with Principal Component Analysis). It was possible to quantify the proportion of "typical" glial cell phenotypes that compose grade II and III oligodendrogliomas and grade II and III astrocytomas in each mixed glioma. Cytometric image analysis may be an important adjunct to routine histopathology for the reproducible identification of neoplasms containing a mixture of oligodendroglial and astrocytic phenotypes.

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography

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

Paul, Jijo; Yang, Cungeng; Wu, Hui

Purpose: To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Methods and Materials: Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from themore » daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. Results: During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R{sup 2} > 0.99) and correlates weakly with the change in GTV (R{sup 2} = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Conclusion: Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.« less

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography.

PubMed

Paul, Jijo; Yang, Cungeng; Wu, Hui; Tai, An; Dalah, Entesar; Zheng, Cheng; Johnstone, Candice; Kong, Feng-Ming; Gore, Elizabeth; Li, X Allen

2017-06-01

To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R 2  > 0.99) and correlates weakly with the change in GTV (R 2  = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

[Quality evaluation of rhubarb dispensing granules based on multi-component simultaneous quantitative analysis and bioassay].

PubMed

Tan, Peng; Zhang, Hai-Zhu; Zhang, Ding-Kun; Wu, Shan-Na; Niu, Ming; Wang, Jia-Bo; Xiao, Xiao-He

2017-07-01

This study attempts to evaluate the quality of Chinese formula granules by combined use of multi-component simultaneous quantitative analysis and bioassay. The rhubarb dispensing granules were used as the model drug for demonstrative study. The ultra-high performance liquid chromatography (UPLC) method was adopted for simultaneously quantitative determination of the 10 anthraquinone derivatives (such as aloe emodin-8-O-β-D-glucoside) in rhubarb dispensing granules; purgative biopotency of different batches of rhubarb dispensing granules was determined based on compound diphenoxylate tablets-induced mouse constipation model; blood activating biopotency of different batches of rhubarb dispensing granules was determined based on in vitro rat antiplatelet aggregation model; SPSS 22.0 statistical software was used for correlation analysis between 10 anthraquinone derivatives and purgative biopotency, blood activating biopotency. The results of multi-components simultaneous quantitative analysisshowed that there was a great difference in chemical characterizationand certain differences inpurgative biopotency and blood activating biopotency among 10 batches of rhubarb dispensing granules. The correlation analysis showed that the intensity of purgative biopotency was significantly correlated with the content of conjugated anthraquinone glycosides (P<0.01), and the intensity of blood activating biopotency was significantly correlated with the content of free anthraquinone (P<0.01). In summary, the combined use of multi-component simultaneous quantitative analysis and bioassay can achieve objective quantification and more comprehensive reflection on overall quality difference among different batches of rhubarb dispensing granules. Copyright© by the Chinese Pharmaceutical Association.

Qualitative and quantitative interpretation of SEM image using digital image processing.

PubMed

Saladra, Dawid; Kopernik, Magdalena

2016-10-01

The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

PubMed Central

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232

Multispectral colour analysis for quantitative evaluation of pseudoisochromatic color deficiency tests

NASA Astrophysics Data System (ADS)

Ozolinsh, Maris; Fomins, Sergejs

2010-11-01

Multispectral color analysis was used for spectral scanning of Ishihara and Rabkin color deficiency test book images. It was done using tunable liquid-crystal LC filters built in the Nuance II analyzer. Multispectral analysis keeps both, information on spatial content of tests and on spectral content. Images were taken in the range of 420-720nm with a 10nm step. We calculated retina neural activity charts taking into account cone sensitivity functions, and processed charts in order to find the visibility of latent symbols in color deficiency plates using cross-correlation technique. In such way the quantitative measure is found for each of diagnostics plate for three different color deficiency carrier types - protanopes, deutanopes and tritanopes. Multispectral color analysis allows to determine the CIE xyz color coordinates of pseudoisochromatic plate design elements and to perform statistical analysis of these data to compare the color quality of available color deficiency test books.

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

Quantitative characterization of nanoscale polycrystalline magnets with electron magnetic circular dichroism.

PubMed

Muto, Shunsuke; Rusz, Ján; Tatsumi, Kazuyoshi; Adam, Roman; Arai, Shigeo; Kocevski, Vancho; Oppeneer, Peter M; Bürgler, Daniel E; Schneider, Claus M

2014-01-01

Electron magnetic circular dichroism (EMCD) allows the quantitative, element-selective determination of spin and orbital magnetic moments, similar to its well-established X-ray counterpart, X-ray magnetic circular dichroism (XMCD). As an advantage over XMCD, EMCD measurements are made using transmission electron microscopes, which are routinely operated at sub-nanometre resolution, thereby potentially allowing nanometre magnetic characterization. However, because of the low intensity of the EMCD signal, it has not yet been possible to obtain quantitative information from EMCD signals at the nanoscale. Here we demonstrate a new approach to EMCD measurements that considerably enhances the outreach of the technique. The statistical analysis introduced here yields robust quantitative EMCD signals. Moreover, we demonstrate that quantitative magnetic information can be routinely obtained using electron beams of only a few nanometres in diameter without imposing any restriction regarding the crystalline order of the specimen.

Thermal heterogeneity within aqueous materials quantified by 1H NMR spectroscopy: Multiparametric validation in silico and in vitro

NASA Astrophysics Data System (ADS)

Lutz, Norbert W.; Bernard, Monique

2018-02-01

We recently suggested a new paradigm for statistical analysis of thermal heterogeneity in (semi-)aqueous materials by 1H NMR spectroscopy, using water as a temperature probe. Here, we present a comprehensive in silico and in vitro validation that demonstrates the ability of this new technique to provide accurate quantitative parameters characterizing the statistical distribution of temperature values in a volume of (semi-)aqueous matter. First, line shape parameters of numerically simulated water 1H NMR spectra are systematically varied to study a range of mathematically well-defined temperature distributions. Then, corresponding models based on measured 1H NMR spectra of agarose gel are analyzed. In addition, dedicated samples based on hydrogels or biological tissue are designed to produce temperature gradients changing over time, and dynamic NMR spectroscopy is employed to analyze the resulting temperature profiles at sub-second temporal resolution. Accuracy and consistency of the previously introduced statistical descriptors of temperature heterogeneity are determined: weighted median and mean temperature, standard deviation, temperature range, temperature mode(s), kurtosis, skewness, entropy, and relative areas under temperature curves. Potential and limitations of this method for quantitative analysis of thermal heterogeneity in (semi-)aqueous materials are discussed in view of prospective applications in materials science as well as biology and medicine.

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

PubMed

Gebresllasie, Fanna; Tsadik, Mache; Berhane, Eyoel

2017-01-01

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

Relationship between environmental management with quality of kampong space room (Case study: RW 3 of Sukun Sub District, Malang City)

NASA Astrophysics Data System (ADS)

Wardhani, D. K.; Azmi, D. S.; Purnamasari, W. D.

2017-06-01

RW 3 Sukun Malang was one of kampong that won the competition kampong environment and had managed to maintain the preservation of the kampong. Society of RW 3 Sukun undertake various activities to manage the environment by optimizing the use of kampong space. Despite RW 3 Sukun had conducted environmental management activities, there are several locations in the kampong space that less well maintained. The purpose of this research was to determine the relation of environmental management with the quality of kampong space in RW 3 Sukun. This research used qualitative and quantitative research approaches. Quantitative research conducted by using descriptive statistical analysis in assessing the quality of kampong space with weighting, scoring, and overlay maps. Quantitative research was also conducted on the relation analysis of environmental management with the quality of kampong space by using typology analysis and pearson correlation analysis. Qualitative research conducted on the analysis of environmental management and the relation analysis of environmental management with the quality of kampong space. Result of this research indicates that environmental management in RW 3 Sukun have relation with the quality of kampong space.

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

Acoustic emission spectral analysis of fiber composite failure mechanisms

NASA Technical Reports Server (NTRS)

Egan, D. M.; Williams, J. H., Jr.

1978-01-01

The acoustic emission of graphite fiber polyimide composite failure mechanisms was investigated with emphasis on frequency spectrum analysis. Although visual examination of spectral densities could not distinguish among fracture sources, a paired-sample t statistical analysis of mean normalized spectral densities did provide quantitative discrimination among acoustic emissions from 10 deg, 90 deg, and plus or minus 45 deg, plus or minus 45 deg sub s specimens. Comparable discrimination was not obtained for 0 deg specimens.

Critiquing qualitative research.

PubMed

Beck, Cheryl Tatano

2009-10-01

The ability to critique research is a valuable skill that is fundamental to a perioperative nurse's ability to base his or her clinical practice on evidence derived from research. Criteria differ for critiquing a quantitative versus a qualitative study (ie, statistics are evaluated in a quantitative study, but not in a qualitative study). This article provides on guidelines for assessing qualitative research. Excerpts from a published qualitative research report are summarized and then critiqued. Questions are provided that help evaluate different sections of a research study (eg, sample, data collection methods, data analysis).

Aggregation and Disaggregation of Senile Plaques in Alzheimer Disease

NASA Astrophysics Data System (ADS)

Cruz, L.; Urbanc, B.; Buldyrev, S. V.; Christie, R.; Gomez-Isla, T.; Havlin, S.; McNamara, M.; Stanley, H. E.; Hyman, B. T.

1997-07-01

We quantitatively analyzed, using laser scanning confocal microscopy, the three-dimensional structure of individual senile plaques in Alzheimer disease. We carried out the quantitative analysis using statistical methods to gain insights about the processes that govern Aβ peptide deposition. Our results show that plaques are complex porous structures with characteristic pore sizes. We interpret plaque morphology in the context of a new dynamical model based on competing aggregation and disaggregation processes in kinetic steady-state equilibrium with an additional diffusion process allowing Aβ deposits to diffuse over the surface of plaques.

Histomorphometric, fractal and lacunarity comparative analysis of sheep (Ovis aries), goat (Capra hircus) and roe deer (Capreolus capreolus) compact bone samples.

PubMed

Gudea, A I; Stefan, A C

2013-08-01

Quantitative and qualitative studies dealing with histomorphometry of the bone tissue play a new role in modern legal medicine/forensic medicine and archaeozoology nowadays. This study deals with the differences found in case of humerus and metapodial bones of recent sheep (Ovis aries), goat (Capra hircus) and roedeer (Capreolus capreolus) specimens, both from a qualitative point of view, but mainly from a quantitative perspective. A novel perspective given by the fractal analysis performed on the digital histological images is approached. This study shows that the qualitative assessment may not be a reliable one due to the close resemblance of the structures. From the quantitative perspective (several measurements performed on osteonal units and statistical processing of data),some of the elements measured show significant differences among 3 species(the primary osteonal diameter, etc.). The fractal analysis and the lacunarity of the images show a great deal of potential, proving that this type of analysis can be of great help in the separation of the material from this perspective.

Real-time quantitative polymerase chain reaction analysis of patients with refractory chronic periodontitis.

PubMed

Marconcini, Simone; Covani, Ugo; Barone, Antonio; Vittorio, Orazio; Curcio, Michele; Barbuti, Serena; Scatena, Fabrizio; Felli, Lamberto; Nicolini, Claudio

2011-07-01

Periodontitis is a complex multifactorial disease and is typically polygenic in origin. Genes play a fundamental part in each biologic process forming complex networks of interactions. However, only some genes have a high number of interactions with other genes in the network and may, therefore, be considered to play an important role. In a preliminary bioinformatic analysis, five genes that showed a higher number of interactions were identified and termed leader genes. In the present study, we use real-time quantitative polymerase chain reaction (PCR) technology to evaluate the expression levels of leader genes in the leukocytes of 10 patients with refractory chronic periodontitis and compare the expression levels with those of the same genes in 24 healthy patients. Blood was collected from 24 healthy human subjects and 10 patients with refractory chronic periodontitis and placed into heparinized blood collection tubes by personnel trained in phlebotomy using a sterile technique. Blood leukocyte cells were immediately lysed by using a kit for total RNA purification from human whole blood. Complementary DNA (cDNA) synthesis was obtained from total RNA and then real-time quantitative PCR was performed. PCR efficiencies were calculated with a relative standard curve derived from a five cDNA dilution series in triplicate that gave regression coefficients >0.98 and efficiencies >96%. The standard curves were obtained using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and growth factor receptor binding protein 2 (GRB2), casitas B-lineage lymphoma (CBL), nuclear factor-KB1 (NFKB1), and REL-A (gene for transcription factor p65) gene primers and amplified with 1.6, 8, 40, 200, and 1,000 ng/μL total cDNA. Curves obtained for each sample showed a linear relationship between RNA concentrations and the cycle threshold value of real-time quantitative PCR for all genes. Data were expressed as mean ± SE (SEM). The groups were compared to the analysis of variance. A probability value <0.01 was considered statistically significant. The present study agrees with the preliminary bioinformatics analysis. In our experiments, the association of pathology with the genes was statistically significant for GRB2 and CBL (P <0.01), and it was not statistically significant for REL-A and NFKB1. This article lends support to our preliminary hypothesis that assigned an important role in refractory aggressive periodontitis to leader genes.

Interpreting comprehensive two-dimensional gas chromatography using peak topography maps with application to petroleum forensics.

PubMed

Ghasemi Damavandi, Hamidreza; Sen Gupta, Ananya; Nelson, Robert K; Reddy, Christopher M

2016-01-01

Comprehensive two-dimensional gas chromatography [Formula: see text] provides high-resolution separations across hundreds of compounds in a complex mixture, thus unlocking unprecedented information for intricate quantitative interpretation. We exploit this compound diversity across the [Formula: see text] topography to provide quantitative compound-cognizant interpretation beyond target compound analysis with petroleum forensics as a practical application. We focus on the [Formula: see text] topography of biomarker hydrocarbons, hopanes and steranes, as they are generally recalcitrant to weathering. We introduce peak topography maps (PTM) and topography partitioning techniques that consider a notably broader and more diverse range of target and non-target biomarker compounds compared to traditional approaches that consider approximately 20 biomarker ratios. Specifically, we consider a range of 33-154 target and non-target biomarkers with highest-to-lowest peak ratio within an injection ranging from 4.86 to 19.6 (precise numbers depend on biomarker diversity of individual injections). We also provide a robust quantitative measure for directly determining "match" between samples, without necessitating training data sets. We validate our methods across 34 [Formula: see text] injections from a diverse portfolio of petroleum sources, and provide quantitative comparison of performance against established statistical methods such as principal components analysis (PCA). Our data set includes a wide range of samples collected following the 2010 Deepwater Horizon disaster that released approximately 160 million gallons of crude oil from the Macondo well (MW). Samples that were clearly collected following this disaster exhibit statistically significant match [Formula: see text] using PTM-based interpretation against other closely related sources. PTM-based interpretation also provides higher differentiation between closely correlated but distinct sources than obtained using PCA-based statistical comparisons. In addition to results based on this experimental field data, we also provide extentive perturbation analysis of the PTM method over numerical simulations that introduce random variability of peak locations over the [Formula: see text] biomarker ROI image of the MW pre-spill sample (sample [Formula: see text] in Additional file 4: Table S1). We compare the robustness of the cross-PTM score against peak location variability in both dimensions and compare the results against PCA analysis over the same set of simulated images. Detailed description of the simulation experiment and discussion of results are provided in Additional file 1: Section S8. We provide a peak-cognizant informational framework for quantitative interpretation of [Formula: see text] topography. Proposed topographic analysis enables [Formula: see text] forensic interpretation across target petroleum biomarkers, while including the nuances of lesser-known non-target biomarkers clustered around the target peaks. This allows potential discovery of hitherto unknown connections between target and non-target biomarkers.

Stereological analysis of bacterial load and lung lesions in nonhuman primates (rhesus macaques) experimentally infected with Mycobacterium tuberculosis.

PubMed

Luciw, Paul A; Oslund, Karen L; Yang, Xiao-Wei; Adamson, Lourdes; Ravindran, Resmi; Canfield, Don R; Tarara, Ross; Hirst, Linda; Christensen, Miles; Lerche, Nicholas W; Offenstein, Heather; Lewinsohn, David; Ventimiglia, Frank; Brignolo, Laurie; Wisner, Erik R; Hyde, Dallas M

2011-11-01

Infection with Mycobacterium tuberculosis primarily produces a multifocal distribution of pulmonary granulomas in which the pathogen resides. Accordingly, quantitative assessment of the bacterial load and pathology is a substantial challenge in tuberculosis. Such assessments are critical for studies of the pathogenesis and for the development of vaccines and drugs in animal models of experimental M. tuberculosis infection. Stereology enables unbiased quantitation of three-dimensional objects from two-dimensional sections and thus is suited to quantify histological lesions. We have developed a protocol for stereological analysis of the lung in rhesus macaques inoculated with a pathogenic clinical strain of M. tuberculosis (Erdman strain). These animals exhibit a pattern of infection and tuberculosis similar to that of naturally infected humans. Conditions were optimized for collecting lung samples in a nonbiased, random manner. Bacterial load in these samples was assessed by a standard plating assay, and granulomas were graded and enumerated microscopically. Stereological analysis provided quantitative data that supported a significant correlation between bacterial load and lung granulomas. Thus this stereological approach enables a quantitative, statistically valid analysis of the impact of M. tuberculosis infection in the lung and will serve as an essential tool for objectively comparing the efficacy of drugs and vaccines.

Three-dimensional modeling and quantitative analysis of gap junction distributions in cardiac tissue.

PubMed

Lackey, Daniel P; Carruth, Eric D; Lasher, Richard A; Boenisch, Jan; Sachse, Frank B; Hitchcock, Robert W

2011-11-01

Gap junctions play a fundamental role in intercellular communication in cardiac tissue. Various types of heart disease including hypertrophy and ischemia are associated with alterations of the spatial arrangement of gap junctions. Previous studies applied two-dimensional optical and electron-microscopy to visualize gap junction arrangements. In normal cardiomyocytes, gap junctions were primarily found at cell ends, but can be found also in more central regions. In this study, we extended these approaches toward three-dimensional reconstruction of gap junction distributions based on high-resolution scanning confocal microscopy and image processing. We developed methods for quantitative characterization of gap junction distributions based on analysis of intensity profiles along the principal axes of myocytes. The analyses characterized gap junction polarization at cell ends and higher-order statistical image moments of intensity profiles. The methodology was tested in rat ventricular myocardium. Our analysis yielded novel quantitative data on gap junction distributions. In particular, the analysis demonstrated that the distributions exhibit significant variability with respect to polarization, skewness, and kurtosis. We suggest that this methodology provides a quantitative alternative to current approaches based on visual inspection, with applications in particular in characterization of engineered and diseased myocardium. Furthermore, we propose that these data provide improved input for computational modeling of cardiac conduction.

A Quantitative Comparative Study of Blended and Traditional Models in the Secondary Advanced Placement Statistics Classroom

ERIC Educational Resources Information Center

Owens, Susan T.

2017-01-01

Technology is becoming an integral tool in the classroom and can make a positive impact on how the students learn. This quantitative comparative research study examined gender-based differences among secondary Advanced Placement (AP) Statistic students comparing Educational Testing Service (ETS) College Board AP Statistic examination scores…

Optimal Hotspots of Dynamic Surfaced-Enhanced Raman Spectroscopy for Drugs Quantitative Detection.

PubMed

Yan, Xiunan; Li, Pan; Zhou, Binbin; Tang, Xianghu; Li, Xiaoyun; Weng, Shizhuang; Yang, Liangbao; Liu, Jinhuai

2017-05-02

Surface-enhanced Raman spectroscopy (SERS) as a powerful qualitative analysis method has been widely applied in many fields. However, SERS for quantitative analysis still suffers from several challenges partially because of the absence of stable and credible analytical strategy. Here, we demonstrate that the optimal hotspots created from dynamic surfaced-enhanced Raman spectroscopy (D-SERS) can be used for quantitative SERS measurements. In situ small-angle X-ray scattering was carried out to in situ real-time monitor the formation of the optimal hotspots, where the optimal hotspots with the most efficient hotspots were generated during the monodisperse Au-sol evaporating process. Importantly, the natural evaporation of Au-sol avoids the nanoparticles instability of salt-induced, and formation of ordered three-dimensional hotspots allows SERS detection with excellent reproducibility. Considering SERS signal variability in the D-SERS process, 4-mercaptopyridine (4-mpy) acted as internal standard to validly correct and improve stability as well as reduce fluctuation of signals. The strongest SERS spectra at the optimal hotspots of D-SERS have been extracted to statistics analysis. By using the SERS signal of 4-mpy as a stable internal calibration standard, the relative SERS intensity of target molecules demonstrated a linear response versus the negative logarithm of concentrations at the point of strongest SERS signals, which illustrates the great potential for quantitative analysis. The public drugs 3,4-methylenedioxymethamphetamine and α-methyltryptamine hydrochloride obtained precise analysis with internal standard D-SERS strategy. As a consequence, one has reason to believe our approach is promising to challenge quantitative problems in conventional SERS analysis.

Ranking and validation of spallation models for isotopic production cross sections of heavy residua

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2017-07-01

The production cross sections of isotopically identified residual nuclei of spallation reactions induced by 136Xe projectiles at 500AMeV on hydrogen target were analyzed in a two-step model. The first stage of the reaction was described by the INCL4.6 model of an intranuclear cascade of nucleon-nucleon and pion-nucleon collisions whereas the second stage was analyzed by means of four different models; ABLA07, GEM2, GEMINI++ and SMM. The quality of the data description was judged quantitatively using two statistical deviation factors; the H-factor and the M-factor. It was found that the present analysis leads to a different ranking of models as compared to that obtained from the qualitative inspection of the data reproduction. The disagreement was caused by sensitivity of the deviation factors to large statistical errors present in some of the data. A new deviation factor, the A factor, was proposed, that is not sensitive to the statistical errors of the cross sections. The quantitative ranking of models performed using the A-factor agreed well with the qualitative analysis of the data. It was concluded that using the deviation factors weighted by statistical errors may lead to erroneous conclusions in the case when the data cover a large range of values. The quality of data reproduction by the theoretical models is discussed. Some systematic deviations of the theoretical predictions from the experimental results are observed.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.

PubMed

Oberg, Ann L; Mahoney, Douglas W

2012-01-01

Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.

Central nervous system antiretroviral efficacy in HIV infection: a qualitative and quantitative review and implications for future research.

PubMed

Cysique, Lucette A; Waters, Edward K; Brew, Bruce J

2011-11-22

There is conflicting information as to whether antiretroviral drugs with better central nervous system (CNS) penetration (neuroHAART) assist in improving neurocognitive function and suppressing cerebrospinal fluid (CSF) HIV RNA. The current review aims to better synthesise existing literature by using an innovative two-phase review approach (qualitative and quantitative) to overcome methodological differences between studies. Sixteen studies, all observational, were identified using a standard citation search. They fulfilled the following inclusion criteria: conducted in the HAART era; sample size > 10; treatment effect involved more than one antiretroviral and none had a retrospective design. The qualitative phase of review of these studies consisted of (i) a blind assessment rating studies on features such as sample size, statistical methods and definitions of neuroHAART, and (ii) a non-blind assessment of the sensitivity of the neuropsychological methods to HIV-associated neurocognitive disorder (HAND). During quantitative evaluation we assessed the statistical power of studies, which achieved a high rating in the qualitative analysis. The objective of the power analysis was to determine the studies ability to assess their proposed research aims. After studies with at least three limitations were excluded in the qualitative phase, six studies remained. All six found a positive effect of neuroHAART on neurocognitive function or CSF HIV suppression. Of these six studies, only two had statistical power of at least 80%. Studies assessed as using more rigorous methods found that neuroHAART was effective in improving neurocognitive function and decreasing CSF viral load, but only two of those studies were adequately statistically powered. Because all of these studies were observational, they represent a less compelling evidence base than randomised control trials for assessing treatment effect. Therefore, large randomised trials are needed to determine the robustness of any neuroHAART effect. However, such trials must be longitudinal, include the full spectrum of HAND, ideally carefully control for co-morbidities, and be based on optimal neuropsychology methods.

Markov model plus k-word distributions: a synergy that produces novel statistical measures for sequence comparison.

PubMed

Dai, Qi; Yang, Yanchun; Wang, Tianming

2008-10-15

Many proposed statistical measures can efficiently compare biological sequences to further infer their structures, functions and evolutionary information. They are related in spirit because all the ideas for sequence comparison try to use the information on the k-word distributions, Markov model or both. Motivated by adding k-word distributions to Markov model directly, we investigated two novel statistical measures for sequence comparison, called wre.k.r and S2.k.r. The proposed measures were tested by similarity search, evaluation on functionally related regulatory sequences and phylogenetic analysis. This offers the systematic and quantitative experimental assessment of our measures. Moreover, we compared our achievements with these based on alignment or alignment-free. We grouped our experiments into two sets. The first one, performed via ROC (receiver operating curve) analysis, aims at assessing the intrinsic ability of our statistical measures to search for similar sequences from a database and discriminate functionally related regulatory sequences from unrelated sequences. The second one aims at assessing how well our statistical measure is used for phylogenetic analysis. The experimental assessment demonstrates that our similarity measures intending to incorporate k-word distributions into Markov model are more efficient.

Immunohistochemical evaluation of inducible nitric oxide synthase in the epithelial lining of odontogenic cysts: A qualitative and quantitative analysis.

PubMed

Akshatha, B K; Karuppiah, Karpagaselvi; Manjunath, G S; Kumarswamy, Jayalakshmi; Papaiah, Lokesh; Rao, Jyothi

2017-01-01

The three common odontogenic cysts include radicular cysts (RCs), dentigerous cysts (DCs), and odontogenic keratocysts (OKCs). Among these 3 cysts, OKC is recently been classified as benign keratocystic odontogenic tumor attributing to its aggressive behavior, recurrence rate, and malignant potential. The present study involved qualitative and quantitative analysis of inducible nitric oxide synthase (iNOS) expression in epithelial lining of RCs, DCs, and OKCs, compare iNOS expression in epithelial linings of all the 3 cysts and determined overexpression of iNOS in OKCs which might contribute to its aggressive behavior and malignant potential. The present study is to investigate the role of iNOS in the pathogenesis of OKCs, DCs, and RCs by evaluating the iNOS expression in the epithelial lining of these cysts. Analysis of iNOS expression in epithelial lining cells of 20 RCs, 20 DCs, and 20 OKCs using immunohistochemistry done. The percentage of positive cells and intensity of stain was assessed and compared among all the 3 cysts using contingency coefficient. Kappa statistics for the two observers were computed for finding interobserver agreement. The percentage of iNOS-positive cells was found to be remarkably high in OKCs (12/20) -57.1% as compared to RCs (6/20) - 28.6% and DCs (3/20) - 14.3%. The interobserver agreement for iNOS-positive percentage cells was arrived with kappa values with OKCs → Statistically significant ( P > 0.000), RCs → statistically significant ( P > 0.001) with no significant values for DCs. No statistical difference exists among 3 study samples in regard to the intensity of staining with iNOS. Increased iNOS expression in OKCs may contribute to bone resorption and accumulation of wild-type p53, hence, making OKCs more aggressive.

Quantitative analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach

USDA-ARS?s Scientific Manuscript database

Porcine reproductive and respiratory syndrome (PRRS) is the most economically significant viral disease facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of the infection within the host and provide crucial information for subsequen...

A Numbers Game: Two Case Studies in Teaching Data Journalism

ERIC Educational Resources Information Center

Treadwell, Greg; Ross, Tara; Lee, Allan; Lowenstein, Jeff Kelly

2016-01-01

Influenced by the practices of social scientists, data journalists seek to create stories that frame social reality through quantitative data analysis. While the use of statistics by journalists is not new, exponential growth in available data and a desire for source material unmediated by political and public-relations framings have seen data…

New Tools for "New" History: Computers and the Teaching of Quantitative Historical Methods.

ERIC Educational Resources Information Center

Burton, Orville Vernon; Finnegan, Terence

1989-01-01

Explains the development of an instructional software package and accompanying workbook which teaches students to apply computerized statistical analysis to historical data, improving the study of social history. Concludes that the use of microcomputers and supercomputers to manipulate historical data enhances critical thinking skills and the use…

Quantitative Analysis of Standardized Dress Code and Minority Academic Achievement

ERIC Educational Resources Information Center

Proctor, J. R.

2013-01-01

This study was designed to investigate if a statistically significant variance exists in African American and Hispanic students' attendance and Texas Assessment of Knowledge and Skills test scores in mathematics before and after the implementation of a standardized dress code. For almost two decades supporters and opponents of public school…

Monitoring Urban Quality of Life: The Porto Experience

ERIC Educational Resources Information Center

Santos, Luis Delfim; Martins, Isabel

2007-01-01

This paper describes the monitoring system of the urban quality of life developed by the Porto City Council, a new tool being used to support urban planning and management. The two components of this system--a quantitative approach based on statistical indicators and a qualitative analysis based on the citizens' perceptions of the conditions of…

An Analysis of Factors Affecting Student Perceptions in a Blended Learning Environment

ERIC Educational Resources Information Center

Peruso, Florence Mary

2012-01-01

The current quantitative study measured the perceptions of students towards online-only learning and towards blended-hybrid learning. Descriptive statistics were implemented to analyze the data from a Likert-type survey, administered to students in degree-seeking programs at an institution of higher learning. A "t"-test and…

Teaching Perspectives of Chinese Teachers: Compatibility with the Goals of the Physical Education Curriculum

ERIC Educational Resources Information Center

Wang, Lijuan; Ha, Amy Sau-ching; Wen, Xu

2014-01-01

This research primarily aimed to examine the compatibility of teaching perspectives of teachers with the Physical Education (PE) curriculum in China. The Teaching Perspective Inventory (Pratt, 1998) was used to collect data from 272 PE teachers. Descriptive statistics, MANOVAs, and correlational procedures were used for quantitative data analysis.…

Preparing Occupational Therapy Students to Address Mental Health Promotion, Prevention, and Intervention in School-Based Practice

ERIC Educational Resources Information Center

Blackwell, Cindy DeRuiter; Bilics, Andrea

2018-01-01

Directors of entry-level occupational therapy (OT) programs were surveyed regarding how their programs prepare students to become mental health practitioners in schools. Analysis of quantitative data included descriptive statistics to examine participants' ratings of their program's ability to prepare students for mental health practice. We found…

Scripted or Non-Scripted: A Comparative Analysis of Two Reading Programs

ERIC Educational Resources Information Center

Bosen, Pamela K.

2014-01-01

The focus of this quantitative comparative study was to analyze school achievement on third-grade reading assessments in 60 similar schools over a three-year period on Washington state standardized criterion-referenced assessments. This study provides statistical data showing the non-scripted programs were consistent for all three years while…

AGE-RELATED DIFFERENCES IN SUSCEPTIBILITY TO CARCINOGENESIS II, APPROACHES FOR APPLICATION AND UNCERTAINTY ANALYSES FOR INDIVIDUAL GENETICALLY ACTING CARCINOGENS

EPA Science Inventory

An earlier paper (Hattis et al., 2003) developed a quantitative likelihood-based statistical analysis of the differences in apparent sensitivity of rodents to mutagenic carcinogens across three life stages (fetal, birth-weaning, and weaning-60 days) relative to exposures in adult...

A Comparative Study of Student Math Skills: Perceptions, Validation, and Recommendations

ERIC Educational Resources Information Center

Jones, Thomas W.; Price, Barbara A.; Randall, Cindy H.

2011-01-01

A study was conducted at a southern university in sophomore level production classes to assess skills such as the order of arithmetic operations, decimal and percent conversion, solving of algebraic expressions, and evaluation of formulas. The study was replicated using business statistics and quantitative analysis classes at a southeastern…

Technology Integration in K-12 Science Classrooms: An Analysis of Barriers and Implications

ERIC Educational Resources Information Center

Hechter, Richard P.; Vermette, Laurie Anne

2013-01-01

This paper examines the barriers to technology integration for Manitoban K-12 inservice science educators (n = 430) based on a 10-item online survey; results are analyzed according to teaching stream using the Technology, Pedagogy, and Content Knowledge (TPACK) framework. Quantitative descriptive statistics indicated that the leading barriers…

Inferring diagnosis and trajectory of wet age-related macular degeneration from OCT imagery of retina

NASA Astrophysics Data System (ADS)

Irvine, John M.; Ghadar, Nastaran; Duncan, Steve; Floyd, David; O'Dowd, David; Lin, Kristie; Chang, Tom

2017-03-01

Quantitative biomarkers for assessing the presence, severity, and progression of age-related macular degeneration (AMD) would benefit research, diagnosis, and treatment. This paper explores development of quantitative biomarkers derived from OCT imagery of the retina. OCT images for approximately 75 patients with Wet AMD, Dry AMD, and no AMD (healthy eyes) were analyzed to identify image features indicative of the patients' conditions. OCT image features provide a statistical characterization of the retina. Healthy eyes exhibit a layered structure, whereas chaotic patterns indicate the deterioration associated with AMD. Our approach uses wavelet and Frangi filtering, combined with statistical features that do not rely on image segmentation, to assess patient conditions. Classification analysis indicates clear separability of Wet AMD from other conditions, including Dry AMD and healthy retinas. The probability of correct classification of was 95.7%, as determined from cross validation. Similar classification analysis predicts the response of Wet AMD patients to treatment, as measured by the Best Corrected Visual Acuity (BCVA). A statistical model predicts BCVA from the imagery features with R2 = 0.846. Initial analysis of OCT imagery indicates that imagery-derived features can provide useful biomarkers for characterization and quantification of AMD: Accurate assessment of Wet AMD compared to other conditions; image-based prediction of outcome for Wet AMD treatment; and features derived from the OCT imagery accurately predict BCVA; unlike many methods in the literature, our techniques do not rely on segmentation of the OCT image. Next steps include larger scale testing and validation.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

A quantitative study of factors influencing quality of life in rural Mexican women diagnosed with HIV.

PubMed

Holtz, Carol; Sowell, Richard; VanBrackle, Lewis; Velasquez, Gabriela; Hernandez-Alonso, Virginia

2014-01-01

This quantitative study explored the level of Quality of Life (QoL) in indigenous Mexican women and identified psychosocial factors that significantly influenced their QoL, using face-to-face interviews with 101 women accessing care in an HIV clinic in Oaxaca, Mexico. Variables included demographic characteristics, levels of depression, coping style, family functioning, HIV-related beliefs, and QoL. Descriptive statistics were used to analyze participant characteristics, and women's scores on data collection instruments. Pearson's R correlational statistics were used to determine the level of significance between study variables. Multiple regression analysis examined all variables that were significantly related to QoL. Pearson's correlational analysis of relationships between Spirituality, Educating Self about HIV, Family Functioning, Emotional Support, Physical Care, and Staying Positive demonstrated positive correlation to QoL. Stigma, depression, and avoidance coping were significantly and negatively associated with QoL. The final regression model indicated that depression and avoidance coping were the best predictor variables for QoL. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

A comparative study of qualitative and quantitative methods for the assessment of adhesive remnant after bracket debonding.

PubMed

Cehreli, S Burcak; Polat-Ozsoy, Omur; Sar, Cagla; Cubukcu, H Evren; Cehreli, Zafer C

2012-04-01

The amount of the residual adhesive after bracket debonding is frequently assessed in a qualitative manner, utilizing the adhesive remnant index (ARI). This study aimed to investigate whether quantitative assessment of the adhesive remnant yields more precise results compared to qualitative methods utilizing the 4- and 5-point ARI scales. Twenty debonded brackets were selected. Evaluation and scoring of the adhesive remnant on bracket bases were made consecutively using: 1. qualitative assessment (visual scoring) and 2. quantitative measurement (image analysis) on digital photographs. Image analysis was made on scanning electron micrographs (SEM) and high-precision elemental maps of the adhesive remnant as determined by energy dispersed X-ray spectrometry. Evaluations were made in accordance with the original 4-point and the modified 5-point ARI scales. Intra-class correlation coefficients (ICCs) were calculated, and the data were evaluated using Friedman test followed by Wilcoxon signed ranks test with Bonferroni correction. ICC statistics indicated high levels of agreement for qualitative visual scoring among examiners. The 4-point ARI scale was compliant with the SEM assessments but indicated significantly less adhesive remnant compared to the results of quantitative elemental mapping. When the 5-point scale was used, both quantitative techniques yielded similar results with those obtained qualitatively. These results indicate that qualitative visual scoring using the ARI is capable of generating similar results with those assessed by quantitative image analysis techniques. In particular, visual scoring with the 5-point ARI scale can yield similar results with both the SEM analysis and elemental mapping.

Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program.

PubMed

Fu, Rongwei; Gartlehner, Gerald; Grant, Mark; Shamliyan, Tatyana; Sedrakyan, Art; Wilt, Timothy J; Griffith, Lauren; Oremus, Mark; Raina, Parminder; Ismaila, Afisi; Santaguida, Pasqualina; Lau, Joseph; Trikalinos, Thomas A

2011-11-01

This article is to establish recommendations for conducting quantitative synthesis, or meta-analysis, using study-level data in comparative effectiveness reviews (CERs) for the Evidence-based Practice Center (EPC) program of the Agency for Healthcare Research and Quality. We focused on recurrent issues in the EPC program and the recommendations were developed using group discussion and consensus based on current knowledge in the literature. We first discussed considerations for deciding whether to combine studies, followed by discussions on indirect comparison and incorporation of indirect evidence. Then, we described our recommendations on choosing effect measures and statistical models, giving special attention to combining studies with rare events; and on testing and exploring heterogeneity. Finally, we briefly presented recommendations on combining studies of mixed design and on sensitivity analysis. Quantitative synthesis should be conducted in a transparent and consistent way. Inclusion of multiple alternative interventions in CERs increases the complexity of quantitative synthesis, whereas the basic issues in quantitative synthesis remain crucial considerations in quantitative synthesis for a CER. We will cover more issues in future versions and update and improve recommendations with the accumulation of new research to advance the goal for transparency and consistency. Copyright © 2011 Elsevier Inc. All rights reserved.

General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters.

PubMed

Hadfield, J D; Nakagawa, S

2010-03-01

Although many of the statistical techniques used in comparative biology were originally developed in quantitative genetics, subsequent development of comparative techniques has progressed in relative isolation. Consequently, many of the new and planned developments in comparative analysis already have well-tested solutions in quantitative genetics. In this paper, we take three recent publications that develop phylogenetic meta-analysis, either implicitly or explicitly, and show how they can be considered as quantitative genetic models. We highlight some of the difficulties with the proposed solutions, and demonstrate that standard quantitative genetic theory and software offer solutions. We also show how results from Bayesian quantitative genetics can be used to create efficient Markov chain Monte Carlo algorithms for phylogenetic mixed models, thereby extending their generality to non-Gaussian data. Of particular utility is the development of multinomial models for analysing the evolution of discrete traits, and the development of multi-trait models in which traits can follow different distributions. Meta-analyses often include a nonrandom collection of species for which the full phylogenetic tree has only been partly resolved. Using missing data theory, we show how the presented models can be used to correct for nonrandom sampling and show how taxonomies and phylogenies can be combined to give a flexible framework with which to model dependence.

[Research progress and development trend of quantitative assessment techniques for urban thermal environment.

PubMed

Sun, Tie Gang; Xiao, Rong Bo; Cai, Yun Nan; Wang, Yao Wu; Wu, Chang Guang

2016-08-01

Quantitative assessment of urban thermal environment has become a focus for urban climate and environmental science since the concept of urban heat island has been proposed. With the continual development of space information and computer simulation technology, substantial progresses have been made on quantitative assessment techniques and methods of urban thermal environment. The quantitative assessment techniques have been developed to dynamics simulation and forecast of thermal environment at various scales based on statistical analysis of thermal environment on urban-scale using the historical data of weather stations. This study reviewed the development progress of ground meteorological observation, thermal infrared remote sensing and numerical simulation. Moreover, the potential advantages and disadvantages, applicability and the development trends of these techniques were also summarized, aiming to add fundamental knowledge of understanding the urban thermal environment assessment and optimization.

Modeling and replicating statistical topology and evidence for CMB nonhomogeneity

PubMed Central

Agami, Sarit

2017-01-01

Under the banner of “big data,” the detection and classification of structure in extremely large, high-dimensional, data sets are two of the central statistical challenges of our times. Among the most intriguing new approaches to this challenge is “TDA,” or “topological data analysis,” one of the primary aims of which is providing nonmetric, but topologically informative, preanalyses of data which make later, more quantitative, analyses feasible. While TDA rests on strong mathematical foundations from topology, in applications, it has faced challenges due to difficulties in handling issues of statistical reliability and robustness, often leading to an inability to make scientific claims with verifiable levels of statistical confidence. We propose a methodology for the parametric representation, estimation, and replication of persistence diagrams, the main diagnostic tool of TDA. The power of the methodology lies in the fact that even if only one persistence diagram is available for analysis—the typical case for big data applications—the replications permit conventional statistical hypothesis testing. The methodology is conceptually simple and computationally practical, and provides a broadly effective statistical framework for persistence diagram TDA analysis. We demonstrate the basic ideas on a toy example, and the power of the parametric approach to TDA modeling in an analysis of cosmic microwave background (CMB) nonhomogeneity. PMID:29078301

Quantifying long-term human impact in contrasting environments: Statistical analysis of modern and fossil pollen records

NASA Astrophysics Data System (ADS)

Broothaerts, Nils; López-Sáez, José Antonio; Verstraeten, Gert

2017-04-01

Reconstructing and quantifying human impact is an important step to understand human-environment interactions in the past. Quantitative measures of human impact on the landscape are needed to fully understand long-term influence of anthropogenic land cover changes on the global climate, ecosystems and geomorphic processes. Nevertheless, quantifying past human impact is not straightforward. Recently, multivariate statistical analysis of fossil pollen records have been proposed to characterize vegetation changes and to get insights in past human impact. Although statistical analysis of fossil pollen data can provide useful insights in anthropogenic driven vegetation changes, still it cannot be used as an absolute quantification of past human impact. To overcome this shortcoming, in this study fossil pollen records were included in a multivariate statistical analysis (cluster analysis and non-metric multidimensional scaling (NMDS)) together with modern pollen data and modern vegetation data. The information on the modern pollen and vegetation dataset can be used to get a better interpretation of the representativeness of the fossil pollen records, and can result in a full quantification of human impact in the past. This methodology was applied in two contrasting environments: SW Turkey and Central Spain. For each region, fossil pollen data from different study sites were integrated, together with modern pollen data and information on modern vegetation. In this way, arboreal cover, grazing pressure and agricultural activities in the past were reconstructed and quantified. The data from SW Turkey provides new integrated information on changing human impact through time in the Sagalassos territory, and shows that human impact was most intense during the Hellenistic and Roman Period (ca. 2200-1750 cal a BP) and decreased and changed in nature afterwards. The data from central Spain shows for several sites that arboreal cover decreases bellow 5% from the Feudal period onwards (ca. 850 cal a BP) related to increasing human impact in the landscape. At other study sites arboreal cover remained above 25% beside significant human impact. Overall, the presented examples from two contrasting environments shows how cluster analysis and NMDS of modern and fossil pollen data can help to provide quantitative insights in anthropogenic land cover changes. Our study extensively discuss and illustrate the possibilities and limitations of statistical analysis of pollen data to quantify human induced land use changes.

Idiopathic normal pressure hydrocephalus, quantitative EEG findings, and the cerebrospinal fluid tap test: a pilot study.

PubMed

Seo, Jong-Geun; Kang, Kyunghun; Jung, Ji-Young; Park, Sung-Pa; Lee, Maan-Gee; Lee, Ho-Won

2014-12-01

In this pilot study, we analyzed relationships between quantitative EEG measurements and clinical parameters in idiopathic normal pressure hydrocephalus patients, along with differences in these quantitative EEG markers between cerebrospinal fluid tap test responders and nonresponders. Twenty-six idiopathic normal pressure hydrocephalus patients (9 cerebrospinal fluid tap test responders and 17 cerebrospinal fluid tap test nonresponders) constituted the final group for analysis. The resting EEG was recorded and relative powers were computed for seven frequency bands. Cerebrospinal fluid tap test nonresponders, when compared with responders, showed a statistically significant increase in alpha2 band power at the right frontal and centrotemporal regions. Higher delta2 band powers in the frontal, central, parietal, and occipital regions and lower alpha1 band powers in the right temporal region significantly correlated with poorer cognitive performance. Higher theta1 band powers in the left parietal and occipital regions significantly correlated with gait dysfunction. And higher delta1 band powers in the right frontal regions significantly correlated with urinary disturbance. Our findings may encourage further research using quantitative EEG in patients with ventriculomegaly as a potential electrophysiological marker for predicting cerebrospinal fluid tap test responders. This study additionally suggests that the delta, theta, and alpha bands are statistically correlated with the severity of symptoms in idiopathic normal pressure hydrocephalus patients.

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.

On sweat analysis for quantitative estimation of dehydration during physical exercise.

PubMed

Ring, Matthias; Lohmueller, Clemens; Rauh, Manfred; Eskofier, Bjoern M

2015-08-01

Quantitative estimation of water loss during physical exercise is of importance because dehydration can impair both muscular strength and aerobic endurance. A physiological indicator for deficit of total body water (TBW) might be the concentration of electrolytes in sweat. It has been shown that concentrations differ after physical exercise depending on whether water loss was replaced by fluid intake or not. However, to the best of our knowledge, this fact has not been examined for its potential to quantitatively estimate TBW loss. Therefore, we conducted a study in which sweat samples were collected continuously during two hours of physical exercise without fluid intake. A statistical analysis of these sweat samples revealed significant correlations between chloride concentration in sweat and TBW loss (r = 0.41, p <; 0.01), and between sweat osmolality and TBW loss (r = 0.43, p <; 0.01). A quantitative estimation of TBW loss resulted in a mean absolute error of 0.49 l per estimation. Although the precision has to be improved for practical applications, the present results suggest that TBW loss estimation could be realizable using sweat samples.

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

LOD significance thresholds for QTL analysis in experimental populations of diploid species

PubMed

Van Ooijen JW

1999-11-01

Linkage analysis with molecular genetic markers is a very powerful tool in the biological research of quantitative traits. The lack of an easy way to know what areas of the genome can be designated as statistically significant for containing a gene affecting the quantitative trait of interest hampers the important prediction of the rate of false positives. In this paper four tables, obtained by large-scale simulations, are presented that can be used with a simple formula to get the false-positives rate for analyses of the standard types of experimental populations with diploid species with any size of genome. A new definition of the term 'suggestive linkage' is proposed that allows a more objective comparison of results across species.

Large-scale quantitative analysis of painting arts.

PubMed

Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong

2014-12-11

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.

Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara

2003-05-01

For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.

Pixel Statistical Analysis of Diabetic vs. Non-diabetic Foot-Sole Spectral Terahertz Reflection Images

NASA Astrophysics Data System (ADS)

Hernandez-Cardoso, G. G.; Alfaro-Gomez, M.; Rojas-Landeros, S. C.; Salas-Gutierrez, I.; Castro-Camus, E.

2018-03-01

In this article, we present a series of hydration mapping images of the foot soles of diabetic and non-diabetic subjects measured by terahertz reflectance. In addition to the hydration images, we present a series of RYG-color-coded (red yellow green) images where pixels are assigned one of the three colors in order to easily identify areas in risk of ulceration. We also present the statistics of the number of pixels with each color as a potential quantitative indicator for diabetic foot-syndrome deterioration.

Quantitative Analysis of Repertoire Scale Immunoglobulin properties in Vaccine Induced B cell Responses

DTIC Science & Technology

Immunosequencing now readily generates 103105 sequences per sample ; however, statistical analysis of these repertoires is challenging because of the high genetic...diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative ...repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance.

Vibrational algorithms for quantitative crystallographic analyses of hydroxyapatite-based biomaterials: I, theoretical foundations.

PubMed

Pezzotti, Giuseppe; Zhu, Wenliang; Boffelli, Marco; Adachi, Tetsuya; Ichioka, Hiroaki; Yamamoto, Toshiro; Marunaka, Yoshinori; Kanamura, Narisato

2015-05-01

The Raman spectroscopic method has quantitatively been applied to the analysis of local crystallographic orientation in both single-crystal hydroxyapatite and human teeth. Raman selection rules for all the vibrational modes of the hexagonal structure were expanded into explicit functions of Euler angles in space and six Raman tensor elements (RTE). A theoretical treatment has also been put forward according to the orientation distribution function (ODF) formalism, which allows one to resolve the statistical orientation patterns of the nm-sized hydroxyapatite crystallite comprised in the Raman microprobe. Close-form solutions could be obtained for the Euler angles and their statistical distributions resolved with respect to the direction of the average texture axis. Polarized Raman spectra from single-crystalline hydroxyapatite and textured polycrystalline (teeth enamel) samples were compared, and a validation of the proposed Raman method could be obtained through confirming the agreement between RTE values obtained from different samples.

[The application of stereology in radiology imaging and cell biology fields].

PubMed

Hu, Na; Wang, Yan; Feng, Yuanming; Lin, Wang

2012-08-01

Stereology is an interdisciplinary method for 3D morphological study developed from mathematics and morphology. It is widely used in medical image analysis and cell biology studies. Because of its unbiased, simple, fast, reliable and non-invasive characteristics, stereology has been widely used in biomedical areas for quantitative analysis and statistics, such as histology, pathology and medical imaging. Because the stereological parameters show distinct differences in different pathology, many scholars use stereological methods to do quantitative analysis in their studies in recent years, for example, in the areas of the condition of cancer cells, tumor grade, disease development and the patient's prognosis, etc. This paper describes the stereological concept and estimation methods, also illustrates the applications of stereology in the fields of CT images, MRI images and cell biology, and finally reflects the universality, the superiority and reliability of stereology.

[Quantitative characterization of nuclear polymorphism of the epithelial cells in fibroadenomatosis and cancer of the breast].

PubMed

Ganina, K P; Petunin, Iu I; Timoshenko, Ia G

1989-01-01

A method for quantitative analysis of epithelial cell nuclear polymorphism was suggested, viz. identification of general statistical population using Petunin's criterion. This criterion was employed to assess heterogeneity of visible surface of interphase epithelial cell nuclei and to assay nuclear DNA level in fibroadenomatous hyperplasia and cancer of the breast. Heterogeneity index (h), alongside with other parameters, appeared useful for quantitative assessment of the disease: heterogeneity index values ranging 0.1-0.4 point to pronounced heterogeneity of epithelial cell nucleus surface and DNA level, and are suggestive of malignant transformation of tissue, whereas benign proliferation of the epithelium is usually characterized by 0.4 less than h less than or equal to 0.9.

Statistical issues in quality control of proteomic analyses: good experimental design and planning.

PubMed

Cairns, David A

2011-03-01

Quality control is becoming increasingly important in proteomic investigations as experiments become more multivariate and quantitative. Quality control applies to all stages of an investigation and statistics can play a key role. In this review, the role of statistical ideas in the design and planning of an investigation is described. This involves the design of unbiased experiments using key concepts from statistical experimental design, the understanding of the biological and analytical variation in a system using variance components analysis and the determination of a required sample size to perform a statistically powerful investigation. These concepts are described through simple examples and an example data set from a 2-D DIGE pilot experiment. Each of these concepts can prove useful in producing better and more reproducible data. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

PubMed

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.

2013-12-01

Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.

Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

PubMed

LaBudde, Robert A; Harnly, James M

2012-01-01

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification.

PubMed

Wang, Shouyi; Bowen, Stephen R; Chaovalitwongse, W Art; Sandison, George A; Grabowski, Thomas J; Kinahan, Paul E

2014-02-21

The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUV(peak)) over lesions of interest. Relative differences in SUV(peak) between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUV(peak) values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.

Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification

NASA Astrophysics Data System (ADS)

Wang, Shouyi; Bowen, Stephen R.; Chaovalitwongse, W. Art; Sandison, George A.; Grabowski, Thomas J.; Kinahan, Paul E.

2014-02-01

The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUVpeak) over lesions of interest. Relative differences in SUVpeak between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUVpeak values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.

EBprot: Statistical analysis of labeling-based quantitative proteomics data.

PubMed

Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon

2015-08-01

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of dynamic row-action maximum likelihood algorithm reconstruction for quantitative 15O brain PET.

PubMed

Ibaraki, Masanobu; Sato, Kaoru; Mizuta, Tetsuro; Kitamura, Keishi; Miura, Shuichi; Sugawara, Shigeki; Shinohara, Yuki; Kinoshita, Toshibumi

2009-09-01

A modified version of row-action maximum likelihood algorithm (RAMLA) using a 'subset-dependent' relaxation parameter for noise suppression, or dynamic RAMLA (DRAMA), has been proposed. The aim of this study was to assess the capability of DRAMA reconstruction for quantitative (15)O brain positron emission tomography (PET). Seventeen healthy volunteers were studied using a 3D PET scanner. The PET study included 3 sequential PET scans for C(15)O, (15)O(2) and H (2) (15) O. First, the number of main iterations (N (it)) in DRAMA was optimized in relation to image convergence and statistical image noise. To estimate the statistical variance of reconstructed images on a pixel-by-pixel basis, a sinogram bootstrap method was applied using list-mode PET data. Once the optimal N (it) was determined, statistical image noise and quantitative parameters, i.e., cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral metabolic rate of oxygen (CMRO(2)) and oxygen extraction fraction (OEF) were compared between DRAMA and conventional FBP. DRAMA images were post-filtered so that their spatial resolutions were matched with FBP images with a 6-mm FWHM Gaussian filter. Based on the count recovery data, N (it) = 3 was determined as an optimal parameter for (15)O PET data. The sinogram bootstrap analysis revealed that DRAMA reconstruction resulted in less statistical noise, especially in a low-activity region compared to FBP. Agreement of quantitative values between FBP and DRAMA was excellent. For DRAMA images, average gray matter values of CBF, CBV, CMRO(2) and OEF were 46.1 +/- 4.5 (mL/100 mL/min), 3.35 +/- 0.40 (mL/100 mL), 3.42 +/- 0.35 (mL/100 mL/min) and 42.1 +/- 3.8 (%), respectively. These values were comparable to corresponding values with FBP images: 46.6 +/- 4.6 (mL/100 mL/min), 3.34 +/- 0.39 (mL/100 mL), 3.48 +/- 0.34 (mL/100 mL/min) and 42.4 +/- 3.8 (%), respectively. DRAMA reconstruction is applicable to quantitative (15)O PET study and is superior to conventional FBP in terms of image quality.

Dental research in Spain. A bibliometric analysis on subjects, authors and institutions (1993-2012).

PubMed

Bueno-Aguilera, F; Jiménez-Contreras, E; Lucena-Martín, C; Pulgar-Encinas, R

2016-03-01

Bibliometrics is defined as the use of statistical methods in the analysis of a body of literature to reveal the historical development of subject fields and patterns of authorship, publication, and use. Our objective was to characterize Spanish scientific output in Dentistry through the analysis of Web of Science database in a 20-year period. By means of a bibliometric study documents were statistically analyzed using indicators that showed quantitative and qualitative aspects of the production. Specifically, time course of the scientific production within the time span was analysed, as were the journals where the article was published and the categories of Journal Citation Reports (JCR) in which they belong, thematic areas, authorship, and finally authors and institutions with the highest production in Spain. By means of the design of a specific search strategy previously described in the scientific literature, we recovered all citable documents about Dentistry signed by Spanish researchers and included in the WoS database between 1993 and 2012. A total of 3006 documents fulfilled the search criteria, of which 2449 (81.5%) were published in journals within the category Dentistry Oral Surgery and Medicine and 557 (18.5%) within other categories of the JCR. During the four quinquenniums studied, the production increased quantitatively (8.6-fold) and qualitatively. Finally, the universities of Granada and Complutense of Madrid were the institutions with the highest production and most prolific authors. The Spanish dental production sharply increased in the last two decades, reaching quantitative and qualitative levels similar to those of the other medical specialties in the country.

Nanoscale Structure of Type I Collagen Fibrils: Quantitative Measurement of D-spacing

PubMed Central

Erickson, Blake; Fang, Ming; Wallace, Joseph M.; Orr, Bradford G.; Les, Clifford M.; Holl, Mark M. Banaszak

2012-01-01

This paper details a quantitative method to measure the D-periodic spacing of Type I collagen fibrils using Atomic Force Microscopy coupled with analysis using a 2D Fast Fourier Transform approach. Instrument calibration, data sampling and data analysis are all discussed and comparisons of the data to the complementary methods of electron microscopy and X-ray scattering are made. Examples of the application of this new approach to the analysis of Type I collagen morphology in disease models of estrogen depletion and Osteogenesis Imperfecta are provided. We demonstrate that it is the D-spacing distribution, not the D-spacing mean, that showed statistically significant differences in estrogen depletion associated with early stage Osteoporosis and Osteogenesis Imperfecta. The ability to quantitatively characterize nanoscale morphological features of Type I collagen fibrils will provide important structural information regarding Type I collagen in many research areas, including tissue aging and disease, tissue engineering, and gene knock out studies. Furthermore, we also envision potential clinical applications including evaluation of tissue collagen integrity under the impact of diseases or drug treatments. PMID:23027700

Ion induced electron emission statistics under Agm- cluster bombardment of Ag

NASA Astrophysics Data System (ADS)

Breuers, A.; Penning, R.; Wucher, A.

2018-05-01

The electron emission from a polycrystalline silver surface under bombardment with Agm- cluster ions (m = 1, 2, 3) is investigated in terms of ion induced kinetic excitation. The electron yield γ is determined directly by a current measurement method on the one hand and implicitly by the analysis of the electron emission statistics on the other hand. Successful measurements of the electron emission spectra ensure a deeper understanding of the ion induced kinetic electron emission process, with particular emphasis on the effect of the projectile cluster size to the yield as well as to emission statistics. The results allow a quantitative comparison to computer simulations performed for silver atoms and clusters impinging onto a silver surface.

Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

PubMed Central

Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

2014-01-01

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

PubMed

Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

2013-12-06

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

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…

Time-dynamics of the two-color emission from vertical-external-cavity surface-emitting lasers

NASA Astrophysics Data System (ADS)

Chernikov, A.; Wichmann, M.; Shakfa, M. K.; Scheller, M.; Moloney, J. V.; Koch, S. W.; Koch, M.

2012-01-01

The temporal stability of a two-color vertical-external-cavity surface-emitting laser is studied using single-shot streak-camera measurements. The collected data is evaluated via quantitative statistical analysis schemes. Dynamically stable and unstable regions for the two-color operation are identified and the dependence on the pump conditions is analyzed.

Quantitative comparison of the absorption spectra of the gas mixtures in analogy to the criterion of Pearson

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Kuzmin, D. A.; Sandykova, E. A.; Shapovalov, A. V.

2015-11-01

An approach to the reduction of the space of the absorption spectra, based on the original criterion for profile analysis of the spectra, was proposed. This criterion dates back to the known statistics chi-square test of Pearson. Introduced criterion allows to quantify the differences of spectral curves.

Effect Size Measures for Mediation Models: Quantitative Strategies for Communicating Indirect Effects

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Kelley, Ken

2011-01-01

The statistical analysis of mediation effects has become an indispensable tool for helping scientists investigate processes thought to be causal. Yet, in spite of many recent advances in the estimation and testing of mediation effects, little attention has been given to methods for communicating effect size and the practical importance of those…

School-to-Work Transition and After: Do Inequalities between the Sexes Defy Diplomas?

ERIC Educational Resources Information Center

Couppie, Thomas; Epiphane, Dominique; Fournier, Christine

1997-01-01

Sex-related differences between the employment opportunities available in France to males and females with comparable levels of education were examined through an analysis of data from two types of sources: statistics derived from quantitative surveys conducted on broad samples of graduates 2-4 years after the end of their training and in-depth…

Helping Students Assess the Relative Importance of Different Intermolecular Interactions

ERIC Educational Resources Information Center

Jasien, Paul G.

2008-01-01

A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…

Laser diagnostics of native cervix dabs with human papilloma virus in high carcinogenic risk

NASA Astrophysics Data System (ADS)

Peresunko, O. P.; Karpenko, Ju. G.; Burkovets, D. N.; Ivashko, P. V.; Nikorych, A. V.; Yermolenko, S. B.; Gruia, Ion; Gruia, M. J.

2015-11-01

The results of experimental studies of coordinate distributions of Mueller matrix elements of the following types of cervical scraping tissue are presented: rate- low-grade - highly differentiated dysplasia (CIN1-CIN3) - adenocarcinoma of high, medium and low levels of differentiation (G1-G3). The rationale for the choice of statistical points 1-4 orders polarized coherent radiation field, transformed as a result of interaction with the oncologic modified biological layers "epithelium-stroma" as a quantitative criterion of polarimetric optical differentiation state of human biological tissues are shown here. The analysis of the obtained Mueller matrix elements and statistical correlation methods, the systematized by types studied tissues is accomplished. The results of research images of Mueller matrix elements m34 for this type of pathology as low-grade dysplasia (CIN2), the results of its statistical and correlation analysis are presented.

Comparing the MRI-based Goutallier Classification to an experimental quantitative MR spectroscopic fat measurement of the supraspinatus muscle.

PubMed

Gilbert, Fabian; Böhm, Dirk; Eden, Lars; Schmalzl, Jonas; Meffert, Rainer H; Köstler, Herbert; Weng, Andreas M; Ziegler, Dirk

2016-08-22

The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy. MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman's rank correlation. Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01). The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.

Quantitative allochem compositional analysis of Lochkovian-Pragian boundary sections in the Prague Basin (Czech Republic)

NASA Astrophysics Data System (ADS)

Weinerová, Hedvika; Hron, Karel; Bábek, Ondřej; Šimíček, Daniel; Hladil, Jindřich

2017-06-01

Quantitative allochem compositional trends across the Lochkovian-Pragian boundary Event were examined at three sections recording the proximal to more distal carbonate ramp environment of the Prague Basin. Multivariate statistical methods (principal component analysis, correspondence analysis, cluster analysis) of point-counted thin section data were used to reconstruct facies stacking patterns and sea-level history. Both the closed-nature allochem percentages and their centred log-ratio (clr) coordinates were used. Both these approaches allow for distinguishing of lowstand, transgressive and highstand system tracts within the Praha Formation, which show gradual transition from crinoid-dominated facies deposited above the storm wave base to dacryoconarid-dominated facies of deep-water environment below the storm wave base. Quantitative compositional data also indicate progradative-retrogradative trends in the macrolithologically monotonous shallow-water succession and enable its stratigraphic correlation with successions from deeper-water environments. Generally, the stratigraphic trends of the clr data are more sensitive to subtle changes in allochem composition in comparison to the results based on raw data. A heterozoan-dominated allochem association in shallow-water environments of the Praha Formation supports the carbonate ramp environment assumed by previous authors.

Quantitative analysis of glycerophospholipids by LC-MS: acquisition, data handling, and interpretation

PubMed Central

Myers, David S.; Ivanova, Pavlina T.; Milne, Stephen B.; Brown, H. Alex

2012-01-01

As technology expands what it is possible to accurately measure, so too the challenges faced by modern mass spectrometry applications expand. A high level of accuracy in lipid quantitation across thousands of chemical species simultaneously is demanded. While relative changes in lipid amounts with varying conditions may provide initial insights or point to novel targets, there are many questions that require determination of lipid analyte absolute quantitation. Glycerophospholipids present a significant challenge in this regard, given the headgroup diversity, large number of possible acyl chain combinations, and vast range of ionization efficiency of species. Lipidomic output is being used more often not just for profiling of the masses of species, but also for highly-targeted flux-based measurements which put additional burdens on the quantitation pipeline. These first two challenges bring into sharp focus the need for a robust lipidomics workflow including deisotoping, differentiation from background noise, use of multiple internal standards per lipid class, and the use of a scriptable environment in order to create maximum user flexibility and maintain metadata on the parameters of the data analysis as it occurs. As lipidomics technology develops and delivers more output on a larger number of analytes, so must the sophistication of statistical post-processing also continue to advance. High-dimensional data analysis methods involving clustering, lipid pathway analysis, and false discovery rate limitation are becoming standard practices in a maturing field. PMID:21683157

Integrality in cervical cancer care: evaluation of access

PubMed Central

Brito-Silva, Keila; Bezerra, Adriana Falangola Benjamin; Chaves, Lucieli Dias Pedreschi; Tanaka, Oswaldo Yoshimi

2014-01-01

OBJECTIVE To evaluate integrity of access to uterine cervical cancer prevention, diagnosis and treatment services. METHODS The tracer condition was analyzed using a mixed quantitative and qualitative approach. The quantitative approach was based on secondary data from the analysis of cytology and biopsy exams performed between 2008 and 2010 on 25 to 59 year-old women in a municipality with a large population and with the necessary technological resources. Data were obtained from the Health Information System and the Regional Cervical Cancer Information System. Statistical analysis was performed using PASW statistic 17.0 software. The qualitative approach involved semi-structured interviews with service managers, health care professionals and users. NVivo 9.0 software was used for the content analysis of the primary data. RESULTS Pap smear coverage was low, possible due to insufficient screening and the difficulty of making appointments in primary care. The numbers of biopsies conducted are similar to those of abnormal cytologies, reflecting easy access to the specialized services. There was higher coverage among younger women. More serious diagnoses, for both cytologies and biopsies, were more prevalent in older women. CONCLUSIONS Insufficient coverage of cytologies, reported by the interviewees allows us to understand access difficulties in primary care, as well as the fragility of screening strategies. PMID:24897045

The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.

Longitudinal studies of the 18F-FDG kinetics after ipilimumab treatment in metastatic melanoma patients based on dynamic FDG PET/CT.

PubMed

Sachpekidis, Christos; Anwar, Hoda; Winkler, Julia K; Kopp-Schneider, Annette; Larribere, Lionel; Haberkorn, Uwe; Hassel, Jessica C; Dimitrakopoulou-Strauss, Antonia

2018-06-05

Immunotherapy has raised the issue of appropriate treatment response evaluation, due to the unique mechanism of action of the immunotherapeutic agents. Aim of this analysis is to evaluate the potential role of quantitative analysis of 2-deoxy-2-( 18 F)fluoro-D-glucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) data in monitoring of patients with metastatic melanoma undergoing ipilimumab therapy. 25 patients with unresectable metastatic melanoma underwent dynamic PET/CT (dPET/CT) of the thorax and upper abdomen as well as static, whole body PET/CT with 18 F-FDG before the start of ipilimumab treatment (baseline PET/CT), after two cycles of treatment (interim PET/CT) and at the end of treatment after four cycles (late PET/CT). The evaluation of dPET/CT studies was based on semi-quantitative (standardized uptake value, SUV) calculation as well as quantitative analysis, based on two-tissue compartment modeling and a fractal approach. Patients' best clinical response, assessed at a mean of 59 weeks, was used as reference. According to their best clinical response, patients were dichotomized in those demonstrating clinical benefit (CB, n = 16 patients) and those demonstrating no clinical benefit (no-CB, n = 9 patients). No statistically significant differences were observed between CB and no-CB regarding either semi-quantitative or quantitative parameters in all scans. On contrary, the application of the recently introduced PET response evaluation criteria for immunotherapy (PERCIMT) led to a correct classification rate of 84% (21/25 patients). Quantitative analysis of 18 F-FDG PET data does not provide additional information in treatment response evaluation of metastatic melanoma patients receiving ipilimumab. PERCIMT criteria correlated better with clinical response.

Quantitative analysis of fetal facial morphology using 3D ultrasound and statistical shape modeling: a feasibility study.

PubMed

Dall'Asta, Andrea; Schievano, Silvia; Bruse, Jan L; Paramasivam, Gowrishankar; Kaihura, Christine Tita; Dunaway, David; Lees, Christoph C

2017-07-01

The antenatal detection of facial dysmorphism using 3-dimensional ultrasound may raise the suspicion of an underlying genetic condition but infrequently leads to a definitive antenatal diagnosis. Despite advances in array and noninvasive prenatal testing, not all genetic conditions can be ascertained from such testing. The aim of this study was to investigate the feasibility of quantitative assessment of fetal face features using prenatal 3-dimensional ultrasound volumes and statistical shape modeling. STUDY DESIGN: Thirteen normal and 7 abnormal stored 3-dimensional ultrasound fetal face volumes were analyzed, at a median gestation of 29 +4  weeks (25 +0 to 36 +1 ). The 20 3-dimensional surface meshes generated were aligned and served as input for a statistical shape model, which computed the mean 3-dimensional face shape and 3-dimensional shape variations using principal component analysis. Ten shape modes explained more than 90% of the total shape variability in the population. While the first mode accounted for overall size differences, the second highlighted shape feature changes from an overall proportionate toward a more asymmetric face shape with a wide prominent forehead and an undersized, posteriorly positioned chin. Analysis of the Mahalanobis distance in principal component analysis shape space suggested differences between normal and abnormal fetuses (median and interquartile range distance values, 7.31 ± 5.54 for the normal group vs 13.27 ± 9.82 for the abnormal group) (P = .056). This feasibility study demonstrates that objective characterization and quantification of fetal facial morphology is possible from 3-dimensional ultrasound. This technique has the potential to assist in utero diagnosis, particularly of rare conditions in which facial dysmorphology is a feature. Copyright © 2017 Elsevier Inc. All rights reserved.

Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

NASA Astrophysics Data System (ADS)

Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

2008-02-01

The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

2015-10-02

As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

GWAMA: software for genome-wide association meta-analysis.

PubMed

Mägi, Reedik; Morris, Andrew P

2010-05-28

Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. The GWAMA (Genome-Wide Association Meta-Analysis) software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.

The application of drug dose equivalence in the quantitative analysis of receptor occupation and drug combinations

PubMed Central

Tallarida, Ronald J.; Raffa, Robert B.

2014-01-01

In this review we show that the concept of dose equivalence for two drugs, the theoretical basis of the isobologram, has a wider use in the analysis of pharmacological data derived from single and combination drug use. In both its application to drug combination analysis with isoboles and certain other actions, listed below, the determination of doses, or receptor occupancies, that yield equal effects provide useful metrics that can be used to obtain quantitative information on drug actions without postulating any intimate mechanism of action. These other drug actions discussed here include (1) combinations of agonists that produce opposite effects, (2) analysis of inverted U-shaped dose effect curves of single agents, (3) analysis on the effect scale as an alternative to isoboles and (4) the use of occupation isoboles to examine competitive antagonism in the dual receptor case. New formulas derived to assess the statistical variance for additive combinations are included, and the more detailed mathematical topics are included in the appendix. PMID:20546783

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

PubMed

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

Morphometric Analysis of Chemoreception Organ in Male and Female Ticks (Acari: Ixodidae).

PubMed

Josek, Tanya; Allan, Brian F; Alleyne, Marianne

2018-05-04

The Haller's organ plays a crucial role in a tick's ability to detect hosts. Even though this sensory organ is vital to tick survival, the morphology of this organ is not well understood. The objective of this study was to characterize variation in the morphological components of the Haller's organ of three medically important tick species using quantitative methods. The Haller's organs of Ixodes scapularis Say (Ixodida: Ixodidae) (black-legged tick), Amblyomma americanum (L.) (Ixodida: Ixodidae) (lone star tick), and Dermacentor variabilis (Say) (Ixodida: Ixodidae) (American dog tick) were morphologically analyzed using environmental scanning electron microscopy and geometric morphometrics, and the results were statistically interpreted using canonical variate analysis. Our data reveal significant, quantitative differences in the morphology of the Haller's organ among all three tick species and that in D. variabilis the sensory structure is sexually dimorphic. Studies like this can serve as a quantitative basis for further studies on sensor physiology, behavior, and tick species life history, potentially leading to novel methods for the prevention of tick-borne disease.

A preliminary study of DTI Fingerprinting on stroke analysis.

PubMed

Ma, Heather T; Ye, Chenfei; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

DTI (Diffusion Tensor Imaging) is a well-known MRI (Magnetic Resonance Imaging) technique which provides useful structural information about human brain. However, the quantitative measurement to physiological variation of subtypes of ischemic stroke is not available. An automatically quantitative method for DTI analysis will enhance the DTI application in clinics. In this study, we proposed a DTI Fingerprinting technology to quantitatively analyze white matter tissue, which was applied in stroke classification. The TBSS (Tract Based Spatial Statistics) method was employed to generate mask automatically. To evaluate the clustering performance of the automatic method, lesion ROI (Region of Interest) is manually drawn on the DWI images as a reference. The results from the DTI Fingerprinting were compared with those obtained from the reference ROIs. It indicates that the DTI Fingerprinting could identify different states of ischemic stroke and has promising potential to provide a more comprehensive measure of the DTI data. Further development should be carried out to improve DTI Fingerprinting technology in clinics.

Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology⋆

PubMed Central

Fu, Wenjiang J.; Stromberg, Arnold J.; Viele, Kert; Carroll, Raymond J.; Wu, Guoyao

2009-01-01

Over the past two decades, there have been revolutionary developments in life science technologies characterized by high throughput, high efficiency, and rapid computation. Nutritionists now have the advanced methodologies for the analysis of DNA, RNA, protein, low-molecular-weight metabolites, as well as access to bioinformatics databases. Statistics, which can be defined as the process of making scientific inferences from data that contain variability, has historically played an integral role in advancing nutritional sciences. Currently, in the era of systems biology, statistics has become an increasingly important tool to quantitatively analyze information about biological macromolecules. This article describes general terms used in statistical analysis of large, complex experimental data. These terms include experimental design, power analysis, sample size calculation, and experimental errors (type I and II errors) for nutritional studies at population, tissue, cellular, and molecular levels. In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies. Moreover, we provided guidelines for nutritionists and other biomedical scientists to plan and conduct studies and to analyze the complex data. Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, ageing, and intrauterine fetal retardation). PMID:20233650

[Statistical analysis of articles in "Chinese journal of applied physiology" from 1999 to 2008].

PubMed

Du, Fei; Fang, Tao; Ge, Xue-ming; Jin, Peng; Zhang, Xiao-hong; Sun, Jin-li

2010-05-01

To evaluate the academic level and influence of "Chinese Journal of Applied Physiology" through statistical analysis for the fund sponsored articles published in the recent ten years. The articles of "Chinese Journal of Applied Physiology" from 1999 to 2008 were investigated. The number and the percentage of the fund sponsored articles, the fund organization and the author region were quantitatively analyzed by using the literature metrology method. The number of the fund sponsored articles increased unceasingly. The ratio of the fund from local government significantly enhanced in the latter five years. Most of the articles were from institutes located at Beijing, Zhejiang and Tianjin. "Chinese Journal of Applied Physiology" has a fine academic level and social influence.

Descriptive statistics and correlation analysis of agronomic traits in a maize recombinant inbred line population.

PubMed

Zhang, H M; Hui, G Q; Luo, Q; Sun, Y; Liu, X H

2014-01-21

Maize (Zea mays L.) is one of the most important crops in the world. In this study, 13 agronomic traits of a recombinant inbred line population that was derived from the cross between Mo17 and Huangzao4 were investigated in maize: ear diameter, ear length, ear axis diameter, ear weight, plant height, ear height, days to pollen shed (DPS), days to silking (DS), the interval between DPS and DS, 100-kernel weight, kernel test weight, ear kernel weight, and kernel rate. Furthermore, the descriptive statistics and correlation analysis of the 13 traits were performed using the SPSS 11.5 software. The results providing the phenotypic data here are needed for the quantitative trait locus mapping of these agronomic traits.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

Adverse effects of metallic artifacts on voxel-wise analysis and tract-based spatial statistics in diffusion tensor imaging.

PubMed

Goto, Masami; Abe, Osamu; Hata, Junichi; Fukunaga, Issei; Shimoji, Keigo; Kunimatsu, Akira; Gomi, Tsutomu

2017-02-01

Background Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that reflects the Brownian motion of water molecules constrained within brain tissue. Fractional anisotropy (FA) is one of the most commonly measured DTI parameters, and can be applied to quantitative analysis of white matter as tract-based spatial statistics (TBSS) and voxel-wise analysis. Purpose To show an association between metallic implants and the results of statistical analysis (voxel-wise group comparison and TBSS) for fractional anisotropy (FA) mapping, in DTI of healthy adults. Material and Methods Sixteen healthy volunteers were scanned with 3-Tesla MRI. A magnetic keeper type of dental implant was used as the metallic implant. DTI was acquired three times in each participant: (i) without a magnetic keeper (FAnon1); (ii) with a magnetic keeper (FAimp); and (iii) without a magnetic keeper (FAnon2) as reproducibility of FAnon1. Group comparisons with paired t-test were performed as FAnon1 vs. FAnon2, and as FAnon1 vs. FAimp. Results Regions of significantly reduced and increased local FA values were revealed by voxel-wise group comparison analysis (a P value of less than 0.05, corrected with family-wise error), but not by TBSS. Conclusion Metallic implants existing outside the field of view produce artifacts that affect the statistical analysis (voxel-wise group comparisons) for FA mapping. When statistical analysis for FA mapping is conducted by researchers, it is important to pay attention to any dental implants present in the mouths of the participants.

Fisher statistics for analysis of diffusion tensor directional information.

PubMed

Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

2012-04-30

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

DIGE Analysis of Human Tissues.

PubMed

Gelfi, Cecilia; Capitanio, Daniele

2018-01-01

Two-dimensional difference gel electrophoresis (2-D DIGE) is an advanced and elegant gel electrophoretic analytical tool for comparative protein assessment. It is based on two-dimensional gel electrophoresis (2-DE) separation of fluorescently labeled protein extracts. The tagging procedures are designed to not interfere with the chemical properties of proteins with respect to their pI and electrophoretic mobility, once a proper labeling protocol is followed. The two-dye or three-dye systems can be adopted and their choice depends on specific applications. Furthermore, the use of an internal pooled standard makes 2-D DIGE a highly accurate quantitative method enabling multiple protein samples to be separated on the same two-dimensional gel. The image matching and cross-gel statistical analysis generates robust quantitative results making data validation by independent technologies successful.

Quantitative analysis of the correlations in the Boltzmann-Grad limit for hard spheres

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

Pulvirenti, M.

2014-12-09

In this contribution I consider the problem of the validity of the Boltzmann equation for a system of hard spheres in the Boltzmann-Grad limit. I briefly review the results available nowadays with a particular emphasis on the celebrated Lanford’s validity theorem. Finally I present some recent results, obtained in collaboration with S. Simonella, concerning a quantitative analysis of the propagation of chaos. More precisely we introduce a quantity (the correlation error) measuring how close a j-particle rescaled correlation function at time t (sufficiently small) is far from the full statistical independence. Roughly speaking, a correlation error of order k, measuresmore » (in the context of the BBKGY hierarchy) the event in which k tagged particles form a recolliding group.« less

Large-Scale Quantitative Analysis of Painting Arts

PubMed Central

Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong

2014-01-01

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images – the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances. PMID:25501877

Quantitative Use of Fluorescent In Situ Hybridization To Examine Relationships between Mycolic Acid-Containing Actinomycetes and Foaming in Activated Sludge Plants

PubMed Central

Davenport, Russell J.; Curtis, Thomas P.; Goodfellow, Michael; Stainsby, Fiona M.; Bingley, Marc

2000-01-01

The formation of viscous foams on aeration basins and secondary clarifiers of activated sludge plants is a common and widespread problem. Foam formation is often attributed to the presence of mycolic acid-containing actinomycetes (mycolata). In order to examine the relationship between the number of mycolata and foam, we developed a group-specific probe targeting the 16S rRNA of the mycolata, a protocol to permeabilize mycolata, and a statistically robust quantification method. Statistical analyses showed that a lipase-based permeabilization method was quantitatively superior to previously described methods (P << 0.05). When mixed liquor and foam samples were examined, most of the mycolata present were rods or cocci, although filamentous mycolata were also observed. A nested analysis of variance showed that virtually all of the measured variance occurred between fields of view and not between samples. On this basis we determined that as few as five fields of view could be used to give a statistically meaningful sample. Quantitative fluorescent in situ hybridization (FISH) was used to examine the relationship between foaming and the concentration of mycolata in a 20-m3 completely mixed activated sludge plant. Foaming occurred when the number of mycolata exceeded a certain threshold value. Baffling of the plant affected foaming without affecting the number of mycolata. We tentatively estimated that the threshold foaming concentration of mycolata was about 2 × 106 cells ml−1 or 4 × 1012 cells m−2. We concluded that quantitative use of FISH is feasible and that quantification is a prerequisite for rational investigation of foaming in activated sludge. PMID:10698786

Less label, more free: approaches in label-free quantitative mass spectrometry.

PubMed

Neilson, Karlie A; Ali, Naveid A; Muralidharan, Sridevi; Mirzaei, Mehdi; Mariani, Michael; Assadourian, Gariné; Lee, Albert; van Sluyter, Steven C; Haynes, Paul A

2011-02-01

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Differentiation of five body fluids from forensic samples by expression analysis of four microRNAs using quantitative PCR.

PubMed

Sauer, Eva; Reinke, Ann-Kathrin; Courts, Cornelius

2016-05-01

Applying molecular genetic approaches for the identification of forensically relevant body fluids, which often yield crucial information for the reconstruction of a potential crime, is a current topic of forensic research. Due to their body fluid specific expression patterns and stability against degradation, microRNAs (miRNA) emerged as a promising molecular species, with a range of candidate markers published. The analysis of miRNA via quantitative Real-Time PCR, however, should be based on a relevant strategy of normalization of non-biological variances to deliver reliable and biologically meaningful results. The herein presented work is the as yet most comprehensive study of forensic body fluid identification via miRNA expression analysis based on a thoroughly validated qPCR procedure and unbiased statistical decision making to identify single source samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Pink Ribbons and Red Dresses: A Mixed Methods Content Analysis of Media Coverage of Breast Cancer and Heart Disease.

PubMed

Champion, Claudine; Berry, Tanya R; Kingsley, Bethan; Spence, John C

2016-10-01

This research examined media coverage of breast cancer (n = 145) and heart disease and stroke (n = 39) news articles, videos, advertisements, and images in a local Canadian context through quantitative and thematic content analyses. Quantitative analysis revealed significant differences between coverage of the diseases in placement, survivors as a source of information, health agency, human interest stories, citation of a research study, the inclusion of risk statistics, discussion of preventative behaviors, and tone used. The thematic analysis revealed themes that characterized a "typical" breast cancer survivor and indicated that "good" citizens and businesses should help the cause of breast cancer. Themes for heart disease and stroke articulated individual responsibility and the ways fundraising reinforced femininity and privilege. Findings provide insight on how these diseases are framed in local Canadian media, which might impact an individual's understanding of the disease.

Quantitative Laser Biospeckle Method for the Evaluation of the Activity of Trypanosoma cruzi Using VDRL Plates and Digital Analysis.

PubMed

Grassi, Hilda Cristina; García, Lisbette C; Lobo-Sulbarán, María Lorena; Velásquez, Ana; Andrades-Grassi, Francisco A; Cabrera, Humberto; Andrades-Grassi, Jesús E; Andrades, Efrén D J

2016-12-01

In this paper we report a quantitative laser Biospeckle method using VDRL plates to monitor the activity of Trypanosoma cruzi and the calibration conditions including three image processing algorithms and three programs (ImageJ and two programs designed in this work). Benznidazole was used as a test drug. Variable volume (constant density) and variable density (constant volume) were used for the quantitative evaluation of parasite activity in calibrated wells of the VDRL plate. The desiccation process within the well was monitored as a function of volume and of the activity of the Biospeckle pattern of the parasites as well as the quantitative effect of the surface parasite quantity (proportion of the object's plane). A statistical analysis was performed with ANOVA, Tukey post hoc and Descriptive Statistics using R and R Commander. Conditions of volume (100μl) and parasite density (2-4x104 parasites/well, in exponential growth phase), assay time (up to 204min), frame number (11 frames), algorithm and program (RCommander/SAGA) for image processing were selected to test the effect of variable concentrations of benznidazole (0.0195 to 20μg/mL / 0.075 to 76.8μM) at various times (1, 61, 128 and 204min) on the activity of the Biospeckle pattern. The flat wells of the VDRL plate were found to be suitable for the quantitative calibration of the activity of Trypanosoma cruzi using the appropriate algorithm and program. Under these conditions, benznidazole produces at 1min an instantaneous effect on the activity of the Biospeckle pattern of T. cruzi, which remains with a similar profile up to 1 hour. A second effect which is dependent on concentrations above 1.25μg/mL and is statistically different from the effect at lower concentrations causes a decrease in the activity of the Biospeckle pattern. This effect is better detected after 1 hour of drug action. This behavior may be explained by an instantaneous effect on a membrane protein of Trypanosoma cruzi that could mediate the translocation of benznidazole. At longer times the effect may possibly be explained by the required transformation of the pro-drug into the active drug.

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

PubMed

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

2017-03-01

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

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Quantitative 3D investigation of Neuronal network in mouse spinal cord model

NASA Astrophysics Data System (ADS)

Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.

2017-01-01

The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.

Combinatorial modification of human histone H4 quantitated by two-dimensional liquid chromatography coupled with top down mass spectrometry.

PubMed

Pesavento, James J; Bullock, Courtney R; LeDuc, Richard D; Mizzen, Craig A; Kelleher, Neil L

2008-05-30

Quantitative proteomics has focused heavily on correlating protein abundances, ratios, and dynamics by developing methods that are protein expression-centric (e.g. isotope coded affinity tag, isobaric tag for relative and absolute quantification, etc.). These methods effectively detect changes in protein abundance but fail to provide a comprehensive perspective of the diversity of proteins such as histones, which are regulated by post-translational modifications. Here, we report the characterization of modified forms of HeLa cell histone H4 with a dynamic range >10(4) using a strictly Top Down mass spectrometric approach coupled with two dimensions of liquid chromatography. This enhanced dynamic range enabled the precise characterization and quantitation of 42 forms uniquely modified by combinations of methylation and acetylation, including those with trimethylated Lys-20, monomethylated Arg-3, and the novel dimethylated Arg-3 (each <1% of all H4 forms). Quantitative analyses revealed distinct trends in acetylation site occupancy depending on Lys-20 methylation state. Because both modifications are dynamically regulated through the cell cycle, we simultaneously investigated acetylation and methylation kinetics through three cell cycle phases and used these data to statistically assess the robustness of our quantitative analysis. This work represents the most comprehensive analysis of histone H4 forms present in human cells reported to date.

Quantitation of flavonoid constituents in citrus fruits.

PubMed

Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M

1999-09-01

Twenty-four flavonoids have been determined in 66 Citrus species and near-citrus relatives, grown in the same field and year, by means of reversed phase high-performance liquid chromatography analysis. Statistical methods have been applied to find relations among the species. The F ratios of 21 flavonoids obtained by applying ANOVA analysis are significant, indicating that a classification of the species using these variables is reasonable to pursue. Principal component analysis revealed that the distributions of Citrus species belonging to different classes were largely in accordance with Tanaka's classification system.

Qualitative and quantitative aspects of pain in lateral posterior thoracotomy patients.

PubMed

Xavier, Thaiza Teixeira; Torres, Gilson de Vasconcelos; da Rocha, Vera Maria

2006-01-01

Descriptive study that proposed to compare the qualitative and quantitative behavior of the pain in lateral posterior thoracotomy patients. The sample was consisted of 18 individuals with an average age of 44 years. The instruments used were physiotherapy evaluation form, numerical pain scale and McGill questionnaire for pain. The pain on the numerical pain scale was considered moderate(5) for both sexes. The descriptors of the McGill questionnaire choosen by the patients with higher frequency were: in the sensorial component, beat4, pointed1, shock2, final and pull2; in the afetive component, tired1, bored1, punishald1 and miserable1 and in the evaluative component was flat. The characteristics of pain in the sensorial group were more evidents on male group. No significant statistical difeferences were observed between quantitative answers concerning pain between the men and women. On the qualitative aspects , was observed an predominancy of the same descriptors of pain in afetive component for both sexes. Pain intensity was categorized as moderate. No significant statistical difference were observed between the pain on the post-operatory lateral posterior thoracotomy. These data demonstrate a necessity for an analysis with a larger study group.

Statistical representative elementary volumes of porous media determined using greyscale analysis of 3D tomograms

NASA Astrophysics Data System (ADS)

Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.

2017-09-01

Digital rock physics carries the dogmatic concept of having to segment volume images for quantitative analysis but segmentation rejects huge amounts of signal information. Information that is essential for the analysis of difficult and marginally resolved samples, such as materials with very small features, is lost during segmentation. In X-ray nanotomography reconstructions of Hod chalk we observed partial volume voxels with an abundance that limits segmentation based analysis. Therefore, we investigated the suitability of greyscale analysis for establishing statistical representative elementary volumes (sREV) for the important petrophysical parameters of this type of chalk, namely porosity, specific surface area and diffusive tortuosity, by using volume images without segmenting the datasets. Instead, grey level intensities were transformed to a voxel level porosity estimate using a Gaussian mixture model. A simple model assumption was made that allowed formulating a two point correlation function for surface area estimates using Bayes' theory. The same assumption enables random walk simulations in the presence of severe partial volume effects. The established sREVs illustrate that in compacted chalk, these simulations cannot be performed in binary representations without increasing the resolution of the imaging system to a point where the spatial restrictions of the represented sample volume render the precision of the measurement unacceptable. We illustrate this by analyzing the origins of variance in the quantitative analysis of volume images, i.e. resolution dependence and intersample and intrasample variance. Although we cannot make any claims on the accuracy of the approach, eliminating the segmentation step from the analysis enables comparative studies with higher precision and repeatability.

Analysis of the quantitative dermatoglyphics of the digito-palmar complex in patients with multiple sclerosis.

PubMed

Supe, S; Milicić, J; Pavićević, R

1997-06-01

Recent studies on the etiopathogenesis of multiple sclerosis (MS) all point out that there is a polygenetical predisposition for this illness. The so called "MS Trait" determines the reactivity of the immunological system upon ecological factors. The development of the glyphological science and the study of the characteristics of the digito-palmar dermatoglyphic complex (for which it was established that they are polygenetically determined characteristics) all enable a better insight into the genetic development during early embriogenesis. The aim of this study was to estimate certain differences in the dermatoglyphics of digito-palmar complexes between the group with multiple sclerosis and the comparable, phenotypically healthy groups of both sexes. This study is based on the analysis of 18 quantitative characteristics of the digito-palmar complex in 125 patients with multiple sclerosis (41 males and 84 females) in comparison to a group of 400 phenotypically healthy patients (200 males and 200 females). The conducted analysis pointed towards a statistically significant decrease of the number of digital and palmar ridges, as well as with lower values of atd angles in a group of MS patients of both sexes. The main discriminators were the characteristic palmar dermatoglyphics with the possibility that the discriminate analysis classifies over 80% of the examinees which exceeds the statistical significance. The results of this study suggest a possible discrimination of patients with MS and the phenotypically health population through the analysis of the dermatoglyphic status, and therefore the possibility that multiple sclerosis is genetically predisposed disease.

Quantitative topographic differentiation of the neonatal EEG.

PubMed

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2006-09-01

To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

Quantifying Morphological Features of α-U3O8 with Image Analysis for Nuclear Forensics.

PubMed

Olsen, Adam M; Richards, Bryony; Schwerdt, Ian; Heffernan, Sean; Lusk, Robert; Smith, Braxton; Jurrus, Elizabeth; Ruggiero, Christy; McDonald, Luther W

2017-03-07

Morphological changes in U 3 O 8 based on calcination temperature have been quantified enabling a morphological feature to serve as a signature of processing history in nuclear forensics. Five separate calcination temperatures were used to synthesize α-U 3 O 8 , and each sample was characterized using powder X-ray diffraction (p-XRD) and scanning electron microscopy (SEM). The p-XRD spectra were used to evaluate the purity of the synthesized U-oxide; the morphological analysis for materials (MAMA) software was utilized to quantitatively characterize the particle shape and size as indicated by the SEM images. Analysis comparing the particle attributes, such as particle area at each of the temperatures, was completed using the Kolmogorov-Smirnov two sample test (K-S test). These results illustrate a distinct statistical difference between each calcination temperature. To provide a framework for forensic analysis of an unknown sample, the sample distributions at each temperature were compared to randomly selected distributions (100, 250, 500, and 750 particles) from each synthesized temperature to determine if they were statistically different. It was found that 750 particles were required to differentiate between all of the synthesized temperatures with a confidence interval of 99.0%. Results from this study provide the first quantitative morphological study of U-oxides, and reveals the potential strength of morphological particle analysis in nuclear forensics by providing a framework for a more rapid characterization of interdicted uranium oxide samples.

Low-frequency quantitative ultrasound imaging of cell death in vivo

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

Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J.

Purpose: Currently, no clinical imaging modality is used routinely to assess tumor response to cancer therapies within hours to days of the delivery of treatment. Here, the authors demonstrate the efficacy of ultrasound at a clinically relevant frequency to quantitatively detect changes in tumors in response to cancer therapies using preclinical mouse models.Methods: Conventional low-frequency and corresponding high-frequency ultrasound (ranging from 4 to 28 MHz) were used along with quantitative spectroscopic and signal envelope statistical analyses on data obtained from xenograft tumors treated with chemotherapy, x-ray radiation, as well as a novel vascular targeting microbubble therapy.Results: Ultrasound-based spectroscopic biomarkers indicatedmore » significant changes in cell-death associated parameters in responsive tumors. Specifically changes in the midband fit, spectral slope, and 0-MHz intercept biomarkers were investigated for different types of treatment and demonstrated cell-death related changes. The midband fit and 0-MHz intercept biomarker derived from low-frequency data demonstrated increases ranging approximately from 0 to 6 dBr and 0 to 8 dBr, respectively, depending on treatments administrated. These data paralleled results observed for high-frequency ultrasound data. Statistical analysis of ultrasound signal envelope was performed as an alternative method to obtain histogram-based biomarkers and provided confirmatory results. Histological analysis of tumor specimens indicated up to 61% cell death present in the tumors depending on treatments administered, consistent with quantitative ultrasound findings indicating cell death. Ultrasound-based spectroscopic biomarkers demonstrated a good correlation with histological morphological findings indicative of cell death (r{sup 2}= 0.71, 0.82; p < 0.001).Conclusions: In summary, the results provide preclinical evidence, for the first time, that quantitative ultrasound used at a clinically relevant frequency, in addition to high-frequency ultrasound, can detect tissue changes associated with cell death in vivo in response to cancer treatments.« less

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

PubMed

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

2006-04-01

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

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics

PubMed Central

Allen, Peter J.; Dorozenko, Kate P.; Roberts, Lynne D.

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these “experts” were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an “answer.” Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities. PMID:26909064

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics.

PubMed

Allen, Peter J; Dorozenko, Kate P; Roberts, Lynne D

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these "experts" were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an "answer." Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities.

Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially-expressed genes from microarray data.

PubMed

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-08-07

There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.

Performing statistical analyses on quantitative data in Taverna workflows: An example using R and maxdBrowse to identify differentially-expressed genes from microarray data

PubMed Central

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-01-01

Background There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Results Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Conclusion Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data. PMID:18687127

What Good Are Statistics that Don't Generalize?

ERIC Educational Resources Information Center

Shaffer, David Williamson; Serlin, Ronald C.

2004-01-01

Quantitative and qualitative inquiry are sometimes portrayed as distinct and incompatible paradigms for research in education. Approaches to combining qualitative and quantitative research typically "integrate" the two methods by letting them co-exist independently within a single research study. Here we describe intra-sample statistical analysis…

Multivariate statistical characterization of charged and uncharged domain walls in multiferroic hexagonal YMnO3 single crystal visualized by a spherical aberration-corrected STEM.

PubMed

Matsumoto, Takao; Ishikawa, Ryo; Tohei, Tetsuya; Kimura, Hideo; Yao, Qiwen; Zhao, Hongyang; Wang, Xiaolin; Chen, Dapeng; Cheng, Zhenxiang; Shibata, Naoya; Ikuhara, Yuichi

2013-10-09

A state-of-the-art spherical aberration-corrected STEM was fully utilized to directly visualize the multiferroic domain structure in a hexagonal YMnO3 single crystal at atomic scale. With the aid of multivariate statistical analysis (MSA), we obtained unbiased and quantitative maps of ferroelectric domain structures with atomic resolution. Such a statistical image analysis of the transition region between opposite polarizations has confirmed atomically sharp transitions of ferroelectric polarization both in antiparallel (uncharged) and tail-to-tail 180° (charged) domain boundaries. Through the analysis, a correlated subatomic image shift of Mn-O layers with that of Y layers, exhibiting a double-arc shape of reversed curvatures, have been elucidated. The amount of image shift in Mn-O layers along the c-axis is statistically significant as small as 0.016 nm, roughly one-third of the evident image shift of 0.048 nm in Y layers. Interestingly, a careful analysis has shown that such a subatomic image shift in Mn-O layers vanishes at the tail-to-tail 180° domain boundaries. Furthermore, taking advantage of the annular bright field (ABF) imaging technique combined with MSA, the tilting of MnO5 bipyramids, the very core mechanism of multiferroicity of the material, is evaluated.

CIOs' Transformational Leadership Behaviors in Community Colleges: A Comparison-Based Approach to Improving Job Satisfaction of Information Technology Workers

ERIC Educational Resources Information Center

Abouelenein, Mahmoud S.

2012-01-01

The purpose of this quantitative, descriptive research study was to determine, through statistical analysis, any correlation between the perceived transformational leadership traits of CIOs at two-year community colleges in Kansas and measures of the job satisfaction among IT workers at those community colleges. The objectives of this research…

Title I ESEA, High School; English as a Second Language: 1979-1980. OEE Evaluation Report.

ERIC Educational Resources Information Center

New York City Board of Education, Brooklyn, NY. Office of Educational Evaluation.

The report is an evaluation of the 1979-80 High School Title I English as a Second Language Program. Two types of information are presented: (1) a narrative description of the program which provides qualitative data regarding the program, and (2) a statistical analysis of test results which consists of quantitative, city-wide data. By integrating…

The Effect of Functional Behavior Assessment on School-Based Interventions: A Meta-Analysis of Single-Case Research

ERIC Educational Resources Information Center

Bruni, Teryn P.; Drevon, Daniel; Hixson, Michael; Wyse, Robert; Corcoran, Samantha; Fursa, Sophie

2017-01-01

The effectiveness of behavior reduction strategies is likely affected by any number of ancillary variables. The purpose of this study was to provide a quantitative review of school-based behavior reduction interventions and some ancillary variables that may modulate the effectiveness of those interventions. Tau-U, an effect size statistic for…

How can my research paper be useful for future meta-analyses on forest restoration practices?

Treesearch

Enrique Andivia; Pedro Villar‑Salvador; Juan A. Oliet; Jaime Puertolas; R. Kasten Dumroese

2018-01-01

Statistical meta-analysis is a powerful and useful tool to quantitatively synthesize the information conveyed in published studies on a particular topic. It allows identifying and quantifying overall patterns and exploring causes of variation. The inclusion of published works in meta-analyses requires, however, a minimum quality standard of the reported data and...

Rocks: A Concrete Activity That Introduces Normal Distribution, Sampling Error, Central Limit Theorem and True Score Theory

ERIC Educational Resources Information Center

Van Duzer, Eric

2011-01-01

This report introduces a short, hands-on activity that addresses a key challenge in teaching quantitative methods to students who lack confidence or experience with statistical analysis. Used near the beginning of the course, this activity helps students develop an intuitive insight regarding a number of abstract concepts which are key to…

A Primer on Value-Added Models: Towards a Better Understanding of the Quantitative Analysis of Student Achievement

ERIC Educational Resources Information Center

Nakamura, Yugo

2013-01-01

Value-added models (VAMs) have received considerable attention as a tool to transform our public education system. However, as VAMs are studied by researchers from a broad range of academic disciplines who remain divided over the best methods in analyzing the models and stakeholders without the extensive statistical background have been excluded…

Grammar and Lexicon in Individuals with Autism: A Quantitative Analysis of a Large Italian Corpus

ERIC Educational Resources Information Center

Tuzzi, Arjuna

2009-01-01

Statistical and linguistic procedures were implemented to analyze a large corpus of texts written by 37 individuals with autism and 92 facilitators (without disabilities), producing written conversations by means of PCs. Such texts were compared and contrasted to identify the specific traits of the lexis of the group of individuals with autism and…

Academic Rigor and Economic Value: GED[R] and High School Students' Perceptions and Misperceptions of the GED[R] vs. the High School Diploma

ERIC Educational Resources Information Center

Horne, Lela M.; Rachal, John R.; Shelley, Kyna

2012-01-01

A mixed methods framework utilized quantitative and qualitative data to determine whether statistically significant differences existed between high school and GED[R] student perceptions of credential value. An exploratory factor analysis (n=326) extracted four factors and then a MANOVA procedure was performed with a stratified quota sample…

Job satisfaction of nurses with master of nursing degrees in Poland: quantitative and qualitative analysis.

PubMed

Brayer, Aneta; Marcinowicz, Ludmila

2018-04-03

Understanding the issue of job satisfaction of nurses with master of nursing degrees may help develop organisational changes necessary for better functioning of health care institutions. This study aimed to evaluate the level of job satisfaction among holders of Masters of Nursing degrees employed at health care institutions and to ascertain its determinants. The cross-sectional study was carried out in randomly selected health care institutions in Poland using the Misener Nurse Practitioner Job Satisfaction Survey and an original survey questionnaire with two open-ended questions. Quantitative data were analysed using descriptive and summary statistics. The participants gave highest satisfaction ratings to their relationships with direct superiors and other nurses, as well as their social contacts at work. The lowest ratings were given to the pension scheme and factors connected with remuneration. A highly statistically significant relationship was found between the job classification and the level of professional satisfaction (p < 0.001). Qualitative analysis of responses to the two open-ended questions supported Herzberg's Two-Factor theory: internal factors promoted satisfaction, whilst external ones caused dissatisfaction. Managers of nurses should strengthen the areas that contribute to higher employee satisfaction, particularly interpersonal relationships, by commendation and recognition of work effects.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

The emergence of modern statistics in agricultural science: analysis of variance, experimental design and the reshaping of research at Rothamsted Experimental Station, 1919-1933.

PubMed

Parolini, Giuditta

2015-01-01

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the mathematician and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher's methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians' tools and expertise into the station research programme. Fisher's statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them.

Quantifying the impact of community quarantine on SARS transmission in Ontario: estimation of secondary case count difference and number needed to quarantine.

PubMed

Bondy, Susan J; Russell, Margaret L; Laflèche, Julie Ml; Rea, Elizabeth

2009-12-24

Community quarantine is controversial, and the decision to use and prepare for it should be informed by specific quantitative evidence of benefit. Case-study reports on 2002-2004 SARS outbreaks have discussed the role of quarantine in the community in transmission. However, this literature has not yielded quantitative estimates of the reduction in secondary cases attributable to quarantine as would be seen in other areas of health policy and cost-effectiveness analysis. Using data from the 2003 Ontario, Canada, SARS outbreak, two novel expressions for the impact of quarantine are presented. Secondary Case Count Difference (SCCD) reflects reduction in the average number of transmissions arising from a SARS case in quarantine, relative to not in quarantine, at onset of symptoms. SCCD was estimated using Poisson and negative binomial regression models (with identity link function) comparing the number of secondary cases to each index case for quarantine relative to non-quarantined index cases. The inverse of this statistic is proposed as the number needed to quarantine (NNQ) to prevent one additional secondary transmission. Our estimated SCCD was 0.133 fewer secondary cases per quarantined versus non-quarantined index case; and a NNQ of 7.5 exposed individuals to be placed in community quarantine to prevent one additional case of transmission in the community. This analysis suggests quarantine can be an effective preventive measure, although these estimates lack statistical precision. Relative to other health policy areas, literature on quarantine tends to lack in quantitative expressions of effectiveness, or agreement on how best to report differences in outcomes attributable to control measure. We hope to further this discussion through presentation of means to calculate and express the impact of population control measures. The study of quarantine effectiveness presents several methodological and statistical challenges. Further research and discussion are needed to understand the costs and benefits of enacting quarantine, and this includes a discussion of how quantitative benefit should be communicated to decision-makers and the public, and evaluated.

Quantifying the impact of community quarantine on SARS transmission in Ontario: estimation of secondary case count difference and number needed to quarantine

PubMed Central

2009-01-01

Background Community quarantine is controversial, and the decision to use and prepare for it should be informed by specific quantitative evidence of benefit. Case-study reports on 2002-2004 SARS outbreaks have discussed the role of quarantine in the community in transmission. However, this literature has not yielded quantitative estimates of the reduction in secondary cases attributable to quarantine as would be seen in other areas of health policy and cost-effectiveness analysis. Methods Using data from the 2003 Ontario, Canada, SARS outbreak, two novel expressions for the impact of quarantine are presented. Secondary Case Count Difference (SCCD) reflects reduction in the average number of transmissions arising from a SARS case in quarantine, relative to not in quarantine, at onset of symptoms. SCCD was estimated using Poisson and negative binomial regression models (with identity link function) comparing the number of secondary cases to each index case for quarantine relative to non-quarantined index cases. The inverse of this statistic is proposed as the number needed to quarantine (NNQ) to prevent one additional secondary transmission. Results Our estimated SCCD was 0.133 fewer secondary cases per quarantined versus non-quarantined index case; and a NNQ of 7.5 exposed individuals to be placed in community quarantine to prevent one additional case of transmission in the community. This analysis suggests quarantine can be an effective preventive measure, although these estimates lack statistical precision. Conclusions Relative to other health policy areas, literature on quarantine tends to lack in quantitative expressions of effectiveness, or agreement on how best to report differences in outcomes attributable to control measure. We hope to further this discussion through presentation of means to calculate and express the impact of population control measures. The study of quarantine effectiveness presents several methodological and statistical challenges. Further research and discussion are needed to understand the costs and benefits of enacting quarantine, and this includes a discussion of how quantitative benefit should be communicated to decision-makers and the public, and evaluated. PMID:20034405

Smile line assessment comparing quantitative measurement and visual estimation.

PubMed

Van der Geld, Pieter; Oosterveld, Paul; Schols, Jan; Kuijpers-Jagtman, Anne Marie

2011-02-01

Esthetic analysis of dynamic functions such as spontaneous smiling is feasible by using digital videography and computer measurement for lip line height and tooth display. Because quantitative measurements are time-consuming, digital videography and semiquantitative (visual) estimation according to a standard categorization are more practical for regular diagnostics. Our objective in this study was to compare 2 semiquantitative methods with quantitative measurements for reliability and agreement. The faces of 122 male participants were individually registered by using digital videography. Spontaneous and posed smiles were captured. On the records, maxillary lip line heights and tooth display were digitally measured on each tooth and also visually estimated according to 3-grade and 4-grade scales. Two raters were involved. An error analysis was performed. Reliability was established with kappa statistics. Interexaminer and intraexaminer reliability values were high, with median kappa values from 0.79 to 0.88. Agreement of the 3-grade scale estimation with quantitative measurement showed higher median kappa values (0.76) than the 4-grade scale estimation (0.66). Differentiating high and gummy smile lines (4-grade scale) resulted in greater inaccuracies. The estimation of a high, average, or low smile line for each tooth showed high reliability close to quantitative measurements. Smile line analysis can be performed reliably with a 3-grade scale (visual) semiquantitative estimation. For a more comprehensive diagnosis, additional measuring is proposed, especially in patients with disproportional gingival display. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Twoplex 12/13 C6 aniline stable isotope and linkage-specific sialic acid labeling 2D-LC-MS workflow for quantitative N-glycomics.

PubMed

Albrecht, Simone; Mittermayr, Stefan; Smith, Josh; Martín, Silvia Millán; Doherty, Margaret; Bones, Jonathan

2017-01-01

Quantitative glycomics represents an actively expanding research field ranging from the discovery of disease-associated glycan alterations to the quantitative characterization of N-glycans on therapeutic proteins. Commonly used analytical platforms for comparative relative quantitation of complex glycan samples include MALDI-TOF-MS or chromatographic glycan profiling with subsequent data alignment and statistical evaluation. Limitations of such approaches include run-to-run technical variation and the potential introduction of subjectivity during data processing. Here, we introduce an offline 2D LC-MS E workflow for the fractionation and relative quantitation of twoplex isotopically labeled N-linked oligosaccharides using neutral 12 C 6 and 13 C 6 aniline (Δmass = 6 Da). Additional linkage-specific derivatization of sialic acids using 4-(4,6-dimethoxy-1,3,5-trizain-2-yl)-4-methylmorpholinium chloride offered simultaneous and advanced in-depth structural characterization. The potential of the method was demonstrated for the differential analysis of structurally defined N-glycans released from serum proteins of patients diagnosed with various stages of colorectal cancer. The described twoplex 12 C 6 / 13 C 6 aniline 2D LC-MS platform is ideally suited for differential glycomic analysis of structurally complex N-glycan pools due to combination and analysis of samples in a single LC-MS injection and the associated minimization in technical variation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.

PubMed

Walker, Martin; Basáñez, María-Gloria; Ouédraogo, André Lin; Hermsen, Cornelus; Bousema, Teun; Churcher, Thomas S

2015-01-16

Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.

African Primary Care Research: Quantitative analysis and presentation of results

PubMed Central

Ogunbanjo, Gboyega A.

2014-01-01

Abstract This article is part of a series on Primary Care Research Methods. The article describes types of continuous and categorical data, how to capture data in a spreadsheet, how to use descriptive and inferential statistics and, finally, gives advice on how to present the results in text, figures and tables. The article intends to help Master's level students with writing the data analysis section of their research proposal and presenting their results in their final research report. PMID:26245435

Quantitative analysis of drainage obtained from aerial photographs and RBV/LANDSAT images

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Formaggio, A. R.; Epiphanio, J. C. N.; Filho, M. V.

1981-01-01

Data obtained from aerial photographs (1:60,000) and LANDSAT return beam vidicon imagery (1:100,000) concerning drainage density, drainage texture, hydrography density, and the average length of channels were compared. Statistical analysis shows that significant differences exist in data from the two sources. The highly drained area lost more information than the less drained area. In addition, it was observed that the loss of information about the number of rivers was higher than that about the length of the channels.

Clinical significance of quantitative analysis of facial nerve enhancement on MRI in Bell's palsy.

PubMed

Song, Mee Hyun; Kim, Jinna; Jeon, Ju Hyun; Cho, Chang Il; Yoo, Eun Hye; Lee, Won-Sang; Lee, Ho-Ki

2008-11-01

Quantitative analysis of the facial nerve on the lesion side as well as the normal side, which allowed for more accurate measurement of facial nerve enhancement in patients with facial palsy, showed statistically significant correlation with the initial severity of facial nerve inflammation, although little prognostic significance was shown. This study investigated the clinical significance of quantitative measurement of facial nerve enhancement in patients with Bell's palsy by analyzing the enhancement pattern and correlating MRI findings with initial severity of facial palsy and clinical outcome. Facial nerve enhancement was measured quantitatively by using the region of interest on pre- and postcontrast T1-weighted images in 44 patients diagnosed with Bell's palsy. The signal intensity increase on the lesion side was first compared with that of the contralateral side and then correlated with the initial degree of facial palsy and prognosis. The lesion side showed significantly higher signal intensity increase compared with the normal side in all of the segments except for the mastoid segment. Signal intensity increase at the internal auditory canal and labyrinthine segments showed correlation with the initial degree of facial palsy but no significant difference was found between different prognostic groups.

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.

PubMed

Chen, Li; Wang, Chi; Qin, Zhaohui S; Wu, Hao

2015-06-15

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed. In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones. An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

QR-STEM: Energy and Environment as a Context for Improving QR and STEM Understandings of 6-12 Grade Teachers II. The Quantitative Reasoning

NASA Astrophysics Data System (ADS)

Mayes, R.; Lyford, M. E.; Myers, J. D.

2009-12-01

The Quantitative Reasoning in STEM (QR STEM) project is a state level Mathematics and Science Partnership Project (MSP) with a focus on the mathematics and statistics that underlies the understanding of complex global scientific issues. This session is a companion session to the QR STEM: The Science presentation. The focus of this session is the quantitative reasoning aspects of the project. As students move from understandings that range from local to global in perspective on issues of energy and environment, there is a significant increase in the need for mathematical and statistical conceptual understanding. These understandings must be accessible to the students within the scientific context, requiring the special understandings that are endemic within quantitative reasoning. The QR STEM project brings together interdisciplinary teams of higher education faculty and middle/high school teachers to explore complex problems in energy and environment. The disciplines include life sciences, physics, chemistry, earth science, statistics, and mathematics. These interdisciplinary teams develop open ended performance tasks to implement in the classroom, based on scientific concepts that underpin energy and environment. Quantitative reasoning is broken down into three components: Quantitative Literacy, Quantitative Interpretation, and Quantitative Modeling. Quantitative Literacy is composed of arithmetic concepts such as proportional reasoning, numeracy, and descriptive statistics. Quantitative Interpretation includes algebraic and geometric concepts that underlie the ability to interpret a model of natural phenomena which is provided for the student. This model may be a table, graph, or equation from which the student is to make predictions or identify trends, or from which they would use statistics to explore correlations or patterns in data. Quantitative modeling is the ability to develop the model from data, including the ability to test hypothesis using statistical procedures. We use the term model very broadly, so it includes visual models such as box models, as well as best fit equation models and hypothesis testing. One of the powerful outcomes of the project is the conversation which takes place between science teachers and mathematics teachers. First they realize that though they are teaching concepts that cross their disciplines, the barrier of scientific language within their subjects restricts students from applying the concepts across subjects. Second the mathematics teachers discover the context of science as a means of providing real world situations that engage students in the utility of mathematics as a tool for solving problems. Third the science teachers discover the barrier to understanding science that is presented by poor quantitative reasoning ability. Finally the students are engaged in exploring energy and environment in a manner which exposes the importance of seeing a problem from multiple interdisciplinary perspectives. The outcome is a democratic citizen capable of making informed decisions, and perhaps a future scientist.

Quantitative analysis of 18F-NaF dynamic PET/CT cannot differentiate malignant from benign lesions in multiple myeloma

PubMed Central

Sachpekidis, Christos; Hillengass, Jens; Goldschmidt, Hartmut; Anwar, Hoda; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-01-01

A renewed interest has been recently developed for the highly sensitive bone-seeking radiopharmaceutical 18F-NaF. Aim of the present study is to evaluate the potential utility of quantitative analysis of 18F-NaF dynamic PET/CT data in differentiating malignant from benign degenerative lesions in multiple myeloma (MM). 80 MM patients underwent whole-body PET/CT and dynamic PET/CT scanning of the pelvis with 18F-NaF. PET/CT data evaluation was based on visual (qualitative) assessment, semi-quantitative (SUV) calculations, and absolute quantitative estimations after application of a 2-tissue compartment model and a non-compartmental approach leading to the extraction of fractal dimension (FD). In total 263 MM lesions were demonstrated on 18F-NaF PET/CT. Semi-quantitative and quantitative evaluations were performed for 25 MM lesions as well as for 25 benign, degenerative and traumatic lesions. Mean SUVaverage for MM lesions was 11.9 and mean SUVmax was 23.2. Respectively, SUVaverage and SUVmax for degenerative lesions were 13.5 and 20.2. Kinetic analysis of 18F-NaF revealed the following mean values for MM lesions: K1 = 0.248 (1/min), k3 = 0.359 (1/min), influx (Ki) = 0.107 (1/min), FD = 1.382, while the respective values for degenerative lesions were: K1 = 0.169 (1/min), k3 = 0.422 (1/min), influx (Ki) = 0.095 (1/min), FD = 1. 411. No statistically significant differences between MM and benign degenerative disease regarding SUVaverage, SUVmax, K1, k3 and influx (Ki) were demonstrated. FD was significantly higher in degenerative than in malignant lesions. The present findings show that quantitative analysis of 18F-NaF PET data cannot differentiate malignant from benign degenerative lesions in MM patients, supporting previously published results, which reflect the limited role of 18F-NaF PET/CT in the diagnostic workup of MM. PMID:28913153

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

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

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

A tutorial in displaying mass spectrometry-based proteomic data using heat maps.

PubMed

Key, Melissa

2012-01-01

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across proteins and biological samples simultaneously. The quality of a heat map can be vastly improved by understanding the options available to display and organize the data in the heat map. This tutorial illustrates how to optimize heat maps for proteomics data by incorporating known characteristics of the data into the image. First, the concepts used to guide the creating of heat maps are demonstrated. Then, these concepts are applied to two types of analysis: visualizing spectral features across biological samples, and presenting the results of tests of statistical significance. For all examples we provide details of computer code in the open-source statistical programming language R, which can be used for biologists and clinicians with little statistical background. Heat maps are a useful tool for presenting quantitative proteomic data organized in a matrix format. Understanding and optimizing the parameters used to create the heat map can vastly improve both the appearance and the interoperation of heat map data.

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis.

PubMed

Ong, Edmund; Cahill, Catherine

2015-07-03

The intracellular trafficking of receptors is a collection of complex and highly controlled processes. Receptor trafficking modulates signaling and overall cell responsiveness to ligands and is, itself, influenced by intra- and extracellular conditions, including ligand-induced signaling. Optimized for use with monolayer-plated cultured cells, but extendable to free-floating tissue slices, this protocol uses immunolabelling and colocalizational analysis to track changes in intracellular receptor trafficking following both chronic/prolonged and acute interventions, including exogenous drug treatment. After drug treatment, cells are double-immunolabelled for the receptor and for markers for the intracellular compartments of interest. Sequential confocal microscopy is then used to capture two-channel photomicrographs of individual cells, which are subjected to computerized colocalizational analysis to yield quantitative colocalization scores. These scores are normalized to permit pooling of independent replicates prior to statistical analysis. Representative photomicrographs may also be processed to generate illustrative figures. Here, we describe a powerful and flexible technique for quantitatively assessing induced receptor trafficking.

Inconsistencies in reporting risk information: a pilot analysis of online news coverage of West Nile Virus.

PubMed

Birnbrauer, Kristina; Frohlich, Dennis Owen; Treise, Debbie

2017-09-01

West Nile Virus (WNV) has been reported as one of the worst epidemics in US history. This study sought to understand how WNV news stories were framed and how risk information was portrayed from its 1999 arrival in the US through the year 2012. The authors conducted a quantitative content analysis of online news articles obtained through Google News ( N = 428). The results of this analysis were compared to the CDC's ArboNET surveillance system. The following story frames were identified in this study: action, conflict, consequence, new evidence, reassurance and uncertainty, with the action frame appearing most frequently. Risk was communicated quantitatively without context in the majority of articles, and only in 2006, the year with the third-highest reported deaths, was risk reported with statistical accuracy. The results from the analysis indicated that at-risk communities were potentially under-informed as accurate risks were not communicated. This study offers evidence about how disease outbreaks are covered in relation to actual disease surveillance data.

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis.

PubMed

Song, Seung Yeob; Lee, Young Koung; Kim, In-Jung

2016-01-01

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950-1100 cm(-1), 1300-1500 cm(-1), and 1500-1700 cm(-1). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R(2)) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Correlation of renal histopathology with renal echogenicity in dogs and cats: an ex-vivo quantitative study.

PubMed

Zotti, Alessandro; Banzato, Tommaso; Gelain, Maria Elena; Centelleghe, Cinzia; Vaccaro, Calogero; Aresu, Luca

2015-04-25

Increased cortical or cortical and medullary echogenicity is one of the most common signs of chronic or acute kidney disease in dogs and cats. Subjective evaluation of the echogenicity is reported to be unreliable. Patient and technical-related factors affect in-vivo quantitative evaluation of the echogenicity of parenchymal organs. The aim of the present study is to investigate the relationship between histopathology and ex-vivo renal cortical echogenicity in dogs and cats devoid of any patient and technical-related biases. Kidney samples were collected from 68 dog and 32 cat cadavers donated by the owners to the Veterinary Teaching Hospital of the University of Padua and standardized ultrasonographic images of each sample were collected. The echogenicity of the renal cortex was quantitatively assessed by means of mean gray value (MGV), and then histopathological analysis was performed. Statistical analysis to evaluate the influence of histological lesions on MGV was performed. The differentiation efficiency of MGV to detect pathological changes in the kidneys was calculated for dogs and cats. Statistical analysis revealed that only glomerulosclerosis was an independent determinant of echogenicity in dogs whereas interstitial nephritis, interstitial necrosis and fibrosis were independent determinants of echogenicity in cats. The global influence of histological lesions on renal echogenicity was higher in cats (23%) than in dogs (12%). Different histopathological lesions influence the echogenicity of the kidneys in dogs and cats. Moreover, MGV is a poor test for distinguishing between normal and pathological kidneys in the dog with a sensitivity of 58.3% and specificity of 59.8%. Instead, it seems to perform globally better in the cat, resulting in a fair test, with a sensitivity of 80.6% and a specificity of 56%.

Dental research in Spain. A bibliometric analysis on subjects, authors and institutions (1993-2012)

PubMed Central

Bueno-Aguilera, Felipe; Lucena-Martín, Cristina; Pulgar-Encinas, Rosa

2016-01-01

Background Bibliometrics is defined as the use of statistical methods in the analysis of a body of literature to reveal the historical development of subject fields and patterns of authorship, publication, and use. Our objective was to characterize Spanish scientific output in Dentistry through the analysis of Web of Science database in a 20-year period. By means of a bibliometric study documents were statistically analyzed using indicators that showed quantitative and qualitative aspects of the production. Specifically, time course of the scientific production within the time span was analysed, as were the journals where the article was published and the categories of Journal Citation Reports (JCR) in which they belong, thematic areas, authorship, and finally authors and institutions with the highest production in Spain. Material and Methods By means of the design of a specific search strategy previously described in the scientific literature, we recovered all citable documents about Dentistry signed by Spanish researchers and included in the WoS database between 1993 and 2012. Results A total of 3006 documents fulfilled the search criteria, of which 2449 (81.5%) were published in journals within the category Dentistry Oral Surgery and Medicine and 557 (18.5%) within other categories of the JCR. During the four quinquenniums studied, the production increased quantitatively (8.6-fold) and qualitatively. Finally, the universities of Granada and Complutense of Madrid were the institutions with the highest production and most prolific authors. Conclusions The Spanish dental production sharply increased in the last two decades, reaching quantitative and qualitative levels similar to those of the other medical specialties in the country. Key words:Dental research, dentistry, publications, Journal impact factor, bibliometrics, biomedical research, Spanish dental production. PMID:26827056

Quantitative analysis of tympanic membrane perforation: a simple and reliable method.

PubMed

Ibekwe, T S; Adeosun, A A; Nwaorgu, O G

2009-01-01

Accurate assessment of the features of tympanic membrane perforation, especially size, site, duration and aetiology, is important, as it enables optimum management. To describe a simple, cheap and effective method of quantitatively analysing tympanic membrane perforations. The system described comprises a video-otoscope (capable of generating still and video images of the tympanic membrane), adapted via a universal serial bus box to a computer screen, with images analysed using the Image J geometrical analysis software package. The reproducibility of results and their correlation with conventional otoscopic methods of estimation were tested statistically with the paired t-test and correlational tests, using the Statistical Package for the Social Sciences version 11 software. The following equation was generated: P/T x 100 per cent = percentage perforation, where P is the area (in pixels2) of the tympanic membrane perforation and T is the total area (in pixels2) for the entire tympanic membrane (including the perforation). Illustrations are shown. Comparison of blinded data on tympanic membrane perforation area obtained independently from assessments by two trained otologists, of comparative years of experience, using the video-otoscopy system described, showed similar findings, with strong correlations devoid of inter-observer error (p = 0.000, r = 1). Comparison with conventional otoscopic assessment also indicated significant correlation, comparing results for two trained otologists, but some inter-observer variation was present (p = 0.000, r = 0.896). Correlation between the two methods for each of the otologists was also highly significant (p = 0.000). A computer-adapted video-otoscope, with images analysed by Image J software, represents a cheap, reliable, technology-driven, clinical method of quantitative analysis of tympanic membrane perforations and injuries.

Topography of brain glucose hypometabolism and epileptic network in glucose transporter 1 deficiency.

PubMed

Akman, Cigdem Inan; Provenzano, Frank; Wang, Dong; Engelstad, Kristin; Hinton, Veronica; Yu, Julia; Tikofsky, Ronald; Ichese, Masonari; De Vivo, Darryl C

2015-02-01

(18)F fluorodeoxyglucose positron emission tomography ((18)F FDG-PET) facilitates examination of glucose metabolism. Previously, we described regional cerebral glucose hypometabolism using (18)F FDG-PET in patients with Glucose transporter 1 Deficiency Syndrome (Glut1 DS). We now expand this observation in Glut1 DS using quantitative image analysis to identify the epileptic network based on the regional distribution of glucose hypometabolism. (18)F FDG-PET scans of 16 Glut1 DS patients and 7 healthy participants were examined using Statistical parametric Mapping (SPM). Summed images were preprocessed for statistical analysis using MATLAB 7.1 and SPM 2 software. Region of interest (ROI) analysis was performed to validate SPM results. Visual analysis of the (18)F FDG-PET images demonstrated prominent regional glucose hypometabolism in the thalamus, neocortical regions and cerebellum bilaterally. Group comparison using SPM analysis confirmed that the regional distribution of glucose hypo-metabolism was present in thalamus, cerebellum, temporal cortex and central lobule. Two mildly affected patients without epilepsy had hypometabolism in cerebellum, inferior frontal cortex, and temporal lobe, but not thalamus. Glucose hypometabolism did not correlate with age at the time of PET imaging, head circumference, CSF glucose concentration at the time of diagnosis, RBC glucose uptake, or CNS score. Quantitative analysis of (18)F FDG-PET imaging in Glut1 DS patients confirmed that hypometabolism was present symmetrically in thalamus, cerebellum, frontal and temporal cortex. The hypometabolism in thalamus correlated with the clinical history of epilepsy. Copyright © 2014. Published by Elsevier B.V.

Recovering incomplete data using Statistical Multiple Imputations (SMI): a case study in environmental chemistry.

PubMed

Mercer, Theresa G; Frostick, Lynne E; Walmsley, Anthony D

2011-10-15

This paper presents a statistical technique that can be applied to environmental chemistry data where missing values and limit of detection levels prevent the application of statistics. A working example is taken from an environmental leaching study that was set up to determine if there were significant differences in levels of leached arsenic (As), chromium (Cr) and copper (Cu) between lysimeters containing preservative treated wood waste and those containing untreated wood. Fourteen lysimeters were setup and left in natural conditions for 21 weeks. The resultant leachate was analysed by ICP-OES to determine the As, Cr and Cu concentrations. However, due to the variation inherent in each lysimeter combined with the limits of detection offered by ICP-OES, the collected quantitative data was somewhat incomplete. Initial data analysis was hampered by the number of 'missing values' in the data. To recover the dataset, the statistical tool of Statistical Multiple Imputation (SMI) was applied, and the data was re-analysed successfully. It was demonstrated that using SMI did not affect the variance in the data, but facilitated analysis of the complete dataset. Copyright © 2011 Elsevier B.V. All rights reserved.

Rapid Analysis of Corni fructus Using Paper Spray-Mass Spectrometry.

PubMed

Guo, Yuan; Gu, Zhixin; Liu, Xuemei; Liu, Jingjing; Ma, Ming; Chen, Bo; Wang, Liping

2017-07-01

Paper spray-mass spectrometry (PS-MS) is a kind of ambient MS technique for the rapid analysis of samples. Corni fructus has been widely used in traditional Chinese compound preparations and healthy food. However, a number of counterfeits of Corni fructus, such as Crataegi fructus, Lycii fructus, and grape skin are illegally sold in crude herb markets. Therefore, the development of a rapid and high-throughput quality evaluation method is important for ensuring the effectiveness and safety of the crude materials of Corni fructus. To develop PS-MS chemical profiles and a semi-quantitative method of Corni fructus for quality assessment and control, and species distinction of Corni fructus. Both positive and negative ion PS-MS chemical profiles were constructed for species distinction. The statistical analysis of the chemical profiles was accomplished by principal component analysis (PCA). Rapid semi-quantitative analysis of loganin and morroniside in the extracts of Corni fructus were accomplished by PS-MS. The profiles of the Corni fructus and Crataegi fructus samples were clearly clustered into two categories. The limit of quantification (LOQ) in the semi-quantitative analysis was 6 μg/mL and 5.6 μg/mL for loganin and morroniside, respectively. PS-MS is a simple, rapid, and high-throughput method for the quality control and species distinction of Corni fructus. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Confirmatory factor analytic structure and measurement invariance of quantitative autistic traits measured by the social responsiveness scale-2.

PubMed

Frazier, Thomas W; Ratliff, Kristin R; Gruber, Chris; Zhang, Yi; Law, Paul A; Constantino, John N

2014-01-01

Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large (N = 9635) accumulated collection of reports on quantitative autistic traits using the Social Responsiveness Scale, representing a broad diversity of age, severity, and reporter type. A two-factor structure (corresponding to social communication impairment and restricted, repetitive behavior) as elaborated in the updated Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) criteria for autism spectrum disorder exhibited acceptable model fit in confirmatory factor analysis. Measurement invariance was appreciable across age, sex, and reporter (self vs other), but somewhat less apparent between clinical and nonclinical populations in this sample comprised of both familial and sporadic autism spectrum disorders. The statistical power afforded by this large sample allowed relative differentiation of three factors among items encompassing social communication impairment (emotion recognition, social avoidance, and interpersonal relatedness) and two factors among items encompassing restricted, repetitive behavior (insistence on sameness and repetitive mannerisms). Cross-trait correlations remained extremely high, that is, on the order of 0.66-0.92. These data clarify domains of statistically significant factoral separation that may relate to partially-but not completely-overlapping biological mechanisms, contributing to variation in human social competency. Given such robust intercorrelations among symptom domains, understanding their co-emergence remains a high priority in conceptualizing common neural mechanisms underlying autistic syndromes.

Quantitative skills as a graduate learning outcome of university science degree programmes: student performance explored through theplanned-enacted-experiencedcurriculum model

NASA Astrophysics Data System (ADS)

Matthews, Kelly E.; Adams, Peter; Goos, Merrilyn

2016-07-01

Application of mathematical and statistical thinking and reasoning, typically referred to as quantitative skills, is essential for university bioscience students. First, this study developed an assessment task intended to gauge graduating students' quantitative skills. The Quantitative Skills Assessment of Science Students (QSASS) was the result, which examined 10 mathematical and statistical sub-topics. Second, the study established an evidential baseline of students' quantitative skills performance and confidence levels by piloting the QSASS with 187 final-year biosciences students at a research-intensive university. The study is framed within the planned-enacted-experienced curriculum model and contributes to science reform efforts focused on enhancing the quantitative skills of university graduates, particularly in the biosciences. The results found, on average, weak performance and low confidence on the QSASS, suggesting divergence between academics' intentions and students' experiences of learning quantitative skills. Implications for curriculum design and future studies are discussed.

Depth-Dependent Glycosaminoglycan Concentration in Articular Cartilage by Quantitative Contrast-Enhanced Micro–Computed Tomography

PubMed Central

Mittelstaedt, Daniel

2015-01-01

Objective A quantitative contrast-enhanced micro–computed tomography (qCECT) method was developed to investigate the depth dependency and heterogeneity of the glycosaminoglycan (GAG) concentration of ex vivo cartilage equilibrated with an anionic radiographic contrast agent, Hexabrix. Design Full-thickness fresh native (n = 19 in 3 subgroups) and trypsin-degraded (n = 6) articular cartilage blocks were imaged using micro–computed tomography (μCT) at high resolution (13.4 μm3) before and after equilibration with various Hexabrix bathing concentrations. The GAG concentration was calculated depth-dependently based on Gibbs-Donnan equilibrium theory. Analysis of variance with Tukey’s post hoc was used to test for statistical significance (P < 0.05) for effect of Hexabrix bathing concentration, and for differences in bulk and zonal GAG concentrations individually and compared between native and trypsin-degraded cartilage. Results The bulk GAG concentration was calculated to be 74.44 ± 6.09 and 11.99 ± 4.24 mg/mL for native and degraded cartilage, respectively. A statistical difference was demonstrated for bulk and zonal GAG between native and degraded cartilage (P < 0.032). A statistical difference was not demonstrated for bulk GAG when comparing Hexabrix bathing concentrations (P > 0.3214) for neither native nor degraded cartilage. Depth-dependent GAG analysis of native cartilage revealed a statistical difference only in the radial zone between 30% and 50% Hexabrix bathing concentrations. Conclusions This nondestructive qCECT methodology calculated the depth-dependent GAG concentration for both native and trypsin-degraded cartilage at high spatial resolution. qCECT allows for more detailed understanding of the topography and depth dependency, which could help diagnose health, degradation, and repair of native and contrived cartilage. PMID:26425259

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

PubMed

Zhang, Kui; Wiener, Howard; Beasley, Mark; George, Varghese; Amos, Christopher I; Allison, David B

2006-08-01

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome-wide QTL analysis for anxiety trait in bipolar disorder type I.

PubMed

Contreras, J; Hare, E; Chavarría-Soley, G; Raventós, H

2018-07-01

Genetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. We assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). We identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). Since confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. We conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety. Published by Elsevier B.V.

Using Statistics to Lie, Distort, and Abuse Data

ERIC Educational Resources Information Center

Bintz, William; Moore, Sara; Adams, Cheryll; Pierce, Rebecca

2009-01-01

Statistics is a branch of mathematics that involves organization, presentation, and interpretation of data, both quantitative and qualitative. Data do not lie, but people do. On the surface, quantitative data are basically inanimate objects, nothing more than lifeless and meaningless symbols that appear on a page, calculator, computer, or in one's…

QuantCrit: Education, Policy, "Big Data" and Principles for a Critical Race Theory of Statistics

ERIC Educational Resources Information Center

Gillborn, David; Warmington, Paul; Demack, Sean

2018-01-01

Quantitative research enjoys heightened esteem among policy-makers, media, and the general public. Whereas qualitative research is frequently dismissed as subjective and impressionistic, statistics are often assumed to be objective and factual. We argue that these distinctions are wholly false; quantitative data is no less socially constructed…

Exploring the statistics of magnetic reconnection X-points in kinetic particle-in-cell turbulence

NASA Astrophysics Data System (ADS)

Haggerty, C. C.; Parashar, T. N.; Matthaeus, W. H.; Shay, M. A.; Yang, Y.; Wan, M.; Wu, P.; Servidio, S.

2017-10-01

Magnetic reconnection is a ubiquitous phenomenon in turbulent plasmas. It is an important part of the turbulent dynamics and heating of space and astrophysical plasmas. We examine the statistics of magnetic reconnection using a quantitative local analysis of the magnetic vector potential, previously used in magnetohydrodynamics simulations, and now employed to fully kinetic particle-in-cell (PIC) simulations. Different ways of reducing the particle noise for analysis purposes, including multiple smoothing techniques, are explored. We find that a Fourier filter applied at the Debye scale is an optimal choice for analyzing PIC data. Finally, we find a broader distribution of normalized reconnection rates compared to the MHD limit with rates as large as 0.5 but with an average of approximately 0.1.

Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates.

PubMed

Schwämmle, Veit; León, Ileana Rodríguez; Jensen, Ole Nørregaard

2013-09-06

Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant changes on the peptide level, for example, in phospho-proteomics experiments. In order to assess the extent of this problem and the implications for large-scale proteome analysis, we investigated and optimized the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. We applied three tools, including standard t test, moderated t test, also known as limma, and rank products for the detection of significantly changing features in simulated and experimental proteomics data sets with missing values. The rank product method was improved to work with data sets containing missing values. Extensive analysis of simulated and experimental data sets revealed that the performance of the statistical analysis tools depended on simple properties of the data sets. High-confidence results were obtained by using the limma and rank products methods for analyses of triplicate data sets that exhibited more than 1000 features and more than 50% missing values. The maximum number of differentially represented features was identified by using limma and rank products methods in a complementary manner. We therefore recommend combined usage of these methods as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling and mass spectrometry experiments and should be applicable to large data sets of any type. An R script that implements the improved rank products algorithm and the combined analysis is available.

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

PubMed

Zhang, Yaping; Hu, Kaiqiang; Beumer, Jan H; Bakkenist, Christopher J; D'Argenio, David Z

2017-04-01

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel benzanthrone probes for membrane and protein studies

NASA Astrophysics Data System (ADS)

Ryzhova, Olga; Vus, Kateryna; Trusova, Valeriya; Kirilova, Elena; Kirilov, Georgiy; Gorbenko, Galyna; Kinnunen, Paavo

2016-09-01

The applicability of a series of novel benzanthrone dyes to monitoring the changes in physicochemical properties of lipid bilayer and to differentiating between the native and aggregated protein states has been evaluated. Based on the quantitative parameters of the dye-membrane and dye-protein binding derived from the fluorimetric titration data, the most prospective membrane probes and amyloid tracers have been selected from the group of examined compounds. Analysis of the red edge excitation shifts of the membrane- and amyloid-bound dyes provided information on the properties of benzanthrone binding sites within the lipid and protein matrixes. To understand how amyloid specificity of benzanthrones correlates with their structure, quantitative structure activity relationship (QSAR) analysis was performed involving a range of quantum chemical molecular descriptors. A statistically significant model was obtained for predicting the sensitivity of novel benzanthrone dyes to amyloid fibrils.

Toward Accurate and Quantitative Comparative Metagenomics

PubMed Central

Nayfach, Stephen; Pollard, Katherine S.

2016-01-01

Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

Toward Accurate and Quantitative Comparative Metagenomics.

PubMed

Nayfach, Stephen; Pollard, Katherine S

2016-08-25

Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Nanoparticle surface characterization and clustering through concentration-dependent surface adsorption modeling.

PubMed

Chen, Ran; Zhang, Yuntao; Sahneh, Faryad Darabi; Scoglio, Caterina M; Wohlleben, Wendel; Haase, Andrea; Monteiro-Riviere, Nancy A; Riviere, Jim E

2014-09-23

Quantitative characterization of nanoparticle interactions with their surrounding environment is vital for safe nanotechnological development and standardization. A recent quantitative measure, the biological surface adsorption index (BSAI), has demonstrated promising applications in nanomaterial surface characterization and biological/environmental prediction. This paper further advances the approach beyond the application of five descriptors in the original BSAI to address the concentration dependence of the descriptors, enabling better prediction of the adsorption profile and more accurate categorization of nanomaterials based on their surface properties. Statistical analysis on the obtained adsorption data was performed based on three different models: the original BSAI, a concentration-dependent polynomial model, and an infinite dilution model. These advancements in BSAI modeling showed a promising development in the application of quantitative predictive modeling in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

Digital pathology and image analysis for robust high-throughput quantitative assessment of Alzheimer disease neuropathologic changes.

PubMed

Neltner, Janna Hackett; Abner, Erin Lynn; Schmitt, Frederick A; Denison, Stephanie Kay; Anderson, Sonya; Patel, Ela; Nelson, Peter T

2012-12-01

Quantitative neuropathologic methods provide information that is important for both research and clinical applications. The technologic advancement of digital pathology and image analysis offers new solutions to enable valid quantification of pathologic severity that is reproducible between raters regardless of experience. Using an Aperio ScanScope XT and its accompanying image analysis software, we designed algorithms for quantitation of amyloid and tau pathologies on 65 β-amyloid (6F/3D antibody) and 48 phospho-tau (PHF-1)-immunostained sections of human temporal neocortex. Quantitative digital pathologic data were compared with manual pathology counts. There were excellent correlations between manually counted and digitally analyzed neuropathologic parameters (R² = 0.56-0.72). Data were highly reproducible among 3 participants with varying degrees of expertise in neuropathology (intraclass correlation coefficient values, >0.910). Digital quantification also provided additional parameters, including average plaque area, which shows statistically significant differences when samples are stratified according to apolipoprotein E allele status (average plaque area, 380.9 μm² in apolipoprotein E [Latin Small Letter Open E]4 carriers vs 274.4 μm² for noncarriers; p < 0.001). Thus, digital pathology offers a rigorous and reproducible method for quantifying Alzheimer disease neuropathologic changes and may provide additional insights into morphologic characteristics that were previously more challenging to assess because of technical limitations.

Predicting Team Performance through Human Behavioral Sensing and Quantitative Workflow Instrumentation

DTIC Science & Technology

2016-07-27

make risk-informed decisions during serious games . Statistical models of intra- game performance were developed to determine whether behaviors in...specific facets of the gameplay workflow were predictive of analytical performance and games outcomes. A study of over seventy instrumented teams revealed...more accurate game decisions. 2 Keywords: Humatics · Serious Games · Human-System Interaction · Instrumentation · Teamwork · Communication Analysis

Nonlinear Analysis of Experimental Measurements 7.6. Theoretical Chemistry

DTIC Science & Technology

2015-01-26

Jianshu Cao, Robert J. Silbey, Jaeyoung Sung. Quantitative Interpretation of the Randomness in Single Enzyme Turnover Times, Biophysical Journal...Universality of Poisson Indicator and Fano Factor of Transport Event Statistics in Ion Channels and Enzyme Kinetics., J. Phys. B: At. Mol. Opt. Phys...TOTAL: 4 01/26/2015 Received Book 4.00 Jianshu Cao, Jianlan Wu. GENERALIZED MICHAELIS–MENTENEQUATION FOR CONFORMATION- MODULATEDMONOMERIC ENZYMES , New

The Direct Impact of Team Cohesiveness and Athletes' Perception of Coaching Leadership Functions on Team Success in NCAA Division I Women's Basketball

ERIC Educational Resources Information Center

Palmer, Mary E.

2013-01-01

This study investigated the direct impact of team cohesiveness and student-athletes' perceptions of coaching behavior/leadership functions on the success of NCAA Division I Women's basketball, based on the teams' win/loss records. The research collection was quantitative in nature. Statistical design and analysis provided justification for the use…

Investigating the quality of mental models deployed by undergraduate engineering students in creating explanations: The case of thermally activated phenomena

NASA Astrophysics Data System (ADS)

Fazio, Claudio; Battaglia, Onofrio Rosario; Di Paola, Benedetto

2013-12-01

This paper describes a method aimed at pointing out the quality of the mental models undergraduate engineering students deploy when asked to create explanations for phenomena or processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are quantitatively analyzed using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of the relevant physics content. The use of statistical implicative analysis tools allows us to successfully identify clusters of students with respect to the similarity to the reasoning categories, defined as “practical or everyday,” “descriptive,” or “explicative.” Through the use of similarity and implication indexes our method also enables us to study the consistency in students’ deployment of mental models. A qualitative analysis of interviews conducted with students after they had completed the questionnaire is used to clarify some aspects which emerged from the quantitative analysis and validate the results obtained. Some implications of this joint use of quantitative and qualitative analysis for the design of a learning environment focused on the understanding of some aspects of the world at the level of causation and mechanisms of functioning are discussed.

Teaching science in a technology rich environment: Probeware's effect on student attitude and achievement

NASA Astrophysics Data System (ADS)

Zelmanowicz, Marc

Purpose The use of technology in the science classroom has been a major part of the initiative toward increasing student attitude and achievement in Science, Technology, Education and Math [STEM] education in the United States. The purpose of this study was to determine the extent to which the use of probeware in a high school science living environment classroom impacts student attitude towards science and/or student achievement on standards-based assessments. This study sought to answer the following quantitative questions with a qualitative component: To what extent does the use of probeware in a high school level living environment course influence student attitudes toward science compared to students who are not using probeware? What is the impact, if any, on student achievement in a living environment course, as measured by New York State Living Environment Regents [NYSLER] exam grades, between students who use probeware and students who do not? Is there a significant difference between the two groups with regard to achieving mastery on the NYSLER exam? Sample The participants in the study were Living Environment students of a suburban high school outside of New York City. Methods The quasiexperimental study examined the effects of the replacement of traditional scientific equipment with probeware on student attitude and achievement in a living environment classroom. Student attitude was measured by the modified Attitude Toward Science Inventory [mATSI] and student achievement was measured by the New York State Living Environment Regents [NSLER] Exam. Descriptive statistics, ANCOVA and hierarchical regression analysis were conducted to answer the research questions in this study. A qualitative component was included to enhance the understanding of the quantitative analysis. Major Findings Through this study, results demonstrated a statistically significant impact of probeware on student attitude, but did not show a statistically significant impact of probeware on student achievement or achievement of mastery; The qualitative component confirmed that probeware positively impact student attitude and achievement. With regards to achievement, the qualitative interviews contradicted the quantitative analysis. Significance Results from this study add to the body of research that probeware can impact student attitude towards science education.

Utility of Gram stain for the microbiological analysis of burn wound surfaces.

PubMed

Elsayed, Sameer; Gregson, Daniel B; Lloyd, Tracie; Crichton, Marilyn; Church, Deirdre L

2003-11-01

Surface swab cultures have attracted attention as a potential alternative to biopsy histology or quantitative culture methods for microbiological burn wound monitoring. To our knowledge, the utility of adding a Gram-stained slide in this context has not been evaluated previously. To determine the degree of correlation of Gram stain with culture for the microbiological analysis of burn wound surfaces. Prospective laboratory analysis. Urban health region/centralized diagnostic microbiology laboratory. Burn patients hospitalized in any Calgary Health Region burn center from November 2000 to September 2001. Gram stain plus culture of burn wound surface swab specimens obtained during routine dressing changes or based on clinical signs of infection. Degree of correlation (complete, high, partial, none), including weighted kappa statistic (kappa(w)), of Gram stain with culture based on quantitative microscopy and degree of culture growth. A total of 375 specimens from 50 burn patients were evaluated. Of these, 239 were negative by culture and Gram stain, 7 were positive by Gram stain only, 89 were positive by culture only, and 40 were positive by both methods. The degree of complete, high, partial, and no correlation of Gram stain with culture was 70.9% (266/375), 1.1% (4/375), 2.4% (9/375), and 25.6% (96/375), respectively. The degree of correlation for all 375 specimens, as expressed by the weighted kappa statistic, was found to be fair (kappa(w) = 0.32).Conclusion.-The Gram stain is not suitable for the microbiological analysis of burn wound surfaces.

Classification of the medicinal plants of the genus Atractylodes using high-performance liquid chromatography with diode array and tandem mass spectrometry detection combined with multivariate statistical analysis.

PubMed

Cho, Hyun-Deok; Kim, Unyong; Suh, Joon Hyuk; Eom, Han Young; Kim, Junghyun; Lee, Seul Gi; Choi, Yong Seok; Han, Sang Beom

2016-04-01

Analytical methods using high-performance liquid chromatography with diode array and tandem mass spectrometry detection were developed for the discrimination of the rhizomes of four Atractylodes medicinal plants: A. japonica, A. macrocephala, A. chinensis, and A. lancea. A quantitative study was performed, selecting five bioactive components, including atractylenolide I, II, III, eudesma-4(14),7(11)-dien-8-one and atractylodin, on twenty-six Atractylodes samples of various origins. Sample extraction was optimized to sonication with 80% methanol for 40 min at room temperature. High-performance liquid chromatography with diode array detection was established using a C18 column with a water/acetonitrile gradient system at a flow rate of 1.0 mL/min, and the detection wavelength was set at 236 nm. Liquid chromatography with tandem mass spectrometry was applied to certify the reliability of the quantitative results. The developed methods were validated by ensuring specificity, linearity, limit of quantification, accuracy, precision, recovery, robustness, and stability. Results showed that cangzhu contained higher amounts of atractylenolide I and atractylodin than baizhu, and especially atractylodin contents showed the greatest variation between baizhu and cangzhu. Multivariate statistical analysis, such as principal component analysis and hierarchical cluster analysis, were also employed for further classification of the Atractylodes plants. The established method was suitable for quality control of the Atractylodes plants. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of uncertainties and convergence of the statistical quantities in turbulent wall-bounded flows by means of a physically based criterion

NASA Astrophysics Data System (ADS)

Andrade, João Rodrigo; Martins, Ramon Silva; Thompson, Roney Leon; Mompean, Gilmar; da Silveira Neto, Aristeu

2018-04-01

The present paper provides an analysis of the statistical uncertainties associated with direct numerical simulation (DNS) results and experimental data for turbulent channel and pipe flows, showing a new physically based quantification of these errors, to improve the determination of the statistical deviations between DNSs and experiments. The analysis is carried out using a recently proposed criterion by Thompson et al. ["A methodology to evaluate statistical errors in DNS data of plane channel flows," Comput. Fluids 130, 1-7 (2016)] for fully turbulent plane channel flows, where the mean velocity error is estimated by considering the Reynolds stress tensor, and using the balance of the mean force equation. It also presents how the residual error evolves in time for a DNS of a plane channel flow, and the influence of the Reynolds number on its convergence rate. The root mean square of the residual error is shown in order to capture a single quantitative value of the error associated with the dimensionless averaging time. The evolution in time of the error norm is compared with the final error provided by DNS data of similar Reynolds numbers available in the literature. A direct consequence of this approach is that it was possible to compare different numerical results and experimental data, providing an improved understanding of the convergence of the statistical quantities in turbulent wall-bounded flows.

Solar granulation and statistical crystallography: A modeling approach using size-shape relations

NASA Technical Reports Server (NTRS)

Noever, D. A.

1994-01-01

The irregular polygonal pattern of solar granulation is analyzed for size-shape relations using statistical crystallography. In contrast to previous work which has assumed perfectly hexagonal patterns for granulation, more realistic accounting of cell (granule) shapes reveals a broader basis for quantitative analysis. Several features emerge as noteworthy: (1) a linear correlation between number of cell-sides and neighboring shapes (called Aboav-Weaire's law); (2) a linear correlation between both average cell area and perimeter and the number of cell-sides (called Lewis's law and a perimeter law, respectively) and (3) a linear correlation between cell area and squared perimeter (called convolution index). This statistical picture of granulation is consistent with a finding of no correlation in cell shapes beyond nearest neighbors. A comparative calculation between existing model predictions taken from luminosity data and the present analysis shows substantial agreements for cell-size distributions. A model for understanding grain lifetimes is proposed which links convective times to cell shape using crystallographic results.

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

NASA Technical Reports Server (NTRS)

Lewalle, Jacques; Ashpis, David E.; Sohn, Ki-Hyeon

1997-01-01

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Toward statistical modeling of saccadic eye-movement and visual saliency.

PubMed

Sun, Xiaoshuai; Yao, Hongxun; Ji, Rongrong; Liu, Xian-Ming

2014-11-01

In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This observations inspired us to model saccadic behavior and visual saliency based on super-Gaussian component (SGC) analysis. Our model sequentially obtains SGC using projection pursuit, and generates eye movements by selecting the location with maximum SGC response. Besides human saccadic behavior simulation, we also demonstrated our superior effectiveness and robustness over state-of-the-arts by carrying out dense experiments on synthetic patterns and human eye fixation benchmarks. Multiple key issues in saliency modeling research, such as individual differences, the effects of scale and blur, are explored in this paper. Based on extensive qualitative and quantitative experimental results, we show promising potentials of statistical approaches for human behavior research.

An astronomer's guide to period searching

NASA Astrophysics Data System (ADS)

Schwarzenberg-Czerny, A.

2003-03-01

We concentrate on analysis of unevenly sampled time series, interrupted by periodic gaps, as often encountered in astronomy. While some of our conclusions may appear surprising, all are based on classical statistical principles of Fisher & successors. Except for discussion of the resolution issues, it is best for the reader to forget temporarily about Fourier transforms and to concentrate on problems of fitting of a time series with a model curve. According to their statistical content we divide the issues into several sections, consisting of: (ii) statistical numerical aspects of model fitting, (iii) evaluation of fitted models as hypotheses testing, (iv) the role of the orthogonal models in signal detection (v) conditions for equivalence of periodograms (vi) rating sensitivity by test power. An experienced observer working with individual objects would benefit little from formalized statistical approach. However, we demonstrate the usefulness of this approach in evaluation of performance of periodograms and in quantitative design of large variability surveys.

How to Make Nothing Out of Something: Analyses of the Impact of Study Sampling and Statistical Interpretation in Misleading Meta-Analytic Conclusions

PubMed Central

Cunningham, Michael R.; Baumeister, Roy F.

2016-01-01

The limited resource model states that self-control is governed by a relatively finite set of inner resources on which people draw when exerting willpower. Once self-control resources have been used up or depleted, they are less available for other self-control tasks, leading to a decrement in subsequent self-control success. The depletion effect has been studied for over 20 years, tested or extended in more than 600 studies, and supported in an independent meta-analysis (Hagger et al., 2010). Meta-analyses are supposed to reduce bias in literature reviews. Carter et al.’s (2015) meta-analysis, by contrast, included a series of questionable decisions involving sampling, methods, and data analysis. We provide quantitative analyses of key sampling issues: exclusion of many of the best depletion studies based on idiosyncratic criteria and the emphasis on mini meta-analyses with low statistical power as opposed to the overall depletion effect. We discuss two key methodological issues: failure to code for research quality, and the quantitative impact of weak studies by novice researchers. We discuss two key data analysis issues: questionable interpretation of the results of trim and fill and Funnel Plot Asymmetry test procedures, and the use and misinterpretation of the untested Precision Effect Test and Precision Effect Estimate with Standard Error (PEESE) procedures. Despite these serious problems, the Carter et al. (2015) meta-analysis results actually indicate that there is a real depletion effect – contrary to their title. PMID:27826272

Analysis of the dependence of extreme rainfalls

NASA Astrophysics Data System (ADS)

Padoan, Simone; Ancey, Christophe; Parlange, Marc

2010-05-01

The aim of spatial analysis is to quantitatively describe the behavior of environmental phenomena such as precipitation levels, wind speed or daily temperatures. A number of generic approaches to spatial modeling have been developed[1], but these are not necessarily ideal for handling extremal aspects given their focus on mean process levels. The areal modelling of the extremes of a natural process observed at points in space is important in environmental statistics; for example, understanding extremal spatial rainfall is crucial in flood protection. In light of recent concerns over climate change, the use of robust mathematical and statistical methods for such analyses has grown in importance. Multivariate extreme value models and the class of maxstable processes [2] have a similar asymptotic motivation to the univariate Generalized Extreme Value (GEV) distribution , but providing a general approach to modeling extreme processes incorporating temporal or spatial dependence. Statistical methods for max-stable processes and data analyses of practical problems are discussed by [3] and [4]. This work illustrates methods to the statistical modelling of spatial extremes and gives examples of their use by means of a real extremal data analysis of Switzerland precipitation levels. [1] Cressie, N. A. C. (1993). Statistics for Spatial Data. Wiley, New York. [2] de Haan, L and Ferreria A. (2006). Extreme Value Theory An Introduction. Springer, USA. [3] Padoan, S. A., Ribatet, M and Sisson, S. A. (2009). Likelihood-Based Inference for Max-Stable Processes. Journal of the American Statistical Association, Theory & Methods. In press. [4] Davison, A. C. and Gholamrezaee, M. (2009), Geostatistics of extremes. Journal of the Royal Statistical Society, Series B. To appear.

Middle school students' earthquake content and preparedness knowledge - A mixed method study

NASA Astrophysics Data System (ADS)

Henson, Harvey, Jr.

The purpose of this study was to assess the effect of earthquake instruction on students' earthquake content and preparedness for earthquakes. This study used an innovative direct instruction on earthquake science content and concepts with an inquiry-based group activity on earthquake safety followed by an earthquake simulation and preparedness video to help middle school students understand and prepare for the regional seismic threat. A convenience sample of 384 sixth and seventh grade students at two small middle schools in southern Illinois was used in this study. Qualitative information was gathered using open-ended survey questions, classroom observations, and semi-structured interviews. Quantitative data were collected using a 21 item content questionnaire administered to test students' General Earthquake Knowledge, Local Earthquake Knowledge, and Earthquake Preparedness Knowledge before and after instruction. A pre-test and post-test survey Likert scale with 21 items was used to collect students' perceptions and attitudes. Qualitative data analysis included quantification of student responses to the open-ended questions and thematic analysis of observation notes and interview transcripts. Quantitative datasets were analyzed using descriptive and inferential statistical methods, including t tests to evaluate the differences in means scores between paired groups before and after interventions and one-way analysis of variance (ANOVA) to test for differences between mean scores of the comparison groups. Significant mean differences between groups were further examined using a Dunnett's C post hoc statistical analysis. Integration and interpretation of the qualitative and quantitative results of the study revealed a significant increase in general, local and preparedness earthquake knowledge among middle school students after the interventions. The findings specifically indicated that these students felt most aware and prepared for an earthquake after an intervention that consisted of an inquiry-based group discussion on safety, earthquake content presentation and earthquake simulation video presentation on preparedness. Variations of the intervention, including no intervention, were not as effective in significantly increasing students' conceptual learning of earthquake knowledge.

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

Quantitative analysis of the polarization characteristics of atherosclerotic plaques

NASA Astrophysics Data System (ADS)

Gubarkova, Ekaterina V.; Kirillin, Michail Y.; Dudenkova, Varvara V.; Kiseleva, Elena B.; Moiseev, Alexander A.; Gelikonov, Grigory V.; Timofeeva, Lidia B.; Fiks, Ilya I.; Feldchtein, Felix I.; Gladkova, Natalia D.

2016-04-01

In this study we demonstrate the capability of cross-polarization optical coherence tomography (CP OCT) to assess collagen and elastin fibers condition in atherosclerotic plaques basing on ratio of the OCT signal levels in cross- and co- polarizations. We consider the depolarization factor (DF) and the effective birefringence (Δn) as quantitative characteristics of CP OCT images. We revealed that calculation of both DF and Δn in the region of interest (fibrous cap) yields a statistically significant difference between stable and unstable plaques (0.46+/-0.21 vs 0.09+/-0.04 for IDF; (4.7+/-1.0)•10-4 vs (2.5+/-0.7)•10-4 for Δn p<0.05). In parallel with CP OCT we used the nonlinear microscopy for analysis of thin cross-section of atherosclerotic plaque, revealing the different average isotropy index of collagen and elastin fibers for stable and unstable plaques (0.30 +/- 0.10 vs 0.70 +/- 0.08; p<0.001). The proposed approach for quantitative assessment of CP OCT images allows cross-scattering and birefringence characterization of stable and unstable atherosclerotic plaques.

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

NASA Astrophysics Data System (ADS)

Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

2015-03-01

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

Point-by-point compositional analysis for atom probe tomography.

PubMed

Stephenson, Leigh T; Ceguerra, Anna V; Li, Tong; Rojhirunsakool, Tanaporn; Nag, Soumya; Banerjee, Rajarshi; Cairney, Julie M; Ringer, Simon P

2014-01-01

This new alternate approach to data processing for analyses that traditionally employed grid-based counting methods is necessary because it removes a user-imposed coordinate system that not only limits an analysis but also may introduce errors. We have modified the widely used "binomial" analysis for APT data by replacing grid-based counting with coordinate-independent nearest neighbour identification, improving the measurements and the statistics obtained, allowing quantitative analysis of smaller datasets, and datasets from non-dilute solid solutions. It also allows better visualisation of compositional fluctuations in the data. Our modifications include:.•using spherical k-atom blocks identified by each detected atom's first k nearest neighbours.•3D data visualisation of block composition and nearest neighbour anisotropy.•using z-statistics to directly compare experimental and expected composition curves. Similar modifications may be made to other grid-based counting analyses (contingency table, Langer-Bar-on-Miller, sinusoidal model) and could be instrumental in developing novel data visualisation options.

Subcellular object quantification with Squassh3C and SquasshAnalyst.

PubMed

Rizk, Aurélien; Mansouri, Maysam; Ballmer-Hofer, Kurt; Berger, Philipp

2015-11-01

Quantitative image analysis plays an important role in contemporary biomedical research. Squassh is a method for automatic detection, segmentation, and quantification of subcellular structures and analysis of their colocalization. Here we present the applications Squassh3C and SquasshAnalyst. Squassh3C extends the functionality of Squassh to three fluorescence channels and live-cell movie analysis. SquasshAnalyst is an interactive web interface for the analysis of Squassh3C object data. It provides segmentation image overview and data exploration, figure generation, object and image filtering, and a statistical significance test in an easy-to-use interface. The overall procedure combines the Squassh3C plug-in for the free biological image processing program ImageJ and a web application working in conjunction with the free statistical environment R, and it is compatible with Linux, MacOS X, or Microsoft Windows. Squassh3C and SquasshAnalyst are available for download at www.psi.ch/lbr/SquasshAnalystEN/SquasshAnalyst.zip.

Functional quantitative susceptibility mapping (fQSM).

PubMed

Balla, Dávid Z; Sanchez-Panchuelo, Rosa M; Wharton, Samuel J; Hagberg, Gisela E; Scheffler, Klaus; Francis, Susan T; Bowtell, Richard

2014-10-15

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful technique, typically based on the statistical analysis of the magnitude component of the complex time-series. Here, we additionally interrogated the phase data of the fMRI time-series and used quantitative susceptibility mapping (QSM) in order to investigate the potential of functional QSM (fQSM) relative to standard magnitude BOLD fMRI. High spatial resolution data (1mm isotropic) were acquired every 3 seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B0. Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM time-series and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatio-temporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data. Our results present the potential of fQSM as a quantitative method of mapping BOLD changes. We also critically discuss the technical challenges and issues linked to this intriguing new technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Statistical analysis for improving data precision in the SPME GC-MS analysis of blackberry (Rubus ulmifolius Schott) volatiles.

PubMed

D'Agostino, M F; Sanz, J; Martínez-Castro, I; Giuffrè, A M; Sicari, V; Soria, A C

2014-07-01

Statistical analysis has been used for the first time to evaluate the dispersion of quantitative data in the solid-phase microextraction (SPME) followed by gas chromatography-mass spectrometry (GC-MS) analysis of blackberry (Rubus ulmifolius Schott) volatiles with the aim of improving their precision. Experimental and randomly simulated data were compared using different statistical parameters (correlation coefficients, Principal Component Analysis loadings and eigenvalues). Non-random factors were shown to significantly contribute to total dispersion; groups of volatile compounds could be associated with these factors. A significant improvement of precision was achieved when considering percent concentration ratios, rather than percent values, among those blackberry volatiles with a similar dispersion behavior. As novelty over previous references, and to complement this main objective, the presence of non-random dispersion trends in data from simple blackberry model systems was evidenced. Although the influence of the type of matrix on data precision was proved, the possibility of a better understanding of the dispersion patterns in real samples was not possible from model systems. The approach here used was validated for the first time through the multicomponent characterization of Italian blackberries from different harvest years. Copyright © 2014 Elsevier B.V. All rights reserved.

Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

NASA Astrophysics Data System (ADS)

Bookstein, Fred L.

1995-08-01

Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

Descriptive statistics.

PubMed

Nick, Todd G

2007-01-01

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

Phase noise optimization in temporal phase-shifting digital holography with partial coherence light sources and its application in quantitative cell imaging.

PubMed

Remmersmann, Christian; Stürwald, Stephan; Kemper, Björn; Langehanenberg, Patrik; von Bally, Gert

2009-03-10

In temporal phase-shifting-based digital holographic microscopy, high-resolution phase contrast imaging requires optimized conditions for hologram recording and phase retrieval. To optimize the phase resolution, for the example of a variable three-step algorithm, a theoretical analysis on statistical errors, digitalization errors, uncorrelated errors, and errors due to a misaligned temporal phase shift is carried out. In a second step the theoretically predicted results are compared to the measured phase noise obtained from comparative experimental investigations with several coherent and partially coherent light sources. Finally, the applicability for noise reduction is demonstrated by quantitative phase contrast imaging of pancreas tumor cells.

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

A continuation of base-line studies for environmentally monitoring space transportation systems at John F. Kennedy Space Center. Executive summary

NASA Technical Reports Server (NTRS)

Stout, I. J.

1980-01-01

Studies conducted in and around John F. Kennedy Space Center, Merrit Island, Florida were designed to establish baseline conditions for various attributes of the biotic and abiotic environment. Features were described and quantitatively measured. Certain condition were found to be appropriate for the detection and assessment of possible environmental perturbations caused by future NASA activities. These include plant communities, mammal populations, rainfall chemistry, fish populations, and the status of rare and endangered species. On the basis of statistical analysis of quantitative data and logistic considerations, it was possible to refine the kinds and amounts of measurements needed to evaluate perturbations in selected environmental components.

Quantitative contrast-enhanced ultrasound evaluation of pathological complete response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy.

PubMed

Wan, Cai-Feng; Liu, Xue-Song; Wang, Lin; Zhang, Jie; Lu, Jin-Song; Li, Feng-Hua

2018-06-01

To clarify whether the quantitative parameters of contrast-enhanced ultrasound (CEUS) can be used to predict pathological complete response (pCR) in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC). Fifty-one patients with histologically proved locally advanced breast cancer scheduled for NAC were enrolled. The quantitative data for CEUS and the tumor diameter were collected at baseline and before surgery, and compared with the pathological response. Multiple logistic regression analysis was performed to examine quantitative parameters at CEUS and the tumor diameter to predict the pCR, and receiver operating characteristic (ROC) curve analysis was used as a summary statistic. Multiple logistic regression analysis revealed that PEAK (the maximum intensity of the time-intensity curve during bolus transit), PEAK%, TTP% (time to peak), and diameter% were significant independent predictors of pCR, and the area under the ROC curve was 0.932(Az 1 ), and the sensitivity and specificity to predict pCR were 93.7% and 80.0%. The area under the ROC curve for the quantitative parameters was 0.927(Az 2 ), and the sensitivity and specificity to predict pCR were 81.2% and 94.3%. For diameter%, the area under the ROC curve was 0.786 (Az 3 ), and the sensitivity and specificity to predict pCR were 93.8% and 54.3%. The values of Az 1 and Az 2 were significantly higher than that of Az 3 (P = 0.027 and P = 0.034, respectively). However, there was no significant difference between the values of Az 1 and Az 2 (P = 0.825). Quantitative analysis of tumor blood perfusion with CEUS is superior to diameter% to predict pCR, and can be used as a functional technique to evaluate tumor response to NAC. Copyright © 2018. Published by Elsevier B.V.

Leadership and Culture-Building in Schools: Quantitative and Qualitative Understandings.

ERIC Educational Resources Information Center

Sashkin, Marshall; Sashkin, Molly G.

Understanding effective school leadership as a function of culture building through quantitative and qualitative analyses is the purpose of this paper. The two-part quantitative phase of the research focused on statistical measures of culture and leadership behavior directed toward culture building in the school. The first quantitative part…

Spatial analysis on future housing markets: economic development and housing implications.

PubMed

Liu, Xin; Wang, Lizhe

2014-01-01

A coupled projection method combining formal modelling and other statistical techniques was developed to delineate the relationship between economic and social drivers for net new housing allocations. Using the example of employment growth in Tyne and Wear, UK, until 2016, the empirical analysis yields housing projections at the macro- and microspatial levels (e.g., region to subregion to elected ward levels). The results have important implications for the strategic planning of locations for housing and employment, demonstrating both intuitively and quantitatively how local economic developments affect housing demand.

Spatial Analysis on Future Housing Markets: Economic Development and Housing Implications

PubMed Central

Liu, Xin; Wang, Lizhe

2014-01-01

A coupled projection method combining formal modelling and other statistical techniques was developed to delineate the relationship between economic and social drivers for net new housing allocations. Using the example of employment growth in Tyne and Wear, UK, until 2016, the empirical analysis yields housing projections at the macro- and microspatial levels (e.g., region to subregion to elected ward levels). The results have important implications for the strategic planning of locations for housing and employment, demonstrating both intuitively and quantitatively how local economic developments affect housing demand. PMID:24892097

Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data

NASA Astrophysics Data System (ADS)

Jiao, Xiangqing; Liao, Yuan; Nguyen, Thai

2017-11-01

Accurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model's effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model's accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Analysis of Nonequivalent Assessments across Different Linguistic Groups Using a Mixed Methods Approach: Understanding the Causes of Differential Item Functioning by Cognitive Interviewing

ERIC Educational Resources Information Center

Benítez, Isabel; Padilla, José-Luis

2014-01-01

Differential item functioning (DIF) can undermine the validity of cross-lingual comparisons. While a lot of efficient statistics for detecting DIF are available, few general findings have been found to explain DIF results. The objective of the article was to study DIF sources by using a mixed method design. The design involves a quantitative phase…

Detection of soybean in soy-based meat substitutes.

PubMed

Abd Allah, M A; Foda, Y H; el-Dashlouty, S; el-Sanafiry, N Y; Abu Salem, F M

1986-01-01

The statistical analysis of the available data indicated that the straight line equations of protein, fat, fibre, calcium, methionine, and lysine could successively be used for forecasting the added soy percent in a given recipe. On the other hand, the areas of the identified bands in the electropherograms of the investigated samples were considered a reasonable tool for the quantitative determination of whole soybean in soy-based meat substitutes.

[Clinical research XXIII. From clinical judgment to meta-analyses].

PubMed

Rivas-Ruiz, Rodolfo; Castelán-Martínez, Osvaldo D; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Noyola-Castillo, Maura E; Talavera, Juan O

2014-01-01

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

Project risk management in the construction of high-rise buildings

NASA Astrophysics Data System (ADS)

Titarenko, Boris; Hasnaoui, Amir; Titarenko, Roman; Buzuk, Liliya

2018-03-01

This paper shows the project risk management methods, which allow to better identify risks in the construction of high-rise buildings and to manage them throughout the life cycle of the project. One of the project risk management processes is a quantitative analysis of risks. The quantitative analysis usually includes the assessment of the potential impact of project risks and their probabilities. This paper shows the most popular methods of risk probability assessment and tries to indicate the advantages of the robust approach over the traditional methods. Within the framework of the project risk management model a robust approach of P. Huber is applied and expanded for the tasks of regression analysis of project data. The suggested algorithms used to assess the parameters in statistical models allow to obtain reliable estimates. A review of the theoretical problems of the development of robust models built on the methodology of the minimax estimates was done and the algorithm for the situation of asymmetric "contamination" was developed.

Evaluation of cerebral maturation by visual and quantitative analysis of resting electroencephalography in children with primary nocturnal enuresis.

PubMed

Hallioğlu, O; Ozge, A; Comelekoglu, U; Topaloglu, A K; Kanik, A; Duzovali, O; Yilgor, E

2001-10-01

This study was undertaken to evaluate resting electroencephalographic (EEG) changes and their relations to cerebral maturation in children with primary nocturnal enuresis. Cerebral maturation is known to be important in the pathogenesis of this disorder. Twenty-five right-handed patients with primary nocturnal enuresis, aged 6 to 14 years, and 23 age- and sex-matched healthy children were included in this cross-sectional case-control study. The abnormalities detected using such techniques as hemispheral asymmetry, regional differences, and hyperventilation response in addition to visual and quantitative EEG analysis were examined statistically by multivariate analysis. A decrease in alpha activity in the left (dominant hemisphere) temporal lobe and in the frontal lobes bilaterally and an increase in delta activity in the right temporal region were observed. We concluded that insufficient cerebral maturation is an important factor in the pathogenesis of primary nocturnal enuresis, and EEG, as a noninvasive and inexpensive method, could be used in evaluating cerebral maturation.

The Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing.

PubMed

Lash, Timothy L

2017-09-15

In the last few years, stakeholders in the scientific community have raised alarms about a perceived lack of reproducibility of scientific results. In reaction, guidelines for journals have been promulgated and grant applicants have been asked to address the rigor and reproducibility of their proposed projects. Neither solution addresses a primary culprit, which is the culture of null hypothesis significance testing that dominates statistical analysis and inference. In an innovative research enterprise, selection of results for further evaluation based on null hypothesis significance testing is doomed to yield a low proportion of reproducible results and a high proportion of effects that are initially overestimated. In addition, the culture of null hypothesis significance testing discourages quantitative adjustments to account for systematic errors and quantitative incorporation of prior information. These strategies would otherwise improve reproducibility and have not been previously proposed in the widely cited literature on this topic. Without discarding the culture of null hypothesis significance testing and implementing these alternative methods for statistical analysis and inference, all other strategies for improving reproducibility will yield marginal gains at best. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

HyphArea--automated analysis of spatiotemporal fungal patterns.

PubMed

Baum, Tobias; Navarro-Quezada, Aura; Knogge, Wolfgang; Douchkov, Dimitar; Schweizer, Patrick; Seiffert, Udo

2011-01-01

In phytopathology quantitative measurements are rarely used to assess crop plant disease symptoms. Instead, a qualitative valuation by eye is often the method of choice. In order to close the gap between subjective human inspection and objective quantitative results, the development of an automated analysis system that is capable of recognizing and characterizing the growth patterns of fungal hyphae in micrograph images was developed. This system should enable the efficient screening of different host-pathogen combinations (e.g., barley-Blumeria graminis, barley-Rhynchosporium secalis) using different microscopy technologies (e.g., bright field, fluorescence). An image segmentation algorithm was developed for gray-scale image data that achieved good results with several microscope imaging protocols. Furthermore, adaptability towards different host-pathogen systems was obtained by using a classification that is based on a genetic algorithm. The developed software system was named HyphArea, since the quantification of the area covered by a hyphal colony is the basic task and prerequisite for all further morphological and statistical analyses in this context. By means of a typical use case the utilization and basic properties of HyphArea could be demonstrated. It was possible to detect statistically significant differences between the growth of an R. secalis wild-type strain and a virulence mutant. Copyright © 2010 Elsevier GmbH. All rights reserved.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

PubMed Central

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-01-01

Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393

Simulating realistic predator signatures in quantitative fatty acid signature analysis

USGS Publications Warehouse

Bromaghin, Jeffrey F.

2015-01-01

Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.

Investigating the Pedagogical Approaches Related to Changes in Attitudes toward Statistics in a Quantitative Methods Course for Psychology Undergraduate Students

ERIC Educational Resources Information Center

Liau, Albert K.; Kiat, John E.; Nie, Youyan

2015-01-01

The purpose of this study was to examine the extent to which the pedagogical approaches used in the course were related to improvements in students' attitudes toward statistics in a Quantitative Methods course for psychology undergraduate students in a Malaysian University. The study examined whether increasing availability of the instructor and…

Emotional and cognitive effects of peer tutoring among secondary school mathematics students

NASA Astrophysics Data System (ADS)

Alegre Ansuategui, Francisco José; Moliner Miravet, Lidón

2017-11-01

This paper describes an experience of same-age peer tutoring conducted with 19 eighth-grade mathematics students in a secondary school in Castellon de la Plana (Spain). Three constructs were analysed before and after launching the program: academic performance, mathematics self-concept and attitude of solidarity. Students' perceptions of the method were also analysed. The quantitative data was gathered by means of a mathematics self-concept questionnaire, an attitude of solidarity questionnaire and the students' numerical ratings. A statistical analysis was performed using Student's t-test. The qualitative information was gathered by means of discussion groups and a field diary. This information was analysed using descriptive analysis and by categorizing the information. Results show statistically significant improvements in all the variables and the positive assessment of the experience and the interactions that took place between the students.

β-Glucuronidase is a suitable internal control gene for mRNA quantitation in pathophysiological and non-pathological livers.

PubMed

Yamaguchi, Hiromi; Matsumoto, Sawako; Ishibashi, Mariko; Hasegawa, Kiyoshi; Sugitani, Masahiko; Takayama, Tadatoshi; Esumi, Mariko

2013-10-01

The level of expression of housekeeping genes is in general considered stable, and a representative gene such as glyceraldehyde-3-phosphate dehydrogenase is commonly used as an internal control for quantitating mRNA. However, expression of housekeeping genes is not always constant under pathological conditions. To determine which genes would be most suitable as internal controls for quantitative gene expression studies in human liver diseases, we quantified 12 representative housekeeping genes in 27 non-cancerous liver tissues (normal, chronic hepatitis C with and without liver cirrhosis). We identified β-glucuronidase as the most suitable gene for studies on liver by rigorous statistical analysis of inter- and intra-group comparisons. We conclude that it is important to determine the most appropriate control gene for the particular condition to be analyzed. © 2013 Elsevier Inc. All rights reserved.

Relationships between microstructure and mechanical properties of Ti-5Al-5Mo-5V-3Cr-1Zr alloy

NASA Astrophysics Data System (ADS)

Li, Z. Y.; Wu, G. Q.; Huang, Z.

2018-03-01

Through a statistical, quantitative analysis on microstructure of Ti-5Al-5Mo-5V-3Cr-1Zr (Ti55531) alloy, the relationships between microstructure and mechanical properties and heat treatment temperatures were investigated. The results show that in Widmanstätten structure, the size of β grain is greatly increased with increasing annealing temperature. Static toughness is related to grain boundary alpha phase discontinuity, the tensile strength is related to acicular alpha phase interface length and acicular alpha phase proportion. In duplex microstructure, the tensile strength is related to the equiaxed alpha proportion. Elongation, static toughness and crack forming work are related to the equiaxed alpha proportion and negatively related to secondary phase proportion. The microstructure can be described quantitatively and the mechanical properties can be predicted by analysis of microstructure.

Association Analysis in Rice: From Application to Utilization

PubMed Central

Zhang, Peng; Zhong, Kaizhen; Shahid, Muhammad Qasim; Tong, Hanhua

2016-01-01

Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure, and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding. PMID:27582745

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study.

PubMed

Ha, Richard; Mema, Eralda; Guo, Xiaotao; Mango, Victoria; Desperito, Elise; Ha, Jason; Wynn, Ralph; Zhao, Binsheng

2016-04-01

The amount of fibroglandular tissue (FGT) has been linked to breast cancer risk based on mammographic density studies. Currently, the qualitative assessment of FGT on mammogram (MG) and magnetic resonance imaging (MRI) is prone to intra and inter-observer variability. The purpose of this study is to develop an objective quantitative FGT measurement tool for breast MRI that could provide significant clinical value. An IRB approved study was performed. Sixty breast MRI cases with qualitative assessment of mammographic breast density and MRI FGT were randomly selected for quantitative analysis from routine breast MRIs performed at our institution from 1/2013 to 12/2014. Blinded to the qualitative data, whole breast and FGT contours were delineated on T1-weighted pre contrast sagittal images using an in-house, proprietary segmentation algorithm which combines the region-based active contours and a level set approach. FGT (%) was calculated by: [segmented volume of FGT (mm(3))/(segmented volume of whole breast (mm(3))] ×100. Statistical correlation analysis was performed between quantified FGT (%) on MRI and qualitative assessments of mammographic breast density and MRI FGT. There was a significant positive correlation between quantitative MRI FGT assessment and qualitative MRI FGT (r=0.809, n=60, P<0.001) and mammographic density assessment (r=0.805, n=60, P<0.001). There was a significant correlation between qualitative MRI FGT assessment and mammographic density assessment (r=0.725, n=60, P<0.001). The four qualitative assessment categories of FGT correlated with the calculated mean quantitative FGT (%) of 4.61% (95% CI, 0-12.3%), 8.74% (7.3-10.2%), 18.1% (15.1-21.1%), 37.4% (29.5-45.3%). Quantitative measures of FGT (%) were computed with data derived from breast MRI and correlated significantly with conventional qualitative assessments. This quantitative technique may prove to be a valuable tool in clinical use by providing computer generated standardized measurements with limited intra or inter-observer variability.

Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

PubMed

White, Paul A; Johnson, George E

2016-05-01

Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the relationships between genetic damage and disease, and the concomitant ability to use genetic toxicity results per se. © Her Majesty the Queen in Right of Canada 2016. Reproduced with the permission of the Minister of Health.

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.

Increased fibulin-1 plasma levels in polycystic ovary syndrome (PCOS) patients: possible contribution to the link between PCOS and cardiovascular risk.

PubMed

Scarinci, E; Tropea, A; Russo, G; Notaristefano, G; Messana, C; Alesiani, O; Fabozzi, S M; Lanzone, A; Apa, R

2018-04-21

To investigate a possible relation between fibulin-1 plasma levels and PCOS. ELISA quantitative determination of human fibulin-1. 50 women with PCOS and 40 control patients who attended the Unit of Human Reproductive Pathophysiology, Università Cattolica del Sacro Cuore, Rome, were enrolled. Ultrasonographic pelvic examinations, hormonal profile assays, oral tolerance test OGTT, lipid profile and ELISA quantitative determination of human fibulin-1 were performed. Fibulin-1 levels were found to be statistically significantly higher in PCOS patients than in matched control women. No statistically significant positive correlation was found between fibulin-1 and AUCi, HOMA-IR, total cholesterol, LDL, AMH, androstenedione and FAI, whereas a statistically significant positive correlation was found between fibulin-1 and 17OHP (p = 0.016) in the PCOS group. However, multivariable linear regression analysis showed that 17 OH P did not independently predict fibulin-1 levels (p = 0.089). Our data could contribute to explain the hypothesized increased cardiovascular risk and vascular damage in patients with PCOS. A better understanding of the cellular and molecular mechanisms involved in cardiometabolic disorders associated with PCOS is mandatory to identify new therapeutic strategies to eventually prevent the progression of cardiovascular diseases in these patients.

To be seen or to hide: visual characteristics of body patterns for camouflage and communication in the Australian giant cuttlefish Sepia apama.

PubMed

Zylinski, S; How, M J; Osorio, D; Hanlon, R T; Marshall, N J

2011-05-01

It might seem obvious that a camouflaged animal must generally match its background whereas to be conspicuous an organism must differ from the background. However, the image parameters (or statistics) that evaluate the conspicuousness of patterns and textures are seldom well defined, and animal coloration patterns are rarely compared quantitatively with their respective backgrounds. Here we examine this issue in the Australian giant cuttlefish Sepia apama. We confine our analysis to the best-known and simplest image statistic, the correlation in intensity between neighboring pixels. Sepia apama can rapidly change their body patterns from assumed conspicuous signaling to assumed camouflage, thus providing an excellent and unique opportunity to investigate how such patterns differ in a single visual habitat. We describe the intensity variance and spatial frequency power spectra of these differing body patterns and compare these patterns with the backgrounds against which they are viewed. The measured image statistics of camouflaged animals closely resemble their backgrounds, while signaling animals differ significantly from their backgrounds. Our findings may provide the basis for a set of general rules for crypsis and signals. Furthermore, our methods may be widely applicable to the quantitative study of animal coloration.

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

NASA Astrophysics Data System (ADS)

Demin, S. A.; Yulmetyev, R. M.; Panischev, O. Yu.; Hänggi, Peter

2008-03-01

On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO - control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.

A comparison of cosegregation analysis methods for the clinical setting.

PubMed

Rañola, John Michael O; Liu, Quanhui; Rosenthal, Elisabeth A; Shirts, Brian H

2018-04-01

Quantitative cosegregation analysis can help evaluate the pathogenicity of genetic variants. However, genetics professionals without statistical training often use simple methods, reporting only qualitative findings. We evaluate the potential utility of quantitative cosegregation in the clinical setting by comparing three methods. One thousand pedigrees each were simulated for benign and pathogenic variants in BRCA1 and MLH1 using United States historical demographic data to produce pedigrees similar to those seen in the clinic. These pedigrees were analyzed using two robust methods, full likelihood Bayes factors (FLB) and cosegregation likelihood ratios (CSLR), and a simpler method, counting meioses. Both FLB and CSLR outperform counting meioses when dealing with pathogenic variants, though counting meioses is not far behind. For benign variants, FLB and CSLR greatly outperform as counting meioses is unable to generate evidence for benign variants. Comparing FLB and CSLR, we find that the two methods perform similarly, indicating that quantitative results from either of these methods could be combined in multifactorial calculations. Combining quantitative information will be important as isolated use of cosegregation in single families will yield classification for less than 1% of variants. To encourage wider use of robust cosegregation analysis, we present a website ( http://www.analyze.myvariant.org ) which implements the CSLR, FLB, and Counting Meioses methods for ATM, BRCA1, BRCA2, CHEK2, MEN1, MLH1, MSH2, MSH6, and PMS2. We also present an R package, CoSeg, which performs the CSLR analysis on any gene with user supplied parameters. Future variant classification guidelines should allow nuanced inclusion of cosegregation evidence against pathogenicity.

Rock Statistics at the Mars Pathfinder Landing Site, Roughness and Roving on Mars

NASA Technical Reports Server (NTRS)

Haldemann, A. F. C.; Bridges, N. T.; Anderson, R. C.; Golombek, M. P.

1999-01-01

Several rock counts have been carried out at the Mars Pathfinder landing site producing consistent statistics of rock coverage and size-frequency distributions. These rock statistics provide a primary element of "ground truth" for anchoring remote sensing information used to pick the Pathfinder, and future, landing sites. The observed rock population statistics should also be consistent with the emplacement and alteration processes postulated to govern the landing site landscape. The rock population databases can however be used in ways that go beyond the calculation of cumulative number and cumulative area distributions versus rock diameter and height. Since the spatial parameters measured to characterize each rock are determined with stereo image pairs, the rock database serves as a subset of the full landing site digital terrain model (DTM). Insofar as a rock count can be carried out in a speedier, albeit coarser, manner than the full DTM analysis, rock counting offers several operational and scientific products in the near term. Quantitative rock mapping adds further information to the geomorphic study of the landing site, and can also be used for rover traverse planning. Statistical analysis of the surface roughness using the rock count proxy DTM is sufficiently accurate when compared to the full DTM to compare with radar remote sensing roughness measures, and with rover traverse profiles.

Advanced quantitative measurement methodology in physics education research

NASA Astrophysics Data System (ADS)

Wang, Jing

The ultimate goal of physics education research (PER) is to develop a theoretical framework to understand and improve the learning process. In this journey of discovery, assessment serves as our headlamp and alpenstock. It sometimes detects signals in student mental structures, and sometimes presents the difference between expert understanding and novice understanding. Quantitative assessment is an important area in PER. Developing research-based effective assessment instruments and making meaningful inferences based on these instruments have always been important goals of the PER community. Quantitative studies are often conducted to provide bases for test development and result interpretation. Statistics are frequently used in quantitative studies. The selection of statistical methods and interpretation of the results obtained by these methods shall be connected to the education background. In this connecting process, the issues of educational models are often raised. Many widely used statistical methods do not make assumptions on the mental structure of subjects, nor do they provide explanations tailored to the educational audience. There are also other methods that consider the mental structure and are tailored to provide strong connections between statistics and education. These methods often involve model assumption and parameter estimation, and are complicated mathematically. The dissertation provides a practical view of some advanced quantitative assessment methods. The common feature of these methods is that they all make educational/psychological model assumptions beyond the minimum mathematical model. The purpose of the study is to provide a comparison between these advanced methods and the pure mathematical methods. The comparison is based on the performance of the two types of methods under physics education settings. In particular, the comparison uses both physics content assessments and scientific ability assessments. The dissertation includes three parts. The first part involves the comparison between item response theory (IRT) and classical test theory (CTT). The two theories both provide test item statistics for educational inferences and decisions. The two theories are both applied to Force Concept Inventory data obtained from students enrolled in The Ohio State University. Effort was made to examine the similarity and difference between the two theories, and the possible explanation to the difference. The study suggests that item response theory is more sensitive to the context and conceptual features of the test items than classical test theory. The IRT parameters provide a better measure than CTT parameters for the educational audience to investigate item features. The second part of the dissertation is on the measure of association for binary data. In quantitative assessment, binary data is often encountered because of its simplicity. The current popular measures of association fail under some extremely unbalanced conditions. However, the occurrence of these conditions is not rare in educational data. Two popular association measures, the Pearson's correlation and the tetrachoric correlation are examined. A new method, model based association is introduced, and an educational testing constraint is discussed. The existing popular methods are compared with the model based association measure with and without the constraint. Connections between the value of association and the context and conceptual features of questions are discussed in detail. Results show that all the methods have their advantages and disadvantages. Special attention to the test and data conditions is necessary. The last part of the dissertation is focused on exploratory factor analysis (EFA). The theoretical advantages of EFA are discussed. Typical misunderstanding and misusage of EFA are explored. The EFA is performed on Lawson's Classroom Test of Scientific Reasoning (LCTSR), a widely used assessment on scientific reasoning skills. The reasoning ability structures for U.S. and Chinese students at different educational levels are given by the analysis. A final discussion on the advanced quantitative assessment methodology and the pure mathematical methodology is presented at the end.

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative analysis of the text and graphic content in ophthalmic slide presentations.

PubMed

Ing, Edsel; Celo, Erdit; Ing, Royce; Weisbrod, Lawrence; Ing, Mercedes

2017-04-01

To determine the characteristics of ophthalmic digital slide presentations. Retrospective quantitative analysis. Slide presentations from a 2015 Canadian primary eye care conference were analyzed for their duration, character and word count, font size, words per minute (wpm), lines per slide, words per slide, slides per minute (spm), text density product (wpm × spm), proportion of graphic content, and Flesch Reading Ease (FRE) score using Microsoft PowerPoint and Word. The median audience evaluation score for the lectures was used to dichotomize the higher scoring lectures (HSL) from the lower scoring lectures (LSL). A priori we hypothesized that there would be a difference in the wpm, spm, text density product, and FRE score between HSL and LSL. Wilcoxon rank-sum tests with Bonferroni correction were utilized. The 17 lectures had medians of 2.5 spm, 20.3 words per slide, 5.0 lines per slide, 28-point sans serif font, 36% graphic content, and text density product of 136.4 words × slides/minute 2 . Although not statistically significant, the HSL had more wpm, fewer words per slide, more graphics per slide, greater text density, and higher FRE score than LSL. There was a statistically significant difference in the spm of the HSL (3.1 ± 1.0) versus the LSL (2.2 ± 1.0) at p = 0.0124. All presenters showed more than 1 slide per minute. The HSL showed more spm than the LSL. The descriptive statistics from this study may aid in the preparation of slides used for teaching and conferences. Copyright © 2017 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Quantitative determination of low-Z elements in single atmospheric particles on boron substrates by automated scanning electron microscopy-energy-dispersive X-ray spectrometry.

PubMed

Choël, Marie; Deboudt, Karine; Osán, János; Flament, Pascal; Van Grieken, René

2005-09-01

Atmospheric aerosols consist of a complex heterogeneous mixture of particles. Single-particle analysis techniques are known to provide unique information on the size-resolved chemical composition of aerosols. A scanning electron microscope (SEM) combined with a thin-window energy-dispersive X-ray (EDX) detector enables the morphological and elemental analysis of single particles down to 0.1 microm with a detection limit of 1-10 wt %, low-Z elements included. To obtain data statistically representative of the air masses sampled, a computer-controlled procedure can be implemented in order to run hundreds of single-particle analyses (typically 1000-2000) automatically in a relatively short period of time (generally 4-8 h, depending on the setup and on the particle loading). However, automated particle analysis by SEM-EDX raises two practical challenges: the accuracy of the particle recognition and the reliability of the quantitative analysis, especially for micrometer-sized particles with low atomic number contents. Since low-Z analysis is hampered by the use of traditional polycarbonate membranes, an alternate choice of substrate is a prerequisite. In this work, boron is being studied as a promising material for particle microanalysis. As EDX is generally said to probe a volume of approximately 1 microm3, geometry effects arise from the finite size of microparticles. These particle geometry effects must be corrected by means of a robust concentration calculation procedure. Conventional quantitative methods developed for bulk samples generate elemental concentrations considerably in error when applied to microparticles. A new methodology for particle microanalysis, combining the use of boron as the substrate material and a reverse Monte Carlo quantitative program, was tested on standard particles ranging from 0.25 to 10 microm. We demonstrate that the quantitative determination of low-Z elements in microparticles is achievable and that highly accurate results can be obtained using the automatic data processing described here compared to conventional methods.

Development of one novel multiple-target plasmid for duplex quantitative PCR analysis of roundup ready soybean.

PubMed

Zhang, Haibo; Yang, Litao; Guo, Jinchao; Li, Xiang; Jiang, Lingxi; Zhang, Dabing

2008-07-23

To enforce the labeling regulations of genetically modified organisms (GMOs), the application of reference molecules as calibrators is becoming essential for practical quantification of GMOs. However, the reported reference molecules with tandem marker multiple targets have been proved not suitable for duplex PCR analysis. In this study, we developed one unique plasmid molecule based on one pMD-18T vector with three exogenous target DNA fragments of Roundup Ready soybean GTS 40-3-2 (RRS), that is, CaMV35S, NOS, and RRS event fragments, plus one fragment of soybean endogenous Lectin gene. This Lectin gene fragment was separated from the three exogenous target DNA fragments of RRS by inserting one 2.6 kb DNA fragment with no relatedness to RRS detection targets in this resultant plasmid. Then, we proved that this design allows the quantification of RRS using the three duplex real-time PCR assays targeting CaMV35S, NOS, and RRS events employing this reference molecule as the calibrator. In these duplex PCR assays, the limits of detection (LOD) and quantification (LOQ) were 10 and 50 copies, respectively. For the quantitative analysis of practical RRS samples, the results of accuracy and precision were similar to those of simplex PCR assays, for instance, the quantitative results were at the 1% level, the mean bias of the simplex and duplex PCR were 4.0% and 4.6%, respectively, and the statistic analysis ( t-test) showed that the quantitative data from duplex and simplex PCR had no significant discrepancy for each soybean sample. Obviously, duplex PCR analysis has the advantages of saving the costs of PCR reaction and reducing the experimental errors in simplex PCR testing. The strategy reported in the present study will be helpful for the development of new reference molecules suitable for duplex PCR quantitative assays of GMOs.

[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.

Quantitative analysis of 18F-NaF dynamic PET/CT cannot differentiate malignant from benign lesions in multiple myeloma.

PubMed

Sachpekidis, Christos; Hillengass, Jens; Goldschmidt, Hartmut; Anwar, Hoda; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2017-01-01

A renewed interest has been recently developed for the highly sensitive bone-seeking radiopharmaceutical 18 F-NaF. Aim of the present study is to evaluate the potential utility of quantitative analysis of 18 F-NaF dynamic PET/CT data in differentiating malignant from benign degenerative lesions in multiple myeloma (MM). 80 MM patients underwent whole-body PET/CT and dynamic PET/CT scanning of the pelvis with 18 F-NaF. PET/CT data evaluation was based on visual (qualitative) assessment, semi-quantitative (SUV) calculations, and absolute quantitative estimations after application of a 2-tissue compartment model and a non-compartmental approach leading to the extraction of fractal dimension (FD). In total 263 MM lesions were demonstrated on 18 F-NaF PET/CT. Semi-quantitative and quantitative evaluations were performed for 25 MM lesions as well as for 25 benign, degenerative and traumatic lesions. Mean SUV average for MM lesions was 11.9 and mean SUV max was 23.2. Respectively, SUV average and SUV max for degenerative lesions were 13.5 and 20.2. Kinetic analysis of 18 F-NaF revealed the following mean values for MM lesions: K 1 = 0.248 (1/min), k 3 = 0.359 (1/min), influx (K i ) = 0.107 (1/min), FD = 1.382, while the respective values for degenerative lesions were: K 1 = 0.169 (1/min), k 3 = 0.422 (1/min), influx (K i ) = 0.095 (1/min), FD = 1. 411. No statistically significant differences between MM and benign degenerative disease regarding SUV average , SUV max , K 1 , k 3 and influx (K i ) were demonstrated. FD was significantly higher in degenerative than in malignant lesions. The present findings show that quantitative analysis of 18 F-NaF PET data cannot differentiate malignant from benign degenerative lesions in MM patients, supporting previously published results, which reflect the limited role of 18 F-NaF PET/CT in the diagnostic workup of MM.

Analyzing Two-Phase Single-Case Data with Non-overlap and Mean Difference Indices: Illustration, Software Tools, and Alternatives.

PubMed

Manolov, Rumen; Losada, José L; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana

2016-01-01

Two-phase single-case designs, including baseline evaluation followed by an intervention, represent the most clinically straightforward option for combining professional practice and research. However, unless they are part of a multiple-baseline schedule, such designs do not allow demonstrating a causal relation between the intervention and the behavior. Although the statistical options reviewed here cannot help overcoming this methodological limitation, we aim to make practitioners and applied researchers aware of the available appropriate options for extracting maximum information from the data. In the current paper, we suggest that the evaluation of behavioral change should include visual and quantitative analyses, complementing the substantive criteria regarding the practical importance of the behavioral change. Specifically, we emphasize the need to use structured criteria for visual analysis, such as the ones summarized in the What Works Clearinghouse Standards, especially if such criteria are complemented by visual aids, as illustrated here. For quantitative analysis, we focus on the non-overlap of all pairs and the slope and level change procedure, as they offer straightforward information and have shown reasonable performance. An illustration is provided of the use of these three pieces of information: visual, quantitative, and substantive. To make the use of visual and quantitative analysis feasible, open source software is referred to and demonstrated. In order to provide practitioners and applied researchers with a more complete guide, several analytical alternatives are commented on pointing out the situations (aims, data patterns) for which these are potentially useful.

Analyzing Two-Phase Single-Case Data with Non-overlap and Mean Difference Indices: Illustration, Software Tools, and Alternatives

PubMed Central

Manolov, Rumen; Losada, José L.; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana

2016-01-01

Two-phase single-case designs, including baseline evaluation followed by an intervention, represent the most clinically straightforward option for combining professional practice and research. However, unless they are part of a multiple-baseline schedule, such designs do not allow demonstrating a causal relation between the intervention and the behavior. Although the statistical options reviewed here cannot help overcoming this methodological limitation, we aim to make practitioners and applied researchers aware of the available appropriate options for extracting maximum information from the data. In the current paper, we suggest that the evaluation of behavioral change should include visual and quantitative analyses, complementing the substantive criteria regarding the practical importance of the behavioral change. Specifically, we emphasize the need to use structured criteria for visual analysis, such as the ones summarized in the What Works Clearinghouse Standards, especially if such criteria are complemented by visual aids, as illustrated here. For quantitative analysis, we focus on the non-overlap of all pairs and the slope and level change procedure, as they offer straightforward information and have shown reasonable performance. An illustration is provided of the use of these three pieces of information: visual, quantitative, and substantive. To make the use of visual and quantitative analysis feasible, open source software is referred to and demonstrated. In order to provide practitioners and applied researchers with a more complete guide, several analytical alternatives are commented on pointing out the situations (aims, data patterns) for which these are potentially useful. PMID:26834691

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Quantitative contrast-enhanced ultrasound for monitoring vedolizumab therapy in inflammatory bowel disease patients: a pilot study.

PubMed

Goertz, Ruediger S; Klett, Daniel; Wildner, Dane; Atreya, Raja; Neurath, Markus F; Strobel, Deike

2018-01-01

Background Microvascularization of the bowel wall can be visualized and quantified non-invasively by software-assisted analysis of derived time-intensity curves. Purpose To perform software-based quantification of bowel wall perfusion using quantitative contrast-enhanced ultrasound (CEUS) according to clinical response in patients with inflammatory bowel disease treated with vedolizumab. Material and Methods In a prospective study, in 18 out of 34 patients, high-frequency ultrasound of bowel wall thickness using color Doppler flow combined with CEUS was performed at baseline and after 14 weeks of treatment with vedolizumab. Clinical activity scores at week 14 were used to differentiate between responders and non-responders. CEUS parameters were calculated by software analysis of the video loops. Results Nine of 18 patients (11 with Crohn's disease and seven with ulcerative colitis) showed response to treatment with vedolizumab. Overall, the responder group showed a significant decrease in the semi-quantitative color Doppler vascularization score. Amplitude-derived CEUS parameters of mural microvascularization such as peak enhancement or wash-in rate decreased in responders, in contrast with non-responders. Time-derived parameters remained stable or increased during treatment in all patients. Conclusion Analysis of bowel microvascularization by CEUS shows statistically significant changes in the wash-in-rate related to response of vedolizumab therapy.

Fast and simultaneous determination of 12 polyphenols in apple peel and pulp by using chemometrics-assisted high-performance liquid chromatography with diode array detection.

PubMed

Wang, Tong; Wu, Hai-Long; Xie, Li-Xia; Zhu, Li; Liu, Zhi; Sun, Xiao-Dong; Xiao, Rong; Yu, Ru-Qin

2017-04-01

In this work, a smart chemometrics-enhanced strategy, high-performance liquid chromatography, and diode array detection coupled with second-order calibration method based on alternating trilinear decomposition algorithm was proposed to simultaneously quantify 12 polyphenols in different kinds of apple peel and pulp samples. The proposed strategy proved to be a powerful tool to solve the problems of coelution, unknown interferences, and chromatographic shifts in the process of high-performance liquid chromatography analysis, making it possible for the determination of 12 polyphenols in complex apple matrices within 10 min under simple conditions of elution. The average recoveries with standard deviations, and figures of merit including sensitivity, selectivity, limit of detection, and limit of quantitation were calculated to validate the accuracy of the proposed method. Compared to the quantitative analysis results from the classic high-performance liquid chromatography method, the statistical and graphical analysis showed that our proposed strategy obtained more reliable results. All results indicated that our proposed method used in the quantitative analysis of apple polyphenols was an accurate, fast, universal, simple, and green one, and it was expected to be developed as an attractive alternative method for simultaneous determination of multitargeted analytes in complex matrices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Human Lymphatic Mesenteric Vessels: Morphology and Possible Function of Aminergic and NPY-ergic Nerve Fibers.

PubMed

D'Andrea, Vito; Panarese, Alessandra; Taurone, Samanta; Coppola, Luigi; Cavallotti, Carlo; Artico, Marco

2015-09-01

The lymphatic vessels have been studied in different organs from a morphological to a clinical point of view. Nevertheless, the knowledge of the catecholaminergic control of the lymphatic circulation is still incomplete. The aim of this work is to study the presence and distribution of the catecholaminergic and NPY-ergic nerve fibers in the whole wall of the human mesenteric lymphatic vessels in order to obtain knowledge about their morphology and functional significance. The following experimental procedures were performed: 1) drawing of tissue containing lymphatic vessels; 2) cutting of tissue; 3) staining of tissue; 4) staining of nerve fibers; 5) histofluorescence microscopy for the staining of catecholaminergic nerve fibers; 6) staining of neuropeptide Y like-immune reactivity; 7) biochemical assay of proteins; 8) measurement of noradrenaline; 9) quantitative analysis of images; 10) statistical analysis of data. Numerous nerve fibers run in the wall of lymphatic vessels. Many of them are catecholaminergic in nature. Some nerve fibers are NPY-positive. The biochemical results on noradrenaline amounts are in agreement with morphological results on catecholaminergic nerve fibers. Moreover, the morphometric results, obtained by the quantitative analysis of images and the subsequent statistical analysis of data, confirm all our morphological and biochemical data. The knowledge of the physiological or pathological mechanism regulating the functions of the lymphatic system is incomplete. Nevertheless the catecholaminergic nerve fibers of the human mesenteric lymphatic vessels come from the adrenergic periarterial plexuses of the mesenterial arterial bed. NPY-ergic nerve fibers may modulate the microcirculatory mesenterial bed in different pathological conditions.