Vitamin D and Depression: A Systematic Review and Meta-Analysis Comparing Studies with and without Biological Flaws

PubMed Central

Spedding, Simon

2014-01-01

Efficacy of Vitamin D supplements in depression is controversial, awaiting further literature analysis. Biological flaws in primary studies is a possible reason meta-analyses of Vitamin D have failed to demonstrate efficacy. This systematic review and meta-analysis of Vitamin D and depression compared studies with and without biological flaws. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was undertaken through four databases for randomized controlled trials (RCTs). Studies were critically appraised for methodological quality and biological flaws, in relation to the hypothesis and study design. Meta-analyses were performed for studies according to the presence of biological flaws. The 15 RCTs identified provide a more comprehensive evidence-base than previous systematic reviews; methodological quality of studies was generally good and methodology was diverse. A meta-analysis of all studies without flaws demonstrated a statistically significant improvement in depression with Vitamin D supplements (+0.78 CI +0.24, +1.27). Studies with biological flaws were mainly inconclusive, with the meta-analysis demonstrating a statistically significant worsening in depression by taking Vitamin D supplements (−1.1 CI −0.7, −1.5). Vitamin D supplementation (≥800 I.U. daily) was somewhat favorable in the management of depression in studies that demonstrate a change in vitamin levels, and the effect size was comparable to that of anti-depressant medication. PMID:24732019

Use of the Global Test Statistic as a Performance Measurement in a Reananlysis of Environmental Health Data

PubMed Central

Dymova, Natalya; Hanumara, R. Choudary; Gagnon, Ronald N.

2009-01-01

Performance measurement is increasingly viewed as an essential component of environmental and public health protection programs. In characterizing program performance over time, investigators often observe multiple changes resulting from a single intervention across a range of categories. Although a variety of statistical tools allow evaluation of data one variable at a time, the global test statistic is uniquely suited for analyses of categories or groups of interrelated variables. Here we demonstrate how the global test statistic can be applied to environmental and occupational health data for the purpose of making overall statements on the success of targeted intervention strategies. PMID:19696393

Use of the global test statistic as a performance measurement in a reanalysis of environmental health data.

PubMed

Dymova, Natalya; Hanumara, R Choudary; Enander, Richard T; Gagnon, Ronald N

2009-10-01

Performance measurement is increasingly viewed as an essential component of environmental and public health protection programs. In characterizing program performance over time, investigators often observe multiple changes resulting from a single intervention across a range of categories. Although a variety of statistical tools allow evaluation of data one variable at a time, the global test statistic is uniquely suited for analyses of categories or groups of interrelated variables. Here we demonstrate how the global test statistic can be applied to environmental and occupational health data for the purpose of making overall statements on the success of targeted intervention strategies.

The Extent and Consequences of P-Hacking in Science

PubMed Central

Head, Megan L.; Holman, Luke; Lanfear, Rob; Kahn, Andrew T.; Jennions, Michael D.

2015-01-01

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as “p-hacking,” occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably common, its effect seems to be weak relative to the real effect sizes being measured. This result suggests that p-hacking probably does not drastically alter scientific consensuses drawn from meta-analyses. PMID:25768323

Designing Intervention Studies: Selected Populations, Range Restrictions, and Statistical Power

PubMed Central

Miciak, Jeremy; Taylor, W. Pat; Stuebing, Karla K.; Fletcher, Jack M.; Vaughn, Sharon

2016-01-01

An appropriate estimate of statistical power is critical for the design of intervention studies. Although the inclusion of a pretest covariate in the test of the primary outcome can increase statistical power, samples selected on the basis of pretest performance may demonstrate range restriction on the selection measure and other correlated measures. This can result in attenuated pretest-posttest correlations, reducing the variance explained by the pretest covariate. We investigated the implications of two potential range restriction scenarios: direct truncation on a selection measure and indirect range restriction on correlated measures. Empirical and simulated data indicated direct range restriction on the pretest covariate greatly reduced statistical power and necessitated sample size increases of 82%–155% (dependent on selection criteria) to achieve equivalent statistical power to parameters with unrestricted samples. However, measures demonstrating indirect range restriction required much smaller sample size increases (32%–71%) under equivalent scenarios. Additional analyses manipulated the correlations between measures and pretest-posttest correlations to guide planning experiments. Results highlight the need to differentiate between selection measures and potential covariates and to investigate range restriction as a factor impacting statistical power. PMID:28479943

Designing Intervention Studies: Selected Populations, Range Restrictions, and Statistical Power.

PubMed

Miciak, Jeremy; Taylor, W Pat; Stuebing, Karla K; Fletcher, Jack M; Vaughn, Sharon

2016-01-01

An appropriate estimate of statistical power is critical for the design of intervention studies. Although the inclusion of a pretest covariate in the test of the primary outcome can increase statistical power, samples selected on the basis of pretest performance may demonstrate range restriction on the selection measure and other correlated measures. This can result in attenuated pretest-posttest correlations, reducing the variance explained by the pretest covariate. We investigated the implications of two potential range restriction scenarios: direct truncation on a selection measure and indirect range restriction on correlated measures. Empirical and simulated data indicated direct range restriction on the pretest covariate greatly reduced statistical power and necessitated sample size increases of 82%-155% (dependent on selection criteria) to achieve equivalent statistical power to parameters with unrestricted samples. However, measures demonstrating indirect range restriction required much smaller sample size increases (32%-71%) under equivalent scenarios. Additional analyses manipulated the correlations between measures and pretest-posttest correlations to guide planning experiments. Results highlight the need to differentiate between selection measures and potential covariates and to investigate range restriction as a factor impacting statistical power.

Spatial analyses for nonoverlapping objects with size variations and their application to coral communities.

PubMed

Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko

2014-07-01

Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Measuring the statistical validity of summary meta‐analysis and meta‐regression results for use in clinical practice

PubMed Central

Riley, Richard D.

2017-01-01

An important question for clinicians appraising a meta‐analysis is: are the findings likely to be valid in their own practice—does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity—where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple (‘leave‐one‐out’) cross‐validation technique, we demonstrate how we may test meta‐analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta‐analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta‐analysis and a tailored meta‐regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within‐study variance, between‐study variance, study sample size, and the number of studies in the meta‐analysis. Finally, we apply Vn to two published meta‐analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta‐analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28620945

Mediation analysis in nursing research: a methodological review

PubMed Central

Liu, Jianghong; Ulrich, Connie

2017-01-01

Mediation statistical models help clarify the relationship between independent predictor variables and dependent outcomes of interest by assessing the impact of third variables. This type of statistical analysis is applicable for many clinical nursing research questions, yet its use within nursing remains low. Indeed, mediational analyses may help nurse researchers develop more effective and accurate prevention and treatment programs as well as help bridge the gap between scientific knowledge and clinical practice. In addition, this statistical approach allows nurse researchers to ask – and answer – more meaningful and nuanced questions that extend beyond merely determining whether an outcome occurs. Therefore, the goal of this paper is to provide a brief tutorial on the use of mediational analyses in clinical nursing research by briefly introducing the technique and, through selected empirical examples from the nursing literature, demonstrating its applicability in advancing nursing science. PMID:26176804

permGPU: Using graphics processing units in RNA microarray association studies.

PubMed

Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros

2010-06-16

Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Advanced Behavioral Analyses Show that the Presence of Food Causes Subtle Changes in C. elegans Movement.

PubMed

Angstman, Nicholas B; Frank, Hans-Georg; Schmitz, Christoph

2016-01-01

As a widely used and studied model organism, Caenorhabditis elegans worms offer the ability to investigate implications of behavioral change. Although, investigation of C. elegans behavioral traits has been shown, analysis is often narrowed down to measurements based off a single point, and thus cannot pick up on subtle behavioral and morphological changes. In the present study videos were captured of four different C. elegans strains grown in liquid cultures and transferred to NGM-agar plates with an E. coli lawn or with no lawn. Using an advanced software, WormLab, the full skeleton and outline of worms were tracked to determine whether the presence of food affects behavioral traits. In all seven investigated parameters, statistically significant differences were found in worm behavior between those moving on NGM-agar plates with an E. coli lawn and NGM-agar plates with no lawn. Furthermore, multiple test groups showed differences in interaction between variables as the parameters that significantly correlated statistically with speed of locomotion varied. In the present study, we demonstrate the validity of a model to analyze C. elegans behavior beyond simple speed of locomotion. The need to account for a nested design while performing statistical analyses in similar studies is also demonstrated. With extended analyses, C. elegans behavioral change can be investigated with greater sensitivity, which could have wide utility in fields such as, but not limited to, toxicology, drug discovery, and RNAi screening.

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994

Influence of Family Structure on Health among Youths with Diabetes.

ERIC Educational Resources Information Center

Thompson, Sanna J.; Auslander, Wendy F.; White, Neil H.

2001-01-01

Discusses the extent to which family structure is significantly associated with health in youth with Type 1 diabetes. Multiple regression analyses demonstrated that family structure remains a significant predictor of youth's health when statistically controlling for race, child's age, family socioeconomic status, and adherence. (BF)

Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species.

PubMed

Huh, Iksoo; Wu, Xin; Park, Taesung; Yi, Soojin V

2017-07-21

DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation. © The Author 2017. Published by Oxford University Press.

Detection of semi-volatile organic compounds in permeable ...

EPA Pesticide Factsheets

Abstract The Edison Environmental Center (EEC) has a research and demonstration permeable parking lot comprised of three different permeable systems: permeable asphalt, porous concrete and interlocking concrete permeable pavers. Water quality and quantity analysis has been ongoing since January, 2010. This paper describes a subset of the water quality analysis, analysis of semivolatile organic compounds (SVOCs) to determine if hydrocarbons were in water infiltrated through the permeable surfaces. SVOCs were analyzed in samples collected from 11 dates over a 3 year period, from 2/8/2010 to 4/1/2013.Results are broadly divided into three categories: 42 chemicals were never detected; 12 chemicals (11 chemical test) were detected at a rate of less than 10% or less; and 22 chemicals were detected at a frequency of 10% or greater (ranging from 10% to 66.5% detections). Fundamental and exploratory statistical analyses were performed on these latter analyses results by grouping results by surface type. The statistical analyses were limited due to low frequency of detections and dilutions of samples which impacted detection limits. The infiltrate data through three permeable surfaces were analyzed as non-parametric data by the Kaplan-Meier estimation method for fundamental statistics; there were some statistically observable difference in concentration between pavement types when using Tarone-Ware Comparison Hypothesis Test. Additionally Spearman Rank order non-parame

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Identification of key micro-organisms involved in Douchi fermentation by statistical analysis and their use in an experimental fermentation.

PubMed

Chen, C; Xiang, J Y; Hu, W; Xie, Y B; Wang, T J; Cui, J W; Xu, Y; Liu, Z; Xiang, H; Xie, Q

2015-11-01

To screen and identify safe micro-organisms used during Douchi fermentation, and verify the feasibility of producing high-quality Douchi using these identified micro-organisms. PCR-denaturing gradient gel electrophoresis (DGGE) and automatic amino-acid analyser were used to investigate the microbial diversity and free amino acids (FAAs) content of 10 commercial Douchi samples. The correlations between microbial communities and FAAs were analysed by statistical analysis. Ten strains with significant positive correlation were identified. Then an experiment on Douchi fermentation by identified strains was carried out, and the nutritional composition in Douchi was analysed. Results showed that FAAs and relative content of isoflavone aglycones in verification Douchi samples were generally higher than those in commercial Douchi samples. Our study indicated that fungi, yeasts, Bacillus and lactic acid bacteria were the key players in Douchi fermentation, and with identified probiotic micro-organisms participating in fermentation, a higher quality Douchi product was produced. This is the first report to analyse and confirm the key micro-organisms during Douchi fermentation by statistical analysis. This work proves fermentation micro-organisms to be the key influencing factor of Douchi quality, and demonstrates the feasibility of fermenting Douchi using identified starter micro-organisms. © 2015 The Society for Applied Microbiology.

Single-Level and Multilevel Mediation Analysis

ERIC Educational Resources Information Center

Tofighi, Davood; Thoemmes, Felix

2014-01-01

Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

Benefits of a one health approach: An example using Rift Valley fever.

PubMed

Rostal, Melinda K; Ross, Noam; Machalaba, Catherine; Cordel, Claudia; Paweska, Janusz T; Karesh, William B

2018-06-01

One Health has been promoted by international institutions as a framework to improve public health outcomes. Despite strong overall interest in One Health, country-, local- and project-level implementation remains limited, likely due to the lack of pragmatic and tested operational methods for implementation and metrics for evaluation. Here we use Rift Valley fever virus as an example to demonstrate the value of using a One Health approach for both scientific and resources advantages. We demonstrate that coordinated, a priori investigations between One Health sectors can yield higher statistical power to elucidate important public health relationships as compared to siloed investigations and post-hoc analyses. Likewise, we demonstrate that across a project or multi-ministry health study a One Health approach can result in improved resource efficiency, with resultant cost-savings (35% in the presented case). The results of these analyses demonstrate that One Health approaches can be directly and tangibly applied to health investigations.

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.

Evaluation and application of summary statistic imputation to discover new height-associated loci.

PubMed

Rüeger, Sina; McDaid, Aaron; Kutalik, Zoltán

2018-05-01

As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian randomisation or LD-score regression.

Evaluation and application of summary statistic imputation to discover new height-associated loci

PubMed Central

2018-01-01

As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian randomisation or LD-score regression. PMID:29782485

Regional analyses of labor markets and demography: a model based Norwegian example.

PubMed

Stambol, L S; Stolen, N M; Avitsland, T

1998-01-01

The authors discuss the regional REGARD model, developed by Statistics Norway to analyze the regional implications of macroeconomic development of employment, labor force, and unemployment. "In building the model, empirical analyses of regional producer behavior in manufacturing industries have been performed, and the relation between labor market development and regional migration has been investigated. Apart from providing a short description of the REGARD model, this article demonstrates the functioning of the model, and presents some results of an application." excerpt

Coordinate based random effect size meta-analysis of neuroimaging studies.

PubMed

Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J

2017-06-01

Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.

[Triple-type theory of statistics and its application in the scientific research of biomedicine].

PubMed

Hu, Liang-ping; Liu, Hui-gang

2005-07-20

To point out the crux of why so many people failed to grasp statistics and to bring forth a "triple-type theory of statistics" to solve the problem in a creative way. Based on the experience in long-time teaching and research in statistics, the "three-type theory" was raised and clarified. Examples were provided to demonstrate that the 3 types, i.e., expressive type, prototype and the standardized type are the essentials for people to apply statistics rationally both in theory and practice, and moreover, it is demonstrated by some instances that the "three types" are correlated with each other. It can help people to see the essence by interpreting and analyzing the problems of experimental designs and statistical analyses in medical research work. Investigations reveal that for some questions, the three types are mutually identical; for some questions, the prototype is their standardized type; however, for some others, the three types are distinct from each other. It has been shown that in some multifactor experimental researches, it leads to the nonexistence of the standardized type corresponding to the prototype at all, because some researchers have committed the mistake of "incomplete control" in setting experimental groups. This is a problem which should be solved by the concept and method of "division". Once the "triple-type" for each question is clarified, a proper experimental design and statistical method can be carried out easily. "Triple-type theory of statistics" can help people to avoid committing statistical mistakes or at least to decrease the misuse rate dramatically and improve the quality, level and speed of biomedical research during the process of applying statistics. It can also help people to improve the quality of statistical textbooks and the teaching effect of statistics and it has demonstrated how to advance biomedical statistics.

Four modes of optical parametric operation for squeezed state generation

NASA Astrophysics Data System (ADS)

Andersen, U. L.; Buchler, B. C.; Lam, P. K.; Wu, J. W.; Gao, J. R.; Bachor, H.-A.

2003-11-01

We report a versatile instrument, based on a monolithic optical parametric amplifier, which reliably generates four different types of squeezed light. We obtained vacuum squeezing, low power amplitude squeezing, phase squeezing and bright amplitude squeezing. We show a complete analysis of this light, including a full quantum state tomography. In addition we demonstrate the direct detection of the squeezed state statistics without the aid of a spectrum analyser. This technique makes the nonclassical properties directly visible and allows complete measurement of the statistical moments of the squeezed quadrature.

[In-house team seminars: working together as a team--from data and statistics to quality development].

PubMed

Berlage, Silvia; Wenzlaff, Paul; Damm, Gabriele; Sens, Brigitte

2010-01-01

The concept of the "ZQ In-house Seminars" provided by external trainers/experts pursues the specific aim to enable all healthcare staff members of hospital departments to analyse statistical data--especially from external quality measurements--and to initiate in-hospital measures of quality improvement based on structured team work. The results of an evaluation in Lower Saxony for the period between 2004 and 2008 demonstrate a sustainable increase in outcome quality of care and a strengthening of team and process orientation in clinical care.

Analysis and meta-analysis of single-case designs: an introduction.

PubMed

Shadish, William R

2014-04-01

The last 10 years have seen great progress in the analysis and meta-analysis of single-case designs (SCDs). This special issue includes five articles that provide an overview of current work on that topic, including standardized mean difference statistics, multilevel models, Bayesian statistics, and generalized additive models. Each article analyzes a common example across articles and presents syntax or macros for how to do them. These articles are followed by commentaries from single-case design researchers and journal editors. This introduction briefly describes each article and then discusses several issues that must be addressed before we can know what analyses will eventually be best to use in SCD research. These issues include modeling trend, modeling error covariances, computing standardized effect size estimates, assessing statistical power, incorporating more accurate models of outcome distributions, exploring whether Bayesian statistics can improve estimation given the small samples common in SCDs, and the need for annotated syntax and graphical user interfaces that make complex statistics accessible to SCD researchers. The article then discusses reasons why SCD researchers are likely to incorporate statistical analyses into their research more often in the future, including changing expectations and contingencies regarding SCD research from outside SCD communities, changes and diversity within SCD communities, corrections of erroneous beliefs about the relationship between SCD research and statistics, and demonstrations of how statistics can help SCD researchers better meet their goals. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Fast and accurate imputation of summary statistics enhances evidence of functional enrichment

PubMed Central

Pasaniuc, Bogdan; Zaitlen, Noah; Shi, Huwenbo; Bhatia, Gaurav; Gusev, Alexander; Pickrell, Joseph; Hirschhorn, Joel; Strachan, David P.; Patterson, Nick; Price, Alkes L.

2014-01-01

Motivation: Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis. Existing hidden Markov models (HMM)-based imputation approaches require individual-level genotypes. Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available. Results: In simulations using 1000 Genomes (1000G) data, this method recovers 84% (54%) of the effective sample size for common (>5%) and low-frequency (1–5%) variants [increasing to 87% (60%) when summary linkage disequilibrium information is available from target samples] versus the gold standard of 89% (67%) for HMM-based imputation, which cannot be applied to summary statistics. Our approach accounts for the limited sample size of the reference panel, a crucial step to eliminate false-positive associations, and it is computationally very fast. As an empirical demonstration, we apply our method to seven case–control phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) data and a study of height in the British 1958 birth cohort (1958BC). Gaussian imputation from summary statistics recovers 95% (105%) of the effective sample size (as quantified by the ratio of χ2 association statistics) compared with HMM-based imputation from individual-level genotypes at the 227 (176) published single nucleotide polymorphisms (SNPs) in the WTCCC (1958BC height) data. In addition, for publicly available summary statistics from large meta-analyses of four lipid traits, we publicly release imputed summary statistics at 1000G SNPs, which could not have been obtained using previously published methods, and demonstrate their accuracy by masking subsets of the data. We show that 1000G imputation using our approach increases the magnitude and statistical evidence of enrichment at genic versus non-genic loci for these traits, as compared with an analysis without 1000G imputation. Thus, imputation of summary statistics will be a valuable tool in future functional enrichment analyses. Availability and implementation: Publicly available software package available at http://bogdan.bioinformatics.ucla.edu/software/. Contact: bpasaniuc@mednet.ucla.edu or aprice@hsph.harvard.edu Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:24990607

Quantum behaviour of pumped and damped triangular Bose-Hubbard systems

NASA Astrophysics Data System (ADS)

Chianca, C. V.; Olsen, M. K.

2017-12-01

We propose and analyse analogs of optical cavities for atoms using three-well Bose-Hubbard models with pumping and losses. We consider triangular configurations. With one well pumped and one damped, we find that both the mean-field dynamics and the quantum statistics show a quantitative dependence on the choice of damped well. The systems we analyse remain far from equilibrium, preserving good coherence between the wells in the steady-state. We find quadrature squeezing and mode entanglement for some parameter regimes and demonstrate that the trimer with pumping and damping at the same well is the stronger option for producing non-classical states. Due to recent experimental advances, it should be possible to demonstrate the effects we investigate and predict.

Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling

PubMed Central

Wood, John

2017-01-01

Recently, evidence for endemically low statistical power has cast neuroscience findings into doubt. If low statistical power plagues neuroscience, then this reduces confidence in the reported effects. However, if statistical power is not uniformly low, then such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analyzing data from an influential study reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modeling, that the sample of 730 studies included in that analysis comprises several subcomponents so the use of a single summary statistic is insufficient to characterize the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Therefore, whereas power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem. SIGNIFICANCE STATEMENT Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered—some very seriously so—but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience. This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research. PMID:28706080

Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

PubMed

Shek, Daniel T L; Ma, Cecilia M S

2011-01-05

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

PubMed Central

Shek, Daniel T. L.; Ma, Cecilia M. S.

2011-01-01

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented. PMID:21218263

Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial

PubMed Central

Hallgren, Kevin A.

2012-01-01

Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen’s kappa and intra-class correlations to assess IRR. PMID:22833776

Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

PubMed

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard

2017-11-01

Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.

The determinants of bond angle variability in protein/peptide backbones: A comprehensive statistical/quantum mechanics analysis.

PubMed

Improta, Roberto; Vitagliano, Luigi; Esposito, Luciana

2015-11-01

The elucidation of the mutual influence between peptide bond geometry and local conformation has important implications for protein structure refinement, validation, and prediction. To gain insights into the structural determinants and the energetic contributions associated with protein/peptide backbone plasticity, we here report an extensive analysis of the variability of the peptide bond angles by combining statistical analyses of protein structures and quantum mechanics calculations on small model peptide systems. Our analyses demonstrate that all the backbone bond angles strongly depend on the peptide conformation and unveil the existence of regular trends as function of ψ and/or φ. The excellent agreement of the quantum mechanics calculations with the statistical surveys of protein structures validates the computational scheme here employed and demonstrates that the valence geometry of protein/peptide backbone is primarily dictated by local interactions. Notably, for the first time we show that the position of the H(α) hydrogen atom, which is an important parameter in NMR structural studies, is also dependent on the local conformation. Most of the trends observed may be satisfactorily explained by invoking steric repulsive interactions; in some specific cases the valence bond variability is also influenced by hydrogen-bond like interactions. Moreover, we can provide a reliable estimate of the energies involved in the interplay between geometry and conformations. © 2015 Wiley Periodicals, Inc.

Overweight, but not obesity, paradox on mortality following coronary artery bypass grafting.

PubMed

Takagi, Hisato; Umemoto, Takuya

2016-09-01

To determine whether an "obesity paradox" on post-coronary artery bypass grafting (CABG) mortality exists, we abstracted exclusively adjusted odds ratios (ORs) and/or hazard ratios (HRs) for mortality from each study, and then combined them in a meta-analysis. MEDLINE and EMBASE were searched through April 2015 using PubMed and OVID, to identify comparative studies, of overweight or obese versus normal weight patients undergoing CABG, reporting adjusted relative risk estimates for short-term (30-day or in-hospital) and/or mid-to-long-term all-cause mortality. Our search identified 14 eligible studies. In total our meta-analysis included data on 79,140 patients undergoing CABG. Pooled analyses in short-term mortality demonstrated that overweight was associated with a statistically significant 15% reduction relative to normal weight (OR, 0.85; 95% confidence interval [CI], 0.74-0.98; p=0.03) and no statistically significant differences between mild obesity, moderate/severe obesity, or overall obesity and normal weight. Pooled analyses in mid-to-long-term mortality demonstrated that overweight was associated with a statistically significant 10% reduction relative to normal weight (HR, 0.90; 95% CI, 0.84 to 0.96; p=0.001); and no statistically significant differences between mild obesity, moderate/severe obesity, or overall obesity and normal weight. Overweight, but not obesity, may be associated with better short-term and mid-to-long-term post-CABG survival relative to normal weight. An overweight, but not obesity, paradox on post-CABG mortality appears to exist. Copyright © 2015 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Euclidean distance can identify the mannitol level that produces the most remarkable integral effect on sugarcane micropropagation in temporary immersion bioreactors.

PubMed

Gómez, Daviel; Hernández, L Ázaro; Yabor, Lourdes; Beemster, Gerrit T S; Tebbe, Christoph C; Papenbrock, Jutta; Lorenzo, José Carlos

2018-03-15

Plant scientists usually record several indicators in their abiotic factor experiments. The common statistical management involves univariate analyses. Such analyses generally create a split picture of the effects of experimental treatments since each indicator is addressed independently. The Euclidean distance combined with the information of the control treatment could have potential as an integrating indicator. The Euclidean distance has demonstrated its usefulness in many scientific fields but, as far as we know, it has not yet been employed for plant experimental analyses. To exemplify the use of the Euclidean distance in this field, we performed an experiment focused on the effects of mannitol on sugarcane micropropagation in temporary immersion bioreactors. Five mannitol concentrations were compared: 0, 50, 100, 150 and 200 mM. As dependent variables we recorded shoot multiplication rate, fresh weight, and levels of aldehydes, chlorophylls, carotenoids and phenolics. The statistical protocol which we then carried out integrated all dependent variables to easily identify the mannitol concentration that produced the most remarkable integral effect. Results provided by the Euclidean distance demonstrate a gradually increasing distance from the control in function of increasing mannitol concentrations. 200 mM mannitol caused the most significant alteration of sugarcane biochemistry and physiology under the experimental conditions described here. This treatment showed the longest statistically significant Euclidean distance to the control treatment (2.38). In contrast, 50 and 100 mM mannitol showed the lowest Euclidean distances (0.61 and 0.84, respectively) and thus poor integrated effects of mannitol. The analysis shown here indicates that the use of the Euclidean distance can contribute to establishing a more integrated evaluation of the contrasting mannitol treatments.

Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change

PubMed Central

Storlie, Collin; Merino-Viteri, Andres; Phillips, Ben; VanDerWal, Jeremy; Welbergen, Justin; Williams, Stephen

2014-01-01

To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km2 study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes. PMID:25252835

Statistical summaries of fatigue data for design purposes

NASA Technical Reports Server (NTRS)

Wirsching, P. H.

1983-01-01

Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.

How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

PubMed

West, Brady T; Sakshaug, Joseph W; Aurelien, Guy Alain S

2016-01-01

Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT), which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data.

How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

PubMed Central

West, Brady T.; Sakshaug, Joseph W.; Aurelien, Guy Alain S.

2016-01-01

Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT), which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data. PMID:27355817

Improving phylogenetic analyses by incorporating additional information from genetic sequence databases.

PubMed

Liang, Li-Jung; Weiss, Robert E; Redelings, Benjamin; Suchard, Marc A

2009-10-01

Statistical analyses of phylogenetic data culminate in uncertain estimates of underlying model parameters. Lack of additional data hinders the ability to reduce this uncertainty, as the original phylogenetic dataset is often complete, containing the entire gene or genome information available for the given set of taxa. Informative priors in a Bayesian analysis can reduce posterior uncertainty; however, publicly available phylogenetic software specifies vague priors for model parameters by default. We build objective and informative priors using hierarchical random effect models that combine additional datasets whose parameters are not of direct interest but are similar to the analysis of interest. We propose principled statistical methods that permit more precise parameter estimates in phylogenetic analyses by creating informative priors for parameters of interest. Using additional sequence datasets from our lab or public databases, we construct a fully Bayesian semiparametric hierarchical model to combine datasets. A dynamic iteratively reweighted Markov chain Monte Carlo algorithm conveniently recycles posterior samples from the individual analyses. We demonstrate the value of our approach by examining the insertion-deletion (indel) process in the enolase gene across the Tree of Life using the phylogenetic software BALI-PHY; we incorporate prior information about indels from 82 curated alignments downloaded from the BAliBASE database.

An add-in implementation of the RESAMPLING syntax under Microsoft EXCEL.

PubMed

Meineke, I

2000-10-01

The RESAMPLING syntax defines a set of powerful commands, which allow the programming of probabilistic statistical models with few, easily memorized statements. This paper presents an implementation of the RESAMPLING syntax using Microsoft EXCEL with Microsoft WINDOWS(R) as a platform. Two examples are given to demonstrate typical applications of RESAMPLING in biomedicine. Details of the implementation with special emphasis on the programming environment are discussed at length. The add-in is available electronically to interested readers upon request. The use of the add-in facilitates numerical statistical analyses of data from within EXCEL in a comfortable way.

Ten Facts about Tuition at Independent Colleges and Universities. A Report from the National Association of Independent Colleges and Universities.

ERIC Educational Resources Information Center

National Association of Independent Colleges and Universities, Washington, DC.

This report seeks to explain the complex relationship between "cost" and "price" at independent private colleges and universities, and to demonstrate that federal student financial aid does not contribute to tuition and fee increases at such institutions. To support these results, 10 facts, drawn from multivariate statistical analyses of data from…

Reporting Point and Interval Estimates of Effect-Size for Planned Contrasts: Fixed within Effect Analyses of Variance

ERIC Educational Resources Information Center

Robey, Randall R.

2004-01-01

The purpose of this tutorial is threefold: (a) review the state of statistical science regarding effect-sizes, (b) illustrate the importance of effect-sizes for interpreting findings in all forms of research and particularly for results of clinical-outcome research, and (c) demonstrate just how easily a criterion on reporting effect-sizes in…

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

PubMed

Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

2016-01-01

Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation.

PubMed

Yang, Harry; Novick, Steven; Burdick, Richard K

Analytical similarity is the foundation for demonstration of biosimilarity between a proposed product and a reference product. For this assessment, currently the U.S. Food and Drug Administration (FDA) recommends a tiered system in which quality attributes are categorized into three tiers commensurate with their risk and approaches of varying statistical rigor are subsequently used for the three-tier quality attributes. Key to the analyses of Tiers 1 and 2 quality attributes is the establishment of equivalence acceptance criterion and quality range. For particular licensure applications, the FDA has provided advice on statistical methods for demonstration of analytical similarity. For example, for Tier 1 assessment, an equivalence test can be used based on an equivalence margin of 1.5 σ R , where σ R is the reference product variability estimated by the sample standard deviation S R from a sample of reference lots. The quality range for demonstrating Tier 2 analytical similarity is of the form X̄ R ± K × σ R where the constant K is appropriately justified. To demonstrate Tier 2 analytical similarity, a large percentage (e.g., 90%) of test product must fall in the quality range. In this paper, through both theoretical derivations and simulations, we show that when the reference drug product lots are correlated, the sample standard deviation S R underestimates the true reference product variability σ R As a result, substituting S R for σ R in the Tier 1 equivalence acceptance criterion and the Tier 2 quality range inappropriately reduces the statistical power and the ability to declare analytical similarity. Also explored is the impact of correlation among drug product lots on Type I error rate and power. Three methods based on generalized pivotal quantities are introduced, and their performance is compared against a two-one-sided tests (TOST) approach. Finally, strategies to mitigate risk of correlation among the reference products lots are discussed. A biosimilar is a generic version of the original biological drug product. A key component of a biosimilar development is the demonstration of analytical similarity between the biosimilar and the reference product. Such demonstration relies on application of statistical methods to establish a similarity margin and appropriate test for equivalence between the two products. This paper discusses statistical issues with demonstration of analytical similarity and provides alternate approaches to potentially mitigate these problems. © PDA, Inc. 2016.

Fast and accurate imputation of summary statistics enhances evidence of functional enrichment.

PubMed

Pasaniuc, Bogdan; Zaitlen, Noah; Shi, Huwenbo; Bhatia, Gaurav; Gusev, Alexander; Pickrell, Joseph; Hirschhorn, Joel; Strachan, David P; Patterson, Nick; Price, Alkes L

2014-10-15

Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis. Existing hidden Markov models (HMM)-based imputation approaches require individual-level genotypes. Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available. In simulations using 1000 Genomes (1000G) data, this method recovers 84% (54%) of the effective sample size for common (>5%) and low-frequency (1-5%) variants [increasing to 87% (60%) when summary linkage disequilibrium information is available from target samples] versus the gold standard of 89% (67%) for HMM-based imputation, which cannot be applied to summary statistics. Our approach accounts for the limited sample size of the reference panel, a crucial step to eliminate false-positive associations, and it is computationally very fast. As an empirical demonstration, we apply our method to seven case-control phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) data and a study of height in the British 1958 birth cohort (1958BC). Gaussian imputation from summary statistics recovers 95% (105%) of the effective sample size (as quantified by the ratio of [Formula: see text] association statistics) compared with HMM-based imputation from individual-level genotypes at the 227 (176) published single nucleotide polymorphisms (SNPs) in the WTCCC (1958BC height) data. In addition, for publicly available summary statistics from large meta-analyses of four lipid traits, we publicly release imputed summary statistics at 1000G SNPs, which could not have been obtained using previously published methods, and demonstrate their accuracy by masking subsets of the data. We show that 1000G imputation using our approach increases the magnitude and statistical evidence of enrichment at genic versus non-genic loci for these traits, as compared with an analysis without 1000G imputation. Thus, imputation of summary statistics will be a valuable tool in future functional enrichment analyses. Publicly available software package available at http://bogdan.bioinformatics.ucla.edu/software/. bpasaniuc@mednet.ucla.edu or aprice@hsph.harvard.edu Supplementary materials are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Across-cohort QC analyses of GWAS summary statistics from complex traits.

PubMed

Chen, Guo-Bo; Lee, Sang Hong; Robinson, Matthew R; Trzaskowski, Maciej; Zhu, Zhi-Xiang; Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Kutalik, Zoltán; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Yang, Jian; Wray, Naomi R; Visscher, Peter M

2016-01-01

Genome-wide association studies (GWASs) have been successful in discovering SNP trait associations for many quantitative traits and common diseases. Typically, the effect sizes of SNP alleles are very small and this requires large genome-wide association meta-analyses (GWAMAs) to maximize statistical power. A trend towards ever-larger GWAMA is likely to continue, yet dealing with summary statistics from hundreds of cohorts increases logistical and quality control problems, including unknown sample overlap, and these can lead to both false positive and false negative findings. In this study, we propose four metrics and visualization tools for GWAMA, using summary statistics from cohort-level GWASs. We propose methods to examine the concordance between demographic information, and summary statistics and methods to investigate sample overlap. (I) We use the population genetics F st statistic to verify the genetic origin of each cohort and their geographic location, and demonstrate using GWAMA data from the GIANT Consortium that geographic locations of cohorts can be recovered and outlier cohorts can be detected. (II) We conduct principal component analysis based on reported allele frequencies, and are able to recover the ancestral information for each cohort. (III) We propose a new statistic that uses the reported allelic effect sizes and their standard errors to identify significant sample overlap or heterogeneity between pairs of cohorts. (IV) To quantify unknown sample overlap across all pairs of cohorts, we propose a method that uses randomly generated genetic predictors that does not require the sharing of individual-level genotype data and does not breach individual privacy.

Across-cohort QC analyses of GWAS summary statistics from complex traits

PubMed Central

Chen, Guo-Bo; Lee, Sang Hong; Robinson, Matthew R; Trzaskowski, Maciej; Zhu, Zhi-Xiang; Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Kutalik, Zoltán; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Yang, Jian; Wray, Naomi R; Visscher, Peter M

2017-01-01

Genome-wide association studies (GWASs) have been successful in discovering SNP trait associations for many quantitative traits and common diseases. Typically, the effect sizes of SNP alleles are very small and this requires large genome-wide association meta-analyses (GWAMAs) to maximize statistical power. A trend towards ever-larger GWAMA is likely to continue, yet dealing with summary statistics from hundreds of cohorts increases logistical and quality control problems, including unknown sample overlap, and these can lead to both false positive and false negative findings. In this study, we propose four metrics and visualization tools for GWAMA, using summary statistics from cohort-level GWASs. We propose methods to examine the concordance between demographic information, and summary statistics and methods to investigate sample overlap. (I) We use the population genetics Fst statistic to verify the genetic origin of each cohort and their geographic location, and demonstrate using GWAMA data from the GIANT Consortium that geographic locations of cohorts can be recovered and outlier cohorts can be detected. (II) We conduct principal component analysis based on reported allele frequencies, and are able to recover the ancestral information for each cohort. (III) We propose a new statistic that uses the reported allelic effect sizes and their standard errors to identify significant sample overlap or heterogeneity between pairs of cohorts. (IV) To quantify unknown sample overlap across all pairs of cohorts, we propose a method that uses randomly generated genetic predictors that does not require the sharing of individual-level genotype data and does not breach individual privacy. PMID:27552965

Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling.

PubMed

Nord, Camilla L; Valton, Vincent; Wood, John; Roiser, Jonathan P

2017-08-23

Recently, evidence for endemically low statistical power has cast neuroscience findings into doubt. If low statistical power plagues neuroscience, then this reduces confidence in the reported effects. However, if statistical power is not uniformly low, then such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analyzing data from an influential study reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modeling, that the sample of 730 studies included in that analysis comprises several subcomponents so the use of a single summary statistic is insufficient to characterize the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Therefore, whereas power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem. SIGNIFICANCE STATEMENT Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered-some very seriously so-but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience. This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research. Copyright © 2017 Nord, Valton et al.

Statistical universals reveal the structures and functions of human music.

PubMed

Savage, Patrick E; Brown, Steven; Sakai, Emi; Currie, Thomas E

2015-07-21

Music has been called "the universal language of mankind." Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation.

Statistical universals reveal the structures and functions of human music

PubMed Central

Savage, Patrick E.; Brown, Steven; Sakai, Emi; Currie, Thomas E.

2015-01-01

Music has been called “the universal language of mankind.” Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation. PMID:26124105

Statistics for NAEG: past efforts, new results, and future plans

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

Gilbert, R.O.; Simpson, J.C.; Kinnison, R.R.

A brief review of Nevada Applied Ecology Group (NAEG) objectives is followed by a summary of past statistical analyses conducted by Pacific Northwest Laboratory for the NAEG. Estimates of spatial pattern of radionuclides and other statistical analyses at NS's 201, 219 and 221 are reviewed as background for new analyses presented in this paper. Suggested NAEG activities and statistical analyses needed for the projected termination date of NAEG studies in March 1986 are given.

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework

NASA Astrophysics Data System (ADS)

Rubin, D.; Aldering, G.; Barbary, K.; Boone, K.; Chappell, G.; Currie, M.; Deustua, S.; Fagrelius, P.; Fruchter, A.; Hayden, B.; Lidman, C.; Nordin, J.; Perlmutter, S.; Saunders, C.; Sofiatti, C.; Supernova Cosmology Project, The

2015-11-01

While recent supernova (SN) cosmology research has benefited from improved measurements, current analysis approaches are not statistically optimal and will prove insufficient for future surveys. This paper discusses the limitations of current SN cosmological analyses in treating outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations. We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects. We apply the framework to real SN observations and demonstrate smaller statistical and systematic uncertainties. We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way. This analysis was primarily performed blinded, in that the basic framework was first validated on simulated data before transitioning to real data. We also discuss possible extensions of the method.

Identification of natural images and computer-generated graphics based on statistical and textural features.

PubMed

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: a primer and applications.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E

2014-04-01

This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Dynamic properties of small-scale solar wind plasma fluctuations.

PubMed

Riazantseva, M O; Budaev, V P; Zelenyi, L M; Zastenker, G N; Pavlos, G P; Safrankova, J; Nemecek, Z; Prech, L; Nemec, F

2015-05-13

The paper presents the latest results of the studies of small-scale fluctuations in a turbulent flow of solar wind (SW) using measurements with extremely high temporal resolution (up to 0.03 s) of the bright monitor of SW (BMSW) plasma spectrometer operating on astrophysical SPECTR-R spacecraft at distances up to 350,000 km from the Earth. The spectra of SW ion flux fluctuations in the range of scales between 0.03 and 100 s are systematically analysed. The difference of slopes in low- and high-frequency parts of spectra and the frequency of the break point between these two characteristic slopes was analysed for different conditions in the SW. The statistical properties of the SW ion flux fluctuations were thoroughly analysed on scales less than 10 s. A high level of intermittency is demonstrated. The extended self-similarity of SW ion flux turbulent flow is constantly observed. The approximation of non-Gaussian probability distribution function of ion flux fluctuations by the Tsallis statistics shows the non-extensive character of SW fluctuations. Statistical characteristics of ion flux fluctuations are compared with the predictions of a log-Poisson model. The log-Poisson parametrization of the structure function scaling has shown that well-defined filament-like plasma structures are, as a rule, observed in the turbulent SW flows. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Predictors of workplace violence among female sex workers in Tijuana, Mexico.

PubMed

Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa

2015-05-01

For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.

Human-modified temperatures induce species changes: Joint attribution.

PubMed

Root, Terry L; MacMynowski, Dena P; Mastrandrea, Michael D; Schneider, Stephen H

2005-05-24

Average global surface-air temperature is increasing. Contention exists over relative contributions by natural and anthropogenic forcings. Ecological studies attribute plant and animal changes to observed warming. Until now, temperature-species connections have not been statistically attributed directly to anthropogenic climatic change. Using modeled climatic variables and observed species data, which are independent of thermometer records and paleoclimatic proxies, we demonstrate statistically significant "joint attribution," a two-step linkage: human activities contribute significantly to temperature changes and human-changed temperatures are associated with discernible changes in plant and animal traits. Additionally, our analyses provide independent testing of grid-box-scale temperature projections from a general circulation model (HadCM3).

Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change.

PubMed

Storlie, Collin; Merino-Viteri, Andres; Phillips, Ben; VanDerWal, Jeremy; Welbergen, Justin; Williams, Stephen

2014-09-01

To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km(2) study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model.

PubMed

Ng'andu, N H

1997-03-30

In the analysis of survival data using the Cox proportional hazard (PH) model, it is important to verify that the explanatory variables analysed satisfy the proportional hazard assumption of the model. This paper presents results of a simulation study that compares five test statistics to check the proportional hazard assumption of Cox's model. The test statistics were evaluated under proportional hazards and the following types of departures from the proportional hazard assumption: increasing relative hazards; decreasing relative hazards; crossing hazards; diverging hazards, and non-monotonic hazards. The test statistics compared include those based on partitioning of failure time and those that do not require partitioning of failure time. The simulation results demonstrate that the time-dependent covariate test, the weighted residuals score test and the linear correlation test have equally good power for detection of non-proportionality in the varieties of non-proportional hazards studied. Using illustrative data from the literature, these test statistics performed similarly.

Improving surveillance for injuries associated with potential motor vehicle safety defects

PubMed Central

Whitfield, R; Whitfield, A

2004-01-01

Objective: To improve surveillance for deaths and injuries associated with potential motor vehicle safety defects. Design: Vehicles in fatal crashes can be studied for indications of potential defects using an "early warning" surveillance statistic previously suggested for screening reports of adverse drug reactions. This statistic is illustrated with time series data for fatal, tire related and fire related crashes. Geographic analyses are used to augment the tire related statistics. Results: A statistical criterion based on the Poisson distribution that tests the likelihood of an expected number of events, given the number of events that actually occurred, is a promising method that can be readily adapted for use in injury surveillance. Conclusions: Use of the demonstrated techniques could have helped to avert a well known injury surveillance failure. This method is adaptable to aid in the direction of engineering and statistical reviews to prevent deaths and injuries associated with potential motor vehicle safety defects using available databases. PMID:15066972

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

PubMed Central

Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

2016-01-01

Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

Contour plot assessment of existing meta-analyses confirms robust association of statin use and acute kidney injury risk.

PubMed

Chevance, Aurélie; Schuster, Tibor; Steele, Russell; Ternès, Nils; Platt, Robert W

2015-10-01

Robustness of an existing meta-analysis can justify decisions on whether to conduct an additional study addressing the same research question. We illustrate the graphical assessment of the potential impact of an additional study on an existing meta-analysis using published data on statin use and the risk of acute kidney injury. A previously proposed graphical augmentation approach is used to assess the sensitivity of the current test and heterogeneity statistics extracted from existing meta-analysis data. In addition, we extended the graphical augmentation approach to assess potential changes in the pooled effect estimate after updating a current meta-analysis and applied the three graphical contour definitions to data from meta-analyses on statin use and acute kidney injury risk. In the considered example data, the pooled effect estimates and heterogeneity indices demonstrated to be considerably robust to the addition of a future study. Supportingly, for some previously inconclusive meta-analyses, a study update might yield statistically significant kidney injury risk increase associated with higher statin exposure. The illustrated contour approach should become a standard tool for the assessment of the robustness of meta-analyses. It can guide decisions on whether to conduct additional studies addressing a relevant research question. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of the Medicare Alzheimer's Disease Demonstration on Medicare Expenditures

PubMed Central

Newcomer, Robert; Miller, Robert; Clay, Ted; Fox, Patrick

1999-01-01

Applicants were randomized either into a group with a limited Medicare community care service benefit and case management or into a control group receiving their regular medical care. Analyses assess whether or not community care management affected health care use. A tendency toward reduced expenditures was observed for the treatment group, combining all demonstration sites, and when observing each separately. These differences were or approached statistical significance in two sites for Medicare Part A and Parts A and B expenditures averaged over 3 years. Expenditure reductions approached budget neutrality with program costs in two sites. PMID:11482124

Statistical Approaches to Adjusting Weights for Dependent Arms in Network Meta-analysis.

PubMed

Su, Yu-Xuan; Tu, Yu-Kang

2018-05-22

Network meta-analysis compares multiple treatments in terms of their efficacy and harm by including evidence from randomized controlled trials. Most clinical trials use parallel design, where patients are randomly allocated to different treatments and receive only one treatment. However, some trials use within person designs such as split-body, split-mouth and cross-over designs, where each patient may receive more than one treatment. Data from treatment arms within these trials are no longer independent, so the correlations between dependent arms need to be accounted for within the statistical analyses. Ignoring these correlations may result in incorrect conclusions. The main objective of this study is to develop statistical approaches to adjusting weights for dependent arms within special design trials. In this study, we demonstrate the following three approaches: the data augmentation approach, the adjusting variance approach, and the reducing weight approach. These three methods could be perfectly applied in current statistic tools such as R and STATA. An example of periodontal regeneration was used to demonstrate how these approaches could be undertaken and implemented within statistical software packages, and to compare results from different approaches. The adjusting variance approach can be implemented within the network package in STATA, while reducing weight approach requires computer software programming to set up the within-study variance-covariance matrix. This article is protected by copyright. All rights reserved.

Assessment of sediment toxicity and chemical concentrations in the San Diego Bay region, California, USA

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

Fairey, R.; Roberts, C.; Jacobi, M.

1998-08-01

Sediment quality within San Diego Bay, Mission Bay, and the Tijuana River Estuary of California was investigated as part of an ongoing statewide monitoring effort (Bay Protection and Toxic Cleanup Program). Study objectives were to determine the incidence, spatial patterns, and spatial extent of toxicity in sediments and porewater; the concentration and distribution of potentially toxic anthropogenic chemicals; and the relationships between toxicity and chemical concentrations. Rhepoxynius abronius survival bioassays, grain size, and total organic carbon analyses were performed on 350 sediment samples. Strongylocentrotus purpuratus development bioassays were performed on 164 pore-water samples. Toxicity was demonstrated throughout the San Diegomore » Bay region, with increased incidence and concordance occurring in areas of industrial and shipping activity. Trace metal and trace synthetic organic analyses were performed on 229 samples. Copper, zinc, mercury, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and chlordane were found to exceed ERM (effects range median) or PEL (probable effects level) sediment quality guidelines and were considered the six major chemicals or chemical groups of concern. Statistical analysis of the relationships between amphipod toxicity, bulk phase sediment chemistry, and physical parameters demonstrated few significant linear relationships. Significant differences in chemical levels were found between toxic and nontoxic responses using multivariate and univariate statistics. Potential sources of anthropogenic chemicals were discussed.« less

A prospective study of differential sources of school-related social support and adolescent global life satisfaction.

PubMed

Siddall, James; Huebner, E Scott; Jiang, Xu

2013-01-01

This study examined the cross-sectional and prospective relationships between three sources of school-related social support (parent involvement, peer support for learning, and teacher-student relationships) and early adolescents' global life satisfaction. The participants were 597 middle school students from 1 large school in the southeastern United States who completed measures of school social climate and life satisfaction on 2 occasions, 5 months apart. The results revealed that school-related experiences in terms of social support for learning contributed substantial amounts of variance to individual differences in adolescents' satisfaction with their lives as a whole. Cross-sectional multiple regression analyses of the differential contributions of the sources of support demonstrated that family and peer support for learning contributed statistically significant, unique variance to global life satisfaction reports. Prospective multiple regression analyses demonstrated that only family support for learning continued to contribute statistically significant, unique variance to the global life satisfaction reports at Time 2. The results suggest that school-related experiences, especially family-school interactions, spill over into adolescents' overall evaluations of their lives at a time when direct parental involvement in schooling and adolescents' global life satisfaction are generally declining. Recommendations for future research and educational policies and practices are discussed. © 2013 American Orthopsychiatric Association.

Meta-analyses on intra-aortic balloon pump in cardiogenic shock complicating acute myocardial infarction may provide biased results.

PubMed

Acconcia, M C; Caretta, Q; Romeo, F; Borzi, M; Perrone, M A; Sergi, D; Chiarotti, F; Calabrese, C M; Sili Scavalli, A; Gaudio, C

2018-04-01

Intra-aortic balloon pump (IABP) is the device most commonly investigated in patients with cardiogenic shock (CS) complicating acute myocardial infarction (AMI). Recently meta-analyses on this topic showed opposite results: some complied with the actual guideline recommendations, while others did not, due to the presence of bias. We investigated the reasons for the discrepancy among meta-analyses and strategies employed to avoid the potential source of bias. Scientific databases were searched for meta-analyses of IABP support in AMI complicated by CS. The presence of clinical diversity, methodological diversity and statistical heterogeneity were analyzed. When we found clinical or methodological diversity, we reanalyzed the data by comparing the patients selected for homogeneous groups. When the fixed effect model was employed despite the presence of statistical heterogeneity, the meta-analysis was repeated adopting the random effect model, with the same estimator used in the original meta-analysis. Twelve meta-analysis were selected. Six meta-analyses of randomized controlled trials (RCTs) were inconclusive because underpowered to detect the IABP effect. Five included RCTs and observational studies (Obs) and one only Obs. Some meta-analyses on RCTs and Obs had biased results due to presence of clinical and/or methodological diversity. The reanalysis of data reallocated for homogeneous groups was no more in contrast with guidelines recommendations. Meta-analyses performed without controlling for clinical and/or methodological diversity, represent a confounding message against a good clinical practice. The reanalysis of data demonstrates the validity of the current guidelines recommendations in addressing clinical decision making in providing IABP support in AMI complicated by CS.

Partner aggression and problem drinking across the lifespan: how much do they decline?

PubMed

O'Leary, K Daniel; Woodin, Erica M

2005-11-01

Cross-sectional analyses from nationally-representative samples demonstrate significant age-related trends in partner aggression and problem drinking. Both behaviors are most prevalent in the early to mid-twenties and increasingly less common thereafter. Aggregate associations based on percentage of individuals displaying the behavior in each age range are dramatically stronger than those found when correlating individuals' ages and behavior. Multilevel modeling demonstrates that group-level effects do not mask associations found at the level of the individual for either problem drinking or partner aggression. An analysis of recent abstracts from psychology journals showed that issues of aggregate and individual data are rarely if ever discussed, and even well-known statistics books in psychology rarely discuss such issues. The interpretation of aggregate data will become increasing important as psychologists themselves, and in collaboration with epidemiologists and sociologists, have access to large data sets that allow for data aggregation. Both aggregate and individual analyses are valid, although they provide answers to different questions. Individual analyses are necessary for predicting individual behavior; aggregate analyses are useful in policy planning for large scale prevention and intervention. Strengths and limitations of cross-sectional community samples and aggregate data are also discussed.

How to Get Statistically Significant Effects in Any ERP Experiment (and Why You Shouldn’t)

PubMed Central

Luck, Steven J.; Gaspelin, Nicholas

2016-01-01

Event-related potential (ERP) experiments generate massive data sets, often containing thousands of values for each participant, even after averaging. The richness of these data sets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant-but-bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand average data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multi-factor statistical analyses. Re-analyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant-but-bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions. PMID:28000253

Nonnormality and Divergence in Posttreatment Alcohol Use

PubMed Central

Witkiewitz, Katie; van der Maas, Han L. J.; Hufford, Michael R.; Marlatt, G. Alan

2007-01-01

Alcohol lapses are the modal outcome following treatment for alcohol use disorders, yet many alcohol researchers have encountered limited success in the prediction and prevention of relapse. One hypothesis is that lapses are unpredictable, but another possibility is the complexity of the relapse process is not captured by traditional statistical methods. Data from Project Matching Alcohol Treatments to Client Heterogeneity (Project MATCH), a multisite alcohol treatment study, were reanalyzed with 2 statistical methodologies: catastrophe and 2-part growth mixture modeling. Drawing on previous investigations of self-efficacy as a dynamic predictor of relapse, the current study revisits the self-efficacy matching hypothesis, which was not statistically supported in Project MATCH. Results from both the catastrophe and growth mixture analyses demonstrated a dynamic relationship between self-efficacy and drinking outcomes. The growth mixture analyses provided evidence in support of the original matching hypothesis: Individuals with lower self-efficacy who received cognitive behavior therapy drank far less frequently than did those with low self-efficacy who received motivational therapy. These results highlight the dynamical nature of the relapse process and the importance of the use of methodologies that accommodate this complexity when evaluating treatment outcomes. PMID:17516769

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

A software platform for statistical evaluation of patient respiratory patterns in radiation therapy.

PubMed

Dunn, Leon; Kenny, John

2017-10-01

The aim of this work was to design and evaluate a software tool for analysis of a patient's respiration, with the goal of optimizing the effectiveness of motion management techniques during radiotherapy imaging and treatment. A software tool which analyses patient respiratory data files (.vxp files) created by the Varian Real-Time Position Management System (RPM) was developed to analyse patient respiratory data. The software, called RespAnalysis, was created in MATLAB and provides four modules, one each for determining respiration characteristics, providing breathing coaching (biofeedback training), comparing pre and post-training characteristics and performing a fraction-by-fraction assessment. The modules analyse respiratory traces to determine signal characteristics and specifically use a Sample Entropy algorithm as the key means to quantify breathing irregularity. Simulated respiratory signals, as well as 91 patient RPM traces were analysed with RespAnalysis to test the viability of using the Sample Entropy for predicting breathing regularity. Retrospective assessment of patient data demonstrated that the Sample Entropy metric was a predictor of periodic irregularity in respiration data, however, it was found to be insensitive to amplitude variation. Additional waveform statistics assessing the distribution of signal amplitudes over time coupled with Sample Entropy method were found to be useful in assessing breathing regularity. The RespAnalysis software tool presented in this work uses the Sample Entropy method to analyse patient respiratory data recorded for motion management purposes in radiation therapy. This is applicable during treatment simulation and during subsequent treatment fractions, providing a way to quantify breathing irregularity, as well as assess the need for breathing coaching. It was demonstrated that the Sample Entropy metric was correlated to the irregularity of the patient's respiratory motion in terms of periodicity, whilst other metrics, such as percentage deviation of inhale/exhale peak positions provided insight into respiratory amplitude regularity. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses

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

Krause, E.; et al.

We present the methodology for and detail the implementation of the Dark Energy Survey (DES) 3x2pt DES Year 1 (Y1) analysis, which combines configuration-space two-point statistics from three different cosmological probes: cosmic shear, galaxy-galaxy lensing, and galaxy clustering, using data from the first year of DES observations. We have developed two independent modeling pipelines and describe the code validation process. We derive expressions for analytical real-space multi-probe covariances, and describe their validation with numerical simulations. We stress-test the inference pipelines in simulated likelihood analyses that vary 6-7 cosmology parameters plus 20 nuisance parameters and precisely resemble the analysis to be presented in the DES 3x2pt analysis paper, using a variety of simulated input data vectors with varying assumptions. We find that any disagreement between pipelines leads to changes in assigned likelihoodmore » $$\\Delta \\chi^2 \\le 0.045$$ with respect to the statistical error of the DES Y1 data vector. We also find that angular binning and survey mask do not impact our analytic covariance at a significant level. We determine lower bounds on scales used for analysis of galaxy clustering (8 Mpc$$~h^{-1}$$) and galaxy-galaxy lensing (12 Mpc$$~h^{-1}$$) such that the impact of modeling uncertainties in the non-linear regime is well below statistical errors, and show that our analysis choices are robust against a variety of systematics. These tests demonstrate that we have a robust analysis pipeline that yields unbiased cosmological parameter inferences for the flagship 3x2pt DES Y1 analysis. We emphasize that the level of independent code development and subsequent code comparison as demonstrated in this paper is necessary to produce credible constraints from increasingly complex multi-probe analyses of current data.« less

Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation.

PubMed

Plante, David T; Landsness, Eric C; Peterson, Michael J; Goldstein, Michael R; Riedner, Brady A; Wanger, Timothy; Guokas, Jeffrey J; Tononi, Giulio; Benca, Ruth M

2012-09-18

Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder. All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data. As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night. Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

[The role of meta-analysis in assessing the treatment of advanced non-small cell lung cancer].

PubMed

Pérol, M; Pérol, D

2004-02-01

Meta-analysis is a statistical method allowing an evaluation of the direction and quantitative importance of a treatment effect observed in randomized trials which have tested the treatment but have not provided a definitive conclusion. In the present review, we discuss the methodology and the contribution of meta-analyses to the treatment of advanced-stage or metastatic non-small-cell lung cancer. In this area of cancerology, meta-analyses have provided determining information demonstrating the impact of chemotherapy on patient survival. They have also helped define a two-drug regimen based on cisplatin as the gold standard treatment for patients with a satisfactory general status. Recently, the meta-analysis method was used to measure the influence of gemcitabin in combination with platinium salts and demonstrated a small but significant benefit in survival, confirming that gemcitabin remains the gold standard treatment in combination with cisplatin.

FARVATX: FAmily-based Rare Variant Association Test for X-linked genes

PubMed Central

Choi, Sungkyoung; Lee, Sungyoung; Qiao, Dandi; Hardin, Megan; Cho, Michael H.; Silverman, Edwin K; Park, Taesung; Won, Sungho

2016-01-01

Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease (COPD). Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods. PMID:27325607

FARVATX: Family-Based Rare Variant Association Test for X-Linked Genes.

PubMed

Choi, Sungkyoung; Lee, Sungyoung; Qiao, Dandi; Hardin, Megan; Cho, Michael H; Silverman, Edwin K; Park, Taesung; Won, Sungho

2016-09-01

Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods. © 2016 WILEY PERIODICALS, INC.

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Time series expression analyses using RNA-seq: a statistical approach.

PubMed

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

GPU-computing in econophysics and statistical physics

NASA Astrophysics Data System (ADS)

Preis, T.

2011-03-01

A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today's GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In particular computationally expensive analyses employed in financial market context are coded on a graphics card architecture which leads to a significant reduction of computing time. In order to demonstrate the wide range of possible applications, a standard model in statistical physics - the Ising model - is ported to a graphics card architecture as well, resulting in large speedup values.

Investigating the relationship between foveal morphology and refractive error in a population with infantile nystagmus syndrome.

PubMed

Healey, Natasha; McLoone, Eibhlin; Mahon, Gerald; Jackson, A Jonathan; Saunders, Kathryn J; McClelland, Julie F

2013-04-26

We explored associations between refractive error and foveal hypoplasia in infantile nystagmus syndrome (INS). We recruited 50 participants with INS (albinism n = 33, nonalbinism infantile nystagmus [NAIN] n = 17) aged 4 to 48 years. Cycloplegic refractive error and logMAR acuity were obtained. Spherical equivalent (SER), most ametropic meridian (MAM) refractive error, and better eye acuity (VA) were used for analyses. High resolution spectral-domain optical coherence tomography (SD-OCT) was used to obtain foveal scans, which were graded using the Foveal Hypoplasia Grading Scale. Associations between grades of severity of foveal hypoplasia, and refractive error and VA were explored. Participants with more severe foveal hypoplasia had significantly higher MAMs and SERs (Kruskal-Wallis H test P = 0.005 and P = 0.008, respectively). There were no statistically significant associations between foveal hypoplasia and cylindrical refractive error (Kruskal-Wallis H test P = 0.144). Analyses demonstrated significant differences between participants with albinism or NAIN in terms of SER and MAM (Mann-Whitney U test P = 0.001). There were no statistically significant differences between astigmatic errors between participants with albinism and NAIN. Controlling for the effects of albinism, results demonstrated no significant associations between SER, and MAM and foveal hypoplasia (partial correlation P > 0.05). Poorer visual acuity was associated statistically significantly with more severe foveal hypoplasia (Kruskal-Wallis H test P = 0.001) and with a diagnosis of albinism (Mann-Whitney U test P = 0.001). Increasing severity of foveal hypoplasia is associated with poorer VA, reflecting reduced cone density in INS. Individuals with INS also demonstrate a significant association between more severe foveal hypoplasia and increasing hyperopia. However, in the absence of albinism, there is no significant relation between refractive outcome and degree of foveal hypoplasia, suggesting that foveal maldevelopment in isolation does not impair significantly the emmetropization process. It likely is that impaired emmetropization evidenced in the albinism group may be attributed to the whole eye effect of albinism.

Spatial variation of volcanic rock geochemistry in the Virunga Volcanic Province: Statistical analysis of an integrated database

NASA Astrophysics Data System (ADS)

Barette, Florian; Poppe, Sam; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2017-10-01

We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.

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.

Median statistics estimates of Hubble and Newton's constants

NASA Astrophysics Data System (ADS)

Bethapudi, Suryarao; Desai, Shantanu

2017-02-01

Robustness of any statistics depends upon the number of assumptions it makes about the measured data. We point out the advantages of median statistics using toy numerical experiments and demonstrate its robustness, when the number of assumptions we can make about the data are limited. We then apply the median statistics technique to obtain estimates of two constants of nature, Hubble constant (H0) and Newton's gravitational constant ( G , both of which show significant differences between different measurements. For H0, we update the analyses done by Chen and Ratra (2011) and Gott et al. (2001) using 576 measurements. We find after grouping the different results according to their primary type of measurement, the median estimates are given by H0 = 72.5^{+2.5}_{-8} km/sec/Mpc with errors corresponding to 95% c.l. (2 σ) and G=6.674702^{+0.0014}_{-0.0009} × 10^{-11} Nm2kg-2 corresponding to 68% c.l. (1σ).

"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

ERIC Educational Resources Information Center

Ozturk, Elif

2012-01-01

The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

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

Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

DOE PAGES

Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...

2014-02-24

The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less

Machine Learning Predictions of a Multiresolution Climate Model Ensemble

NASA Astrophysics Data System (ADS)

Anderson, Gemma J.; Lucas, Donald D.

2018-05-01

Statistical models of high-resolution climate models are useful for many purposes, including sensitivity and uncertainty analyses, but building them can be computationally prohibitive. We generated a unique multiresolution perturbed parameter ensemble of a global climate model. We use a novel application of a machine learning technique known as random forests to train a statistical model on the ensemble to make high-resolution model predictions of two important quantities: global mean top-of-atmosphere energy flux and precipitation. The random forests leverage cheaper low-resolution simulations, greatly reducing the number of high-resolution simulations required to train the statistical model. We demonstrate that high-resolution predictions of these quantities can be obtained by training on an ensemble that includes only a small number of high-resolution simulations. We also find that global annually averaged precipitation is more sensitive to resolution changes than to any of the model parameters considered.

Single-case research design in pediatric psychology: considerations regarding data analysis.

PubMed

Cohen, Lindsey L; Feinstein, Amanda; Masuda, Akihiko; Vowles, Kevin E

2014-03-01

Single-case research allows for an examination of behavior and can demonstrate the functional relation between intervention and outcome in pediatric psychology. This review highlights key assumptions, methodological and design considerations, and options for data analysis. Single-case methodology and guidelines are reviewed with an in-depth focus on visual and statistical analyses. Guidelines allow for the careful evaluation of design quality and visual analysis. A number of statistical techniques have been introduced to supplement visual analysis, but to date, there is no consensus on their recommended use in single-case research design. Single-case methodology is invaluable for advancing pediatric psychology science and practice, and guidelines have been introduced to enhance the consistency, validity, and reliability of these studies. Experts generally agree that visual inspection is the optimal method of analysis in single-case design; however, statistical approaches are becoming increasingly evaluated and used to augment data interpretation.

A phylogenetic transform enhances analysis of compositional microbiota data.

PubMed

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-02-15

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

Geostatistics and GIS: tools for characterizing environmental contamination.

PubMed

Henshaw, Shannon L; Curriero, Frank C; Shields, Timothy M; Glass, Gregory E; Strickland, Paul T; Breysse, Patrick N

2004-08-01

Geostatistics is a set of statistical techniques used in the analysis of georeferenced data that can be applied to environmental contamination and remediation studies. In this study, the 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) contamination at a Superfund site in western Maryland is evaluated. Concern about the site and its future clean up has triggered interest within the community because residential development surrounds the area. Spatial statistical methods, of which geostatistics is a subset, are becoming increasingly popular, in part due to the availability of geographic information system (GIS) software in a variety of application packages. In this article, the joint use of ArcGIS software and the R statistical computing environment are demonstrated as an approach for comprehensive geostatistical analyses. The spatial regression method, kriging, is used to provide predictions of DDE levels at unsampled locations both within the site and the surrounding areas where residential development is ongoing.

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

PubMed Central

Williams, Ryan J.; Howe, Adina; Hofmockel, Kirsten S.

2014-01-01

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities. PMID:25101065

Neighborhood archetypes for population health research: is there no place like home?

PubMed

Weden, Margaret M; Bird, Chloe E; Escarce, José J; Lurie, Nicole

2011-01-01

This study presents a new, latent archetype approach for studying place in population health. Latent class analysis is used to show how the number, defining attributes, and change/stability of neighborhood archetypes can be characterized and tested for statistical significance. The approach is demonstrated using data on contextual determinants of health for US neighborhoods defined by census tracts in 1990 and 2000. Six archetypes (prevalence 13-20%) characterize the statistically significant combinations of contextual determinants of health from the social environment, built environment, commuting and migration patterns, and demographics and household composition of US neighborhoods. Longitudinal analyses based on the findings demonstrate notable stability (76.4% of neighborhoods categorized as the same archetype ten years later), with exceptions reflecting trends in (ex)urbanization, gentrification/downgrading, and racial/ethnic reconfiguration. The findings and approach is applicable to both research and practice (e.g. surveillance) and can be scaled up or down to study health and place in other geographical contexts or historical periods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Association between periodontal disease and mortality in people with CKD: a meta-analysis of cohort studies.

PubMed

Zhang, Jian; Jiang, Hong; Sun, Min; Chen, Jianghua

2017-08-16

Periodontal disease occurs relatively prevalently in people with chronic kidney disease (CKD), but it remains indeterminate whether periodontal disease is an independent risk factor for premature death in this population. Interventions to reduce mortality in CKD population consistently yield to unsatisfactory results and new targets are necessitated. So this meta-analysis aimed to evaluate the association between periodontal disease and mortality in the CKD population. Pubmed, Embase, Web of Science, Scopus and abstracts from recent relevant meeting were searched by two authors independently. Relative risks (RRs) with 95% confidence intervals (CIs) were calculated for overall and subgroup meta-analyses. Statistical heterogeneity was explored by chi-square test and quantified by the I 2 statistic. Eight cohort studies comprising 5477 individuals with CKD were incorporated. The overall pooled data demonstrated that periodontal disease was associated with all-cause death in CKD population (RR, 1.254; 95% CI 1.046-1.503; P = 0.005), with a moderate heterogeneity, I 2  = 52.2%. However, no evident association was observed between periodontal disease and cardiovascular mortality (RR, 1.30, 95% CI, 0.82-2.06; P = 0.259). Besides, statistical heterogeneity was substantial (I 2  = 72.5%; P = 0.012). Associations for mortality were similar between subgroups, such as the different stages of CKD, adjustment for confounding factors. Specific to all-cause death, sensitivity and cumulative analyses both suggested that our results were robust. As for cardiovascular mortality, the association with periodontal disease needs to be further strengthened. We demonstrated that periodontal disease was associated with an increased risk of all-cause death in CKD people. Yet no adequate evidence suggested periodontal disease was also at elevated risk for cardiovascular death.

Analysis of Anatomic and Functional Measures in X-Linked Retinoschisis

PubMed Central

Cukras, Catherine A.; Huryn, Laryssa A.; Jeffrey, Brett P.; Turriff, Amy; Sieving, Paul A.

2018-01-01

Purpose To examine the symmetry of structural and functional parameters between eyes in patients with X-linked retinoschisis (XLRS), as well as changes in visual acuity and electrophysiology over time. Methods This is a single-center observational study of 120 males with XLRS who were evaluated at the National Eye Institute. Examinations included best-corrected visual acuity for all participants, as well as ERG recording and optical coherence tomography (OCT) on a subset of participants. Statistical analyses were performed using nonparametric Spearman correlations and linear regression. Results Our analyses demonstrated a statistically significant correlation of structural and functional measures between the two eyes of XLRS patients for all parameters. OCT central macular thickness (n = 78; Spearman r = 0.83, P < 0.0001) and ERG b/a ratio (n = 78; Spearman r = 0.82, P < 0.0001) were the most strongly correlated between a participant's eyes, whereas visual acuity was less strongly correlated (n = 120; Spearman r = 0.47, P < 0.0001). Stability of visual acuity was observed with an average change of less than one letter (n = 74; OD −0.66 and OS −0.70 letters) in a mean follow-up time of 6.8 years. There was no statistically significant change in the ERG b/a ratio within eyes over time. Conclusions Although a broad spectrum of clinical phenotypes is observed across individuals with XLRS, our study demonstrates a significant correlation of structural and functional findings between the two eyes and stability of measures of acuity and ERG parameters over time. These results highlight the utility of the fellow eye as a useful reference for monocular interventional trials.

Fighting bias with statistics: Detecting gender differences in responses to items on a preschool science assessment

NASA Astrophysics Data System (ADS)

Greenberg, Ariela Caren

Differential item functioning (DIF) and differential distractor functioning (DDF) are methods used to screen for item bias (Camilli & Shepard, 1994; Penfield, 2008). Using an applied empirical example, this mixed-methods study examined the congruency and relationship of DIF and DDF methods in screening multiple-choice items. Data for Study I were drawn from item responses of 271 female and 236 male low-income children on a preschool science assessment. Item analyses employed a common statistical approach of the Mantel-Haenszel log-odds ratio (MH-LOR) to detect DIF in dichotomously scored items (Holland & Thayer, 1988), and extended the approach to identify DDF (Penfield, 2008). Findings demonstrated that the using MH-LOR to detect DIF and DDF supported the theoretical relationship that the magnitude and form of DIF and are dependent on the DDF effects, and demonstrated the advantages of studying DIF and DDF in multiple-choice items. A total of 4 items with DIF and DDF and 5 items with only DDF were detected. Study II incorporated an item content review, an important but often overlooked and under-published step of DIF and DDF studies (Camilli & Shepard). Interviews with 25 female and 22 male low-income preschool children and an expert review helped to interpret the DIF and DDF results and their comparison, and determined that a content review process of studied items can reveal reasons for potential item bias that are often congruent with the statistical results. Patterns emerged and are discussed in detail. The quantitative and qualitative analyses were conducted in an applied framework of examining the validity of the preschool science assessment scores for evaluating science programs serving low-income children, however, the techniques can be generalized for use with measures across various disciplines of research.

Imaging of Al/Fe ratios in synthetic Al-goethite revealed by nanoscale secondary ion mass spectrometry.

PubMed

Pohl, Lydia; Kölbl, Angelika; Werner, Florian; Mueller, Carsten W; Höschen, Carmen; Häusler, Werner; Kögel-Knabner, Ingrid

2018-04-30

Aluminium (Al)-substituted goethite is ubiquitous in soils and sediments. The extent of Al-substitution affects the physicochemical properties of the mineral and influences its macroscale properties. Bulk analysis only provides total Al/Fe ratios without providing information with respect to the Al-substitution of single minerals. Here, we demonstrate that nanoscale secondary ion mass spectrometry (NanoSIMS) enables the precise determination of Al-content in single minerals, while simultaneously visualising the variation of the Al/Fe ratio. Al-substituted goethite samples were synthesized with increasing Al concentrations of 0.1, 3, and 7 % and analysed by NanoSIMS in combination with established bulk spectroscopic methods (XRD, FTIR, Mössbauer spectroscopy). The high spatial resolution (50-150 nm) of NanoSIMS is accompanied by a high number of single-point measurements. We statistically evaluated the Al/Fe ratios derived from NanoSIMS, while maintaining the spatial information and reassigning it to its original localization. XRD analyses confirmed increasing concentration of incorporated Al within the goethite structure. Mössbauer spectroscopy revealed 11 % of the goethite samples generated at high Al concentrations consisted of hematite. The NanoSIMS data show that the Al/Fe ratios are in agreement with bulk data derived from total digestion and demonstrated small spatial variability between single-point measurements. More advantageously, statistical analysis and reassignment of single-point measurements allowed us to identify distinct spots with significantly higher or lower Al/Fe ratios. NanoSIMS measurements confirmed the capacity to produce images, which indicated the uniform increase in Al-concentrations in goethite. Using a combination of statistical analysis with information from complementary spectroscopic techniques (XRD, FTIR and Mössbauer spectroscopy) we were further able to reveal spots with lower Al/Fe ratios as hematite. Copyright © 2018 John Wiley & Sons, Ltd.

Influence of neurophysiological hippotherapy on the transference of the centre of gravity among children with cerebral palsy.

PubMed

Maćków, Anna; Małachowska-Sobieska, Monika; Demczuk-Włodarczyk, Ewa; Sidorowska, Marta; Szklarska, Alicja; Lipowicz, Anna

2014-01-01

The aim of the study was to present the influence of neurophysiological hippotherapy on the transference of the centre of gravity (COG) among children with cerebral palsy (CP). The study involved 19 children aged 4-13 years suffering from CP who demonstrated an asymmetric (A/P) model of compensation. Body balance was studied with the Cosmogamma Balance Platform. An examination on this platform was performed before and after a session of neurophysiological hippotherapy. In order to compare the correlations and differences between the examinations, the results were analysed using Student's T-test for dependent samples at p ≤ 0.05 as the level of statistical significance and descriptive statistics were calculated. The mean value of the body's centre of gravity in the frontal plane (COG X) was 18.33 (mm) during the first examination, changing by 21.84 (mm) after neurophysiological hippotherapy towards deloading of the antigravity lower limb (p ≤ 0.0001). The other stabilographic parameters increased; however, only the change in average speed of antero - posterior COG oscillation was statistically significant (p = 0.0354). 1. One session of neurophysiological hippotherapy induced statistically significant changes in the position of the centre of gravity in the body in the frontal plane and the average speed of COG oscillation in the sagittal plane among CP children demonstrating an asymmetric model of compensation (A/P).

Uncommon knowledge of a common phenomenon: intuitions and statistical thinking about gender birth ratio

NASA Astrophysics Data System (ADS)

Peled, Ofra N.; Peled, Irit; Peled, Jonathan U.

2013-01-01

The phenomenon of birth of a baby is a common and familiar one, and yet college students participating in a general biology class did not possess the expected common knowledge of the equal probability of gender births. We found that these students held strikingly skewed conceptions regarding gender birth ratio, estimating the number of female births to be more than twice the number of male births. Possible sources of these beliefs were analysed, showing flaws in statistical thinking such as viewing small unplanned samples as representing the whole population and making inferences from an inappropriate population. Some educational implications are discussed and a short teaching example (using data assembly) demonstrates an instructional direction that might facilitate conceptual change.

Cormack Research Project: Glasgow University

NASA Technical Reports Server (NTRS)

Skinner, Susan; Ryan, James M.

1998-01-01

The aim of this project was to investigate and improve upon existing methods of analysing data from COMITEL on the Gamma Ray Observatory for neutrons emitted during solar flares. In particular, a strategy for placing confidence intervals on neutron energy distributions, due to uncertainties on the response matrix has been developed. We have also been able to demonstrate the superior performance of one of a range of possible statistical regularization strategies. A method of generating likely models of neutron energy distributions has also been developed as a tool to this end. The project involved solving an inverse problem with noise being added to the data in various ways. To achieve this pre-existing C code was used to run Fortran subroutines which performed statistical regularization on the data.

Statistical Learning Analysis in Neuroscience: Aiming for Transparency

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Haxby, James V.; Pollmann, Stefan

2009-01-01

Encouraged by a rise of reciprocal interest between the machine learning and neuroscience communities, several recent studies have demonstrated the explanatory power of statistical learning techniques for the analysis of neural data. In order to facilitate a wider adoption of these methods, neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures. We argue that such transparency requires “neuroscience-aware” technology for the performance of multivariate pattern analyses of neural data that can be documented in a comprehensive, yet comprehensible way. Recently, we introduced PyMVPA, a specialized Python framework for machine learning based data analysis that addresses this demand. Here, we review its features and applicability to various neural data modalities. PMID:20582270

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

Experimental design matters for statistical analysis: how to handle blocking.

PubMed

Jensen, Signe M; Schaarschmidt, Frank; Onofri, Andrea; Ritz, Christian

2018-03-01

Nowadays, evaluation of the effects of pesticides often relies on experimental designs that involve multiple concentrations of the pesticide of interest or multiple pesticides at specific comparable concentrations and, possibly, secondary factors of interest. Unfortunately, the experimental design is often more or less neglected when analysing data. Two data examples were analysed using different modelling strategies. First, in a randomized complete block design, mean heights of maize treated with a herbicide and one of several adjuvants were compared. Second, translocation of an insecticide applied to maize as a seed treatment was evaluated using incomplete data from an unbalanced design with several layers of hierarchical sampling. Extensive simulations were carried out to further substantiate the effects of different modelling strategies. It was shown that results from suboptimal approaches (two-sample t-tests and ordinary ANOVA assuming independent observations) may be both quantitatively and qualitatively different from the results obtained using an appropriate linear mixed model. The simulations demonstrated that the different approaches may lead to differences in coverage percentages of confidence intervals and type 1 error rates, confirming that misleading conclusions can easily happen when an inappropriate statistical approach is chosen. To ensure that experimental data are summarized appropriately, avoiding misleading conclusions, the experimental design should duly be reflected in the choice of statistical approaches and models. We recommend that author guidelines should explicitly point out that authors need to indicate how the statistical analysis reflects the experimental design. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Statistical modelling for recurrent events: an application to sports injuries

PubMed Central

Ullah, Shahid; Gabbett, Tim J; Finch, Caroline F

2014-01-01

Background Injuries are often recurrent, with subsequent injuries influenced by previous occurrences and hence correlation between events needs to be taken into account when analysing such data. Objective This paper compares five different survival models (Cox proportional hazards (CoxPH) model and the following generalisations to recurrent event data: Andersen-Gill (A-G), frailty, Wei-Lin-Weissfeld total time (WLW-TT) marginal, Prentice-Williams-Peterson gap time (PWP-GT) conditional models) for the analysis of recurrent injury data. Methods Empirical evaluation and comparison of different models were performed using model selection criteria and goodness-of-fit statistics. Simulation studies assessed the size and power of each model fit. Results The modelling approach is demonstrated through direct application to Australian National Rugby League recurrent injury data collected over the 2008 playing season. Of the 35 players analysed, 14 (40%) players had more than 1 injury and 47 contact injuries were sustained over 29 matches. The CoxPH model provided the poorest fit to the recurrent sports injury data. The fit was improved with the A-G and frailty models, compared to WLW-TT and PWP-GT models. Conclusions Despite little difference in model fit between the A-G and frailty models, in the interest of fewer statistical assumptions it is recommended that, where relevant, future studies involving modelling of recurrent sports injury data use the frailty model in preference to the CoxPH model or its other generalisations. The paper provides a rationale for future statistical modelling approaches for recurrent sports injury. PMID:22872683

Applications of spatial statistical network models to stream data

USGS Publications Warehouse

Isaak, Daniel J.; Peterson, Erin E.; Ver Hoef, Jay M.; Wenger, Seth J.; Falke, Jeffrey A.; Torgersen, Christian E.; Sowder, Colin; Steel, E. Ashley; Fortin, Marie-Josée; Jordan, Chris E.; Ruesch, Aaron S.; Som, Nicholas; Monestiez, Pascal

2014-01-01

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology.

PubMed

Keeble, Claire; Thwaites, Peter Adam; Barber, Stuart; Law, Graham Richard; Baxter, Paul David

2017-09-26

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results.

Comparison of bacterial community structure and dynamics during the thermophilic composting of different types of solid wastes: anaerobic digestion residue, pig manure and chicken manure

PubMed Central

Song, Caihong; Li, Mingxiao; Jia, Xuan; Wei, Zimin; Zhao, Yue; Xi, Beidou; Zhu, Chaowei; Liu, Dongming

2014-01-01

This study investigated the impact of composting substrate types on the bacterial community structure and dynamics during composting processes. To this end, pig manure (PM), chicken manure (CM), a mixture of PM and CM (PM + CM), and a mixture of PM, CM and anaerobic digestion residue (ADR) (PM + CM + ADR) were selected for thermophilic composting. The bacterial community structure and dynamics during the composting process were detected and analysed by polymerase chain reaction–denaturing gradient gel electrophoresis (DGGE) coupled with a statistic analysis. The physical-chemical analyses indicated that compared to single-material composting (PM, CM), co-composting (PM + CM, PM + CM + ADR) could promote the degradation of organic matter and strengthen the ability of conserving nitrogen. A DGGE profile and statistical analysis demonstrated that co-composting, especially PM + CM + ADR, could improve the bacterial community structure and functional diversity, even in the thermophilic stage. Therefore, co-composting could weaken the screening effect of high temperature on bacterial communities. Dominant sequencing analyses indicated a dramatic shift in the dominant bacterial communities from single-material composting to co-composting. Notably, compared with PM, PM + CM increased the quantity of xylan-degrading bacteria and reduced the quantity of human pathogens. PMID:24963997

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Statistical Data Analyses of Trace Chemical, Biochemical, and Physical Analytical Signatures

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

Udey, Ruth Norma

Analytical and bioanalytical chemistry measurement results are most meaningful when interpreted using rigorous statistical treatments of the data. The same data set may provide many dimensions of information depending on the questions asked through the applied statistical methods. Three principal projects illustrated the wealth of information gained through the application of statistical data analyses to diverse problems.

The analgesic effects of exogenous melatonin in humans.

PubMed

Andersen, Lars Peter Holst

2016-10-01

The hormone, melatonin is produced with circadian rhythm by the pineal gland in humans. The melatonin rhythm provides an endogenous synchronizer, modulating e.g. blood pressure, body temperature, cortisol rhythm, sleep-awake-cycle, immune function and anti-oxidative defence. Interestingly, a number of experimental animal studies demonstrate significant dose-dependent anti-nociceptive effects of exogenous melatonin. Similarly, recent experimental- and clinical studies in humans indicate significant analgesic effects. In study I, we systematically reviewed all randomized studies investigating clinical effects of perioperative melatonin. Meta-analyses demonstrated significant analgesic and anxiolytic effects of melatonin in surgical patients, equating reductions of 20 mm and 19 mm, respectively on a VAS, compared with placebo. Profound heterogeneity between the included studies was, however, present. In study II, we aimed to investigate the analgesic, anti-hyperalgesic and anti-inflammatory effects of exogenous melatonin in a validated human inflammatory pain model, the human burn model. The study was performed as a randomized, double blind placebo-controlled crossover study. Primary outcomes were pain during the burn injury and areas of secondary hyperalgesia. No significant effects of exogenous melatonin were observed with respect to primary or secondary outcomes, compared to placebo. Study III and IV estimated the pharmacokinetic variables of exogenous melatonin. Oral melatonin demonstrated a t max value of 41 minutes. Bioavailability of oral melatonin was only 3%. Elimination t 1/2 were approximately 45 minutes following both oral and intravenous administration, respectively. High-dose intravenous melatonin was not associated with increased sedation, in terms of simple reaction times, compared to placebo. Similarly, no other adverse effects were reported. In Study V, we aimed to re-analyse data obtained from a randomized analgesic drug trial by a selection of standard statistical test. Furthermore, we presented an integrated assessment method of longitudinally measured pain intensity and opioid consumption. Our analyses documented that the employed statistical method impacted the statistical significance of post-operative analgesic outcomes. Furthermore, the novel integrated assessment method combines two interdependent outcomes, lowers the risk of type 2 errors, increases the statistical power, and provides a more accurate description of post-operative analgesic efficacy. Exogenous melatonin may offer an effective and safe analgesic drug. At this moment, however, the results of human studies have been contradictory. High-quality randomized experimental- and clinical studies are still needed to establish a "genuine" analgesic effect of the drug in humans. Other perioperative effects of exogenous melatonin should also be investigated, before melatonin can be introduced for clinical routine use in surgical patients. Despite promising experimental and clinical findings, several unanswered questions also relate to optimal dosage, timing of administration and administration route of exogenous melatonin.

Homeopathy: meta-analyses of pooled clinical data.

PubMed

Hahn, Robert G

2013-01-01

In the first decade of the evidence-based era, which began in the mid-1990s, meta-analyses were used to scrutinize homeopathy for evidence of beneficial effects in medical conditions. In this review, meta-analyses including pooled data from placebo-controlled clinical trials of homeopathy and the aftermath in the form of debate articles were analyzed. In 1997 Klaus Linde and co-workers identified 89 clinical trials that showed an overall odds ratio of 2.45 in favor of homeopathy over placebo. There was a trend toward smaller benefit from studies of the highest quality, but the 10 trials with the highest Jadad score still showed homeopathy had a statistically significant effect. These results challenged academics to perform alternative analyses that, to demonstrate the lack of effect, relied on extensive exclusion of studies, often to the degree that conclusions were based on only 5-10% of the material, or on virtual data. The ultimate argument against homeopathy is the 'funnel plot' published by Aijing Shang's research group in 2005. However, the funnel plot is flawed when applied to a mixture of diseases, because studies with expected strong treatments effects are, for ethical reasons, powered lower than studies with expected weak or unclear treatment effects. To conclude that homeopathy lacks clinical effect, more than 90% of the available clinical trials had to be disregarded. Alternatively, flawed statistical methods had to be applied. Future meta-analyses should focus on the use of homeopathy in specific diseases or groups of diseases instead of pooling data from all clinical trials. © 2013 S. Karger GmbH, Freiburg.

Statistical methods for incomplete data: Some results on model misspecification.

PubMed

McIsaac, Michael; Cook, R J

2017-02-01

Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse probability weighted estimating equations, augmented inverse probability weighted estimating equations and multiple imputation when the requisite auxiliary models are misspecified. We compute limiting values for settings involving binary responses and covariates and illustrate the effects of model misspecification using simulations based on data from a breast cancer clinical trial. We demonstrate that, even when both auxiliary models are misspecified, the asymptotic biases of double-robust augmented inverse probability weighted estimators are often smaller than the asymptotic biases of estimators arising from complete-case analyses, inverse probability weighting or multiple imputation. We further demonstrate that use of inverse probability weighting or multiple imputation with slightly misspecified auxiliary models can actually result in greater asymptotic bias than the use of naïve, complete case analyses. These asymptotic results are shown to be consistent with empirical results from simulation studies.

Increased left hemisphere impairment in high-functioning autism: a tract based spatial statistics study.

PubMed

Perkins, Thomas John; Stokes, Mark Andrew; McGillivray, Jane Anne; Mussap, Alexander Julien; Cox, Ivanna Anne; Maller, Jerome Joseph; Bittar, Richard Garth

2014-11-30

There is evidence emerging from Diffusion Tensor Imaging (DTI) research that autism spectrum disorders (ASD) are associated with greater impairment in the left hemisphere. Although this has been quantified with volumetric region of interest analyses, it has yet to be tested with white matter integrity analysis. In the present study, tract based spatial statistics was used to contrast white matter integrity of 12 participants with high-functioning autism or Aspergers syndrome (HFA/AS) with 12 typically developing individuals. Fractional Anisotropy (FA) was examined, in addition to axial, radial and mean diffusivity (AD, RD and MD). In the left hemisphere, participants with HFA/AS demonstrated significantly reduced FA in predominantly thalamic and fronto-parietal pathways and increased RD. Symmetry analyses confirmed that in the HFA/AS group, WM disturbance was significantly greater in the left compared to right hemisphere. These findings contribute to a growing body of literature suggestive of reduced FA in ASD, and provide preliminary evidence for RD impairments in the left hemisphere. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Geographical origin discrimination of lentils (Lens culinaris Medik.) using 1H NMR fingerprinting and multivariate statistical analyses.

PubMed

Longobardi, Francesco; Innamorato, Valentina; Di Gioia, Annalisa; Ventrella, Andrea; Lippolis, Vincenzo; Logrieco, Antonio F; Catucci, Lucia; Agostiano, Angela

2017-12-15

Lentil samples coming from two different countries, i.e. Italy and Canada, were analysed using untargeted 1 H NMR fingerprinting in combination with chemometrics in order to build models able to classify them according to their geographical origin. For such aim, Soft Independent Modelling of Class Analogy (SIMCA), k-Nearest Neighbor (k-NN), Principal Component Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the NMR data and the results were compared. The best combination of average recognition (100%) and cross-validation prediction abilities (96.7%) was obtained for the PCA-LDA. All the statistical models were validated both by using a test set and by carrying out a Monte Carlo Cross Validation: the obtained performances were found to be satisfying for all the models, with prediction abilities higher than 95% demonstrating the suitability of the developed methods. Finally, the metabolites that mostly contributed to the lentil discrimination were indicated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Trial Sequential Analysis in systematic reviews with meta-analysis.

PubMed

Wetterslev, Jørn; Jakobsen, Janus Christian; Gluud, Christian

2017-03-06

Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors) and too many false negative conclusions (type II errors). We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D 2 ) measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in systematic reviews with traditional meta-analyses can be reduced using Trial Sequential Analysis. Several empirical studies have demonstrated that the Trial Sequential Analysis provides better control of type I errors and of type II errors than the traditional naïve meta-analysis. Trial Sequential Analysis represents analysis of meta-analytic data, with transparent assumptions, and better control of type I and type II errors than the traditional meta-analysis using naïve unadjusted confidence intervals.

Criterion Validity and Practical Utility of the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) in Assessments of Police Officer Candidates.

PubMed

Tarescavage, Anthony M; Corey, David M; Gupton, Herbert M; Ben-Porath, Yossef S

2015-01-01

Minnesota Multiphasic Personality Inventory-2-Restructured Form scores for 145 male police officer candidates were compared with supervisor ratings of field performance and problem behaviors during their initial probationary period. Results indicated that the officers produced meaningfully lower and less variant substantive scale scores compared to the general population. After applying a statistical correction for range restriction, substantive scale scores from all domains assessed by the inventory demonstrated moderate to large correlations with performance criteria. The practical significance of these results was assessed with relative risk ratio analyses that examined the utility of specific cutoffs on scales demonstrating associations with performance criteria.

Analysis of Cross-Sectional Univariate Measurements for Family Dyads Using Linear Mixed Modeling

PubMed Central

Knafl, George J.; Dixon, Jane K.; O'Malley, Jean P.; Grey, Margaret; Deatrick, Janet A.; Gallo, Agatha M.; Knafl, Kathleen A.

2010-01-01

Outcome measurements from members of the same family are likely correlated. Such intrafamilial correlation (IFC) is an important dimension of the family as a unit but is not always accounted for in analyses of family data. This article demonstrates the use of linear mixed modeling to account for IFC in the important special case of univariate measurements for family dyads collected at a single point in time. Example analyses of data from partnered parents having a child with a chronic condition on their child's adaptation to the condition and on the family's general functioning and management of the condition are provided. Analyses of this kind are reasonably straightforward to generate with popular statistical tools. Thus, it is recommended that IFC be reported as standard practice reflecting the fact that a family dyad is more than just the aggregate of two individuals. Moreover, not accounting for IFC can affect the conclusions. PMID:19307316

Early Warning Signs of Suicide in Service Members Who Engage in Unauthorized Acts of Violence

DTIC Science & Technology

2016-06-01

observable to military law enforcement personnel. Statistical analyses tested for differences in warning signs between cases of suicide, violence, or...indicators, (2) Behavioral Change indicators, (3) Social indicators, and (4) Occupational indicators. Statistical analyses were conducted to test for...6 Coding _________________________________________________________________ 7 Statistical

[Statistical analysis using freely-available "EZR (Easy R)" software].

PubMed

Kanda, Yoshinobu

2015-10-01

Clinicians must often perform statistical analyses for purposes such evaluating preexisting evidence and designing or executing clinical studies. R is a free software environment for statistical computing. R supports many statistical analysis functions, but does not incorporate a statistical graphical user interface (GUI). The R commander provides an easy-to-use basic-statistics GUI for R. However, the statistical function of the R commander is limited, especially in the field of biostatistics. Therefore, the author added several important statistical functions to the R commander and named it "EZR (Easy R)", which is now being distributed on the following website: http://www.jichi.ac.jp/saitama-sct/. EZR allows the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates and so on, by point-and-click access. In addition, by saving the script automatically created by EZR, users can learn R script writing, maintain the traceability of the analysis, and assure that the statistical process is overseen by a supervisor.

Primary implant stability in a bone model simulating clinical situations for the posterior maxilla: an in vitro study

PubMed Central

2016-01-01

Purpose The aim of this study was to determine the influence of anatomical conditions on primary stability in the models simulating posterior maxilla. Methods Polyurethane blocks were designed to simulate monocortical (M) and bicortical (B) conditions. Each condition had four subgroups measuring 3 mm (M3, B3), 5 mm (M5, B5), 8 mm (M8, B8), and 12 mm (M12, B12) in residual bone height (RBH). After implant placement, the implant stability quotient (ISQ), Periotest value (PTV), insertion torque (IT), and reverse torque (RT) were measured. Two-factor ANOVA (two cortical conditions×four RBHs) and additional analyses for simple main effects were performed. Results A significant interaction between cortical condition and RBH was demonstrated for all methods measuring stability with two-factor ANOVA. In the analyses for simple main effects, ISQ and PTV were statistically higher in the bicortical groups than the corresponding monocortical groups, respectively. In the monocortical group, ISQ and PTV showed a statistically significant rise with increasing RBH. Measurements of IT and RT showed a similar tendency, measuring highest in the M3 group, followed by the M8, the M5, and the M12 groups. In the bicortical group, all variables showed a similar tendency, with different degrees of rise and decline. The B8 group showed the highest values, followed by the B12, the B5, and the B3 groups. The highest coefficient was demonstrated between ISQ and PTV. Conclusions Primary stability was enhanced by the presence of bicortex and increased RBH, which may be better demonstrated by ISQ and PTV than by IT and RT. PMID:27588215

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

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

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 (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 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. 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. 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. 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. © 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.

On Improving the Quality and Interpretation of Environmental Assessments using Statistical Analysis and Geographic Information Systems

NASA Astrophysics Data System (ADS)

Karuppiah, R.; Faldi, A.; Laurenzi, I.; Usadi, A.; Venkatesh, A.

2014-12-01

An increasing number of studies are focused on assessing the environmental footprint of different products and processes, especially using life cycle assessment (LCA). This work shows how combining statistical methods and Geographic Information Systems (GIS) with environmental analyses can help improve the quality of results and their interpretation. Most environmental assessments in literature yield single numbers that characterize the environmental impact of a process/product - typically global or country averages, often unchanging in time. In this work, we show how statistical analysis and GIS can help address these limitations. For example, we demonstrate a method to separately quantify uncertainty and variability in the result of LCA models using a power generation case study. This is important for rigorous comparisons between the impacts of different processes. Another challenge is lack of data that can affect the rigor of LCAs. We have developed an approach to estimate environmental impacts of incompletely characterized processes using predictive statistical models. This method is applied to estimate unreported coal power plant emissions in several world regions. There is also a general lack of spatio-temporal characterization of the results in environmental analyses. For instance, studies that focus on water usage do not put in context where and when water is withdrawn. Through the use of hydrological modeling combined with GIS, we quantify water stress on a regional and seasonal basis to understand water supply and demand risks for multiple users. Another example where it is important to consider regional dependency of impacts is when characterizing how agricultural land occupation affects biodiversity in a region. We developed a data-driven methodology used in conjuction with GIS to determine if there is a statistically significant difference between the impacts of growing different crops on different species in various biomes of the world.

Analysis of repeated measurement data in the clinical trials

PubMed Central

Singh, Vineeta; Rana, Rakesh Kumar; Singhal, Richa

2013-01-01

Statistics is an integral part of Clinical Trials. Elements of statistics span Clinical Trial design, data monitoring, analyses and reporting. A solid understanding of statistical concepts by clinicians improves the comprehension and the resulting quality of Clinical Trials. In biomedical research it has been seen that researcher frequently use t-test and ANOVA to compare means between the groups of interest irrespective of the nature of the data. In Clinical Trials we record the data on the patients more than two times. In such a situation using the standard ANOVA procedures is not appropriate as it does not consider dependencies between observations within subjects in the analysis. To deal with such types of study data Repeated Measure ANOVA should be used. In this article the application of One-way Repeated Measure ANOVA has been demonstrated by using the software SPSS (Statistical Package for Social Sciences) Version 15.0 on the data collected at four time points 0 day, 15th day, 30th day, and 45th day of multicentre clinical trial conducted on Pandu Roga (~Iron Deficiency Anemia) with an Ayurvedic formulation Dhatrilauha. PMID:23930038

An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.

PubMed

Kim, Junghi; Bai, Yun; Pan, Wei

2015-12-01

We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods. © 2015 WILEY PERIODICALS, INC.

High order statistical signatures from source-driven measurements of subcritical fissile systems

NASA Astrophysics Data System (ADS)

Mattingly, John Kelly

1998-11-01

This research focuses on the development and application of high order statistical analyses applied to measurements performed with subcritical fissile systems driven by an introduced neutron source. The signatures presented are derived from counting statistics of the introduced source and radiation detectors that observe the response of the fissile system. It is demonstrated that successively higher order counting statistics possess progressively higher sensitivity to reactivity. Consequently, these signatures are more sensitive to changes in the composition, fissile mass, and configuration of the fissile assembly. Furthermore, it is shown that these techniques are capable of distinguishing the response of the fissile system to the introduced source from its response to any internal or inherent sources. This ability combined with the enhanced sensitivity of higher order signatures indicates that these techniques will be of significant utility in a variety of applications. Potential applications include enhanced radiation signature identification of weapons components for nuclear disarmament and safeguards applications and augmented nondestructive analysis of spent nuclear fuel. In general, these techniques expand present capabilities in the analysis of subcritical measurements.

Statistical approaches in published ophthalmic clinical science papers: a comparison to statistical practice two decades ago.

PubMed

Zhang, Harrison G; Ying, Gui-Shuang

2018-02-09

The aim of this study is to evaluate the current practice of statistical analysis of eye data in clinical science papers published in British Journal of Ophthalmology ( BJO ) and to determine whether the practice of statistical analysis has improved in the past two decades. All clinical science papers (n=125) published in BJO in January-June 2017 were reviewed for their statistical analysis approaches for analysing primary ocular measure. We compared our findings to the results from a previous paper that reviewed BJO papers in 1995. Of 112 papers eligible for analysis, half of the studies analysed the data at an individual level because of the nature of observation, 16 (14%) studies analysed data from one eye only, 36 (32%) studies analysed data from both eyes at ocular level, one study (1%) analysed the overall summary of ocular finding per individual and three (3%) studies used the paired comparison. Among studies with data available from both eyes, 50 (89%) of 56 papers in 2017 did not analyse data from both eyes or ignored the intereye correlation, as compared with in 60 (90%) of 67 papers in 1995 (P=0.96). Among studies that analysed data from both eyes at an ocular level, 33 (92%) of 36 studies completely ignored the intereye correlation in 2017, as compared with in 16 (89%) of 18 studies in 1995 (P=0.40). A majority of studies did not analyse the data properly when data from both eyes were available. The practice of statistical analysis did not improve in the past two decades. Collaborative efforts should be made in the vision research community to improve the practice of statistical analysis for ocular data. © 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.

Using R-Project for Free Statistical Analysis in Extension Research

ERIC Educational Resources Information Center

Mangiafico, Salvatore S.

2013-01-01

One option for Extension professionals wishing to use free statistical software is to use online calculators, which are useful for common, simple analyses. A second option is to use a free computing environment capable of performing statistical analyses, like R-project. R-project is free, cross-platform, powerful, and respected, but may be…

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

Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

PubMed

Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

2016-06-01

Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (p<0.001) compared to BCC tissue group. Histopathology indicated that these differences partially arise from BCC-related characteristic changes in tissue morphology. Wilks lambda statistics demonstrated the potential of all investigated polarimetric properties for computer assisted classification of the two tissue groups. Based on differences in polarimetric properties, partial least square (PLS) regression classified the samples with 100% accuracy, sensitivity and specificity. These findings indicate that optical polarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. 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.

A canonical neural mechanism for behavioral variability

NASA Astrophysics Data System (ADS)

Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

2017-05-01

The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.

Bullying as a Stressor in Mid-Adolescent Girls and Boys-Associations with Perceived Stress, Recurrent Pain, and Salivary Cortisol.

PubMed

Östberg, Viveca; Låftman, Sara B; Modin, Bitte; Lindfors, Petra

2018-02-20

Bullying involves repeated exposure to negative actions while also invoking a power asymmetry between the involved parties. From a stress perspective, being bullied can be seen as a severe and chronic stressor, and an everyday social-evaluative threat, coupled with a shortage of effective social resources for dealing with this particular stressor. The aim of this study was to investigate whether exposure to bullying among mid-adolescent girls and boys is associated with subjective and objective stress-related outcomes in terms of perceived stress, recurrent pain, and salivary cortisol. The data came from the School Stress and Support Study (TriSSS) including students in grades 8-9 in two schools in Stockholm, Sweden, in 2010 (study sample n = 392; cortisol subsample n = 198). Bullying was self-reported and measured by multiple items. The statistical analyses included binary logistic and linear (OLS) regression. Being bullied was associated with greater perceived stress and an increased risk of recurrent pain, among both boys and girls. Also, bullied students had lower cortisol output (AUC G ) and lower cortisol awakening response (CAR G ) as compared to those who were not bullied. Gender-stratified analyses demonstrated that these associations were statistically significant for boys but not for girls. In conclusion, this study demonstrated that being bullied was related to both subjective and objective stress markers among mid-adolescent girls and boys, pointing to the necessity of continuously working against bullying.

Toxic essential oils. Part V: Behaviour modulating and toxic properties of thujones and thujone-containing essential oils of Salvia officinalis L., Artemisia absinthium L., Thuja occidentalis L. and Tanacetum vulgare L.

PubMed

Radulović, Niko S; Genčić, Marija S; Stojanović, Nikola M; Randjelović, Pavle J; Stojanović-Radić, Zorica Z; Stojiljković, Nenad I

2017-07-01

Neurotoxic thujones (α- and β-diastereoisomers) are common constituents of plant essential oils. In this study, we employed a statistical approach to determine the contribution of thujones to the overall observed behaviour-modulating and toxic effects of essential oils (Salvia officinalis L., Artemisia absinthium L., Thuja occidentalis L. and Tanacetum vulgare L.) containing these monoterpene ketones. The data from three in vivo neuropharmacological tests on rats (open field, light-dark, and diazepam-induced sleep), and toxicity assays (brine shrimp, and antimicrobial activity against a panel of microorganisms), together with the data from detailed chemical analyses, were subjected to a multivariate statistical treatment to reveal the possible correlation(s) between the content of essential-oil constituents and the observed effects. The results strongly imply that the toxic and behaviour-modulating activity of the oils (hundreds of constituents) should not be associated exclusively with thujones. The statistical analyses pinpointed to a number of essential-oil constituents other than thujones that demonstrated a clear correlation with either the toxicity, antimicrobial effect or the activity on CNS. Thus, in addition to the thujone content, the amount and toxicity of other constituents should be taken into consideration when making risk assessment and determining the regulatory status of plants in food and medicines. Copyright © 2017 Elsevier Ltd. All rights reserved.

diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.

PubMed

Lun, Aaron T L; Smyth, Gordon K

2015-08-19

Chromatin conformation capture with high-throughput sequencing (Hi-C) is a technique that measures the in vivo intensity of interactions between all pairs of loci in the genome. Most conventional analyses of Hi-C data focus on the detection of statistically significant interactions. However, an alternative strategy involves identifying significant changes in the interaction intensity (i.e., differential interactions) between two or more biological conditions. This is more statistically rigorous and may provide more biologically relevant results. Here, we present the diffHic software package for the detection of differential interactions from Hi-C data. diffHic provides methods for read pair alignment and processing, counting into bin pairs, filtering out low-abundance events and normalization of trended or CNV-driven biases. It uses the statistical framework of the edgeR package to model biological variability and to test for significant differences between conditions. Several options for the visualization of results are also included. The use of diffHic is demonstrated with real Hi-C data sets. Performance against existing methods is also evaluated with simulated data. On real data, diffHic is able to successfully detect interactions with significant differences in intensity between biological conditions. It also compares favourably to existing software tools on simulated data sets. These results suggest that diffHic is a viable approach for differential analyses of Hi-C data.

Robust approaches to quantification of margin and uncertainty for sparse data

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

Hund, Lauren; Schroeder, Benjamin B.; Rumsey, Kelin

Characterizing the tails of probability distributions plays a key role in quantification of margins and uncertainties (QMU), where the goal is characterization of low probability, high consequence events based on continuous measures of performance. When data are collected using physical experimentation, probability distributions are typically fit using statistical methods based on the collected data, and these parametric distributional assumptions are often used to extrapolate about the extreme tail behavior of the underlying probability distribution. In this project, we character- ize the risk associated with such tail extrapolation. Specifically, we conducted a scaling study to demonstrate the large magnitude of themore » risk; then, we developed new methods for communicat- ing risk associated with tail extrapolation from unvalidated statistical models; lastly, we proposed a Bayesian data-integration framework to mitigate tail extrapolation risk through integrating ad- ditional information. We conclude that decision-making using QMU is a complex process that cannot be achieved using statistical analyses alone.« less

A phylogenetic transform enhances analysis of compositional microbiota data

PubMed Central

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-01-01

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities. DOI: http://dx.doi.org/10.7554/eLife.21887.001 PMID:28198697

Using conventional F-statistics to study unconventional sex-chromosome differentiation.

PubMed

Rodrigues, Nicolas; Dufresnes, Christophe

2017-01-01

Species with undifferentiated sex chromosomes emerge as key organisms to understand the astonishing diversity of sex-determination systems. Whereas new genomic methods are widening opportunities to study these systems, the difficulty to separately characterize their X and Y homologous chromosomes poses limitations. Here we demonstrate that two simple F -statistics calculated from sex-linked genotypes, namely the genetic distance ( F st ) between sexes and the inbreeding coefficient ( F is ) in the heterogametic sex, can be used as reliable proxies to compare sex-chromosome differentiation between populations. We correlated these metrics using published microsatellite data from two frog species ( Hyla arborea and Rana temporaria ), and show that they intimately relate to the overall amount of X-Y differentiation in populations. However, the fits for individual loci appear highly variable, suggesting that a dense genetic coverage will be needed for inferring fine-scale patterns of differentiation along sex-chromosomes. The applications of these F -statistics, which implies little sampling requirement, significantly facilitate population analyses of sex-chromosomes.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

PubMed

Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

Influence of family environment on language outcomes in children with myelomeningocele.

PubMed

Vachha, B; Adams, R

2005-09-01

Previously, our studies demonstrated language differences impacting academic performance among children with myelomeningocele and shunted hydrocephalus (MMSH). This follow-up study considers the environmental facilitators within families (achievement orientation, intellectual-cultural orientation, active recreational orientation, independence) among a cohort of children with MMSH and their relationship to language performance. Fifty-eight monolingual, English-speaking children (36 females; mean age: 10.1 years; age range: 7-16 years) with MMSH were evaluated. Exclusionary criteria were prior shunt infection; seizure or shunt malfunction within the previous 3 months; uncorrected visual or auditory impairments; prior diagnoses of mental retardation or attention deficit disorder. The Comprehensive Assessment of Spoken Language (CASL) and the Wechsler Abbreviated Scale of Intelligence (WASI) were administered individually to all participants. The CASL Measures four subsystems: lexical, syntactic, supralinguistic and pragmatic. Parents completed the Family Environment Scale (FES) questionnaire and provided background demographic information. Spearman correlation analyses and partial correlation analyses were performed. Mean intelligence scores for the MMSH group: full scale IQ 92.2 (SD = 11.9). The CASL revealed statistically significant difficulty for supralinguistic and pragmatic (or social) language tasks. FES scores fell within the average range for the group. Spearman correlation and partial correlation analyses revealed statistically significant positive relationships for the FES 'intellectual-cultural orientation' variable and performance within the four language subsystems. Socio-economic status (SES) characteristics were analyzed and did not discriminate language performance when the intellectual-cultural orientation factor was taken into account. The role of family facilitators on language skills in children with MMSH has not previously been described. The relationship between language performance and the families' value on intellectual/cultural activities seems both statistically and intuitively sound. Focused interest in the integration of family values and practices should assist developmental specialists in supporting families and children within their most natural environment.

Predictors of persistent pain after total knee arthroplasty: a systematic review and meta-analysis.

PubMed

Lewis, G N; Rice, D A; McNair, P J; Kluger, M

2015-04-01

Several studies have identified clinical, psychosocial, patient characteristic, and perioperative variables that are associated with persistent postsurgical pain; however, the relative effect of these variables has yet to be quantified. The aim of the study was to provide a systematic review and meta-analysis of predictor variables associated with persistent pain after total knee arthroplasty (TKA). Included studies were required to measure predictor variables prior to or at the time of surgery, include a pain outcome measure at least 3 months post-TKA, and include a statistical analysis of the effect of the predictor variable(s) on the outcome measure. Counts were undertaken of the number of times each predictor was analysed and the number of times it was found to have a significant relationship with persistent pain. Separate meta-analyses were performed to determine the effect size of each predictor on persistent pain. Outcomes from studies implementing uni- and multivariable statistical models were analysed separately. Thirty-two studies involving almost 30 000 patients were included in the review. Preoperative pain was the predictor that most commonly demonstrated a significant relationship with persistent pain across uni- and multivariable analyses. In the meta-analyses of data from univariate models, the largest effect sizes were found for: other pain sites, catastrophizing, and depression. For data from multivariate models, significant effects were evident for: catastrophizing, preoperative pain, mental health, and comorbidities. Catastrophizing, mental health, preoperative knee pain, and pain at other sites are the strongest independent predictors of persistent pain after TKA. © The Author 2014. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Association Study between Lead and Zinc Accumulation at Different Physiological Systems of Cattle by Canonical Correlation and Canonical Correspondence Analyses

NASA Astrophysics Data System (ADS)

Karmakar, Partha; Das, Pradip Kumar; Mondal, Seema Sarkar; Karmakar, Sougata; Mazumdar, Debasis

2010-10-01

Pb pollution from automobile exhausts around highways is a persistent problem in India. Pb intoxication in mammalian body is a complex phenomenon which is influence by agonistic and antagonistic interactions of several other heavy metals and micronutrients. An attempt has been made to study the association between Pb and Zn accumulation in different physiological systems of cattles (n = 200) by application of both canonical correlation and canonical correspondence analyses. Pb was estimated from plasma, liver, bone, muscle, kidney, blood and milk where as Zn was measured from all these systems except bone, blood and milk. Both statistical techniques demonstrated that there was a strong association among blood-Pb, liver-Zn, kidney-Zn and muscle-Zn. From observations, it can be assumed that Zn accumulation in cattles' muscle, liver and kidney directs Pb mobilization from those organs which in turn increases Pb pool in blood. It indicates antagonistic activity of Zn to the accumulation of Pb. Although there were some contradictions between the observations obtained from the two different statistical methods, the overall pattern of Pb accumulation in various organs as influenced by Zn were same. It is mainly due to the fact that canonical correlation is actually a special type of canonical correspondence analyses where linear relationship is followed between two groups of variables instead of Gaussian relationship.

Comparison of bacterial community structure and dynamics during the thermophilic composting of different types of solid wastes: anaerobic digestion residue, pig manure and chicken manure.

PubMed

Song, Caihong; Li, Mingxiao; Jia, Xuan; Wei, Zimin; Zhao, Yue; Xi, Beidou; Zhu, Chaowei; Liu, Dongming

2014-09-01

This study investigated the impact of composting substrate types on the bacterial community structure and dynamics during composting processes. To this end, pig manure (PM), chicken manure (CM), a mixture of PM and CM (PM + CM), and a mixture of PM, CM and anaerobic digestion residue (ADR) (PM + CM + ADR) were selected for thermophilic composting. The bacterial community structure and dynamics during the composting process were detected and analysed by polymerase chain reaction-denaturing gradient gel electrophoresis (DGGE) coupled with a statistic analysis. The physical-chemical analyses indicated that compared to single-material composting (PM, CM), co-composting (PM + CM, PM + CM + ADR) could promote the degradation of organic matter and strengthen the ability of conserving nitrogen. A DGGE profile and statistical analysis demonstrated that co-composting, especially PM + CM + ADR, could improve the bacterial community structure and functional diversity, even in the thermophilic stage. Therefore, co-composting could weaken the screening effect of high temperature on bacterial communities. Dominant sequencing analyses indicated a dramatic shift in the dominant bacterial communities from single-material composting to co-composting. Notably, compared with PM, PM + CM increased the quantity of xylan-degrading bacteria and reduced the quantity of human pathogens. © 2014 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Hospital inpatient self-administration of medicine programmes: a critical literature review.

PubMed

Wright, Julia; Emerson, Angela; Stephens, Martin; Lennan, Elaine

2006-06-01

The Department of Health, pharmaceutical and nursing bodies have advocated the benefits of self-administration programmes (SAPs), but their implementation within UK hospitals has been limited. Perceived barriers are: anticipated increased workload, insufficient resources and patient safety concerns. This review aims to discover if benefits of SAPs are supported in the literature in relation to risk and resource implications. Electronic databases were searched up to March 2004. Published English language articles that described and evaluated implementation of an SAP were included. Outcomes reported were: compliance measures, errors, knowledge, patient satisfaction, and nursing and pharmacy time. Most of the 51 papers reviewed had methodological flaws. SAPs varied widely in content and structure. Twelve studies (10 controlled) measured compliance by tablet counts. Of 7 studies subjected to statistical analysis, four demonstrated a significant difference in compliance between SAP and controls. Eight studies (5 controlled) measured errors as an outcome. Of the two evaluated statistically, only one demonstrated significantly fewer medication errors in the SAP group than in controls. Seventeen papers (11 controlled) studied the effect of SAPs on patients' medication knowledge. Ten of the 11 statistically analysed studies showed that SAP participants knew significantly more about some aspects of their medication than did controls. Seventeen studies (5 controlled), measured patient satisfaction. Two studies were statistically analysed and these studies suggested that patients were satisfied and preferred SAP. Seven papers studied pharmacy time, three studied nursing time but results were not compared to controls. The paucity of well-designed studies, flawed methodology and inadequate reporting in many papers make conclusions hard to draw. Conclusive evidence that SAPs improve compliance was not provided. Although patients participating in SAPs make errors, small numbers of patients are often responsible for a large number of errors. Whilst most studies suggest that SAPs increase patient's knowledge in part, it is difficult to separate out the effect of the educational component of many SAPs. Most patients who participated in SAPs were satisfied with their care and many would choose to take part in a SAP in the future. No studies measured the total resource requirement of implementing and maintaining a SAP.

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character. 

Biomechanical Analysis of Military Boots. Phase 1. Materials Testing of Military and Commercial Footwear

DTIC Science & Technology

1992-10-01

N=8) and Results of 44 Statistical Analyses for Impact Test Performed on Forefoot of Unworn Footwear A-2. Summary Statistics (N=8) and Results of...on Forefoot of Worn Footwear Vlll Tables (continued) Table Page B-2. Summary Statistics (N=4) and Results of 76 Statistical Analyses for Impact...used tests to assess heel and forefoot shock absorption, upper and sole durability, and flexibility (Cavanagh, 1978). Later, the number of tests was

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

PubMed Central

2011-01-01

Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim. PMID:21473747

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Statistical review. Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. The median power to detect small, medium, and large effect sizes was .40 (interquartile range [IQR]=.24-.71), .98 (IQR=.85-1.00), and 1.00 (IQR=1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR=.26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Quantum behaviour of open pumped and damped Bose-Hubbard trimers

NASA Astrophysics Data System (ADS)

Chianca, C. V.; Olsen, M. K.

2018-01-01

We propose and analyse analogs of optical cavities for atoms using three-well inline Bose-Hubbard models with pumping and losses. With one well pumped and one damped, we find that both the mean-field dynamics and the quantum statistics show a qualitative dependence on the choice of damped well. The systems we analyse remain far from equilibrium, although most do enter a steady-state regime. We find quadrature squeezing, bipartite and tripartite inseparability and entanglement, and states exhibiting the EPR paradox, depending on the parameter regimes. We also discover situations where the mean-field solutions of our models are noticeably different from the quantum solutions for the mean fields. Due to recent experimental advances, it should be possible to demonstrate the effects we predict and investigate in this article.

Information filtering via biased heat conduction.

PubMed

Liu, Jian-Guo; Zhou, Tao; Guo, Qiang

2011-09-01

The process of heat conduction has recently found application in personalized recommendation [Zhou et al., Proc. Natl. Acad. Sci. USA 107, 4511 (2010)], which is of high diversity but low accuracy. By decreasing the temperatures of small-degree objects, we present an improved algorithm, called biased heat conduction, which could simultaneously enhance the accuracy and diversity. Extensive experimental analyses demonstrate that the accuracy on MovieLens, Netflix, and Delicious datasets could be improved by 43.5%, 55.4% and 19.2%, respectively, compared with the standard heat conduction algorithm and also the diversity is increased or approximately unchanged. Further statistical analyses suggest that the present algorithm could simultaneously identify users' mainstream and special tastes, resulting in better performance than the standard heat conduction algorithm. This work provides a creditable way for highly efficient information filtering.

A study of the comparative effects of various means of motion cueing during a simulated compensatory tracking task

NASA Technical Reports Server (NTRS)

Mckissick, B. T.; Ashworth, B. R.; Parrish, R. V.; Martin, D. J., Jr.

1980-01-01

NASA's Langley Research Center conducted a simulation experiment to ascertain the comparative effects of motion cues (combinations of platform motion and g-seat normal acceleration cues) on compensatory tracking performance. In the experiment, a full six-degree-of-freedom YF-16 model was used as the simulated pursuit aircraft. The Langley Visual Motion Simulator (with in-house developed wash-out), and a Langley developed g-seat were principal components of the simulation. The results of the experiment were examined utilizing univariate and multivariate techniques. The statistical analyses demonstrate that the platform motion and g-seat cues provide additional information to the pilot that allows substantial reduction of lateral tracking error. Also, the analyses show that the g-seat cue helps reduce vertical error.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.

PubMed

Skinner, Jeff; Kotliarov, Yuri; Varma, Sudhir; Mine, Karina L; Yambartsev, Anatoly; Simon, Richard; Huyen, Yentram; Morgun, Andrey

2011-07-14

DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Exploring Science Teachers' Affective States: Pedagogical Discontentment, Self-efficacy, Intentions to Reform, and Their Relationships

NASA Astrophysics Data System (ADS)

Kahveci, Ajda; Kahveci, Murat; Mansour, Nasser; Alarfaj, Maher Mohammed

2017-06-01

Teachers play a key role in moving reform-based science education practices into the classroom. Based on research that emphasizes the importance of teachers' affective states, this study aimed to explore the constructs pedagogical discontentment, science teaching self-efficacy, intentions to reform, and their correlations. Also, it aimed to provide empirical evidence in light of a previously proposed theoretical model while focusing on an entirely new context in Middle East. Data were collected in Saudi Arabia with a total of randomly selected 994 science teachers, 656 of whom were females and 338 were males. To collect the data, the Arabic versions of the Science Teachers' Pedagogical Discontentment scale, the Science Teaching Efficacy Beliefs Instrument and the Intentions to Reform Science Teaching scale were developed. For assuring the validity of the instruments in a non-Western context, rigorous cross-cultural validations procedures were followed. Factor analyses were conducted for construct validation and descriptive statistical analyses were performed including frequency distributions and normality checks. Univariate analyses of variance were run to explore statistically significant differences between groups of teachers. Cross-tabulation and correlation analyses were conducted to explore relationships. The findings suggest effect of teacher characteristics such as age and professional development program attendance on the affective states. The results demonstrate that teachers who attended a relatively higher number of programs had lower level of intentions to reform raising issues regarding the conduct and outcomes of professional development. Some of the findings concerning interrelationships among the three constructs challenge and serve to expand the previously proposed theoretical model.

Empirically Derived Personality Subtyping for Predicting Clinical Symptoms and Treatment Response in Bulimia Nervosa

PubMed Central

Haynos, Ann F.; Pearson, Carolyn M.; Utzinger, Linsey M.; Wonderlich, Stephen A.; Crosby, Ross D.; Mitchell, James E.; Crow, Scott J.; Peterson, Carol B.

2016-01-01

Objective Evidence suggests that eating disorder subtypes reflecting under-controlled, over-controlled, and low psychopathology personality traits constitute reliable phenotypes that differentiate treatment response. This study is the first to use statistical analyses to identify these subtypes within treatment-seeking individuals with bulimia nervosa (BN) and to use these statistically derived clusters to predict clinical outcomes. Methods Using variables from the Dimensional Assessment of Personality Pathology–Basic Questionnaire, K-means cluster analyses identified under-controlled, over-controlled, and low psychopathology subtypes within BN patients (n = 80) enrolled in a treatment trial. Generalized linear models examined the impact of personality subtypes on Eating Disorder Examination global score, binge eating frequency, and purging frequency cross-sectionally at baseline and longitudinally at end of treatment (EOT) and follow-up. In the longitudinal models, secondary analyses were conducted to examine personality subtype as a potential moderator of response to Cognitive Behavioral Therapy-Enhanced (CBT-E) or Integrative Cognitive-Affective Therapy for BN (ICAT-BN). Results There were no baseline clinical differences between groups. In the longitudinal models, personality subtype predicted binge eating (p = .03) and purging (p = .01) frequency at EOT and binge eating frequency at follow-up (p = .045). The over-controlled group demonstrated the best outcomes on these variables. In secondary analyses, there was a treatment by subtype interaction for purging at follow-up (p = .04), which indicated a superiority of CBT-E over ICAT-BN for reducing purging among the over-controlled group. Discussion Empirically derived personality subtyping is appears to be a valid classification system with potential to guide eating disorder treatment decisions. PMID:27611235

40 CFR 91.512 - Request for public hearing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis for... will be made available to the public during Agency business hours. ...

A retrospective survey of research design and statistical analyses in selected Chinese medical journals in 1998 and 2008.

PubMed

Jin, Zhichao; Yu, Danghui; Zhang, Luoman; Meng, Hong; Lu, Jian; Gao, Qingbin; Cao, Yang; Ma, Xiuqiang; Wu, Cheng; He, Qian; Wang, Rui; He, Jia

2010-05-25

High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative.

A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology

ERIC Educational Resources Information Center

Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.

2010-01-01

This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

Seeking a fingerprint: analysis of point processes in actigraphy recording

NASA Astrophysics Data System (ADS)

Gudowska-Nowak, Ewa; Ochab, Jeremi K.; Oleś, Katarzyna; Beldzik, Ewa; Chialvo, Dante R.; Domagalik, Aleksandra; Fąfrowicz, Magdalena; Marek, Tadeusz; Nowak, Maciej A.; Ogińska, Halszka; Szwed, Jerzy; Tyburczyk, Jacek

2016-05-01

Motor activity of humans displays complex temporal fluctuations which can be characterised by scale-invariant statistics, thus demonstrating that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Previous studies on humans regularly deprived of sleep or suffering from sleep disorders predicted a change in the invariant scale parameters with respect to those for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organisation can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterising complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterising slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups.

Effects of different preservation methods on inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) molecular markers in botanic samples.

PubMed

Wang, Xiaolong; Li, Lin; Zhao, Jiaxin; Li, Fangliang; Guo, Wei; Chen, Xia

2017-04-01

To evaluate the effects of different preservation methods (stored in a -20°C ice chest, preserved in liquid nitrogen and dried in silica gel) on inter simple sequence repeat (ISSR) or random amplified polymorphic DNA (RAPD) analyses in various botanical specimens (including broad-leaved plants, needle-leaved plants and succulent plants) for different times (three weeks and three years), we used a statistical analysis based on the number of bands, genetic index and cluster analysis. The results demonstrate that methods used to preserve samples can provide sufficient amounts of genomic DNA for ISSR and RAPD analyses; however, the effect of different preservation methods on these analyses vary significantly, and the preservation time has little effect on these analyses. Our results provide a reference for researchers to select the most suitable preservation method depending on their study subject for the analysis of molecular markers based on genomic DNA. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Algorithm for Identifying Erroneous Rain-Gauge Readings

NASA Technical Reports Server (NTRS)

Rickman, Doug

2005-01-01

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

A canonical neural mechanism for behavioral variability

PubMed Central

Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

2017-01-01

The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5–6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these ‘universal' statistics. PMID:28530225

A psychometric evaluation of the Rorschach comprehensive system's perceptual thinking index.

PubMed

Dao, Tam K; Prevatt, Frances

2006-04-01

In this study, we investigated evidence for reliability and validity of the Perceptual Thinking Index (PTI; Exner, 2000a, 2000b) among an adult inpatient population. We conducted reliability and validity analyses on 107 patients who met the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision; American Psychiatric Association, 2000) criteria for a schizophrenia-spectrum disorder (SSD) or mood disorder with no psychotic features (MD). Results provided support for interrater reliability as well as internal consistency of the PTI. Furthermore, the PTI was an effective index in differentiating SSD patients from patients diagnosed with an MD. Finally, the PTI demonstrated adequate diagnostic statistics that can be useful in the classification of patients diagnosed with SSD and MD. We discuss methodological issues, implications for assessment practice, and directions for future research.

Usefulness and limitations of various guinea-pig test methods in detecting human skin sensitizers-validation of guinea-pig tests for skin hypersensitivity.

PubMed

Marzulli, F; Maguire, H C

1982-02-01

Several guinea-pig predictive test methods were evaluated by comparison of results with those obtained with human predictive tests, using ten compounds that have been used in cosmetics. The method involves the statistical analysis of the frequency with which guinea-pig tests agree with the findings of tests in humans. In addition, the frequencies of false positive and false negative predictive findings are considered and statistically analysed. The results clearly demonstrate the superiority of adjuvant tests (complete Freund's adjuvant) in determining skin sensitizers and the overall superiority of the guinea-pig maximization test in providing results similar to those obtained by human testing. A procedure is suggested for utilizing adjuvant and non-adjuvant test methods for characterizing compounds as of weak, moderate or strong sensitizing potential.

Citation of previous meta-analyses on the same topic: a clue to perpetuation of incorrect methods?

PubMed

Li, Tianjing; Dickersin, Kay

2013-06-01

Systematic reviews and meta-analyses serve as a basis for decision-making and clinical practice guidelines and should be carried out using appropriate methodology to avoid incorrect inferences. We describe the characteristics, statistical methods used for meta-analyses, and citation patterns of all 21 glaucoma systematic reviews we identified pertaining to the effectiveness of prostaglandin analog eye drops in treating primary open-angle glaucoma, published between December 2000 and February 2012. We abstracted data, assessed whether appropriate statistical methods were applied in meta-analyses, and examined citation patterns of included reviews. We identified two forms of problematic statistical analyses in 9 of the 21 systematic reviews examined. Except in 1 case, none of the 9 reviews that used incorrect statistical methods cited a previously published review that used appropriate methods. Reviews that used incorrect methods were cited 2.6 times more often than reviews that used appropriate statistical methods. We speculate that by emulating the statistical methodology of previous systematic reviews, systematic review authors may have perpetuated incorrect approaches to meta-analysis. The use of incorrect statistical methods, perhaps through emulating methods described in previous research, calls conclusions of systematic reviews into question and may lead to inappropriate patient care. We urge systematic review authors and journal editors to seek the advice of experienced statisticians before undertaking or accepting for publication a systematic review and meta-analysis. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Reporting quality of statistical methods in surgical observational studies: protocol for systematic review.

PubMed

Wu, Robert; Glen, Peter; Ramsay, Tim; Martel, Guillaume

2014-06-28

Observational studies dominate the surgical literature. Statistical adjustment is an important strategy to account for confounders in observational studies. Research has shown that published articles are often poor in statistical quality, which may jeopardize their conclusions. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines have been published to help establish standards for statistical reporting.This study will seek to determine whether the quality of statistical adjustment and the reporting of these methods are adequate in surgical observational studies. We hypothesize that incomplete reporting will be found in all surgical observational studies, and that the quality and reporting of these methods will be of lower quality in surgical journals when compared with medical journals. Finally, this work will seek to identify predictors of high-quality reporting. This work will examine the top five general surgical and medical journals, based on a 5-year impact factor (2007-2012). All observational studies investigating an intervention related to an essential component area of general surgery (defined by the American Board of Surgery), with an exposure, outcome, and comparator, will be included in this systematic review. Essential elements related to statistical reporting and quality were extracted from the SAMPL guidelines and include domains such as intent of analysis, primary analysis, multiple comparisons, numbers and descriptive statistics, association and correlation analyses, linear regression, logistic regression, Cox proportional hazard analysis, analysis of variance, survival analysis, propensity analysis, and independent and correlated analyses. Each article will be scored as a proportion based on fulfilling criteria in relevant analyses used in the study. A logistic regression model will be built to identify variables associated with high-quality reporting. A comparison will be made between the scores of surgical observational studies published in medical versus surgical journals. Secondary outcomes will pertain to individual domains of analysis. Sensitivity analyses will be conducted. This study will explore the reporting and quality of statistical analyses in surgical observational studies published in the most referenced surgical and medical journals in 2013 and examine whether variables (including the type of journal) can predict high-quality reporting.

Statistical analyses of commercial vehicle accident factors. Volume 1 Part 1

DOT National Transportation Integrated Search

1978-02-01

Procedures for conducting statistical analyses of commercial vehicle accidents have been established and initially applied. A file of some 3,000 California Highway Patrol accident reports from two areas of California during a period of about one year...

40 CFR 90.712 - Request for public hearing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sampling plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis... Clerk and will be made available to the public during Agency business hours. ...

A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

PubMed

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A Quantitative Analysis of Latino Acculturation and Alcohol Use: Myth Versus Reality.

PubMed

Alvarez, Miriam J; Frietze, Gabriel; Ramos, Corin; Field, Craig; Zárate, Michael A

2017-07-01

Research on health among Latinos often focuses on acculturation processes and the associated stressors that influence drinking behavior. Given the common use of acculturation measures and the state of the knowledge on alcohol-related health among Latino populations, the current analyses tested the efficacy of acculturation measures to predict various indicators of alcohol consumption. Specifically, this quantitative review assessed the predictive utility of acculturation on alcohol consumption behaviors (frequency, volume, and quantity). Two main analyses were conducted-a p-curve analysis and a meta-analysis of the observed associations between acculturation and drinking behavior. Results demonstrated that current measures of acculturation are a statistically significant predictor of alcohol use (Z = -20.75, p < 0.0001). The meta-analysis included a cumulative sample size of 29,589 Latino participants across 31 studies. A random-effects model yielded a weighted average correlation of 0.16 (95% confidence interval = 0.12, 0.19). Additional subgroup analyses examined the effects of gender and using different scales to measure acculturation. Altogether, results demonstrated that acculturation is a useful predictor of alcohol use. In addition, the meta-analysis revealed that a small positive correlation exists between acculturation and alcohol use in Latinos with a between-study variance of only 1.5% (τ 2  = 0.015). Our analyses reveal that the association between current measures of acculturation and alcohol use is relatively small. Copyright © 2017 by the Research Society on Alcoholism.

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

PubMed Central

Zhang, Lin; Vranckx, Katleen; Janssens, Koen; Sandrin, Todd R.

2015-01-01

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level. PMID:25590854

Use of MALDI-TOF mass spectrometry and a custom database to characterize bacteria indigenous to a unique cave environment (Kartchner Caverns, AZ, USA).

PubMed

Zhang, Lin; Vranckx, Katleen; Janssens, Koen; Sandrin, Todd R

2015-01-02

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

Analysis of longitudinal data from animals where some data are missing in SPSS

PubMed Central

Duricki, DA; Soleman, S; Moon, LDF

2017-01-01

Testing of therapies for disease or injury often involves analysis of longitudinal data from animals. Modern analytical methods have advantages over conventional methods (particularly where some data are missing) yet are not used widely by pre-clinical researchers. We provide here an easy to use protocol for analysing longitudinal data from animals and present a click-by-click guide for performing suitable analyses using the statistical package SPSS. We guide readers through analysis of a real-life data set obtained when testing a therapy for brain injury (stroke) in elderly rats. We show that repeated measures analysis of covariance failed to detect a treatment effect when a few data points were missing (due to animal drop-out) whereas analysis using an alternative method detected a beneficial effect of treatment; specifically, we demonstrate the superiority of linear models (with various covariance structures) analysed using Restricted Maximum Likelihood estimation (to include all available data). This protocol takes two hours to follow. PMID:27196723

Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition

PubMed Central

Schilbach, Leonhard; Bzdok, Danilo; Timmermans, Bert; Fox, Peter T.; Laird, Angela R.; Vogeley, Kai; Eickhoff, Simon B.

2012-01-01

Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states. PMID:22319593

Supply Chain Collaboration: Information Sharing in a Tactical Operating Environment

DTIC Science & Technology

2013-06-01

architecture, there are four tiers: Client (Web Application Clients ), Presentation (Web-Server), Processing (Application-Server), Data (Database...organization in each period. This data will be collected to analyze. i) Analyses and Validation: We will do a statistics test in this data, Pareto ...notes, outstanding deliveries, and inventory. i) Analyses and Validation: We will do a statistics test in this data, Pareto analyses and confirmation

Statistic analyses of the color experience according to the age of the observer.

PubMed

Hunjet, Anica; Parac-Osterman, Durdica; Vucaj, Edita

2013-04-01

Psychological experience of color is a real state of the communication between the environment and color, and it will depend on the source of the light, angle of the view, and particular on the observer and his health condition. Hering's theory or a theory of the opponent processes supposes that cones, which are situated in the retina of the eye, are not sensible on the three chromatic domains (areas, fields, zones) (red, green and purple-blue), but they produce a signal based on the principle of the opposed pairs of colors. A reason of this theory depends on the fact that certain disorders of the color eyesight, which include blindness to certain colors, cause blindness to pairs of opponent colors. This paper presents a demonstration of the experience of blue and yellow tone according to the age of the observer. For the testing of the statistically significant differences in the omission in the color experience according to the color of the background we use following statistical tests: Mann-Whitnney U Test, Kruskal-Wallis ANOVA and Median test. It was proven that the differences are statistically significant in the elderly persons (older than 35 years).

Analysis of Feature Intervisibility and Cumulative Visibility Using GIS, Bayesian and Spatial Statistics: A Study from the Mandara Mountains, Northern Cameroon

PubMed Central

Wright, David K.; MacEachern, Scott; Lee, Jaeyong

2014-01-01

The locations of diy-geδ-bay (DGB) sites in the Mandara Mountains, northern Cameroon are hypothesized to occur as a function of their ability to see and be seen from points on the surrounding landscape. A series of geostatistical, two-way and Bayesian logistic regression analyses were performed to test two hypotheses related to the intervisibility of the sites to one another and their visual prominence on the landscape. We determine that the intervisibility of the sites to one another is highly statistically significant when compared to 10 stratified-random permutations of DGB sites. Bayesian logistic regression additionally demonstrates that the visibility of the sites to points on the surrounding landscape is statistically significant. The location of sites appears to have also been selected on the basis of lower slope than random permutations of sites. Using statistical measures, many of which are not commonly employed in archaeological research, to evaluate aspects of visibility on the landscape, we conclude that the placement of DGB sites improved their conspicuousness for enhanced ritual, social cooperation and/or competition purposes. PMID:25383883

An Asynchronous Many-Task Implementation of In-Situ Statistical Analysis using Legion.

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

Pebay, Philippe Pierre; Bennett, Janine Camille

2015-11-01

In this report, we propose a framework for the design and implementation of in-situ analy- ses using an asynchronous many-task (AMT) model, using the Legion programming model together with the MiniAero mini-application as a surrogate for full-scale parallel scientific computing applications. The bulk of this work consists of converting the Learn/Derive/Assess model which we had initially developed for parallel statistical analysis using MPI [PTBM11], from a SPMD to an AMT model. In this goal, we propose an original use of the concept of Legion logical regions as a replacement for the parallel communication schemes used for the only operation ofmore » the statistics engines that require explicit communication. We then evaluate this proposed scheme in a shared memory environment, using the Legion port of MiniAero as a proxy for a full-scale scientific application, as a means to provide input data sets of variable size for the in-situ statistical analyses in an AMT context. We demonstrate in particular that the approach has merit, and warrants further investigation, in collaboration with ongoing efforts to improve the overall parallel performance of the Legion system.« less

Statistical Methods Applied to Gamma-ray Spectroscopy Algorithms in Nuclear Security Missions

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

Fagan, Deborah K.; Robinson, Sean M.; Runkle, Robert C.

2012-10-01

In a wide range of nuclear security missions, gamma-ray spectroscopy is a critical research and development priority. One particularly relevant challenge is the interdiction of special nuclear material for which gamma-ray spectroscopy supports the goals of detecting and identifying gamma-ray sources. This manuscript examines the existing set of spectroscopy methods, attempts to categorize them by the statistical methods on which they rely, and identifies methods that have yet to be considered. Our examination shows that current methods effectively estimate the effect of counting uncertainty but in many cases do not address larger sources of decision uncertainty—ones that are significantly moremore » complex. We thus explore the premise that significantly improving algorithm performance requires greater coupling between the problem physics that drives data acquisition and statistical methods that analyze such data. Untapped statistical methods, such as Bayes Modeling Averaging and hierarchical and empirical Bayes methods have the potential to reduce decision uncertainty by more rigorously and comprehensively incorporating all sources of uncertainty. We expect that application of such methods will demonstrate progress in meeting the needs of nuclear security missions by improving on the existing numerical infrastructure for which these analyses have not been conducted.« less

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

Time from Prior Chemotherapy Enhances Prognostic Risk Grouping in the Second-line Setting of Advanced Urothelial Carcinoma: A Retrospective Analysis of Pooled, Prospective Phase 2 Trials

PubMed Central

Sonpavde, Guru; Pond, Gregory R.; Fougeray, Ronan; Choueiri, Toni K.; Qu, Angela Q.; Vaughn, David J.; Niegisch, Guenter; Albers, Peter; James, Nicholas D.; Wong, Yu-Ning; Ko, Yoo-Joung; Sridhar, Srikala S.; Galsky, Matthew D.; Petrylak, Daniel P.; Vaishampayan, Ulka N.; Khan, Awais; Vogelzang, Nicholas J.; Beer, Tomasz M.; Stadler, Walter M.; O’Donnell, Peter H.; Sternberg, Cora N.; Rosenberg, Jonathan E.; Bellmunt, Joaquim

2014-01-01

Background Outcomes for patients in the second-line setting of advanced urothelial carcinoma (UC) are dismal. The recognized prognostic factors in this context are Eastern Cooperative Oncology Group (ECOG) performance status (PS) >0, hemoglobin level (Hb) <10 g/dl, and liver metastasis (LM). Objectives The purpose of this retrospective study of prospective trials was to investigate the prognostic value of time from prior chemotherapy (TFPC) independent of known prognostic factors. Design, setting, and participants: Data from patients from seven prospective trials with available baseline TFPC, Hb, PS, and LM values were used for retrospective analysis (n = 570). External validation was conducted in a second-line phase 3 trial comparing best supportive care (BSC) versus vinflunine plus BSC (n = 352). Outcome measurements and statistical analysis Cox proportional hazards regression was used to evaluate the association of factors, with overall survival (OS) and progression-free survival (PFS) being the respective primary and secondary outcome measures. Results and limitations ECOG-PS >0, LM, Hb <10 g/dl, and shorter TFPC were significant prognostic factors for OS and PFS on multivariable analysis. Patients with zero, one, two, and three to four factors demonstrated median OS of 12.2, 6.7, 5.1, and 3.0 mo, respectively (concordance statistic = 0.638). Setting of prior chemotherapy (metastatic disease vs perioperative) and prior platinum agent (cisplatin or carboplatin) were not prognostic factors. External validation demonstrated a significant association of TFPC with PFS on univariable and most multivariable analyses, and with OS on univariable analyses. Limitations of retrospective analyses are applicable. Conclusions Shorter TFPC enhances prognostic classification independent of ECOG-PS>0, Hb<10 g/ dl, and LM in the setting of second-line therapy for advanced UC. These data may facilitate drug development and interpretation of trials. PMID:23206856

Diet misreporting can be corrected: confirmation of the association between energy intake and fat-free mass in adolescents.

PubMed

Vainik, Uku; Konstabel, Kenn; Lätt, Evelin; Mäestu, Jarek; Purge, Priit; Jürimäe, Jaak

2016-10-01

Subjective energy intake (sEI) is often misreported, providing unreliable estimates of energy consumed. Therefore, relating sEI data to health outcomes is difficult. Recently, Börnhorst et al. compared various methods to correct sEI-based energy intake estimates. They criticised approaches that categorise participants as under-reporters, plausible reporters and over-reporters based on the sEI:total energy expenditure (TEE) ratio, and thereafter use these categories as statistical covariates or exclusion criteria. Instead, they recommended using external predictors of sEI misreporting as statistical covariates. We sought to confirm and extend these findings. Using a sample of 190 adolescent boys (mean age=14), we demonstrated that dual-energy X-ray absorptiometry-measured fat-free mass is strongly associated with objective energy intake data (onsite weighted breakfast), but the association with sEI (previous 3-d dietary interview) is weak. Comparing sEI with TEE revealed that sEI was mostly under-reported (74 %). Interestingly, statistically controlling for dietary reporting groups or restricting samples to plausible reporters created a stronger-than-expected association between fat-free mass and sEI. However, the association was an artifact caused by selection bias - that is, data re-sampling and simulations showed that these methods overestimated the effect size because fat-free mass was related to sEI both directly and indirectly via TEE. A more realistic association between sEI and fat-free mass was obtained when the model included common predictors of misreporting (e.g. BMI, restraint). To conclude, restricting sEI data only to plausible reporters can cause selection bias and inflated associations in later analyses. Therefore, we further support statistically correcting sEI data in nutritional analyses. The script for running simulations is provided.

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA.

PubMed

Festing, M F

2001-01-01

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.

Research of Extension of the Life Cycle of Helicopter Rotor Blade in Hungary

DTIC Science & Technology

2003-02-01

Radiography (DXR), and (iii) Vibration Diagnostics (VD) with Statistical Energy Analysis (SEA) were semi- simultaneously applied [1]. The used three...2.2. Vibration Diagnostics (VD)) Parallel to the NDT measurements the Statistical Energy Analysis (SEA) as a vibration diagnostical tool were...noises were analysed with a dual-channel real time frequency analyser (BK2035). In addition to the Statistical Energy Analysis measurement a small

A systematic review of the quality of statistical methods employed for analysing quality of life data in cancer randomised controlled trials.

PubMed

Hamel, Jean-Francois; Saulnier, Patrick; Pe, Madeline; Zikos, Efstathios; Musoro, Jammbe; Coens, Corneel; Bottomley, Andrew

2017-09-01

Over the last decades, Health-related Quality of Life (HRQoL) end-points have become an important outcome of the randomised controlled trials (RCTs). HRQoL methodology in RCTs has improved following international consensus recommendations. However, no international recommendations exist concerning the statistical analysis of such data. The aim of our study was to identify and characterise the quality of the statistical methods commonly used for analysing HRQoL data in cancer RCTs. Building on our recently published systematic review, we analysed a total of 33 published RCTs studying the HRQoL methods reported in RCTs since 1991. We focussed on the ability of the methods to deal with the three major problems commonly encountered when analysing HRQoL data: their multidimensional and longitudinal structure and the commonly high rate of missing data. All studies reported HRQoL being assessed repeatedly over time for a period ranging from 2 to 36 months. Missing data were common, with compliance rates ranging from 45% to 90%. From the 33 studies considered, 12 different statistical methods were identified. Twenty-nine studies analysed each of the questionnaire sub-dimensions without type I error adjustment. Thirteen studies repeated the HRQoL analysis at each assessment time again without type I error adjustment. Only 8 studies used methods suitable for repeated measurements. Our findings show a lack of consistency in statistical methods for analysing HRQoL data. Problems related to multiple comparisons were rarely considered leading to a high risk of false positive results. It is therefore critical that international recommendations for improving such statistical practices are developed. Copyright © 2017. Published by Elsevier Ltd.

Sunspot activity and influenza pandemics: a statistical assessment of the purported association.

PubMed

Towers, S

2017-10-01

Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), and Yeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. In addition, in each analysis arbitrary selections or assumptions were also made, and the authors did not assess the robustness of their analyses to changes in those arbitrary assumptions. Varying the arbitrary assumptions to other, equally valid, assumptions negates the claims of significance. Indeed, an arbitrary selection made in one of the analyses appears to have resulted in almost maximal apparent significance; changing it only slightly yields a null result. This analysis applies statistically rigorous methodology to examine the purported sunspot/pandemic link, using more statistically powerful un-binned analysis methods, rather than relying on arbitrarily binned data. The analyses are repeated using both the Wolf and Group sunspot numbers. In all cases, no statistically significant evidence of any association was found. However, while the focus in this particular analysis was on the purported relationship of influenza pandemics to sunspot activity, the faults found in the past analyses are common pitfalls; inattention to analysis reproducibility and robustness assessment are common problems in the sciences, that are unfortunately not noted often enough in review.

Modeling stimulus variation in three common implicit attitude tasks.

PubMed

Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M

2017-08-01

We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.

Information filtering via biased heat conduction

NASA Astrophysics Data System (ADS)

Liu, Jian-Guo; Zhou, Tao; Guo, Qiang

2011-09-01

The process of heat conduction has recently found application in personalized recommendation [Zhou , Proc. Natl. Acad. Sci. USA PNASA60027-842410.1073/pnas.1000488107107, 4511 (2010)], which is of high diversity but low accuracy. By decreasing the temperatures of small-degree objects, we present an improved algorithm, called biased heat conduction, which could simultaneously enhance the accuracy and diversity. Extensive experimental analyses demonstrate that the accuracy on MovieLens, Netflix, and Delicious datasets could be improved by 43.5%, 55.4% and 19.2%, respectively, compared with the standard heat conduction algorithm and also the diversity is increased or approximately unchanged. Further statistical analyses suggest that the present algorithm could simultaneously identify users' mainstream and special tastes, resulting in better performance than the standard heat conduction algorithm. This work provides a creditable way for highly efficient information filtering.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

PubMed

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions

PubMed Central

Hahn, Beth A.; Dreitz, Victoria J.; George, T. Luke

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer’s sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer’s sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales. PMID:29065128

A Retrospective Survey of Research Design and Statistical Analyses in Selected Chinese Medical Journals in 1998 and 2008

PubMed Central

Jin, Zhichao; Yu, Danghui; Zhang, Luoman; Meng, Hong; Lu, Jian; Gao, Qingbin; Cao, Yang; Ma, Xiuqiang; Wu, Cheng; He, Qian; Wang, Rui; He, Jia

2010-01-01

Background High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. Methodology/Principal Findings Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. Conclusions/Significance Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative. PMID:20520824

Use of Statistical Analyses in the Ophthalmic Literature

PubMed Central

Lisboa, Renato; Meira-Freitas, Daniel; Tatham, Andrew J.; Marvasti, Amir H.; Sharpsten, Lucie; Medeiros, Felipe A.

2014-01-01

Purpose To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to sequentially add knowledge of more advanced techniques to their statistical repertoire. Design Cross-sectional study Methods All articles published from January 2012 to December 2012 in Ophthalmology, American Journal of Ophthalmology and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus. Main Outcome Measures Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire. Results Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. In order to understand more than half (51.4%) of the articles published, readers were expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, while knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles in retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared to cornea. Conclusions Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of published studies in the literature. The frequency of use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge in order to critically appraise articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers and educators involved in the design of courses for residents and medical students. PMID:24612977

Health research needs more comprehensive accessibility measures: integrating time and transport modes from open data.

PubMed

Tenkanen, Henrikki; Saarsalmi, Perttu; Järv, Olle; Salonen, Maria; Toivonen, Tuuli

2016-07-28

In this paper, we demonstrate why and how both temporality and multimodality should be integrated in health related studies that include accessibility perspective, in this case healthy food accessibility. We provide evidence regarding the importance of using multimodal spatio-temporal accessibility measures when conducting research in urban contexts and propose a methodological approach for integrating different travel modes and temporality to spatial accessibility analyses. We use the Helsinki metropolitan area (Finland) as our case study region to demonstrate the effects of temporality and modality on the results. Spatial analyses were carried out on 250 m statistical grid squares. We measured travel times between the home location of inhabitants and open grocery stores providing healthy food at 5 p.m., 10 p.m., and 1 a.m. using public transportation and private cars. We applied the so-called door-to-door approach for the travel time measurements to obtain more realistic and comparable results between travel modes. The analyses are based on open access data and publicly available open-source tools, thus similar analyses can be conducted in urban regions worldwide. Our results show that both time and mode of transport have a prominent impact on the outcome of the analyses; thus, understanding the realities of accessibility in a city may be very different according to the setting of the analysis used. In terms of travel time, there is clear variation in the results at different times of the day. In terms of travel mode, our results show that when analyzed in a comparable manner, public transport can be an even faster mode than a private car to access healthy food, especially in central areas of the city where the service network is dense and public transportation system is effective. This study demonstrates that time and transport modes are essential components when modeling health-related accessibility in urban environments. Neglecting them from spatial analyses may lead to overly simplified or even erroneous images of the realities of accessibility. Hence, there is a risk that health related planning and decisions based on simplistic accessibility measures might cause unwanted outcomes in terms of inequality among different groups of people.

Global atmospheric circulation statistics, 1000-1 mb

NASA Technical Reports Server (NTRS)

Randel, William J.

1992-01-01

The atlas presents atmospheric general circulation statistics derived from twelve years (1979-90) of daily National Meteorological Center (NMC) operational geopotential height analyses; it is an update of a prior atlas using data over 1979-1986. These global analyses are available on pressure levels covering 1000-1 mb (approximately 0-50 km). The geopotential grids are a combined product of the Climate Analysis Center (which produces analyses over 70-1 mb) and operational NMC analyses (over 1000-100 mb). Balance horizontal winds and hydrostatic temperatures are derived from the geopotential fields.

Response surface methodology as an approach to determine optimal activities of lipase entrapped in sol-gel matrix using different vegetable oils.

PubMed

Pinheiro, Rubiane C; Soares, Cleide M F; de Castro, Heizir F; Moraes, Flavio F; Zanin, Gisella M

2008-03-01

The conditions for maximization of the enzymatic activity of lipase entrapped in sol-gel matrix were determined for different vegetable oils using an experimental design. The effects of pH, temperature, and biocatalyst loading on lipase activity were verified using a central composite experimental design leading to a set of 13 assays and the surface response analysis. For canola oil and entrapped lipase, statistical analyses showed significant effects for pH and temperature and also the interactions between pH and temperature and temperature and biocatalyst loading. For the olive oil and entrapped lipase, it was verified that the pH was the only variable statistically significant. This study demonstrated that response surface analysis is a methodology appropriate for the maximization of the percentage of hydrolysis, as a function of pH, temperature, and lipase loading.

Identification of the isomers using principal component analysis (PCA) method

NASA Astrophysics Data System (ADS)

Kepceoǧlu, Abdullah; Gündoǧdu, Yasemin; Ledingham, Kenneth William David; Kilic, Hamdi Sukur

2016-03-01

In this work, we have carried out a detailed statistical analysis for experimental data of mass spectra from xylene isomers. Principle Component Analysis (PCA) was used to identify the isomers which cannot be distinguished using conventional statistical methods for interpretation of their mass spectra. Experiments have been carried out using a linear TOF-MS coupled to a femtosecond laser system as an energy source for the ionisation processes. We have performed experiments and collected data which has been analysed and interpreted using PCA as a multivariate analysis of these spectra. This demonstrates the strength of the method to get an insight for distinguishing the isomers which cannot be identified using conventional mass analysis obtained through dissociative ionisation processes on these molecules. The PCA results dependending on the laser pulse energy and the background pressure in the spectrometers have been presented in this work.

[School performance of former premature infants in the first four years of school].

PubMed

Frenzel, J; Paalhorn, U

1992-12-01

School achievement during the first four grades was analysed by means of subject marks in 203 prematurely born and in 140 maturely born children. In subjects referring to behaviour in the classroom, no statistically significant differences in average marks could be found between prematurely born children and the control group. The average marks in performance subjects were slightly higher in the subgroup of very prematurely born children. However, statistically significant lower marks were observed in the subject of sports only, and for formerly immature children also in the subject of manual training. The higher the educational level of the mothers, the better the average marks without sports. No relationships between school performance and manifestation of postnatal risk factor like Apgar score, blood gas values and duration of oxygen dependency could be seen. These results demonstrate that school performance of former premature infants lies within the normal variance of their grade.

Anisotropic analysis of trabecular architecture in human femur bone radiographs using quaternion wavelet transforms.

PubMed

Sangeetha, S; Sujatha, C M; Manamalli, D

2014-01-01

In this work, anisotropy of compressive and tensile strength regions of femur trabecular bone are analysed using quaternion wavelet transforms. The normal and abnormal femur trabecular bone radiographic images are considered for this study. The sub-anatomic regions, which include compressive and tensile regions, are delineated using pre-processing procedures. These delineated regions are subjected to quaternion wavelet transforms and statistical parameters are derived from the transformed images. These parameters are correlated with apparent porosity, which is derived from the strength regions. Further, anisotropy is also calculated from the transformed images and is analyzed. Results show that the anisotropy values derived from second and third phase components of quaternion wavelet transform are found to be distinct for normal and abnormal samples with high statistical significance for both compressive and tensile regions. These investigations demonstrate that architectural anisotropy derived from QWT analysis is able to differentiate normal and abnormal samples.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

PubMed Central

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

Effect of oxygen on volatile and sensory characteristics of Cabernet Sauvignon during secondary shelf life.

PubMed

Lee, Dong-Hyun; Kang, Bo-Sik; Park, Hyun-Jin

2011-11-09

The oxidation of Cabernet Sauvignon wines during secondary shelf life was studied by headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-quadrupole mass spectrometry (GC-qMS) and sensory tests, with the support of multivariate statistical analyses such as OPLS-DA loading plot and PCA score plot. Four different oxidation conditions were established during a 1-week secondary shelf life. Samples collected on a regular basis were analyzed to determine the changes of volatile chemicals, with sensory characteristics evaluated through pattern recognition models. During secondary shelf life the separation among collected samples depended on the degree of oxidation in wine. Isoamyl acetate, ethyl decanoate, nonanoic acid, n-decanoic acid, undecanoic acid, 2-furancarboxylic acid, dodecanoic acid, and phenylacetaldehyde were determined to be associated with the oxidation of the wine. PCA sensory evaluation revealed that least oxidized wine and fresh wine was well-separated from more oxidized wines, demonstrating that sensory characteristics of less oxidized wines tend toward "fruity", "citrous", and "sweetness", while those of more oxidized wines are positively correlated with "animal", "bitterness", and "dairy". The study also demonstrates that OPLS-DA and PCA are very useful statistical tools for the understanding of wine oxidation.

A new image encryption algorithm based on the fractional-order hyperchaotic Lorenz system

NASA Astrophysics Data System (ADS)

Wang, Zhen; Huang, Xia; Li, Yu-Xia; Song, Xiao-Na

2013-01-01

We propose a new image encryption algorithm on the basis of the fractional-order hyperchaotic Lorenz system. While in the process of generating a key stream, the system parameters and the derivative order are embedded in the proposed algorithm to enhance the security. Such an algorithm is detailed in terms of security analyses, including correlation analysis, information entropy analysis, run statistic analysis, mean-variance gray value analysis, and key sensitivity analysis. The experimental results demonstrate that the proposed image encryption scheme has the advantages of large key space and high security for practical image encryption.

Comparing highly ordered monolayers of nanoparticles fabricated using electrophoretic deposition: Cobalt ferrite nanoparticles versus iron oxide nanoparticles

DOE PAGES

Dickerson, James H.; Krejci, Alex J.; Garcia, Adriana -Mendoza; ...

2015-08-01

Ordered assemblies of nanoparticles remain challenging to fabricate, yet could open the door to many potential applications of nanomaterials. Here, we demonstrate that locally ordered arrays of nanoparticles, using electrophoretic deposition, can be extended to produce long-range order among the constituents. Voronoi tessellations along with multiple statistical analyses show dramatic increases in order compared with previously reported assemblies formed through electric field-assisted assembly. As a result, based on subsequent physical measurements of the nanoparticles and the deposition system, the underlying mechanisms that generate increased order are inferred.

Building a framework for ergonomic research on laparoscopic instrument handles.

PubMed

Li, Zheng; Wang, Guohui; Tan, Juan; Sun, Xulong; Lin, Hao; Zhu, Shaihong

2016-06-01

Laparoscopic surgery carries the advantage of minimal invasiveness, but ergonomic design of the instruments used has progressed slowly. Previous studies have demonstrated that the handle of laparoscopic instruments is vital for both surgical performance and surgeon's health. This review provides an overview of the sub-discipline of handle ergonomics, including an evaluation framework, objective and subjective assessment systems, data collection and statistical analyses. Furthermore, a framework for ergonomic research on laparoscopic instrument handles is proposed to standardize work on instrument design. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Incorrect likelihood methods were used to infer scaling laws of marine predator search behaviour.

PubMed

Edwards, Andrew M; Freeman, Mervyn P; Breed, Greg A; Jonsen, Ian D

2012-01-01

Ecologists are collecting extensive data concerning movements of animals in marine ecosystems. Such data need to be analysed with valid statistical methods to yield meaningful conclusions. We demonstrate methodological issues in two recent studies that reached similar conclusions concerning movements of marine animals (Nature 451:1098; Science 332:1551). The first study analysed vertical movement data to conclude that diverse marine predators (Atlantic cod, basking sharks, bigeye tuna, leatherback turtles and Magellanic penguins) exhibited "Lévy-walk-like behaviour", close to a hypothesised optimal foraging strategy. By reproducing the original results for the bigeye tuna data, we show that the likelihood of tested models was calculated from residuals of regression fits (an incorrect method), rather than from the likelihood equations of the actual probability distributions being tested. This resulted in erroneous Akaike Information Criteria, and the testing of models that do not correspond to valid probability distributions. We demonstrate how this led to overwhelming support for a model that has no biological justification and that is statistically spurious because its probability density function goes negative. Re-analysis of the bigeye tuna data, using standard likelihood methods, overturns the original result and conclusion for that data set. The second study observed Lévy walk movement patterns by mussels. We demonstrate several issues concerning the likelihood calculations (including the aforementioned residuals issue). Re-analysis of the data rejects the original Lévy walk conclusion. We consequently question the claimed existence of scaling laws of the search behaviour of marine predators and mussels, since such conclusions were reached using incorrect methods. We discourage the suggested potential use of "Lévy-like walks" when modelling consequences of fishing and climate change, and caution that any resulting advice to managers of marine ecosystems would be problematic. For reproducibility and future work we provide R source code for all calculations.

Power estimation using simulations for air pollution time-series studies

PubMed Central

2012-01-01

Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Methods Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. Results In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. Conclusions These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided. PMID:22995599

Power estimation using simulations for air pollution time-series studies.

PubMed

Winquist, Andrea; Klein, Mitchel; Tolbert, Paige; Sarnat, Stefanie Ebelt

2012-09-20

Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided.

SU-E-J-85: Leave-One-Out Perturbation (LOOP) Fitting Algorithm for Absolute Dose Film Calibration

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

Chu, A; Ahmad, M; Chen, Z

2014-06-01

Purpose: To introduce an outliers-recognition fitting routine for film dosimetry. It cannot only be flexible with any linear and non-linear regression but also can provide information for the minimal number of sampling points, critical sampling distributions and evaluating analytical functions for absolute film-dose calibration. Methods: The technique, leave-one-out (LOO) cross validation, is often used for statistical analyses on model performance. We used LOO analyses with perturbed bootstrap fitting called leave-one-out perturbation (LOOP) for film-dose calibration . Given a threshold, the LOO process detects unfit points (“outliers”) compared to other cohorts, and a bootstrap fitting process follows to seek any possibilitiesmore » of using perturbations for further improvement. After that outliers were reconfirmed by a traditional t-test statistics and eliminated, then another LOOP feedback resulted in the final. An over-sampled film-dose- calibration dataset was collected as a reference (dose range: 0-800cGy), and various simulated conditions for outliers and sampling distributions were derived from the reference. Comparisons over the various conditions were made, and the performance of fitting functions, polynomial and rational functions, were evaluated. Results: (1) LOOP can prove its sensitive outlier-recognition by its statistical correlation to an exceptional better goodness-of-fit as outliers being left-out. (2) With sufficient statistical information, the LOOP can correct outliers under some low-sampling conditions that other “robust fits”, e.g. Least Absolute Residuals, cannot. (3) Complete cross-validated analyses of LOOP indicate that the function of rational type demonstrates a much superior performance compared to the polynomial. Even with 5 data points including one outlier, using LOOP with rational function can restore more than a 95% value back to its reference values, while the polynomial fitting completely failed under the same conditions. Conclusion: LOOP can cooperate with any fitting routine functioning as a “robust fit”. In addition, it can be set as a benchmark for film-dose calibration fitting performance.« less

A modified method of 3D-SSP analysis for amyloid PET imaging using [¹¹C]BF-227.

PubMed

Kaneta, Tomohiro; Okamura, Nobuyuki; Minoshima, Satoshi; Furukawa, Katsutoshi; Tashiro, Manabu; Furumoto, Shozo; Iwata, Ren; Fukuda, Hiroshi; Takahashi, Shoki; Yanai, Kazuhiko; Kudo, Yukitsuka; Arai, Hiroyuki

2011-12-01

Three-dimensional stereotactic surface projection (3D-SSP) analyses have been widely used in dementia imaging studies. However, 3D-SSP sometimes shows paradoxical results on amyloid positron emission tomography (PET) analyses. This is thought to be caused by errors in anatomical standardization (AS) based on an (18)F-fluorodeoxyglucose (FDG) template. We developed a new method of 3D-SSP analysis for amyloid PET imaging, and used it to analyze (11)C-labeled 2-(2-[2-dimethylaminothiazol-5-yl]ethenyl)-6-(2-[fluoro]ethoxy)benzoxazole (BF-227) PET images of subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The subjects were 20 with MCI, 19 patients with AD, and 17 healthy controls. Twelve subjects with MCI were followed up for 3 years or more, and conversion to AD was seen in 6 cases. All subjects underwent PET with both FDG and BF-227. For AS and 3D-SSP analyses of PET data, Neurostat (University of Washington, WA, USA) was used. Method 1 involves AS for BF-227 images using an FDG template. In this study, we developed a new method (Method 2) for AS: First, an FDG image was subjected to AS using an FDG template. Then, the BF-227 image of the same patient was registered to the FDG image, and AS was performed using the transformation parameters calculated for AS of the corresponding FDG images. Regional values were normalized by the average value obtained at the cerebellum and values were calculated for the frontal, parietal, temporal, and occipital lobes. For statistical comparison of the 3 groups, we applied one-way analysis of variance followed by the Bonferroni post hoc test. For statistical comparison between converters and non-converters, the t test was applied. Statistical significance was defined as p < 0.05. Among the 56 cases we studied, Method 1 demonstrated slight distortions after AS of the image in 16 cases and heavy distortions in 4 cases in which the distortions were not observed with Method 2. Both methods demonstrated that the values in AD and MCI patients were significantly higher than those in the controls, in the parietal, temporal, and occipital lobes. However, only Method 2 showed significant differences in the frontal lobes. In addition, Method 2 could demonstrate a significantly higher value in MCI-to-AD converters in the parietal and frontal lobes. Method 2 corrects AS errors that often occur when using Method 1, and has made appropriate 3D-SSP analysis of amyloid PET imaging possible. This new method of 3D-SSP analysis for BF-227 PET could prove useful for detecting differences between normal groups and AD and MCI groups, and between converters and non-converters.

The mediating effect of calling on the relationship between medical school students’ academic burnout and empathy

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits

NASA Astrophysics Data System (ADS)

Tsutsumi, Morito; Seya, Hajime

2009-12-01

This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

Body size affects the strength of social interactions and spatial organization of a schooling fish (Pseudomugil signifer)

NASA Astrophysics Data System (ADS)

Romenskyy, Maksym; Herbert-Read, James E.; Ward, Ashley J. W.; Sumpter, David J. T.

2017-04-01

While a rich variety of self-propelled particle models propose to explain the collective motion of fish and other animals, rigorous statistical comparison between models and data remains a challenge. Plausible models should be flexible enough to capture changes in the collective behaviour of animal groups at their different developmental stages and group sizes. Here, we analyse the statistical properties of schooling fish (Pseudomugil signifer) through a combination of experiments and simulations. We make novel use of a Boltzmann inversion method, usually applied in molecular dynamics, to identify the effective potential of the mean force of fish interactions. Specifically, we show that larger fish have a larger repulsion zone, but stronger attraction, resulting in greater alignment in their collective motion. We model the collective dynamics of schools using a self-propelled particle model, modified to include varying particle speed and a local repulsion rule. We demonstrate that the statistical properties of the fish schools are reproduced by our model, thereby capturing a number of features of the behaviour and development of schooling fish.

The journals are full of great studies but can we believe the statistics? Revisiting the mass privatisation - mortality debate.

PubMed

Gerry, Christopher J

2012-07-01

Cross-national statistical analyses based on country-level panel data are increasingly popular in social epidemiology. To provide reliable results on the societal determinants of health, analysts must give very careful consideration to conceptual and methodological issues: aggregate (historical) data are typically compatible with multiple alternative stories of the data-generating process. Studies in this field which fail to relate their empirical approach to the true underlying data-generating process are likely to produce misleading results if, for example, they misspecify their models by failing to explore the statistical properties of the longitudinal aspect of their data or by ignoring endogeneity issues. We illustrate the importance of this extra need for care with reference to a recent debate on whether discussing the role of rapid mass privatisation can explain post-communist mortality fluctuations. We demonstrate that the finding that rapid mass privatisation was a "crucial determinant" of male mortality fluctuations in the post-communist world is rejected once better consideration is given to the way in which the data are generated. Copyright © 2012 Elsevier Ltd. All rights reserved.

NASA DOE POD NDE Capabilities Data Book

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2015-01-01

This data book contains the Directed Design of Experiments for Validating Probability of Detection (POD) Capability of NDE Systems (DOEPOD) analyses of the nondestructive inspection data presented in the NTIAC, Nondestructive Evaluation (NDE) Capabilities Data Book, 3rd ed., NTIAC DB-97-02. DOEPOD is designed as a decision support system to validate inspection system, personnel, and protocol demonstrating 0.90 POD with 95% confidence at critical flaw sizes, a90/95. The test methodology used in DOEPOD is based on the field of statistical sequential analysis founded by Abraham Wald. Sequential analysis is a method of statistical inference whose characteristic feature is that the number of observations required by the procedure is not determined in advance of the experiment. The decision to terminate the experiment depends, at each stage, on the results of the observations previously made. A merit of the sequential method, as applied to testing statistical hypotheses, is that test procedures can be constructed which require, on average, a substantially smaller number of observations than equally reliable test procedures based on a predetermined number of observations.

Empirically derived personality subtyping for predicting clinical symptoms and treatment response in bulimia nervosa.

PubMed

Haynos, Ann F; Pearson, Carolyn M; Utzinger, Linsey M; Wonderlich, Stephen A; Crosby, Ross D; Mitchell, James E; Crow, Scott J; Peterson, Carol B

2017-05-01

Evidence suggests that eating disorder subtypes reflecting under-controlled, over-controlled, and low psychopathology personality traits constitute reliable phenotypes that differentiate treatment response. This study is the first to use statistical analyses to identify these subtypes within treatment-seeking individuals with bulimia nervosa (BN) and to use these statistically derived clusters to predict clinical outcomes. Using variables from the Dimensional Assessment of Personality Pathology-Basic Questionnaire, K-means cluster analyses identified under-controlled, over-controlled, and low psychopathology subtypes within BN patients (n = 80) enrolled in a treatment trial. Generalized linear models examined the impact of personality subtypes on Eating Disorder Examination global score, binge eating frequency, and purging frequency cross-sectionally at baseline and longitudinally at end of treatment (EOT) and follow-up. In the longitudinal models, secondary analyses were conducted to examine personality subtype as a potential moderator of response to Cognitive Behavioral Therapy-Enhanced (CBT-E) or Integrative Cognitive-Affective Therapy for BN (ICAT-BN). There were no baseline clinical differences between groups. In the longitudinal models, personality subtype predicted binge eating (p = 0.03) and purging (p = 0.01) frequency at EOT and binge eating frequency at follow-up (p = 0.045). The over-controlled group demonstrated the best outcomes on these variables. In secondary analyses, there was a treatment by subtype interaction for purging at follow-up (p = 0.04), which indicated a superiority of CBT-E over ICAT-BN for reducing purging among the over-controlled group. Empirically derived personality subtyping appears to be a valid classification system with potential to guide eating disorder treatment decisions. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2017; 50:506-514). © 2016 Wiley Periodicals, Inc.

Pediatric patient safety events during hospitalization: approaches to accounting for institution-level effects.

PubMed

Slonim, Anthony D; Marcin, James P; Turenne, Wendy; Hall, Matt; Joseph, Jill G

2007-12-01

To determine the rates, patient, and institutional characteristics associated with the occurrence of patient safety indicators (PSIs) in hospitalized children and the degree of statistical difference derived from using three approaches of controlling for institution level effects. Pediatric Health Information System Dataset consisting of all pediatric discharges (<21 years of age) from 34 academic, freestanding children's hospitals for calendar year 2003. The rates of PSIs were computed for all discharges. The patient and institutional characteristics associated with these PSIs were calculated. The analyses sequentially applied three increasingly conservative methods to control for the institution-level effects robust standard error estimation, a fixed effects model, and a random effects model. The degree of difference from a "base state," which excluded institution-level variables, and between the models was calculated. The effects of these analyses on the interpretation of the PSIs are presented. PSIs are relatively infrequent events in hospitalized children ranging from 0 per 10,000 (postoperative hip fracture) to 87 per 10,000 (postoperative respiratory failure). Significant variables associated PSIs included age (neonates), race (Caucasians), payor status (public insurance), severity of illness (extreme), and hospital size (>300 beds), which all had higher rates of PSIs than their reference groups in the bivariable logistic regression results. The three different approaches of adjusting for institution-level effects demonstrated that there were similarities in both the clinical and statistical significance across each of the models. Institution-level effects can be appropriately controlled for by using a variety of methods in the analyses of administrative data. Whenever possible, resource-conservative methods should be used in the analyses especially if clinical implications are minimal.

Effects of environmental pollution with aromatic hydrocarbons on endocrine and metabolic functions of the human placenta.

PubMed

Wierzba, Waldemar; Radowicki, Stanisław; Bojar, Iwona; Pinkas, Jarosław

2018-03-14

Phenol and 1-hydroxypyrene are biological markers of exposure to polycyclic aromatic hydrocarbons (PAH) that have certain negative effects on parenchymal organs such as the human placenta. The literature presents only few reports regarding the effects of elevated PAH levels on the functions of the human placenta. The aim of the work is to assess the effects of elevated PAH levels in excreted urine on the endocrine and metabolic functions of the human placenta obtained from a normal pregnancy. Tissue material from 50 afterbirths from Płock constituted a study group, whereas 50 afterbirths from Kutno constituted a control group. Immunohistochemical reactions with the peroxidase method using LSAB kits (DAKO, Denmark) were performed. The extent and intensity of reactions were analysed. The levels of phenols and 1-hydroxypyrene in the excreted urine of pregnant women (undergoing delivery) were detected using gas chromatography and colorimetry. The statistical analysis used the PQStat v.1.6.2 software; moreover, t-student and chi-square tests were used. Differences were considered to be significant at the significance level of 95% (p<0.05). The levels of phenol and 1-hydroxypyrene in the excreted urine were demonstrated to be statistically significantly higher in patients living in the area of Płock. Statistically lower expression of placental glutathione transferase and lower immunohistochemical demonstration of the placental phosphatase activity were observed in placentas from Płock. It has been demonstrated that the expression of the oestrogen receptor activity and placental gonadotropin is significantly higher in placentas from areas not contaminated with aromatic hydrocarbons (Kutno). The course of pregnancy in the environment with elevated levels of aromatic hydrocarbons leads to impaired placental functioning and reduced endocrine and metabolic activity of the placenta.

Effect of telecare on use of health and social care services: findings from the Whole Systems Demonstrator cluster randomised trial

PubMed Central

Steventon, Adam; Bardsley, Martin; Billings, John; Dixon, Jennifer; Doll, Helen; Beynon, Michelle; Hirani, Shashi; Cartwright, Martin; Rixon, Lorna; Knapp, Martin; Henderson, Catherine; Rogers, Anne; Hendy, Jane; Fitzpatrick, Ray; Newman, Stanton

2013-01-01

Objective: to assess the impact of telecare on the use of social and health care. Part of the evaluation of the Whole Systems Demonstrator trial. Participants and setting: a total of 2,600 people with social care needs were recruited from 217 general practices in three areas in England. Design: a cluster randomised trial comparing telecare with usual care, general practice being the unit of randomisation. Participants were followed up for 12 months and analyses were conducted as intention-to-treat. Data sources: trial data were linked at the person level to administrative data sets on care funded at least in part by local authorities or the National Health Service. Main outcome measures: the proportion of people admitted to hospital within 12 months. Secondary endpoints included mortality, rates of secondary care use (seven different metrics), contacts with general practitioners and practice nurses, proportion of people admitted to permanent residential or nursing care, weeks in domiciliary social care and notional costs. Results: 46.8% of intervention participants were admitted to hospital, compared with 49.2% of controls. Unadjusted differences were not statistically significant (odds ratio: 0.90, 95% CI: 0.75–1.07, P = 0.211). They reached statistical significance after adjusting for baseline covariates, but this was not replicated when adjusting for the predictive risk score. Secondary metrics including impacts on social care use were not statistically significant. Conclusions: telecare as implemented in the Whole Systems Demonstrator trial did not lead to significant reductions in service use, at least in terms of results assessed over 12 months. International Standard Randomised Controlled Trial Number Register ISRCTN43002091. PMID:23443509

Secondary Analysis of National Longitudinal Transition Study 2 Data

ERIC Educational Resources Information Center

Hicks, Tyler A.; Knollman, Greg A.

2015-01-01

This review examines published secondary analyses of National Longitudinal Transition Study 2 (NLTS2) data, with a primary focus upon statistical objectives, paradigms, inferences, and methods. Its primary purpose was to determine which statistical techniques have been common in secondary analyses of NLTS2 data. The review begins with an…

A Nonparametric Geostatistical Method For Estimating Species Importance

Treesearch

Andrew J. Lister; Rachel Riemann; Michael Hoppus

2001-01-01

Parametric statistical methods are not always appropriate for conducting spatial analyses of forest inventory data. Parametric geostatistical methods such as variography and kriging are essentially averaging procedures, and thus can be affected by extreme values. Furthermore, non normal distributions violate the assumptions of analyses in which test statistics are...

"Who Was 'Shadow'?" The Computer Knows: Applying Grammar-Program Statistics in Content Analyses to Solve Mysteries about Authorship.

ERIC Educational Resources Information Center

Ellis, Barbara G.; Dick, Steven J.

1996-01-01

Employs the statistics-documentation portion of a word-processing program's grammar-check feature together with qualitative analyses to determine that Henry Watterson, long-time editor of the "Louisville Courier-Journal," was probably the South's famed Civil War correspondent "Shadow." (TB)

Aircraft Maneuvers for the Evaluation of Flying Qualities and Agility. Volume 1. Maneuver Development Process and Initial Maneuver Set

DTIC Science & Technology

1993-08-01

subtitled "Simulation Data," consists of detailed infonrnation on the design parmneter variations tested, subsequent statistical analyses conducted...used with confidence during the design process. The data quality can be examined in various forms such as statistical analyses of measure of merit data...merit, such as time to capture or nmaximurn pitch rate, can be calculated from the simulation time history data. Statistical techniques are then used

Dietary magnesium and potassium intakes and circulating magnesium are associated with heel bone ultrasound attenuation and osteoporotic fracture risk in the EPIC-Norfolk cohort study.

PubMed

Hayhoe, Richard P G; Lentjes, Marleen A H; Luben, Robert N; Khaw, Kay-Tee; Welch, Ailsa A

2015-08-01

In our aging population, maintenance of bone health is critical to reduce the risk of osteoporosis and potentially debilitating consequences of fractures in older individuals. Among modifiable lifestyle and dietary factors, dietary magnesium and potassium intakes are postulated to influence bone quality and osteoporosis, principally via calcium-dependent alteration of bone structure and turnover. We investigated the influence of dietary magnesium and potassium intakes, as well as circulating magnesium, on bone density status and fracture risk in an adult population in the United Kingdom. A random subset of 4000 individuals from the European Prospective Investigation into Cancer and Nutrition-Norfolk cohort of 25,639 men and women with baseline data was used for bone density cross-sectional analyses and combined with fracture cases (n = 1502) for fracture case-cohort longitudinal analyses (mean follow-up 13.4 y). Relevant biological, lifestyle, and dietary covariates were used in multivariate regression analyses to determine associations between dietary magnesium and potassium intakes and calcaneal broadband ultrasound attenuation (BUA), as well as in Prentice-weighted Cox regression to determine associated risk of fracture. Separate analyses, excluding dietary covariates, investigated associations of BUA and fractures with serum magnesium concentration. Statistically significant positive trends in calcaneal BUA for women (n = 1360) but not men (n = 968) were apparent across increasing quintiles of magnesium plus potassium (Mg+K) z score intake (P = 0.03) or potassium intake alone (P = 0.04). Reduced hip fracture risk in both men (n = 1958) and women (n = 2755) was evident for individuals in specific Mg+K z score intake quintiles compared with the lowest. Statistically significant trends in fracture risk in men across serum magnesium concentration groups were apparent for spine fractures (P = 0.02) and total hip, spine, and wrist fractures (P = 0.02). None of these individual statistically significant associations remained after adjustment for multiple testing. These findings enhance the limited literature studying the association of magnesium and potassium with bone density and demonstrate that further investigation is warranted into the mechanisms involved and the potential protective role against osteoporosis. © 2015 American Society for Nutrition.

Kidney function changes with aging in adults: comparison between cross-sectional and longitudinal data analyses in renal function assessment.

PubMed

Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas

2015-12-01

The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.

How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

PubMed Central

Yashin, Anatoliy I.; Arbeev, Konstantin G.; Wu, Deqing; Arbeeva, Liubov; Kulminski, Alexander; Kulminskaya, Irina; Akushevich, Igor; Ukraintseva, Svetlana V.

2016-01-01

Background and Objective To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues. Data and Methods We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging and on dynamic interaction between aging and longevity. We investigated properties of genes related to selected variants and their roles in signaling and metabolic pathways. Results We showed that the use of different QC procedures results in different sets of genetic variants associated with life span. We selected 24 genetic variants negatively associated with life span. We showed that the joint analyses of genetic data at the time of bio-specimen collection and follow up data substantially improved significance of associations of selected 24 SNPs with life span. We also showed that aging related changes in physiological variables and in hidden biomarkers of aging differ for the groups of carriers and non-carriers of selected variants. Conclusions . The results of these analyses demonstrated benefits of using biodemographic models and methods in genetic association studies of these traits. Our findings showed that the absence of a large number of genetic variants with deleterious effects may make substantial contribution to exceptional longevity. These effects are dynamically mediated by a number of physiological variables and hidden biomarkers of aging. The results of these research demonstrated benefits of using integrative statistical models of mortality risks in genetic studies of human aging and longevity. PMID:27773987

A robust and efficient statistical method for genetic association studies using case and control samples from multiple cohorts

PubMed Central

2013-01-01

Background The theoretical basis of genome-wide association studies (GWAS) is statistical inference of linkage disequilibrium (LD) between any polymorphic marker and a putative disease locus. Most methods widely implemented for such analyses are vulnerable to several key demographic factors and deliver a poor statistical power for detecting genuine associations and also a high false positive rate. Here, we present a likelihood-based statistical approach that accounts properly for non-random nature of case–control samples in regard of genotypic distribution at the loci in populations under study and confers flexibility to test for genetic association in presence of different confounding factors such as population structure, non-randomness of samples etc. Results We implemented this novel method together with several popular methods in the literature of GWAS, to re-analyze recently published Parkinson’s disease (PD) case–control samples. The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals. In particular, the new method detected 44 significant SNPs within 25 chromosomal regions of size < 1 Mb but only 6 SNPs in two of these regions were previously detected by the trend test based methods. It discovered two SNPs located 1.18 Mb and 0.18 Mb from the PD candidates, FGF20 and PARK8, without invoking false positive risk. Conclusions We developed a novel likelihood-based method which provides adequate estimation of LD and other population model parameters by using case and control samples, the ease in integration of these samples from multiple genetically divergent populations and thus confers statistically robust and powerful analyses of GWAS. On basis of simulation studies and analysis of real datasets, we demonstrated significant improvement of the new method over the non-parametric trend test, which is the most popularly implemented in the literature of GWAS. PMID:23394771

Performance monitoring in hip fracture surgery--how big a database do we really need?

PubMed

Edwards, G A D; Metcalfe, A J; Johansen, A; O'Doherty, D

2010-04-01

Systems for collecting information about patient care are increasingly common in orthopaedic practice. Databases can allow various comparisons to be made over time. Significant decisions regarding service delivery and clinical practice may be made based on their results. We set out to determine the number of cases needed for comparison of 30-day mortality, inpatient wound infection rates and mean hospital length of stay, with a power of 80% for the demonstration of an effect at a significance level of p<0.05. We analysed 2 years of prospectively collected data on 1050 hip fracture patients admitted to a city teaching hospital. Detection of a 10% difference in 30-day mortality would require 14,065 patients in each arm of any comparison, demonstration of a 50% difference would require 643 patients in each arm; for wound infections, demonstration of a 10% difference in incidence would require 23,921 patients in each arm and 1127 patients for demonstration of a 50% difference; for length of stay, a difference of 10% would require 1479 patients and 6660 patients for a 50% difference. This study demonstrates the importance of considering the population sizes before comparisons are made on the basis of basic hip fracture outcome data. Our data also help illustrate the impact of sample size considerations when interpreting the results of performance monitoring. Many researchers will be used to the fact that rare outcomes such as inpatient mortality or wound infection require large sample sizes before differences can be reliably demonstrated between populations. This study gives actual figures that researchers could use when planning studies. Statistically meaningful analyses will only be possible with major multi-centre collaborations, as will be possible if hospital Trusts participate in the National Hip Fracture Database. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Evaluation of Solid Rocket Motor Component Data Using a Commercially Available Statistical Software Package

NASA Technical Reports Server (NTRS)

Stefanski, Philip L.

2015-01-01

Commercially available software packages today allow users to quickly perform the routine evaluations of (1) descriptive statistics to numerically and graphically summarize both sample and population data, (2) inferential statistics that draws conclusions about a given population from samples taken of it, (3) probability determinations that can be used to generate estimates of reliability allowables, and finally (4) the setup of designed experiments and analysis of their data to identify significant material and process characteristics for application in both product manufacturing and performance enhancement. This paper presents examples of analysis and experimental design work that has been conducted using Statgraphics®(Registered Trademark) statistical software to obtain useful information with regard to solid rocket motor propellants and internal insulation material. Data were obtained from a number of programs (Shuttle, Constellation, and Space Launch System) and sources that include solid propellant burn rate strands, tensile specimens, sub-scale test motors, full-scale operational motors, rubber insulation specimens, and sub-scale rubber insulation analog samples. Besides facilitating the experimental design process to yield meaningful results, statistical software has demonstrated its ability to quickly perform complex data analyses and yield significant findings that might otherwise have gone unnoticed. One caveat to these successes is that useful results not only derive from the inherent power of the software package, but also from the skill and understanding of the data analyst.

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

PubMed Central

Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

2014-01-01

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging

PubMed Central

Dória, Maria Luisa; McKenzie, James S.; Mroz, Anna; Phelps, David L.; Speller, Abigail; Rosini, Francesca; Strittmatter, Nicole; Golf, Ottmar; Veselkov, Kirill; Brown, Robert; Ghaem-Maghami, Sadaf; Takats, Zoltan

2016-01-01

Ovarian cancer is highly prevalent among European women, and is the leading cause of gynaecological cancer death. Current histopathological diagnoses of tumour severity are based on interpretation of, for example, immunohistochemical staining. Desorption electrospray mass spectrometry imaging (DESI-MSI) generates spatially resolved metabolic profiles of tissues and supports an objective investigation of tumour biology. In this study, various ovarian tissue types were analysed by DESI-MSI and co-registered with their corresponding haematoxylin and eosin (H&E) stained images. The mass spectral data reveal tissue type-dependent lipid profiles which are consistent across the n = 110 samples (n = 107 patients) used in this study. Multivariate statistical methods were used to classify samples and identify molecular features discriminating between tissue types. Three main groups of samples (epithelial ovarian carcinoma, borderline ovarian tumours, normal ovarian stroma) were compared as were the carcinoma histotypes (serous, endometrioid, clear cell). Classification rates >84% were achieved for all analyses, and variables differing statistically between groups were determined and putatively identified. The changes noted in various lipid types help to provide a context in terms of tumour biochemistry. The classification of unseen samples demonstrates the capability of DESI-MSI to characterise ovarian samples and to overcome existing limitations in classical histopathology. PMID:27976698

[Sanitation and racial inequality conditions in urban Brazil: an analysis focused on the indigenous population based on the 2010 Population Census].

PubMed

Raupp, Ludimila; Fávaro, Thatiana Regina; Cunha, Geraldo Marcelo; Santos, Ricardo Ventura

2017-01-01

The aims of this study were to analyze and describe the presence and infrastructure of basic sanitation in the urban areas of Brazil, contrasting indigenous with non-indigenous households. Methods: A cross-sectional study based on microdata from the 2010 Census was conducted. The analyses were based on descriptive statistics (prevalence) and the construction of multiple logistic regression models (adjusted by socioeconomic and demographic covariates). The odds ratios were estimated for the association between the explanatory variables (covariates) and the outcome variables (water supply, sewage, garbage collection, and adequate sanitation). The statistical significance level established was 5%. Among the analyzed services, sewage proved to be the most precarious. Regarding race or color, indigenous households presented the lowest rate of sanitary infrastructure in Urban Brazil. The adjusted regression showed that, in general, indigenous households were at a disadvantage when compared to other categories of race or color, especially in terms of the presence of garbage collection services. These inequalities were much more pronounced in the South and Southeastern regions. The analyses of this study not only confirm the profile of poor conditions and infrastructure of the basic sanitation of indigenous households in urban areas, but also demonstrate the persistence of inequalities associated with race or color in the country.

Experimental design of an interlaboratory study for trace metal analysis of liquid fluids. [for aerospace vehicles

NASA Technical Reports Server (NTRS)

Greenbauer-Seng, L. A.

1983-01-01

The accurate determination of trace metals and fuels is an important requirement in much of the research into and development of alternative fuels for aerospace applications. Recognizing the detrimental effects of certain metals on fuel performance and fuel systems at the part per million and in some cases part per billion levels requires improved accuracy in determining these low concentration elements. Accurate analyses are also required to ensure interchangeability of analysis results between vendor, researcher, and end use for purposes of quality control. Previous interlaboratory studies have demonstrated the inability of different laboratories to agree on the results of metal analysis, particularly at low concentration levels, yet typically good precisions are reported within a laboratory. An interlaboratory study was designed to gain statistical information about the sources of variation in the reported concentrations. Five participant laboratories were used on a fee basis and were not informed of the purpose of the analyses. The effects of laboratory, analytical technique, concentration level, and ashing additive were studied in four fuel types for 20 elements of interest. The prescribed sample preparation schemes (variations of dry ashing) were used by all of the laboratories. The analytical data were statistically evaluated using a computer program for the analysis of variance technique.

System Synthesis in Preliminary Aircraft Design using Statistical Methods

NASA Technical Reports Server (NTRS)

DeLaurentis, Daniel; Mavris, Dimitri N.; Schrage, Daniel P.

1996-01-01

This paper documents an approach to conceptual and preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically design of experiments (DOE) and response surface methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an overall evaluation criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in a innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting a solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a high speed civil transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabalistic designs (and eventually robust ones).

Production and characterization of curcumin microcrystals and evaluation of the antimicrobial and sensory aspects in minimally processed carrots.

PubMed

Silva, Anderson Clayton da; Santos, Priscila Dayane de Freitas; Palazzi, Nicole Campezato; Leimann, Fernanda Vitória; Fuchs, Renata Hernandez Barros; Bracht, Lívia; Gonçalves, Odinei Hess

2017-05-24

Nontoxic conserving agents are in demand by the food industry due to consumers concern about synthetic conservatives, especially in minimally processed food. The antimicrobial activity of curcumin, a natural phenolic compound, has been extensively investigated but hydrophobicity is an issue when applying curcumin to foodstuff. The objective of this work was to evaluate curcumin microcrystals as an antimicrobial agent in minimally processed carrots. The antimicrobial activity of curcumin microcrystals was evaluated in vitro against Gram-positive (Bacillus cereus and Staphylococcus aureus) and Gram-negative (Escherichia coli and Pseudomonas aeruginosa) microorganisms, showing a statistically significant (p < 0.05) decrease in the minimum inhibitory concentration compared to in natura, pristine curcumin. Curcumin microcrystals were effective in inhibiting psychrotrophic and mesophile microorganisms in minimally processed carrots. Sensory analyses were carried out showing no significant difference (p < 0.05) between curcumin microcrystal-treated carrots and non-treated carrots in triangular and tetrahedral discriminative tests. Sensory tests also showed that curcumin microcrystals could be added as a natural preservative in minimally processed carrots without causing noticeable differences that could be detected by the consumer. One may conclude that the analyses of the minimally processed carrots demonstrated that curcumin microcrystals are a suitable natural compound to inhibit the natural microbiota of carrots from a statistical point of view.

Proper joint analysis of summary association statistics requires the adjustment of heterogeneity in SNP coverage pattern.

PubMed

Zhang, Han; Wheeler, William; Song, Lei; Yu, Kai

2017-07-07

As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Explaining nitrate pollution pressure on the groundwater resource in Kinshasa using a multivariate statistical modelling approach

NASA Astrophysics Data System (ADS)

Mfumu Kihumba, Antoine; Vanclooster, Marnik

2013-04-01

Drinking water in Kinshasa, the capital of the Democratic Republic of Congo, is provided by extracting groundwater from the local aquifer, particularly in peripheral areas. The exploited groundwater body is mainly unconfined and located within a continuous detrital aquifer, primarily composed of sedimentary formations. However, the aquifer is subjected to an increasing threat of anthropogenic pollution pressure. Understanding the detailed origin of this pollution pressure is important for sustainable drinking water management in Kinshasa. The present study aims to explain the observed nitrate pollution problem, nitrate being considered as a good tracer for other pollution threats. The analysis is made in terms of physical attributes that are readily available using a statistical modelling approach. For the nitrate data, use was made of a historical groundwater quality assessment study, for which the data were re-analysed. The physical attributes are related to the topography, land use, geology and hydrogeology of the region. Prior to the statistical modelling, intrinsic and specific vulnerability for nitrate pollution was assessed. This vulnerability assessment showed that the alluvium area in the northern part of the region is the most vulnerable area. This area consists of urban land use with poor sanitation. Re-analysis of the nitrate pollution data demonstrated that the spatial variability of nitrate concentrations in the groundwater body is high, and coherent with the fragmented land use of the region and the intrinsic and specific vulnerability maps. For the statistical modeling use was made of multiple regression and regression tree analysis. The results demonstrated the significant impact of land use variables on the Kinshasa groundwater nitrate pollution and the need for a detailed delineation of groundwater capture zones around the monitoring stations. Key words: Groundwater , Isotopic, Kinshasa, Modelling, Pollution, Physico-chemical.

Inferential Statistics in "Language Teaching Research": A Review and Ways Forward

ERIC Educational Resources Information Center

Lindstromberg, Seth

2016-01-01

This article reviews all (quasi)experimental studies appearing in the first 19 volumes (1997-2015) of "Language Teaching Research" (LTR). Specifically, it provides an overview of how statistical analyses were conducted in these studies and of how the analyses were reported. The overall conclusion is that there has been a tight adherence…

Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

PubMed

Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

2010-06-30

QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but also allows for analyzing the effect descriptors have on the statistical model's performance. The presented Bioclipse plugins equip scientists with graphical tools that make QSAR-ML easily accessible for the community.

Towards interoperable and reproducible QSAR analyses: Exchange of datasets

PubMed Central

2010-01-01

Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but also allows for analyzing the effect descriptors have on the statistical model's performance. The presented Bioclipse plugins equip scientists with graphical tools that make QSAR-ML easily accessible for the community. PMID:20591161

Targeting intensive versus conventional glycaemic control for type 1 diabetes mellitus: a systematic review with meta-analyses and trial sequential analyses of randomised clinical trials

PubMed Central

Kähler, Pernille; Grevstad, Berit; Almdal, Thomas; Gluud, Christian; Wetterslev, Jørn; Vaag, Allan; Hemmingsen, Bianca

2014-01-01

Objective To assess the benefits and harms of targeting intensive versus conventional glycaemic control in patients with type 1 diabetes mellitus. Design A systematic review with meta-analyses and trial sequential analyses of randomised clinical trials. Data sources The Cochrane Library, MEDLINE, EMBASE, Science Citation Index Expanded and LILACS to January 2013. Study selection Randomised clinical trials that prespecified different targets of glycaemic control in participants at any age with type 1 diabetes mellitus were included. Data extraction Two authors independently assessed studies for inclusion and extracted data. Results 18 randomised clinical trials included 2254 participants with type 1 diabetes mellitus. All trials had high risk of bias. There was no statistically significant effect of targeting intensive glycaemic control on all-cause mortality (risk ratio 1.16, 95% CI 0.65 to 2.08) or cardiovascular mortality (0.49, 0.19 to 1.24). Targeting intensive glycaemic control reduced the relative risks for the composite macrovascular outcome (0.63, 0.41 to 0.96; p=0.03), and nephropathy (0.37, 0.27 to 0.50; p<0.00001. The effect estimates of retinopathy, ketoacidosis and retinal photocoagulation were not consistently statistically significant between random and fixed effects models. The risk of severe hypoglycaemia was significantly increased with intensive glycaemic targets (1.40, 1.01 to 1.94). Trial sequential analyses showed that the amount of data needed to demonstrate a relative risk reduction of 10% were, in general, inadequate. Conclusions There was no significant effect towards improved all-cause mortality when targeting intensive glycaemic control compared with conventional glycaemic control. However, there may be beneficial effects of targeting intensive glycaemic control on the composite macrovascular outcome and on nephropathy, and detrimental effects on severe hypoglycaemia. Notably, the data for retinopathy and ketoacidosis were inconsistent. There was a severe lack of reporting on patient relevant outcomes, and all trials had poor bias control. PMID:25138801

Ecogeographic Genetic Epidemiology

PubMed Central

Sloan, Chantel D.; Duell, Eric J.; Shi, Xun; Irwin, Rebecca; Andrew, Angeline S.; Williams, Scott M.; Moore, Jason H.

2009-01-01

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial “clusters” of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic Information Systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence. PMID:19025788

Effects of prevailing winds on turbidity of a shallow estuary.

PubMed

Cho, Hyun Jung

2007-06-01

Estuarine waters are generally more turbid than lakes or marine waters due to greater algal mass and continual re-suspension of sediments. The varying effects of diurnal and seasonal prevailing winds on the turbidity condition of a wind-dominated estuary were investigated by spatial and statistical analyses of wind direction, water level, turbidity, chlorophyll a, and PAR (Photosynthetically Active Radiation) collected in Lake Pontchartrain, Louisiana, USA. The prolonged prevailing winds were responsible for the long-term, large-scale turbidity pattern of the estuary, whereas the short-term changes in wind direction had differential effects on turbidity and water level in varying locations. There were temporal and spatial changes in the relationship between vertical light attenuation coefficient (Kd) and turbidity, which indicate difference in phytoplankton and color also affect Kd. This study demonstrates that the effect of wind on turbidity and water level on different shores can be identified through system-specific analyses of turbidity patterns.

Tree-ring variation in western larch (Larix occidentalis Nutt. ) exposed to sulfur dioxide emissions

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

Fox, C.A.; Kincaid, W.B.; Nash, T.H. III

1984-12-01

Tree-ring analysis of western larch (Larix occidentialis Nutt) demonstrated both direct and indirect affects of sulfur dioxide emissions from the lead/zinc smelter at Trail, B.C. Tree cores were collected from 5 stands known to have been polluted and from 3 control stands. Age effects were removed by fitting theoretical growth curves, and macrocliate was modeled using the average of the controls and two laged values thereof. Separate analyses were performed for years before and after installation of two tall stacks, for drought and nondrought years, and for years prior to initiation of smelting. Regression analyses revealed a negative effect onmore » annual growth that diminished with increasing distance from the smelter and during drought years. Furthermore, chronology statistics suggested an increase in sensitivity to climate that persisted decades beyond implementation of pollution controls, which reduced emissions 10-fold. 38 references, 6 figures, 3 tables.« less

Effects of Prevailing Winds on Turbidity of a Shallow Estuary

PubMed Central

Cho, Hyun Jung

2007-01-01

Estuarine waters are generally more turbid than lakes or marine waters due to greater algal mass and continual re-suspension of sediments. The varying effects of diurnal and seasonal prevailing winds on the turbidity condition of a wind-dominated estuary were investigated by spatial and statistical analyses of wind direction, water level, turbidity, chlorophyll a, and PAR (Photosynthetically Active Radiation) collected in Lake Pontchartrain, Louisiana, USA. The prolonged prevailing winds were responsible for the long-term, large-scale turbidity pattern of the estuary, whereas the short-term changes in wind direction had differential effects on turbidity and water level in varying locations. There were temporal and spatial changes in the relationship between vertical light attenuation coefficient (Kd) and turbidity, which indicate difference in phytoplankton and color also affect Kd. This study demonstrates that the effect of wind on turbidity and water level on different shores can be identified through system-specific analyses of turbidity patterns. PMID:17617683

Accounting for standard errors of vision-specific latent trait in regression models.

PubMed

Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

2014-07-11

To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Does the emergency surgery score accurately predict outcomes in emergent laparotomies?

PubMed

Peponis, Thomas; Bohnen, Jordan D; Sangji, Naveen F; Nandan, Anirudh R; Han, Kelsey; Lee, Jarone; Yeh, D Dante; de Moya, Marc A; Velmahos, George C; Chang, David C; Kaafarani, Haytham M A

2017-08-01

The emergency surgery score is a mortality-risk calculator for emergency general operation patients. We sought to examine whether the emergency surgery score predicts 30-day morbidity and mortality in a high-risk group of patients undergoing emergent laparotomy. Using the 2011-2012 American College of Surgeons National Surgical Quality Improvement Program database, we identified all patients who underwent emergent laparotomy using (1) the American College of Surgeons National Surgical Quality Improvement Program definition of "emergent," and (2) all Current Procedural Terminology codes denoting a laparotomy, excluding aortic aneurysm rupture. Multivariable logistic regression analyses were performed to measure the correlation (c-statistic) between the emergency surgery score and (1) 30-day mortality, and (2) 30-day morbidity after emergent laparotomy. As sensitivity analyses, the correlation between the emergency surgery score and 30-day mortality was also evaluated in prespecified subgroups based on Current Procedural Terminology codes. A total of 26,410 emergent laparotomy patients were included. Thirty-day mortality and morbidity were 10.2% and 43.8%, respectively. The emergency surgery score correlated well with mortality (c-statistic = 0.84); scores of 1, 11, and 22 correlated with mortalities of 0.4%, 39%, and 100%, respectively. Similarly, the emergency surgery score correlated well with morbidity (c-statistic = 0.74); scores of 0, 7, and 11 correlated with complication rates of 13%, 58%, and 79%, respectively. The morbidity rates plateaued for scores higher than 11. Sensitivity analyses demonstrated that the emergency surgery score effectively predicts mortality in patients undergoing emergent (1) splenic, (2) gastroduodenal, (3) intestinal, (4) hepatobiliary, or (5) incarcerated ventral hernia operation. The emergency surgery score accurately predicts outcomes in all types of emergent laparotomy patients and may prove valuable as a bedside decision-making tool for patient and family counseling, as well as for adequate risk-adjustment in emergent laparotomy quality benchmarking efforts. Copyright © 2017 Elsevier Inc. All rights reserved.

Morphology of sustentaculum tali: Biomechanical importance and correlation with angular dimensions of the talus.

PubMed

Mahato, Niladri Kumar

2011-12-01

The talus and the calcaneus share the bulk of load transmitted from the leg to the skeleton of the foot. The present study analyses the inter-relationship between the superior articular surface and the angular dimensions of the talus with the morphology of the sustentaculum tali. Identification of possible relationships between different angular parameters of the talus morphology and the sustentaculum tali in context of load transmission through the foot. One articular surface and three angular parameters at the junction of the head and the body were measured from dried human talar bones. Corresponding calcaneal samples were measured for four dimensions at the sustentaculum tali. Correlation and regression statistical values between parameters were worked out and analysed. Several parameters within the talus demonstrated significant correlations amongst themselves. The neck vertical angle showed a strong correlation with the articulating surface area below the head of the talus. The inter-relationship between articular and angular parameters within the talus demonstrates strong correlation for certain parameters. Data presented in the study may be helpful to adjust calcaneal and talar screw placement techniques, prosthesis designing and bio-mechanical studies at this important region. Copyright © 2011 Elsevier Ltd. All rights reserved.

A two-factor error model for quantitative steganalysis

NASA Astrophysics Data System (ADS)

Böhme, Rainer; Ker, Andrew D.

2006-02-01

Quantitative steganalysis refers to the exercise not only of detecting the presence of hidden stego messages in carrier objects, but also of estimating the secret message length. This problem is well studied, with many detectors proposed but only a sparse analysis of errors in the estimators. A deep understanding of the error model, however, is a fundamental requirement for the assessment and comparison of different detection methods. This paper presents a rationale for a two-factor model for sources of error in quantitative steganalysis, and shows evidence from a dedicated large-scale nested experimental set-up with a total of more than 200 million attacks. Apart from general findings about the distribution functions found in both classes of errors, their respective weight is determined, and implications for statistical hypothesis tests in benchmarking scenarios or regression analyses are demonstrated. The results are based on a rigorous comparison of five different detection methods under many different external conditions, such as size of the carrier, previous JPEG compression, and colour channel selection. We include analyses demonstrating the effects of local variance and cover saturation on the different sources of error, as well as presenting the case for a relative bias model for between-image error.

Smoke-free legislation and the incidence of paediatric respiratory infections and wheezing/asthma: interrupted time series analyses in the four UK nations

PubMed Central

Been, Jasper V.; Szatkowski, Lisa; van Staa, Tjeerd-Pieter; Leufkens, Hubert G.; van Schayck, Onno C.; Sheikh, Aziz; de Vries, Frank; Souverein, Patrick

2015-01-01

We investigated the association between introduction of smoke-free legislation in the UK (March 2006 for Scotland, April 2007 for Wales and Northern Ireland, and July 2007 for England) and the incidence of respiratory diseases among children. We extracted monthly counts of new diagnoses of wheezing/asthma and RTIs among children aged 0–12 years from all general practices in the Clinical Practice Research Datalink during 1997–2012. Interrupted time series analyses were performed using generalised additive mixed models, adjusting for underlying incidence trends, population size changes, seasonal factors, and pandemic influenza, as appropriate. 366,642 new wheezing/asthma diagnoses and 4,324,789 RTIs were observed over 9,536,003 patient-years. There was no statistically significant change in the incidence of wheezing/asthma after introduction of smoke-free legislation in England (incidence rate ratio (IRR) 0.94, 95% CI 0.81–1.09) or any other UK country (Scotland: IRR 0.99, 95% CI 0.83–1.19; Wales: IRR 1.09, 95% CI 0.89–1.35; Northern Ireland: IRR 0.96, 95% CI 0.76–1.22). Similarly no statistically significant changes in RTI incidence were demonstrated (England: IRR 0.95, 95% CI 0.86–1.06; Scotland: IRR 0.96, 95% CI 0.83–1.11; Wales: IRR 0.97, 95% CI 0.86–1.09; Northern Ireland: IRR 0.90, 95% CI 0.79–1.03). There were no demonstrable reductions in the incidence of paediatric wheezing/asthma or RTIs following introduction of smoke-free legislation in the UK. PMID:26463498

Which is the optimal risk stratification system for surgically treated localized primary GIST? Comparison of three contemporary prognostic criteria in 171 tumors and a proposal for a modified Armed Forces Institute of Pathology risk criteria.

PubMed

Goh, Brian K P; Chow, Pierce K H; Yap, Wai-Ming; Kesavan, Sittampalam M; Song, In-Chin; Paul, Pradeep G; Ooi, Boon-Swee; Chung, Yaw-Fui A; Wong, Wai-Keong

2008-08-01

This study aims to validate and compare the performance of the National Institute of Health (NIH) criteria, Huang modified NIH criteria, and Armed Forces Institute of Pathology (AFIP) risk criteria for gastrointestinal stromal tumors (GISTs) in a large series of localized primary GISTs surgically treated at a single institution to determine the ideal risk stratification system for GIST. The clinicopathological features of 171 consecutive patients who underwent surgical resection for GISTs were retrospectively reviewed. Statistical analyses were performed to compare the prognostic value of the three risk criteria by analyzing the discriminatory ability linear trend, homogeneity, monotonicity of gradients, and Akaike information criteria. The median actuarial recurrence-free survival (RFS) for all 171 patients was 70%. On multivariate analyses, size >10 cm, mitotic count >5/50 high-power field, tumor necrosis, and serosal involvement were independent prognostic factors of RFS. All three risk criteria demonstrated a statistically significant difference in the recurrence rate, median actuarial RFS, actuarial 5-year RFS, and tumor-specific death across the different stages. Comparison of the various risk-stratification systems demonstrated that our proposed modified AFIP criteria had the best independent predictive value of RFS when compared with the other systems. The NIH, modified NIH, and AFIP criteria are useful in the prognostication of GIST, and the AFIP risk criteria provided the best prognostication among the three systems for primary localized GIST. However, remarkable prognostic heterogeneity exists in the AFIP high-risk category, and with our proposed modification, this system provides the most accurate prognostic information.

Impact of human development on safety consciousness in construction.

PubMed

Baradan, Selim; Dikmen, Seyyit Umit; Akboga Kale, Ozge

2018-05-03

The International Labour Organization (ILO) reports that the risk of fatal occupational injuries in developing countries is almost twice as high as in developed countries, indicating a potential relationship between the fatality rates and the development level. The human development index (HDI), based on life expectancy, knowledge level and purchasing power parity, endorsed by the United Nations Development Programme, is a widely accepted measure of the development level. This study investigates the relationship between the HDI and the fatality rates reported by the ILO. A 23-country data set is used to demonstrate the general trend of the relationship followed by country-specific analyses for Australia, Spain, Hungary and Turkey. The study conducted is limited to fatal occupational injuries in construction, where the accidents are notoriously high. The results demonstrate a statistically significant inverse relationship between the fatality rates and the HDI.

[Colonic perforation during colonoscopy. 100 cases].

PubMed

Hureau, J; Avtan, L; Germain, M; Blanc, D; Chaussade, G

1992-01-01

The analysis of 100 cases of colon perforation during colposcopic examinations highly demonstrates such a statement. The perforation risk during colposcopies is generally of the order of 0.2% for a diagnosis coloscopy. According to the statistic data used, it can reach 0.5 to 3% in therapy coloscopy. This is a risk inherent to the technique used. It is thus required to analyse the causes and take the appropriate measures to reduce it to a minimum. Mortality due to such a complication remains high (14%), i.e about 0.015 to 0.1% (#2/10000) of all colposcopies. In 11% of the patients, serious sequelae are to be observed. This demonstrates the significance of the medico-legal problem set by these perforations during colposcopies. The whole personnel responsibility can be involved: colposcopist, surgeon, anesthetist and hospital unit.

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

LandScape: a simple method to aggregate p-values and other stochastic variables without a priori grouping.

PubMed

Wiuf, Carsten; Schaumburg-Müller Pallesen, Jonatan; Foldager, Leslie; Grove, Jakob

2016-08-01

In many areas of science it is custom to perform many, potentially millions, of tests simultaneously. To gain statistical power it is common to group tests based on a priori criteria such as predefined regions or by sliding windows. However, it is not straightforward to choose grouping criteria and the results might depend on the chosen criteria. Methods that summarize, or aggregate, test statistics or p-values, without relying on a priori criteria, are therefore desirable. We present a simple method to aggregate a sequence of stochastic variables, such as test statistics or p-values, into fewer variables without assuming a priori defined groups. We provide different ways to evaluate the significance of the aggregated variables based on theoretical considerations and resampling techniques, and show that under certain assumptions the FWER is controlled in the strong sense. Validity of the method was demonstrated using simulations and real data analyses. Our method may be a useful supplement to standard procedures relying on evaluation of test statistics individually. Moreover, by being agnostic and not relying on predefined selected regions, it might be a practical alternative to conventionally used methods of aggregation of p-values over regions. The method is implemented in Python and freely available online (through GitHub, see the Supplementary information).

Economic evaluation of factorial randomised controlled trials: challenges, methods and recommendations

PubMed Central

Gray, Alastair

2017-01-01

Increasing numbers of economic evaluations are conducted alongside randomised controlled trials. Such studies include factorial trials, which randomise patients to different levels of two or more factors and can therefore evaluate the effect of multiple treatments alone and in combination. Factorial trials can provide increased statistical power or assess interactions between treatments, but raise additional challenges for trial‐based economic evaluations: interactions may occur more commonly for costs and quality‐adjusted life‐years (QALYs) than for clinical endpoints; economic endpoints raise challenges for transformation and regression analysis; and both factors must be considered simultaneously to assess which treatment combination represents best value for money. This article aims to examine issues associated with factorial trials that include assessment of costs and/or cost‐effectiveness, describe the methods that can be used to analyse such studies and make recommendations for health economists, statisticians and trialists. A hypothetical worked example is used to illustrate the challenges and demonstrate ways in which economic evaluations of factorial trials may be conducted, and how these methods affect the results and conclusions. Ignoring interactions introduces bias that could result in adopting a treatment that does not make best use of healthcare resources, while considering all interactions avoids bias but reduces statistical power. We also introduce the concept of the opportunity cost of ignoring interactions as a measure of the bias introduced by not taking account of all interactions. We conclude by offering recommendations for planning, analysing and reporting economic evaluations based on factorial trials, taking increased analysis costs into account. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28470760

A review of geographic variation and Geographic Information Systems (GIS) applications in prescription drug use research.

PubMed

Wangia, Victoria; Shireman, Theresa I

2013-01-01

While understanding geography's role in healthcare has been an area of research for over 40 years, the application of geography-based analyses to prescription medication use is limited. The body of literature was reviewed to assess the current state of such studies to demonstrate the scale and scope of projects in order to highlight potential research opportunities. To review systematically how researchers have applied geography-based analyses to medication use data. Empiric, English language research articles were identified through PubMed and bibliographies. Original research articles were independently reviewed as to the medications or classes studied, data sources, measures of medication exposure, geographic units of analysis, geospatial measures, and statistical approaches. From 145 publications matching key search terms, forty publications met the inclusion criteria. Cardiovascular and psychotropic classes accounted for the largest proportion of studies. Prescription drug claims were the primary source, and medication exposure was frequently captured as period prevalence. Medication exposure was documented across a variety of geopolitical units such as countries, provinces, regions, states, and postal codes. Most results were descriptive and formal statistical modeling capitalizing on geospatial techniques was rare. Despite the extensive research on small area variation analysis in healthcare, there are a limited number of studies that have examined geographic variation in medication use. Clearly, there is opportunity to collaborate with geographers and GIS professionals to harness the power of GIS technologies and to strengthen future medication studies by applying more robust geospatial statistical methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantitative Susceptibility Mapping after Sports-Related Concussion.

PubMed

Koch, K M; Meier, T B; Karr, R; Nencka, A S; Muftuler, L T; McCrea, M

2018-06-07

Quantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion. Longitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping. Statistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations. The results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion. © 2018 by American Journal of Neuroradiology.

A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.

PubMed

Shadish, William R; Hedges, Larry V; Pustejovsky, James E; Boyajian, Jonathan G; Sullivan, Kristynn J; Andrade, Alma; Barrientos, Jeannette L

2014-01-01

We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.

A quantitative comparative analysis of Advancement via Independent Determination (AVID) in Texas middle schools

NASA Astrophysics Data System (ADS)

Reed, Krystal Astra

The "Advancement via Individual Determination (AVID) program was designed to provide resources and strategies that enable underrepresented minority students to attend 4-year colleges" (AVID Center, 2013, p. 2). These students are characterized as the forgotten middle in that they have high test scores, average-to-low grades, minority or low socioeconomic status, and will be first-generation college students (AVID, 2011). Research indicates (Huerta, Watt, & Butcher, 2013) that strict adherence to 11 program components supports success of students enrolled in AVID, and AVID certification depends on districts following those components. Several studies (AVID Center, 2013) have investigated claims about the AVID program through qualitative analyses; however, very few have addressed this program quantitatively. This researcher sought to determine whether differences existed between student achievement and attendance rates between AVID and non-AVID middle schools. To achieve this goal, the researcher compared eighth-grade science and seventh- and eighth-grade mathematics scores from the 2007 to 2011 Texas Assessment of Knowledge and Skills (TAKS) and overall attendance rates in demographically equivalent AVID and non-AVID middle schools. Academic Excellence Indicator System (AEIS) reports from the Texas Education Agency (TEA) were used to obtain 2007 to 2011 TAKS results and attendance information for the selected schools. The results indicated a statistically significant difference between AVID demonstration students and non-AVID students in schools with similar CI. No statistically significant differences were found on any component of the TAKS for AVID economically disadvantaged students. The mean scores indicated an achievement gap between non-AVID and AVID demonstration middle schools. The findings from the other three research questions indicated no statistically significant differences between AVID and non-AVID student passing rates on the seventh- and eighth-grade TAKS math tests or on overall attendance rates. The mean scores on the eighth-grade TAKS science test revealed some positive results in the academic performance of economically disadvantaged in non-AVID demonstration middle schools. Specifically, the results indicated that the mean passing percentage of AVID demonstration was lower than that of non-AVID middle schools. The TAKS scores showed a small achievement gap between non-AVID and AVID demonstration middle schools.

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate framework for visually assessing the statistical significance of spatial clusters.

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

Bootstrap versus Statistical Effect Size Corrections: A Comparison with Data from the Finding Embedded Figures Test.

ERIC Educational Resources Information Center

Thompson, Bruce; Melancon, Janet G.

Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…

Intellicount: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning

PubMed Central

Fantuzzo, J. A.; Mirabella, V. R.; Zahn, J. D.

2017-01-01

Abstract Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual analysis by a human observer. Here, we describe Intellicount, a high-throughput, fully-automated synapse quantification program which applies a novel machine learning (ML)-based image processing algorithm to systematically improve region of interest (ROI) identification over simple thresholding techniques. Through processing large datasets from both human and mouse neurons, we demonstrate that this approach allows image processing to proceed independently of carefully set thresholds, thus reducing the need for human intervention. As a result, this method can efficiently and accurately process large image datasets with minimal interaction by the experimenter, making it less prone to bias and less liable to human error. Furthermore, Intellicount is integrated into an intuitive graphical user interface (GUI) that provides a set of valuable features, including automated and multifunctional figure generation, routine statistical analyses, and the ability to run full datasets through nested folders, greatly expediting the data analysis process. PMID:29218324

Permutation Tests of Hierarchical Cluster Analyses of Carrion Communities and Their Potential Use in Forensic Entomology.

PubMed

van der Ham, Joris L

2016-05-19

Forensic entomologists can use carrion communities' ecological succession data to estimate the postmortem interval (PMI). Permutation tests of hierarchical cluster analyses of these data provide a conceptual method to estimate part of the PMI, the post-colonization interval (post-CI). This multivariate approach produces a baseline of statistically distinct clusters that reflect changes in the carrion community composition during the decomposition process. Carrion community samples of unknown post-CIs are compared with these baseline clusters to estimate the post-CI. In this short communication, I use data from previously published studies to demonstrate the conceptual feasibility of this multivariate approach. Analyses of these data produce series of significantly distinct clusters, which represent carrion communities during 1- to 20-day periods of the decomposition process. For 33 carrion community samples, collected over an 11-day period, this approach correctly estimated the post-CI within an average range of 3.1 days. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Trends in selected streamflow statistics at 19 long-term streamflow-gaging stations indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico, 1922-2009

USGS Publications Warehouse

Barbie, Dana L.; Wehmeyer, Loren L.

2012-01-01

Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.

Measuring anxiety after spinal cord injury: Development and psychometric characteristics of the SCI-QOL Anxiety item bank and linkage with GAD-7.

PubMed

Kisala, Pamela A; Tulsky, David S; Kalpakjian, Claire Z; Heinemann, Allen W; Pohlig, Ryan T; Carle, Adam; Choi, Seung W

2015-05-01

To develop a calibrated item bank and computer adaptive test to assess anxiety symptoms in individuals with spinal cord injury (SCI), transform scores to the Patient Reported Outcomes Measurement Information System (PROMIS) metric, and create a statistical linkage with the Generalized Anxiety Disorder (GAD)-7, a widely used anxiety measure. Grounded-theory based qualitative item development methods; large-scale item calibration field testing; confirmatory factor analysis; graded response model item response theory analyses; statistical linking techniques to transform scores to a PROMIS metric; and linkage with the GAD-7. Setting Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Participants Adults with traumatic SCI. Spinal Cord Injury-Quality of Life (SCI-QOL) Anxiety Item Bank Seven hundred sixteen individuals with traumatic SCI completed 38 items assessing anxiety, 17 of which were PROMIS items. After 13 items (including 2 PROMIS items) were removed, factor analyses confirmed unidimensionality. Item response theory analyses were used to estimate slopes and thresholds for the final 25 items (15 from PROMIS). The observed Pearson correlation between the SCI-QOL Anxiety and GAD-7 scores was 0.67. The SCI-QOL Anxiety item bank demonstrates excellent psychometric properties and is available as a computer adaptive test or short form for research and clinical applications. SCI-QOL Anxiety scores have been transformed to the PROMIS metric and we provide a method to link SCI-QOL Anxiety scores with those of the GAD-7.

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

PubMed

Bohler, Anwesha; Eijssen, Lars M T; van Iersel, Martijn P; Leemans, Christ; Willighagen, Egon L; Kutmon, Martina; Jaillard, Magali; Evelo, Chris T

2015-08-23

Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

PubMed

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genetic polymorphisms of pharmacogenomic VIP variants in the Yi population from China.

PubMed

Yan, Mengdan; Li, Dianzhen; Zhao, Guige; Li, Jing; Niu, Fanglin; Li, Bin; Chen, Peng; Jin, Tianbo

2018-03-30

Drug response and target therapeutic dosage are different among individuals. The variability is largely genetically determined. With the development of pharmacogenetics and pharmacogenomics, widespread research have provided us a wealth of information on drug-related genetic polymorphisms, and the very important pharmacogenetic (VIP) variants have been identified for the major populations around the world whereas less is known regarding minorities in China, including the Yi ethnic group. Our research aims to screen the potential genetic variants in Yi population on pharmacogenomics and provide a theoretical basis for future medication guidance. In the present study, 80 VIP variants (selected from the PharmGKB database) were genotyped in 100 unrelated and healthy Yi adults recruited for our research. Through statistical analysis, we made a comparison between the Yi and other 11 populations listed in the HapMap database for significant SNPs detection. Two specific SNPs were subsequently enrolled in an observation on global allele distribution with the frequencies downloaded from ALlele FREquency Database. Moreover, F-statistics (Fst), genetic structure and phylogenetic tree analyses were conducted for determination of genetic similarity between the 12 ethnic groups. Using the χ2 tests, rs1128503 (ABCB1), rs7294 (VKORC1), rs9934438 (VKORC1), rs1540339 (VDR) and rs689466 (PTGS2) were identified as the significantly different loci for further analysis. The global allele distribution revealed that the allele "A" of rs1540339 and rs9934438 were more frequent in Yi people, which was consistent with the most populations in East Asia. F-statistics (Fst), genetic structure and phylogenetic tree analyses demonstrated that the Yi and CHD shared a closest relationship on their genetic backgrounds. Additionally, Yi was considered similar to the Han people from Shaanxi province among the domestic ethnic populations in China. Our results demonstrated significant differences on several polymorphic SNPs and supplement the pharmacogenomic information for the Yi population, which could provide new strategies for optimizing clinical medication in accordance with the genetic determinants of drug toxicity and efficacy. Copyright © 2018 Elsevier B.V. All rights reserved.

Latinos in science: Identifying factors that influence the low percentage of Latino representation in the sciences

NASA Astrophysics Data System (ADS)

Miranda, Susan Jennifer

A mixed methods approach was used to identify factors that influence the underrepresentation of Latinos in the domain of science. The researcher investigated the role of family influences, academic preparation, and personal motivations to determine science-related career choices by Latinos. Binary logistic regression analyses were conducted using information from Latinos gathered from the National Education Longitudinal Study of 1988 (NELS: 88) administered by the National Center for Education Statistics. For the present study, data were analyzed using participants' responses as high school seniors, college students, and post-baccalaureates. Students responded to questions on school, work, parental academic influences, personal aspirations, and self-perception. To provide more insight into the experiences of Latinos in science and support the statistical analyses, nine students majoring in science in a private, urban university located in the northeastern part of the country were interviewed. Eleven variables related to parents' academic support and students' perceptions of parental support were taken together as predictors for two separate criteria from the survey. These results identified parents' level of education and the importance of academics to parents in their teen's college choice as significant predictors in determining college major in science. When the criterion was degree in science, the significant predictor was the frequency parents contacted high school as volunteers. Student interviews supported this information, demonstrating the importance of parental support in attaining a degree in science. Academic preparation was also analyzed. Students' reasons for taking science classes in high school was a significant predictor for science major; significant predictors for science degree were the emphasis placed on objectives in math and science classes and number of courses in biology and physics. Student interviews supported this information and demonstrated the influence their own motivation placed on their goals. Survey data were also obtained about the students' test scores and academic achievement. Data collected from the statistical and interview components of the study developed a greater understanding for the lack of Latinos in the sciences as influenced by personal and familial factors.

Information processing requirements for on-board monitoring of automatic landing

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Karmarkar, J. S.

1977-01-01

A systematic procedure is presented for determining the information processing requirements for on-board monitoring of automatic landing systems. The monitoring system detects landing anomalies through use of appropriate statistical tests. The time-to-correct aircraft perturbations is determined from covariance analyses using a sequence of suitable aircraft/autoland/pilot models. The covariance results are used to establish landing safety and a fault recovery operating envelope via an event outcome tree. This procedure is demonstrated with examples using the NASA Terminal Configured Vehicle (B-737 aircraft). The procedure can also be used to define decision height, assess monitoring implementation requirements, and evaluate alternate autoland configurations.

Evaluating mediation and moderation effects in school psychology: A presentation of methods and review of current practice

PubMed Central

Fairchild, Amanda J.; McQuillin, Samuel D.

2017-01-01

Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described. PMID:20006988

Evaluating mediation and moderation effects in school psychology: a presentation of methods and review of current practice.

PubMed

Fairchild, Amanda J; McQuillin, Samuel D

2010-02-01

Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described.

DESIGNING ENVIRONMENTAL MONITORING DATABASES FOR STATISTIC ASSESSMENT

EPA Science Inventory

Databases designed for statistical analyses have characteristics that distinguish them from databases intended for general use. EMAP uses a probabilistic sampling design to collect data to produce statistical assessments of environmental conditions. In addition to supporting the ...

Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

PubMed

Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V

2018-04-01

A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.

Errors in statistical decision making Chapter 2 in Applied Statistics in Agricultural, Biological, and Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...

The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth

ERIC Educational Resources Information Center

Steyvers, Mark; Tenenbaum, Joshua B.

2005-01-01

We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…

Contrast enhanced dual energy spectral mammogram, an emerging addendum in breast imaging.

PubMed

Kariyappa, Kalpana D; Gnanaprakasam, Francis; Anand, Subhapradha; Krishnaswami, Murali; Ramachandran, Madan

2016-11-01

To assess the role of contrast-enhanced dual-energy spectral mammogram (CEDM) as a problem-solving tool in equivocal cases. 44 consenting females with equivocal findings on full-field digital mammogram underwent CEDM. All the images were interpreted by two radiologists independently. Confidence of presence was plotted on a three-point Likert scale and probability of cancer was assigned on Breast Imaging Reporting and Data System scoring. Histopathology was taken as the gold standard. Statistical analyses of all variables were performed. 44 breast lesions were included in the study, among which 77.3% lesions were malignant or precancerous and 22.7% lesions were benign or inconclusive. 20% of lesions were identified only on CEDM. True extent of the lesion was made out in 15.9% of cases, multifocality was established in 9.1% of cases and ductal extension was demonstrated in 6.8% of cases. Statistical significance for CEDM was p-value <0.05. Interobserver kappa value was 0.837. CEDM has a useful role in identifying occult lesions in dense breasts and in triaging lesions. In a mammographically visible lesion, CEDM characterizes the lesion, affirms the finding and better demonstrates response to treatment. Hence, we conclude that CEDM is a useful complementary tool to standard mammogram. Advances in knowledge: CEDM can detect and demonstrate lesions even in dense breasts with the advantage of feasibility of stereotactic biopsy in the same setting. Hence, it has the potential to be a screening modality with need for further studies and validation.

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

Kreuzer-Martin, Helen W.; Hegg, Eric L.

The use of isotopic signatures for forensic analysis of biological materials is well-established, and the same general principles that apply to interpretation of stable isotope content of C, N, O, and H apply to the analysis of microorganisms. Heterotrophic microorganisms derive their isotopic content from their growth substrates, which are largely plant and animal products, and the water in their culture medium. Thus the isotope signatures of microbes are tied to their growth environment. The C, N, O, and H isotope ratios of spores have been demonstrated to constitute highly discriminating signatures for sample matching. They can rule out specificmore » samples of media and/or water as possible production media, and can predict isotope ratio ranges of the culture media and water used to produce a given sample. These applications have been developed and tested through analyses of approximately 250 samples of Bacillus subtilis spores and over 500 samples of culture media, providing a strong statistical basis for data interpretation. A Bayesian statistical framework for integrating stable isotope data with other types of signatures derived from microorganisms has been able to characterize the culture medium used to produce spores of various Bacillus species, leveraging isotopic differences in different medium types and demonstrating the power of data integration for forensic investigations.« less

A comparison of spectral magnitude and phase-locking value analyses of the frequency-following response to complex tones

PubMed Central

Zhu, Li; Bharadwaj, Hari; Xia, Jing; Shinn-Cunningham, Barbara

2013-01-01

Two experiments, both presenting diotic, harmonic tone complexes (100 Hz fundamental), were conducted to explore the envelope-related component of the frequency-following response (FFRENV), a measure of synchronous, subcortical neural activity evoked by a periodic acoustic input. Experiment 1 directly compared two common analysis methods, computing the magnitude spectrum and the phase-locking value (PLV). Bootstrapping identified which FFRENV frequency components were statistically above the noise floor for each metric and quantified the statistical power of the approaches. Across listeners and conditions, the two methods produced highly correlated results. However, PLV analysis required fewer processing stages to produce readily interpretable results. Moreover, at the fundamental frequency of the input, PLVs were farther above the metric's noise floor than spectral magnitudes. Having established the advantages of PLV analysis, the efficacy of the approach was further demonstrated by investigating how different acoustic frequencies contribute to FFRENV, analyzing responses to complex tones composed of different acoustic harmonics of 100 Hz (Experiment 2). Results show that the FFRENV response is dominated by peripheral auditory channels responding to unresolved harmonics, although low-frequency channels driven by resolved harmonics also contribute. These results demonstrate the utility of the PLV for quantifying the strength of FFRENV across conditions. PMID:23862815

Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle

NASA Technical Reports Server (NTRS)

Coroneos, Rula; Pai, Shantaram, S.; Murthy, Pappu

2013-01-01

This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson??s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.

Statistical aspects of the TNK-S2B trial of tenecteplase versus alteplase in acute ischemic stroke: an efficient, dose-adaptive, seamless phase II/III design.

PubMed

Levin, Bruce; Thompson, John L P; Chakraborty, Bibhas; Levy, Gilberto; MacArthur, Robert; Haley, E Clarke

2011-08-01

TNK-S2B, an innovative, randomized, seamless phase II/III trial of tenecteplase versus rt-PA for acute ischemic stroke, terminated for slow enrollment before regulatory approval of use of phase II patients in phase III. (1) To review the trial design and comprehensive type I error rate simulations and (2) to discuss issues raised during regulatory review, to facilitate future approval of similar designs. In phase II, an early (24-h) outcome and adaptive sequential procedure selected one of three tenecteplase doses for phase III comparison with rt-PA. Decision rules comparing this dose to rt-PA would cause stopping for futility at phase II end, or continuation to phase III. Phase III incorporated two co-primary hypotheses, allowing for a treatment effect at either end of the trichotomized Rankin scale. Assuming no early termination, four interim analyses and one final analysis of 1908 patients provided an experiment-wise type I error rate of <0.05. Over 1,000 distribution scenarios, each involving 40,000 replications, the maximum type I error in phase III was 0.038. Inflation from the dose selection was more than offset by the one-half continuity correction in the test statistics. Inflation from repeated interim analyses was more than offset by the reduction from the clinical stopping rules for futility at the first interim analysis. Design complexity and evolving regulatory requirements lengthened the review process. (1) The design was innovative and efficient. Per protocol, type I error was well controlled for the co-primary phase III hypothesis tests, and experiment-wise. (2a) Time must be allowed for communications with regulatory reviewers from first design stages. (2b) Adequate type I error control must be demonstrated. (2c) Greater clarity is needed on (i) whether this includes demonstration of type I error control if the protocol is violated and (ii) whether simulations of type I error control are acceptable. (2d) Regulatory agency concerns that protocols for futility stopping may not be followed may be allayed by submitting interim analysis results to them as these analyses occur.

A retrospective cohort mortality study of blending and packaging workers of Mobil Corporation.

PubMed

Collingwood, K W; Milcarek, B I; Raabe, G K

1991-01-01

This retrospective cohort mortality study examined 2,467 workers in lubrication products blending and packaging (B&P) operations at two refineries of Mobil Corporation between January 1, 1945 and December 31, 1978. Ninety-seven percent were male. Compared with U.S. males, there were significantly fewer deaths observed among males due to all causes, external causes, and diseases of the circulatory, respiratory, digestive, and genitourinary systems. Deaths observed from all cancer were fewer than expected, although not statistically significant. No statistically significant excess cause-specific mortality occurred at B&P facilities combined or separately. Nonsignificant increases in mortality were observed for cancers of the stomach, large intestine, prostate, the category of "other lymphatic tissue" cancer, and leukemia and aleukemia. Analyses demonstrated a statistically significant pattern of increasing SMR with employment duration for "other lymphatic tissue" cancer. Within the highest cumulative duration of employment category, the excess was confined to workers after 30 or more years since first employment. Although the interpretation of cancer mortality patterns is limited due to small numbers of deaths, the absence of associations with specific B&P departments is evidence against a causal interpretation.

Derivation from first principles of the statistical distribution of the mass peak intensities of MS data.

PubMed

Ipsen, Andreas

2015-02-03

Despite the widespread use of mass spectrometry (MS) in a broad range of disciplines, the nature of MS data remains very poorly understood, and this places important constraints on the quality of MS data analysis as well as on the effectiveness of MS instrument design. In the following, a procedure for calculating the statistical distribution of the mass peak intensity for MS instruments that use analog-to-digital converters (ADCs) and electron multipliers is presented. It is demonstrated that the physical processes underlying the data-generation process, from the generation of the ions to the signal induced at the detector, and on to the digitization of the resulting voltage pulse, result in data that can be well-approximated by a Gaussian distribution whose mean and variance are determined by physically meaningful instrumental parameters. This allows for a very precise understanding of the signal-to-noise ratio of mass peak intensities and suggests novel ways of improving it. Moreover, it is a prerequisite for being able to address virtually all data analytical problems in downstream analyses in a statistically rigorous manner. The model is validated with experimental data.

How to get statistically significant effects in any ERP experiment (and why you shouldn't).

PubMed

Luck, Steven J; Gaspelin, Nicholas

2017-01-01

ERP experiments generate massive datasets, often containing thousands of values for each participant, even after averaging. The richness of these datasets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant but bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand-averaged data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multifactor statistical analyses. Reanalyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant but bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions. © 2016 Society for Psychophysiological Research.

Compositional data analysis for physical activity, sedentary time and sleep research.

PubMed

Dumuid, Dorothea; Stanford, Tyman E; Martin-Fernández, Josep-Antoni; Pedišić, Željko; Maher, Carol A; Lewis, Lucy K; Hron, Karel; Katzmarzyk, Peter T; Chaput, Jean-Philippe; Fogelholm, Mikael; Hu, Gang; Lambert, Estelle V; Maia, José; Sarmiento, Olga L; Standage, Martyn; Barreira, Tiago V; Broyles, Stephanie T; Tudor-Locke, Catrine; Tremblay, Mark S; Olds, Timothy

2017-01-01

The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children's daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.

Post Hoc Analyses of ApoE Genotype-Defined Subgroups in Clinical Trials.

PubMed

Kennedy, Richard E; Cutter, Gary R; Wang, Guoqiao; Schneider, Lon S

2016-01-01

Many post hoc analyses of clinical trials in Alzheimer's disease (AD) and mild cognitive impairment (MCI) are in small Phase 2 trials. Subject heterogeneity may lead to statistically significant post hoc results that cannot be replicated in larger follow-up studies. We investigated the extent of this problem using simulation studies mimicking current trial methods with post hoc analyses based on ApoE4 carrier status. We used a meta-database of 24 studies, including 3,574 subjects with mild AD and 1,171 subjects with MCI/prodromal AD, to simulate clinical trial scenarios. Post hoc analyses examined if rates of progression on the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) differed between ApoE4 carriers and non-carriers. Across studies, ApoE4 carriers were younger and had lower baseline scores, greater rates of progression, and greater variability on the ADAS-cog. Up to 18% of post hoc analyses for 18-month trials in AD showed greater rates of progression for ApoE4 non-carriers that were statistically significant but unlikely to be confirmed in follow-up studies. The frequency of erroneous conclusions dropped below 3% with trials of 100 subjects per arm. In MCI, rates of statistically significant differences with greater progression in ApoE4 non-carriers remained below 3% unless sample sizes were below 25 subjects per arm. Statistically significant differences for ApoE4 in post hoc analyses often reflect heterogeneity among small samples rather than true differential effect among ApoE4 subtypes. Such analyses must be viewed cautiously. ApoE genotype should be incorporated into the design stage to minimize erroneous conclusions.

Methodological Standards for Meta-Analyses and Qualitative Systematic Reviews of Cardiac Prevention and Treatment Studies: A Scientific Statement From the American Heart Association.

PubMed

Rao, Goutham; Lopez-Jimenez, Francisco; Boyd, Jack; D'Amico, Frank; Durant, Nefertiti H; Hlatky, Mark A; Howard, George; Kirley, Katherine; Masi, Christopher; Powell-Wiley, Tiffany M; Solomonides, Anthony E; West, Colin P; Wessel, Jennifer

2017-09-05

Meta-analyses are becoming increasingly popular, especially in the fields of cardiovascular disease prevention and treatment. They are often considered to be a reliable source of evidence for making healthcare decisions. Unfortunately, problems among meta-analyses such as the misapplication and misinterpretation of statistical methods and tests are long-standing and widespread. The purposes of this statement are to review key steps in the development of a meta-analysis and to provide recommendations that will be useful for carrying out meta-analyses and for readers and journal editors, who must interpret the findings and gauge methodological quality. To make the statement practical and accessible, detailed descriptions of statistical methods have been omitted. Based on a survey of cardiovascular meta-analyses, published literature on methodology, expert consultation, and consensus among the writing group, key recommendations are provided. Recommendations reinforce several current practices, including protocol registration; comprehensive search strategies; methods for data extraction and abstraction; methods for identifying, measuring, and dealing with heterogeneity; and statistical methods for pooling results. Other practices should be discontinued, including the use of levels of evidence and evidence hierarchies to gauge the value and impact of different study designs (including meta-analyses) and the use of structured tools to assess the quality of studies to be included in a meta-analysis. We also recommend choosing a pooling model for conventional meta-analyses (fixed effect or random effects) on the basis of clinical and methodological similarities among studies to be included, rather than the results of a test for statistical heterogeneity. © 2017 American Heart Association, Inc.

Assessment and statistics of surgically induced astigmatism.

PubMed

Naeser, Kristian

2008-05-01

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

Psychometrics Matter in Health Behavior: A Long-term Reliability Generalization Study.

PubMed

Pickett, Andrew C; Valdez, Danny; Barry, Adam E

2017-09-01

Despite numerous calls for increased understanding and reporting of reliability estimates, social science research, including the field of health behavior, has been slow to respond and adopt such practices. Therefore, we offer a brief overview of reliability and common reporting errors; we then perform analyses to examine and demonstrate the variability of reliability estimates by sample and over time. Using meta-analytic reliability generalization, we examined the variability of coefficient alpha scores for a well-designed, consistent, nationwide health study, covering a span of nearly 40 years. For each year and sample, reliability varied. Furthermore, reliability was predicted by a sample characteristic that differed among age groups within each administration. We demonstrated that reliability is influenced by the methods and individuals from which a given sample is drawn. Our work echoes previous calls that psychometric properties, particularly reliability of scores, are important and must be considered and reported before drawing statistical conclusions.

Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography

PubMed Central

Gray Roncal, William; Prasad, Judy A.; Fernandes, Hugo L.; Gürsoy, Doga; De Andrade, Vincent; Fezzaa, Kamel; Xiao, Xianghui; Vogelstein, Joshua T.; Jacobsen, Chris; Körding, Konrad P.

2017-01-01

Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (µCT) for producing mesoscale (∼1 µm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for µCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts. PMID:29085899

Laser-induced plasmonic colours on metals

NASA Astrophysics Data System (ADS)

Guay, Jean-Michel; Calà Lesina, Antonino; Côté, Guillaume; Charron, Martin; Poitras, Daniel; Ramunno, Lora; Berini, Pierre; Weck, Arnaud

2017-07-01

Plasmonic resonances in metallic nanoparticles have been used since antiquity to colour glasses. The use of metal nanostructures for surface colourization has attracted considerable interest following recent developments in plasmonics. However, current top-down colourization methods are not ideally suited to large-scale industrial applications. Here we use a bottom-up approach where picosecond laser pulses can produce a full palette of non-iridescent colours on silver, gold, copper and aluminium. We demonstrate the process on silver coins weighing up to 5 kg and bearing large topographic variations (~1.5 cm). We find that colours are related to a single parameter, the total accumulated fluence, making the process suitable for high-throughput industrial applications. Statistical image analyses of laser-irradiated surfaces reveal various nanoparticle size distributions. Large-scale finite-difference time-domain computations based on these nanoparticle distributions reproduce trends seen in reflectance measurements, and demonstrate the key role of plasmonic resonances in colour formation.

Laser-induced plasmonic colours on metals

PubMed Central

Guay, Jean-Michel; Calà Lesina, Antonino; Côté, Guillaume; Charron, Martin; Poitras, Daniel; Ramunno, Lora; Berini, Pierre; Weck, Arnaud

2017-01-01

Plasmonic resonances in metallic nanoparticles have been used since antiquity to colour glasses. The use of metal nanostructures for surface colourization has attracted considerable interest following recent developments in plasmonics. However, current top-down colourization methods are not ideally suited to large-scale industrial applications. Here we use a bottom-up approach where picosecond laser pulses can produce a full palette of non-iridescent colours on silver, gold, copper and aluminium. We demonstrate the process on silver coins weighing up to 5 kg and bearing large topographic variations (∼1.5 cm). We find that colours are related to a single parameter, the total accumulated fluence, making the process suitable for high-throughput industrial applications. Statistical image analyses of laser-irradiated surfaces reveal various nanoparticle size distributions. Large-scale finite-difference time-domain computations based on these nanoparticle distributions reproduce trends seen in reflectance measurements, and demonstrate the key role of plasmonic resonances in colour formation. PMID:28719576

Prognostic factors in patients with advanced cancer: use of the patient-generated subjective global assessment in survival prediction.

PubMed

Martin, Lisa; Watanabe, Sharon; Fainsinger, Robin; Lau, Francis; Ghosh, Sunita; Quan, Hue; Atkins, Marlis; Fassbender, Konrad; Downing, G Michael; Baracos, Vickie

2010-10-01

To determine whether elements of a standard nutritional screening assessment are independently prognostic of survival in patients with advanced cancer. A prospective nested cohort of patients with metastatic cancer were accrued from different units of a Regional Palliative Care Program. Patients completed a nutritional screen on admission. Data included age, sex, cancer site, height, weight history, dietary intake, 13 nutrition impact symptoms, and patient- and physician-reported performance status (PS). Univariate and multivariate survival analyses were conducted. Concordance statistics (c-statistics) were used to test the predictive accuracy of models based on training and validation sets; a c-statistic of 0.5 indicates the model predicts the outcome as well as chance; perfect prediction has a c-statistic of 1.0. A training set of patients in palliative home care (n = 1,164) was used to identify prognostic variables. Primary disease site, PS, short-term weight change (either gain or loss), dietary intake, and dysphagia predicted survival in multivariate analysis (P < .05). A model including only patients separated by disease site and PS with high c-statistics between predicted and observed responses for survival in the training set (0.90) and validation set (0.88; n = 603). The addition of weight change, dietary intake, and dysphagia did not further improve the c-statistic of the model. The c-statistic was also not altered by substituting physician-rated palliative PS for patient-reported PS. We demonstrate a high probability of concordance between predicted and observed survival for patients in distinct palliative care settings (home care, tertiary inpatient, ambulatory outpatient) based on patient-reported information.

Detecting anomalies in CMB maps: a new method

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

Neelakanta, Jayanth T., E-mail: jayanthtn@gmail.com

2015-10-01

Ever since WMAP announced its first results, different analyses have shown that there is weak evidence for several large-scale anomalies in the CMB data. While the evidence for each anomaly appears to be weak, the fact that there are multiple seemingly unrelated anomalies makes it difficult to account for them via a single statistical fluke. So, one is led to considering a combination of these anomalies. But, if we ''hand-pick'' the anomalies (test statistics) to consider, we are making an a posteriori choice. In this article, we propose two statistics that do not suffer from this problem. The statistics aremore » linear and quadratic combinations of the a{sub ℓ m}'s with random co-efficients, and they test the null hypothesis that the a{sub ℓ m}'s are independent, normally-distributed, zero-mean random variables with an m-independent variance. The motivation for considering multiple modes is this: because most physical models that lead to large-scale anomalies result in coupling multiple ℓ and m modes, the ''coherence'' of this coupling should get enhanced if a combination of different modes is considered. In this sense, the statistics are thus much more generic than those that have been hitherto considered in literature. Using fiducial data, we demonstrate that the method works and discuss how it can be used with actual CMB data to make quite general statements about the incompatibility of the data with the null hypothesis.« less

Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly.

PubMed

Liem, Franziskus; Mérillat, Susan; Bezzola, Ladina; Hirsiger, Sarah; Philipp, Michel; Madhyastha, Tara; Jäncke, Lutz

2015-03-01

FreeSurfer is a tool to quantify cortical and subcortical brain anatomy automatically and noninvasively. Previous studies have reported reliability and statistical power analyses in relatively small samples or only selected one aspect of brain anatomy. Here, we investigated reliability and statistical power of cortical thickness, surface area, volume, and the volume of subcortical structures in a large sample (N=189) of healthy elderly subjects (64+ years). Reliability (intraclass correlation coefficient) of cortical and subcortical parameters is generally high (cortical: ICCs>0.87, subcortical: ICCs>0.95). Surface-based smoothing increases reliability of cortical thickness maps, while it decreases reliability of cortical surface area and volume. Nevertheless, statistical power of all measures benefits from smoothing. When aiming to detect a 10% difference between groups, the number of subjects required to test effects with sufficient power over the entire cortex varies between cortical measures (cortical thickness: N=39, surface area: N=21, volume: N=81; 10mm smoothing, power=0.8, α=0.05). For subcortical regions this number is between 16 and 76 subjects, depending on the region. We also demonstrate the advantage of within-subject designs over between-subject designs. Furthermore, we publicly provide a tool that allows researchers to perform a priori power analysis and sensitivity analysis to help evaluate previously published studies and to design future studies with sufficient statistical power. Copyright © 2014 Elsevier Inc. All rights reserved.

Evidence-based pathology in its second decade: toward probabilistic cognitive computing.

PubMed

Marchevsky, Alberto M; Walts, Ann E; Wick, Mark R

2017-03-01

Evidence-based pathology advocates using a combination of best available data ("evidence") from the literature and personal experience for the diagnosis, estimation of prognosis, and assessment of other variables that impact individual patient care. Evidence-based pathology relies on systematic reviews of the literature, evaluation of the quality of evidence as categorized by evidence levels and statistical tools such as meta-analyses, estimates of probabilities and odds, and others. However, it is well known that previously "statistically significant" information usually does not accurately forecast the future for individual patients. There is great interest in "cognitive computing" in which "data mining" is combined with "predictive analytics" designed to forecast future events and estimate the strength of those predictions. This study demonstrates the use of IBM Watson Analytics software to evaluate and predict the prognosis of 101 patients with typical and atypical pulmonary carcinoid tumors in which Ki-67 indices have been determined. The results obtained with this system are compared with those previously reported using "routine" statistical software and the help of a professional statistician. IBM Watson Analytics interactively provides statistical results that are comparable to those obtained with routine statistical tools but much more rapidly, with considerably less effort and with interactive graphics that are intuitively easy to apply. It also enables analysis of natural language variables and yields detailed survival predictions for patient subgroups selected by the user. Potential applications of this tool and basic concepts of cognitive computing are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Development of a Computer-Adaptive Physical Function Instrument for Social Security Administration Disability Determination

PubMed Central

Ni, Pengsheng; McDonough, Christine M.; Jette, Alan M.; Bogusz, Kara; Marfeo, Elizabeth E.; Rasch, Elizabeth K.; Brandt, Diane E.; Meterko, Mark; Chan, Leighton

2014-01-01

Objectives To develop and test an instrument to assess physical function (PF) for Social Security Administration (SSA) disability programs, the SSA-PF. Item Response Theory (IRT) analyses were used to 1) create a calibrated item bank for each of the factors identified in prior factor analyses, 2) assess the fit of the items within each scale, 3) develop separate Computer-Adaptive Test (CAT) instruments for each scale, and 4) conduct initial psychometric testing. Design Cross-sectional data collection; IRT analyses; CAT simulation. Setting Telephone and internet survey. Participants Two samples: 1,017 SSA claimants, and 999 adults from the US general population. Interventions None. Main Outcome Measure Model fit statistics, correlation and reliability coefficients, Results IRT analyses resulted in five unidimensional SSA-PF scales: Changing & Maintaining Body Position, Whole Body Mobility, Upper Body Function, Upper Extremity Fine Motor, and Wheelchair Mobility for a total of 102 items. High CAT accuracy was demonstrated by strong correlations between simulated CAT scores and those from the full item banks. Comparing the simulated CATs to the full item banks, very little loss of reliability or precision was noted, except at the lower and upper ranges of each scale. No difference in response patterns by age or sex was noted. The distributions of claimant scores were shifted to the lower end of each scale compared to those of a sample of US adults. Conclusions The SSA-PF instrument contributes important new methodology for measuring the physical function of adults applying to the SSA disability programs. Initial evaluation revealed that the SSA-PF instrument achieved considerable breadth of coverage in each content domain and demonstrated noteworthy psychometric properties. PMID:23578594

Development of a computer-adaptive physical function instrument for Social Security Administration disability determination.

PubMed

Ni, Pengsheng; McDonough, Christine M; Jette, Alan M; Bogusz, Kara; Marfeo, Elizabeth E; Rasch, Elizabeth K; Brandt, Diane E; Meterko, Mark; Haley, Stephen M; Chan, Leighton

2013-09-01

To develop and test an instrument to assess physical function for Social Security Administration (SSA) disability programs, the SSA-Physical Function (SSA-PF) instrument. Item response theory (IRT) analyses were used to (1) create a calibrated item bank for each of the factors identified in prior factor analyses, (2) assess the fit of the items within each scale, (3) develop separate computer-adaptive testing (CAT) instruments for each scale, and (4) conduct initial psychometric testing. Cross-sectional data collection; IRT analyses; CAT simulation. Telephone and Internet survey. Two samples: SSA claimants (n=1017) and adults from the U.S. general population (n=999). None. Model fit statistics, correlation, and reliability coefficients. IRT analyses resulted in 5 unidimensional SSA-PF scales: Changing & Maintaining Body Position, Whole Body Mobility, Upper Body Function, Upper Extremity Fine Motor, and Wheelchair Mobility for a total of 102 items. High CAT accuracy was demonstrated by strong correlations between simulated CAT scores and those from the full item banks. On comparing the simulated CATs with the full item banks, very little loss of reliability or precision was noted, except at the lower and upper ranges of each scale. No difference in response patterns by age or sex was noted. The distributions of claimant scores were shifted to the lower end of each scale compared with those of a sample of U.S. adults. The SSA-PF instrument contributes important new methodology for measuring the physical function of adults applying to the SSA disability programs. Initial evaluation revealed that the SSA-PF instrument achieved considerable breadth of coverage in each content domain and demonstrated noteworthy psychometric properties. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Statistical quality control through overall vibration analysis

NASA Astrophysics Data System (ADS)

Carnero, M. ^a. Carmen; González-Palma, Rafael; Almorza, David; Mayorga, Pedro; López-Escobar, Carlos

2010-05-01

The present study introduces the concept of statistical quality control in automotive wheel bearings manufacturing processes. Defects on products under analysis can have a direct influence on passengers' safety and comfort. At present, the use of vibration analysis on machine tools for quality control purposes is not very extensive in manufacturing facilities. Noise and vibration are common quality problems in bearings. These failure modes likely occur under certain operating conditions and do not require high vibration amplitudes but relate to certain vibration frequencies. The vibration frequencies are affected by the type of surface problems (chattering) of ball races that are generated through grinding processes. The purpose of this paper is to identify grinding process variables that affect the quality of bearings by using statistical principles in the field of machine tools. In addition, an evaluation of the quality results of the finished parts under different combinations of process variables is assessed. This paper intends to establish the foundations to predict the quality of the products through the analysis of self-induced vibrations during the contact between the grinding wheel and the parts. To achieve this goal, the overall self-induced vibration readings under different combinations of process variables are analysed using statistical tools. The analysis of data and design of experiments follows a classical approach, considering all potential interactions between variables. The analysis of data is conducted through analysis of variance (ANOVA) for data sets that meet normality and homoscedasticity criteria. This paper utilizes different statistical tools to support the conclusions such as chi squared, Shapiro-Wilks, symmetry, Kurtosis, Cochran, Hartlett, and Hartley and Krushal-Wallis. The analysis presented is the starting point to extend the use of predictive techniques (vibration analysis) for quality control. This paper demonstrates the existence of predictive variables (high-frequency vibration displacements) that are sensible to the processes setup and the quality of the products obtained. Based on the result of this overall vibration analysis, a second paper will analyse self-induced vibration spectrums in order to define limit vibration bands, controllable every cycle or connected to permanent vibration-monitoring systems able to adjust sensible process variables identified by ANOVA, once the vibration readings exceed established quality limits.

Cancer Statistics Animator

Cancer.gov

This tool allows users to animate cancer trends over time by cancer site and cause of death, race, and sex. Provides access to incidence, mortality, and survival. Select the type of statistic, variables, format, and then extract the statistics in a delimited format for further analyses.

Intermittent catheterisation with hydrophilic and non-hydrophilic urinary catheters: systematic literature review and meta-analyses.

PubMed

Rognoni, Carla; Tarricone, Rosanna

2017-01-10

Intermittent catheterisation is the method of choice for the management of bladder dysfunctions. Different urinary catheters are available, but there is conflicting evidence on which type of catheter is best. The present study provides an objective evaluation of the clinical effectiveness of different subsets of urinary catheters. A systematic literature review was performed for published RCTs regarding hydrophilic coated and PVC (standard) catheters for intermittent catheterisation. Separate meta-analyses were conducted to combine data on frequencies of urinary tract infections (UTIs) and haematuria. Two separate analyses were performed, including or excluding reused standard catheters. Seven studies were eligible for inclusion in the review. The meta-analyses exploring UTI frequencies showed a lower risk ratio associated with hydrophilic catheters in comparison to standard ones (RR = 0.84; 95% CI, 0.75-0.94; p = 0.003). Results for the "reuse" scenario were consistent with the ones related to "single-use" scenario in terms of frequency of UTIs. The meta-analyses exploring haematuria were not able to demonstrate any statistically significant difference between hydrophilic catheters in comparison to standard ones. The findings confirm previously reported benefits of hydrophilic catheters but a broader evaluation that takes into account also patient preferences, compliance of therapy, quality of life and costs would be needed to assess the economic sustainability of these advanced devices.

Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

NASA Astrophysics Data System (ADS)

Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen

2018-07-01

Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper, we use massive asymptotically optimal data compression to reduce the dimensionality of the data space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parametrized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate DELFI with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological data sets.

Occipital and Cingulate Hypometabolism are Significantly Under-Reported on 18-Fluorodeoxyglucose Positron Emission Tomography Scans of Patients with Lewy Body Dementia.

PubMed

Hamed, Moath; Schraml, Frank; Wilson, Jeffrey; Galvin, James; Sabbagh, Marwan N

2018-01-01

To determine whether occipital and cingulate hypometabolism is being under-reported or missed on 18-fluorodeoxyglucose positron emission tomography (FDG-PET) CT scans in patients with Dementia with Lewy Bodies (DLB). Recent studies have reported higher sensitivity and specificity for occipital and cingulate hypometabolism on FDG-PET of DLB patients. This retrospective chart review looked at regions of interest (ROI's) in FDG-PET CT scan reports in 35 consecutive patients with a clinical diagnosis of probable, possible, or definite DLB as defined by the latest DLB Consortium Report. ROI's consisting of glucose hypometabolism in frontal, parietal, temporal, occipital, and cingulate areas were tabulated and charted separately by the authors from the reports. A blinded Nuclear medicine physician read the images independently and marked ROI's separately. A Cohen's Kappa coefficient statistic was calculated to determine agreement between the reports and the blinded reads. On the radiology reports, 25.71% and 17.14% of patients reported occipital and cingulate hypometabolism respectively. Independent reads demonstrated significant disagreement with the proportion of occipital and cingulate hypometabolism being reported on initial reads: 91.43% and 85.71% respectively. Cohen's Kappa statistic determinations demonstrated significant agreement only with parietal hypometabolism (p<0.05). Occipital and cingulate hypometabolism is under-reported and missed frequently on clinical interpretations of FDG-PET scans of patients with DLB, but the frequency of hypometabolism is even higher than previously reported. Further studies with more statistical power and receiver operating characteristic analyses are needed to delineate the sensitivity and specificity of these in vivo biomarkers.

Correlation between Mitochondrial Reactive Oxygen and Severity of Atherosclerosis.

PubMed

Dorighello, Gabriel G; Paim, Bruno A; Kiihl, Samara F; Ferreira, Mônica S; Catharino, Rodrigo R; Vercesi, Anibal E; Oliveira, Helena C F

2016-01-01

Atherosclerosis has been associated with mitochondria dysfunction and damage. Our group demonstrated previously that hypercholesterolemic mice present increased mitochondrial reactive oxygen (mtROS) generation in several tissues and low NADPH/NADP+ ratio. Here, we investigated whether spontaneous atherosclerosis in these mice could be modulated by treatments that replenish or spare mitochondrial NADPH, named citrate supplementation, cholesterol synthesis inhibition, or both treatments simultaneously. Robust statistical analyses in pooled group data were performed in order to explain the variation of atherosclerosis lesion areas as related to the classic atherosclerosis risk factors such as plasma lipids, obesity, and oxidative stress, including liver mtROS. Using three distinct statistical tools (univariate correlation, adjusted correlation, and multiple regression) with increasing levels of stringency, we identified a novel significant association and a model that reliably predicts the extent of atherosclerosis due to variations in mtROS. Thus, results show that atherosclerosis lesion area is positively and independently correlated with liver mtROS production rates. Based on these findings, we propose that modulation of mitochondrial redox state influences the atherosclerosis extent.

First application of comet assay in blood cells of Mediterranean loggerhead sea turtle (Caretta caretta).

PubMed

Caliani, Ilaria; Campani, Tommaso; Giannetti, Matteo; Marsili, Letizia; Casini, Silvia; Fossi, Maria Cristina

2014-05-01

The aim of this study was to validate the comet assay in erythrocytes of Caretta caretta, a species never investigated for genotoxicity. We studied 31 loggerhead sea turtles from three Italian marine rescue centres. Peripheral blood samples were collected from all the animals and the comet assay applied. All comet cells were analysed using two methods: visual scoring and computer image analysis. The % DNA in tail mean value ± SD and Damage Index were 21.56 ± 15.41 and 134.83 ± 94.12, respectively. A strong and statistically significant statistically correlation between the two analytical methods was observed (r = 0.95; p < 0.05). These results demonstrate that the comet assay is a useful method to detect the possible effects of genotoxic agents in loggerhead sea turtle and to increase the knowledge about the ecotoxicological health status of this threatened species. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Grammar of Exchange: A Comparative Study of Reciprocal Constructions Across Languages

PubMed Central

Majid, Asifa; Evans, Nicholas; Gaby, Alice; Levinson, Stephen C.

2010-01-01

Cultures are built on social exchange. Most languages have dedicated grammatical machinery for expressing this. To demonstrate that statistical methods can also be applied to grammatical meaning, we here ask whether the underlying meanings of these grammatical constructions are based on shared common concepts. To explore this, we designed video stimuli of reciprocated actions (e.g., “giving to each other”) and symmetrical states (e.g., “sitting next to each other”), and with the help of a team of linguists collected responses from 20 languages around the world. Statistical analyses revealed that many languages do, in fact, share a common conceptual core for reciprocal meanings but that this is not a universally expressed concept. The recurrent pattern of conceptual packaging found across languages is compatible with the view that there is a shared non-linguistic understanding of reciprocation. But, nevertheless, there are considerable differences between languages in the exact extensional patterns, highlighting that even in the domain of grammar semantics is highly language-specific. PMID:21713188

The Matching Relation and Situation-Specific Bias Modulation in Professional Football Play Selection

PubMed Central

Stilling, Stephanie T; Critchfield, Thomas S

2010-01-01

The utility of a quantitative model depends on the extent to which its fitted parameters vary systematically with environmental events of interest. Professional football statistics were analyzed to determine whether play selection (passing versus rushing plays) could be accounted for with the generalized matching equation, and in particular whether variations in play selection across game situations would manifest as changes in the equation's fitted parameters. Statistically significant changes in bias were found for each of five types of game situations; no systematic changes in sensitivity were observed. Further analyses suggested relationships between play selection bias and both turnover probability (which can be described in terms of punishment) and yards-gained variance (which can be described in terms of variable-magnitude reinforcement schedules). The present investigation provides a useful demonstration of association between face-valid, situation-specific effects in a domain of everyday interest, and a theoretically important term of a quantitative model of behavior. Such associations, we argue, are an essential focus in translational extensions of quantitative models. PMID:21119855

Quantitative EEG analysis of the maturational changes associated with childhood absence epilepsy

NASA Astrophysics Data System (ADS)

Rosso, O. A.; Hyslop, W.; Gerlach, R.; Smith, R. L. L.; Rostas, J. A. P.; Hunter, M.

2005-10-01

This study aimed to examine the background electroencephalography (EEG) in children with childhood absence epilepsy, a condition whose presentation has strong developmental links. EEG hallmarks of absence seizure activity are widely accepted and there is recognition that the bulk of inter-ictal EEG in this group is normal to the naked eye. This multidisciplinary study aimed to use the normalized total wavelet entropy (NTWS) (Signal Processing 83 (2003) 1275) to examine the background EEG of those patients demonstrating absence seizure activity, and compare it with children without absence epilepsy. This calculation can be used to define the degree of order in a system, with higher levels of entropy indicating a more disordered (chaotic) system. Results were subjected to further statistical analyses of significance. Entropy values were calculated for patients versus controls. For all channels combined, patients with absence epilepsy showed (statistically significant) lower entropy values than controls. The size of the difference in entropy values was not uniform, with certain EEG electrodes consistently showing greater differences than others.

Nutrient-enriched formula versus standard term formula for preterm infants following hospital discharge.

PubMed

Henderson, G; Fahey, T; McGuire, W

2007-10-17

Preterm infants are often growth-restricted at hospital discharge. Feeding infants after hospital discharge with nutrient-enriched formula rather than standard term formula might facilitate "catch-up" growth and improve development. To determine the effect of feeding nutrient-enriched formula compared with standard term formula on growth and development for preterm infants following hospital discharge. The standard search strategy of the Cochrane Neonatal Review Group were used. This included searches of the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 2, 2007), MEDLINE (1966 - May 2007), EMBASE (1980 - May 2007), CINAHL (1982 - May 2007), conference proceedings, and previous reviews. Randomised or quasi-randomised controlled trials that compared the effect of feeding preterm infants following hospital discharge with nutrient-enriched formula compared with standard term formula. Data was extracted using the standard methods of the Cochrane Neonatal Review Group, with separate evaluation of trial quality and data extraction by two authors, and synthesis of data using weighted mean difference and a fixed effects model for meta-analysis. Seven trials were found that were eligible for inclusion. These recruited a total of 631 infants and were generally of good methodological quality. The trials found little evidence that feeding with nutrient-enriched formula milk affected growth and development. Because of differences in the way individual trials measured and presented outcomes, data synthesis was limited. Growth data from two trials found that, at six months post-term, infants fed with nutrient-enriched formula had statistically significantly lower weights [weighted mean difference: -601 (95% confidence interval -1028, -174) grams], lengths [-18.8 (-30.0, -7.6) millimetres], and head circumferences [-10.2 ( -18.0, -2.4) millimetres], than infants fed standard term formula. At 12 to 18 months post-term, meta-analyses of data from three trials did not find any statistically significant differences in growth parameters. However, examination of these meta-analyses demonstrated statistical heterogeneity. Meta-analyses of data from two trials did not reveal a statistically significant difference in Bayley Mental Development or Psychomotor Development Indices. There are not yet any data on growth or development through later childhood. The available data do not provide strong evidence that feeding preterm infants following hospital discharge with nutrient-enriched formula compared with standard term formula affects growth rates or development up to 18 months post-term.

Dissecting the genetics of complex traits using summary association statistics.

PubMed

Pasaniuc, Bogdan; Price, Alkes L

2017-02-01

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

Statistical innovations in diagnostic device evaluation.

PubMed

Yu, Tinghui; Li, Qin; Gray, Gerry; Yue, Lilly Q

2016-01-01

Due to rapid technological development, innovations in diagnostic devices are proceeding at an extremely fast pace. Accordingly, the needs for adopting innovative statistical methods have emerged in the evaluation of diagnostic devices. Statisticians in the Center for Devices and Radiological Health at the Food and Drug Administration have provided leadership in implementing statistical innovations. The innovations discussed in this article include: the adoption of bootstrap and Jackknife methods, the implementation of appropriate multiple reader multiple case study design, the application of robustness analyses for missing data, and the development of study designs and data analyses for companion diagnostics.

On the structure of personality disorder traits: conjoint analyses of the CAT-PD, PID-5, and NEO-PI-3 trait models.

PubMed

Wright, Aidan G C; Simms, Leonard J

2014-01-01

The current study examines the relations among contemporary models of pathological and normal range personality traits. Specifically, we report on (a) conjoint exploratory factor analyses of the Computerized Adaptive Test of Personality Disorder static form (CAT-PD-SF) with the Personality Inventory for the Diagnostic and Statistical Manual of Mental Disorders, fifth edition and NEO Personality Inventory-3 First Half, and (b) unfolding hierarchical analyses of the three measures in a large general psychiatric outpatient sample (n = 628; 64% Female). A five-factor solution provided conceptually coherent alignment among the CAT-PD-SF, PID-5, and NEO-PI-3FH scales. Hierarchical solutions suggested that higher-order factors bear strong resemblance to dimensions that emerge from structural models of psychopathology (e.g., Internalizing and Externalizing spectra). These results demonstrate that the CAT-PD-SF adheres to the consensual structure of broad trait domains at the five-factor level. Additionally, patterns of scale loadings further inform questions of structure and bipolarity of facet and domain level constructs. Finally, hierarchical analyses strengthen the argument for using broad dimensions that span normative and pathological functioning to scaffold a quantitatively derived phenotypic structure of psychopathology to orient future research on explanatory, etiological, and maintenance mechanisms.

Cytotoxic analysis and chemical characterization of fractions of the hydroalcoholic extract of the Euterpe oleracea Mart. seed in the MCF-7 cell line.

PubMed

Freitas, Dayanne da S; Morgado-Díaz, José A; Gehren, Adriana S; Vidal, Flávia C B; Fernandes, Raquel Maria T; Romão, Wanderson; Tose, Lilian V; Frazão, Fabiola N S; Costa, Maria Célia P; Silva, Dulcelena F; Nascimento, Maria do Desterro S B

2017-06-01

To analyse the antineoplastic activity of fractions derived from the hydroalcoholic extract of Euterpe oleracea Mart. seed in the MCF-7 cell line and to identify the compounds responsible for the antineoplastic action. Cells were treated with 10, 20, 40 and 60 μg/ml with the hexane, chloroform and ethyl acetate fraction (EAF) of the hydroalcoholic extract of açaí seed, for 24 and 48 h. After treatment, cell viability was measured using MTT assay and cell death was assessed using the Annexin-Pi assay. The most cytotoxic fraction under study was analysed by mass spectrometry using an electrospray ionization source and a cyclotron analyser coupled to a Fourier transform. Data were analysed statistically by analysis of variance (ANOVA) or by Student's t-test, where appropriate. All fractions caused significant reduction in the cell viability, but the EAF was the most cytotoxic (P < 0.001). It was observed the absence of significant annexin staining but increase Pi staining (P < 0.001). The EAF is composed of epicatechin, proanthocyanidin A 2 and trimeric and tetrameric procyanidins. In this study, we demonstrated that EAF was the most effective fraction in reducing cell viability and causing necroptosis in the MCF-7 cell. © 2017 Royal Pharmaceutical Society.

Comparison of linear measurements and analyses taken from plaster models and three-dimensional images.

PubMed

Porto, Betina Grehs; Porto, Thiago Soares; Silva, Monica Barros; Grehs, Renésio Armindo; Pinto, Ary dos Santos; Bhandi, Shilpa H; Tonetto, Mateus Rodrigues; Bandéca, Matheus Coelho; dos Santos-Pinto, Lourdes Aparecida Martins

2014-11-01

Digital models are an alternative for carrying out analyses and devising treatment plans in orthodontics. The objective of this study was to evaluate the accuracy and the reproducibility of measurements of tooth sizes, interdental distances and analyses of occlusion using plaster models and their digital images. Thirty pairs of plaster models were chosen at random, and the digital images of each plaster model were obtained using a laser scanner (3Shape R-700, 3Shape A/S). With the plaster models, the measurements were taken using a caliper (Mitutoyo Digimatic(®), Mitutoyo (UK) Ltd) and the MicroScribe (MS) 3DX (Immersion, San Jose, Calif). For the digital images, the measurement tools used were those from the O3d software (Widialabs, Brazil). The data obtained were compared statistically using the Dahlberg formula, analysis of variance and the Tukey test (p < 0.05). The majority of the measurements, obtained using the caliper and O3d were identical, and both were significantly different from those obtained using the MS. Intra-examiner agreement was lowest when using the MS. The results demonstrated that the accuracy and reproducibility of the tooth measurements and analyses from the plaster models using the caliper and from the digital models using O3d software were identical.

Statistical process control as a tool for controlling operating room performance: retrospective analysis and benchmarking.

PubMed

Chen, Tsung-Tai; Chang, Yun-Jau; Ku, Shei-Ling; Chung, Kuo-Piao

2010-10-01

There is much research using statistical process control (SPC) to monitor surgical performance, including comparisons among groups to detect small process shifts, but few of these studies have included a stabilization process. This study aimed to analyse the performance of surgeons in operating room (OR) and set a benchmark by SPC after stabilized process. The OR profile of 499 patients who underwent laparoscopic cholecystectomy performed by 16 surgeons at a tertiary hospital in Taiwan during 2005 and 2006 were recorded. SPC was applied to analyse operative and non-operative times using the following five steps: first, the times were divided into two segments; second, they were normalized; third, they were evaluated as individual processes; fourth, the ARL(0) was calculated;, and fifth, the different groups (surgeons) were compared. Outliers were excluded to ensure stability for each group and to facilitate inter-group comparison. The results showed that in the stabilized process, only one surgeon exhibited a significantly shorter total process time (including operative time and non-operative time). In this study, we use five steps to demonstrate how to control surgical and non-surgical time in phase I. There are some measures that can be taken to prevent skew and instability in the process. Also, using SPC, one surgeon can be shown to be a real benchmark. © 2010 Blackwell Publishing Ltd.

Model-based iterative reconstruction in low-dose CT colonography-feasibility study in 65 patients for symptomatic investigation.

PubMed

Vardhanabhuti, Varut; James, Julia; Nensey, Rehaan; Hyde, Christopher; Roobottom, Carl

2015-05-01

To compare image quality on computed tomographic colonography (CTC) acquired at standard dose (STD) and low dose (LD) using filtered-back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) techniques. A total of 65 symptomatic patients were prospectively enrolled for the study and underwent STD and LD CTC with filtered-back projection, adaptive statistical iterative reconstruction, and MBIR to allow direct per-patient comparison. Objective image noise, subjective image analyses, and polyp detection were assessed. Objective image noise analysis demonstrates significant noise reduction using MBIR technique (P < .05) despite being acquired at lower doses. Subjective image analyses were superior for LD MBIR in all parameters except visibility of extracolonic lesions (two-dimensional) and visibility of colonic wall (three-dimensional) where there were no significant differences. There was no significant difference in polyp detection rates (P > .05). Doses: LD (dose-length product, 257.7), STD (dose-length product, 483.6). LD MBIR CTC objectively shows improved image noise using parameters in our study. Subjectively, image quality is maintained. Polyp detection shows no significant difference but because of small numbers needs further validation. Average dose reduction of 47% can be achieved. This study confirms feasibility of using MBIR in this context of CTC in symptomatic population. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

On the reliable probing of discrete ‘plasma bullet’ propagation

NASA Astrophysics Data System (ADS)

Svarnas, P.; Gazeli, K.; Gkelios, A.; Amanatides, E.; Mataras, D.

2018-04-01

This report is devoted to the imaging of the spatiotemporal evolution of ‘plasma bullets’ during their propagation at atmospheric pressure. Although numerous studies have been realized on this topic with high gating rate cameras, triggering issues and statistical analyses of single-shot events over different cycles of the driving high voltage have not been discussed properly. The present work demonstrates the related difficulties faced due to the inherently erratic propagation of the bullets. A way of capturing and statistically analysing discrete bullet events is introduced, which is reliable even when low gating rate cameras are used and multiple bullets are formed within the voltage cycle. The method is based on plasma observations by means of two photoelectron multiplier tubes. It is suggested that these signals correlate better with bullet propagation events than the driving voltage or bullet current waveforms do, and allow either the elimination of issues arising from erratic propagation and hardware delays or at least the quantification of certain uncertainties. Herein, the entire setup, the related concept and the limits of accuracy are discussed in detail. Snapshots of the bullets are captured and commented on, with the bullets being produced by a sinusoidally driven single-electrode plasma jet reactor operating with helium. Finally, the instantaneous velocities of bullets on the order of 104-105 m s-1 are measured and propagation phases are distinguished in good agreement with the bibliography.

Fundamentals and Catalytic Innovation: The Statistical and Data Management Center of the Antibacterial Resistance Leadership Group

PubMed Central

Huvane, Jacqueline; Komarow, Lauren; Hill, Carol; Tran, Thuy Tien T.; Pereira, Carol; Rosenkranz, Susan L.; Finnemeyer, Matt; Earley, Michelle; Jiang, Hongyu (Jeanne); Wang, Rui; Lok, Judith

2017-01-01

Abstract The Statistical and Data Management Center (SDMC) provides the Antibacterial Resistance Leadership Group (ARLG) with statistical and data management expertise to advance the ARLG research agenda. The SDMC is active at all stages of a study, including design; data collection and monitoring; data analyses and archival; and publication of study results. The SDMC enhances the scientific integrity of ARLG studies through the development and implementation of innovative and practical statistical methodologies and by educating research colleagues regarding the application of clinical trial fundamentals. This article summarizes the challenges and roles, as well as the innovative contributions in the design, monitoring, and analyses of clinical trials and diagnostic studies, of the ARLG SDMC. PMID:28350899

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

PubMed Central

2013-01-01

Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699

Increased mortality associated with extreme-heat exposure in King County, Washington, 1980-2010

NASA Astrophysics Data System (ADS)

Isaksen, Tania Busch; Fenske, Richard A.; Hom, Elizabeth K.; Ren, You; Lyons, Hilary; Yost, Michael G.

2016-01-01

Extreme heat has been associated with increased mortality, particularly in temperate climates. Few epidemiologic studies have considered the Pacific Northwest region in their analyses. This study quantified the historical (May to September, 1980-2010) heat-mortality relationship in the most populous Pacific Northwest County, King County, Washington. A relative risk (RR) analysis was used to explore the relationship between heat and all-cause mortality on 99th percentile heat days, while a time series analysis, using a piece-wise linear model fit, was used to estimate the effect of heat intensity on mortality, adjusted for temporal trends. For all ages, all causes, we found a 10 % (1.10 (95 % confidence interval (CI), 1.06, 1.14)) increase in the risk of death on a heat day versus non-heat day. When considering the intensity effect of heat on all-cause mortality, we found a 1.69 % (95 % CI, 0.69, 2.70) increase in the risk of death per unit of humidex above 36.0 °C. Mortality stratified by cause and age produced statistically significant results using both types of analyses for: all-cause, non-traumatic, circulatory, cardiovascular, cerebrovascular, and diabetes causes of death. All-cause mortality was statistically significantly modified by the type of synoptic weather type. These results demonstrate that heat, expressed as humidex, is associated with increased mortality on heat days, and that risk increases with heat's intensity. While age was the only individual-level characteristic found to modify mortality risks, statistically significant increases in diabetes-related mortality for the 45-64 age group suggests that underlying health status may contribute to these risks.

Exploring patient support by breast care nurses and geographical residence as moderators of the unmet needs and self-efficacy of Australian women with breast cancer: Results from a cross-sectional, nationwide survey.

PubMed

Ahern, Tracey; Gardner, Anne; Courtney, Mary

2016-08-01

This study investigated whether use of services of a breast care nurse (BCN) at any time during treatment for breast cancer led to reduced unmet needs and increased self-efficacy among women with breast cancer. A secondary aim was to analyse comparisons between urban and rural and remote dwellers. Participants were Australian women who completed treatment for breast cancer at least 6 months before the survey date, recruited through two national databases of women diagnosed with breast cancer. The cross-sectional online survey consisted of two well validated measures, the SCNS-SF34 and the CASE-Cancer Scale. Statistical data were analysed using SPSS, with chi-square used to measure statistical significance. A total of 902 participants responded to the survey. Unmet needs in the psychological domain were most prominent. Respondents who used the services of a BCN were significantly less likely to report unmet needs regarding tiredness, anxiety; future outlook; feelings about death and dying; patient care and support from medical staff; and provision of health systems and information. Scores of self-efficacy showed women using the services of a BCN had significantly higher self-efficacy when seeking and obtaining information (ρ ≤ 0.001) and understanding and participating in care (ρ = 0.032). Urban dwellers were more likely to have choice of health care service, but overall neither unmet needs nor perceived self-efficacy varied statistically significantly by remoteness. Women with breast cancer experience a range of unmet needs; however those using BCN services demonstrated positive outcomes in terms of decreased unmet needs and increased self-efficacy. Copyright © 2016 Elsevier Ltd. All rights reserved.

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Comparison of futility monitoring guidelines using completed phase III oncology trials.

PubMed

Zhang, Qiang; Freidlin, Boris; Korn, Edward L; Halabi, Susan; Mandrekar, Sumithra; Dignam, James J

2017-02-01

Futility (inefficacy) interim monitoring is an important component in the conduct of phase III clinical trials, especially in life-threatening diseases. Desirable futility monitoring guidelines allow timely stopping if the new therapy is harmful or if it is unlikely to demonstrate to be sufficiently effective if the trial were to continue to its final analysis. There are a number of analytical approaches that are used to construct futility monitoring boundaries. The most common approaches are based on conditional power, sequential testing of the alternative hypothesis, or sequential confidence intervals. The resulting futility boundaries vary considerably with respect to the level of evidence required for recommending stopping the study. We evaluate the performance of commonly used methods using event histories from completed phase III clinical trials of the Radiation Therapy Oncology Group, Cancer and Leukemia Group B, and North Central Cancer Treatment Group. We considered published superiority phase III trials with survival endpoints initiated after 1990. There are 52 studies available for this analysis from different disease sites. Total sample size and maximum number of events (statistical information) for each study were calculated using protocol-specified effect size, type I and type II error rates. In addition to the common futility approaches, we considered a recently proposed linear inefficacy boundary approach with an early harm look followed by several lack-of-efficacy analyses. For each futility approach, interim test statistics were generated for three schedules with different analysis frequency, and early stopping was recommended if the interim result crossed a futility stopping boundary. For trials not demonstrating superiority, the impact of each rule is summarized as savings on sample size, study duration, and information time scales. For negative studies, our results show that the futility approaches based on testing the alternative hypothesis and repeated confidence interval rules yielded less savings (compared to the other two rules). These boundaries are too conservative, especially during the first half of the study (<50% of information). The conditional power rules are too aggressive during the second half of the study (>50% of information) and may stop a trial even when there is a clinically meaningful treatment effect. The linear inefficacy boundary with three or more interim analyses provided the best results. For positive studies, we demonstrated that none of the futility rules would have stopped the trials. The linear inefficacy boundary futility approach is attractive from statistical, clinical, and logistical standpoints in clinical trials evaluating new anti-cancer agents.

ISSUES IN THE STATISTICAL ANALYSIS OF SMALL-AREA HEALTH DATA. (R825173)

EPA Science Inventory

The availability of geographically indexed health and population data, with advances in computing, geographical information systems and statistical methodology, have opened the way for serious exploration of small area health statistics based on routine data. Such analyses may be...

Integrated design and manufacturing for the high speed civil transport (a combined aerodynamics/propulsion optimization study)

NASA Technical Reports Server (NTRS)

Baecher, Juergen; Bandte, Oliver; DeLaurentis, Dan; Lewis, Kemper; Sicilia, Jose; Soboleski, Craig

1995-01-01

This report documents the efforts of a Georgia Tech High Speed Civil Transport (HSCT) aerospace student design team in completing a design methodology demonstration under NASA's Advanced Design Program (ADP). Aerodynamic and propulsion analyses are integrated into the synthesis code FLOPS in order to improve its prediction accuracy. Executing the integrated product and process development (IPPD) methodology proposed at the Aerospace Systems Design Laboratory (ASDL), an improved sizing process is described followed by a combined aero-propulsion optimization, where the objective function, average yield per revenue passenger mile ($/RPM), is constrained by flight stability, noise, approach speed, and field length restrictions. Primary goals include successful demonstration of the application of the response surface methodolgy (RSM) to parameter design, introduction to higher fidelity disciplinary analysis than normally feasible at the conceptual and early preliminary level, and investigations of relationships between aerodynamic and propulsion design parameters and their effect on the objective function, $/RPM. A unique approach to aircraft synthesis is developed in which statistical methods, specifically design of experiments and the RSM, are used to more efficiently search the design space for optimum configurations. In particular, two uses of these techniques are demonstrated. First, response model equations are formed which represent complex analysis in the form of a regression polynomial. Next, a second regression equation is constructed, not for modeling purposes, but instead for the purpose of optimization at the system level. Such an optimization problem with the given tools normally would be difficult due to the need for hard connections between the various complex codes involved. The statistical methodology presents an alternative and is demonstrated via an example of aerodynamic modeling and planform optimization for a HSCT.

GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

NASA Astrophysics Data System (ADS)

Mancini, F.; Ceppi, C.; Ritrovato, G.

2010-09-01

This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

Statistics for the Relative Detectability of Chemicals in Weak Gaseous Plumes in LWIR Hyperspectral Imagery

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

Metoyer, Candace N.; Walsh, Stephen J.; Tardiff, Mark F.

2008-10-30

The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data frommore » the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures.« less

Underpowered samples, false negatives, and unconscious learning.

PubMed

Vadillo, Miguel A; Konstantinidis, Emmanouil; Shanks, David R

2016-02-01

The scientific community has witnessed growing concern about the high rate of false positives and unreliable results within the psychological literature, but the harmful impact of false negatives has been largely ignored. False negatives are particularly concerning in research areas where demonstrating the absence of an effect is crucial, such as studies of unconscious or implicit processing. Research on implicit processes seeks evidence of above-chance performance on some implicit behavioral measure at the same time as chance-level performance (that is, a null result) on an explicit measure of awareness. A systematic review of 73 studies of contextual cuing, a popular implicit learning paradigm, involving 181 statistical analyses of awareness tests, reveals how underpowered studies can lead to failure to reject a false null hypothesis. Among the studies that reported sufficient information, the meta-analytic effect size across awareness tests was d z = 0.31 (95 % CI 0.24-0.37), showing that participants' learning in these experiments was conscious. The unusually large number of positive results in this literature cannot be explained by selective publication. Instead, our analyses demonstrate that these tests are typically insensitive and underpowered to detect medium to small, but true, effects in awareness tests. These findings challenge a widespread and theoretically important claim about the extent of unconscious human cognition.

Resting State Functional Connectivity within the Cingulate Cortex Jointly Predicts Agreeableness and Stressor-Evoked Cardiovascular Reactivity

PubMed Central

Ryan, John P.; Sheu, Lei K.; Gianaros, Peter J.

2010-01-01

Exaggerated cardiovascular reactivity to stress confers risk for cardiovascular disease. Further, individual differences in stressor-evoked cardiovascular reactivity covary with the functionality of cortical and limbic brain areas, particularly within the cingulate cortex. What remains unclear, however, is how individual differences in personality traits interact with cingulate functionality in the prediction of stressor-evoked cardiovascular reactivity. Accordingly, we tested the associations between (i) a particular personality trait, Agreeableness, which is associated with emotional reactions to conflict, (ii) resting state functional connectivity within the cingulate cortex, and (iii) stressor-evoked blood pressure (BP) reactivity. Participants (N=39, 19 men, aged 20–37 yrs) completed a resting functional connectivity MRI protocol, followed by two standardized stressor tasks that engaged conflict processing and evoked BP reactivity. Agreeableness covaried positively with BP reactivity across individuals. Moreover, connectivity analyses demonstrated that a more positive functional connectivity between the posterior cingulate (BA31) and the perigenual anterior cingulate (BA32) covaried positively with Agreeableness and with BP reactivity. Finally, statistical mediation analyses demonstrated that BA31–BA32 connectivity mediated the covariation between Agreeableness and BP reactivity. Functional connectivity within the cingulate appears to link Agreeableness and a risk factor for cardiovascular disease, stressor-evoked BP reactivity. PMID:21130172

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

PubMed

Tuuli, Methodius G; Odibo, Anthony O

2011-08-01

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

Using a Five-Step Procedure for Inferential Statistical Analyses

ERIC Educational Resources Information Center

Kamin, Lawrence F.

2010-01-01

Many statistics texts pose inferential statistical problems in a disjointed way. By using a simple five-step procedure as a template for statistical inference problems, the student can solve problems in an organized fashion. The problem and its solution will thus be a stand-by-itself organic whole and a single unit of thought and effort. The…

Statistical studies of selected trace elements with reference to geology and genesis of the Carlin gold deposit, Nevada

USGS Publications Warehouse

Harris, Michael; Radtke, Arthur S.

1976-01-01

Linear regression and discriminant analyses techniques were applied to gold, mercury, arsenic, antimony, barium, copper, molybdenum, lead, zinc, boron, tellurium, selenium, and tungsten analyses from drill holes into unoxidized gold ore at the Carlin gold mine near Carlin, Nev. The statistical treatments employed were used to judge proposed hypotheses on the origin and geochemical paragenesis of this disseminated gold deposit.

The Effects of Using a Wiki on Student Engagement and Learning of Report Writing Skills in a University Statistics Course

ERIC Educational Resources Information Center

Neumann, David L.; Hood, Michelle

2009-01-01

A wiki was used as part of a blended learning approach to promote collaborative learning among students in a first year university statistics class. One group of students analysed a data set and communicated the results by jointly writing a practice report using a wiki. A second group analysed the same data but communicated the results in a…

Extreme between-study homogeneity in meta-analyses could offer useful insights.

PubMed

Ioannidis, John P A; Trikalinos, Thomas A; Zintzaras, Elias

2006-10-01

Meta-analyses are routinely evaluated for the presence of large between-study heterogeneity. We examined whether it is also important to probe whether there is extreme between-study homogeneity. We used heterogeneity tests with left-sided statistical significance for inference and developed a Monte Carlo simulation test for testing extreme homogeneity in risk ratios across studies, using the empiric distribution of the summary risk ratio and heterogeneity statistic. A left-sided P=0.01 threshold was set for claiming extreme homogeneity to minimize type I error. Among 11,803 meta-analyses with binary contrasts from the Cochrane Library, 143 (1.21%) had left-sided P-value <0.01 for the asymptotic Q statistic and 1,004 (8.50%) had left-sided P-value <0.10. The frequency of extreme between-study homogeneity did not depend on the number of studies in the meta-analyses. We identified examples where extreme between-study homogeneity (left-sided P-value <0.01) could result from various possibilities beyond chance. These included inappropriate statistical inference (asymptotic vs. Monte Carlo), use of a specific effect metric, correlated data or stratification using strong predictors of outcome, and biases and potential fraud. Extreme between-study homogeneity may provide useful insights about a meta-analysis and its constituent studies.

Metal and physico-chemical variations at a hydroelectric reservoir analyzed by Multivariate Analyses and Artificial Neural Networks: environmental management and policy/decision-making tools.

PubMed

Cavalcante, Y L; Hauser-Davis, R A; Saraiva, A C F; Brandão, I L S; Oliveira, T F; Silveira, A M

2013-01-01

This paper compared and evaluated seasonal variations in physico-chemical parameters and metals at a hydroelectric power station reservoir by applying Multivariate Analyses and Artificial Neural Networks (ANN) statistical techniques. A Factor Analysis was used to reduce the number of variables: the first factor was composed of elements Ca, K, Mg and Na, and the second by Chemical Oxygen Demand. The ANN showed 100% correct classifications in training and validation samples. Physico-chemical analyses showed that water pH values were not statistically different between the dry and rainy seasons, while temperature, conductivity, alkalinity, ammonia and DO were higher in the dry period. TSS, hardness and COD, on the other hand, were higher during the rainy season. The statistical analyses showed that Ca, K, Mg and Na are directly connected to the Chemical Oxygen Demand, which indicates a possibility of their input into the reservoir system by domestic sewage and agricultural run-offs. These statistical applications, thus, are also relevant in cases of environmental management and policy decision-making processes, to identify which factors should be further studied and/or modified to recover degraded or contaminated water bodies. Copyright © 2012 Elsevier B.V. All rights reserved.

From sexless to sexy: Why it is time for human genetics to consider and report analyses of sex.

PubMed

Powers, Matthew S; Smith, Phillip H; McKee, Sherry A; Ehringer, Marissa A

2017-01-01

Science has come a long way with regard to the consideration of sex differences in clinical and preclinical research, but one field remains behind the curve: human statistical genetics. The goal of this commentary is to raise awareness and discussion about how to best consider and evaluate possible sex effects in the context of large-scale human genetic studies. Over the course of this commentary, we reinforce the importance of interpreting genetic results in the context of biological sex, establish evidence that sex differences are not being considered in human statistical genetics, and discuss how best to conduct and report such analyses. Our recommendation is to run stratified analyses by sex no matter the sample size or the result and report the findings. Summary statistics from stratified analyses are helpful for meta-analyses, and patterns of sex-dependent associations may be hidden in a combined dataset. In the age of declining sequencing costs, large consortia efforts, and a number of useful control samples, it is now time for the field of human genetics to appropriately include sex in the design, analysis, and reporting of results.

Does speed matter? The impact of operative time on outcome in laparoscopic surgery

PubMed Central

Jackson, Timothy D.; Wannares, Jeffrey J.; Lancaster, R. Todd; Rattner, David W.

2012-01-01

Introduction Controversy exists concerning the importance of operative time on patient outcomes. It is unclear whether faster is better or haste makes waste or similarly whether slower procedures represent a safe, meticulous approach or inexperienced dawdling. The objective of the present study was to determine the effect of operative time on 30-day outcomes in laparoscopic surgery. Methods Patients who underwent laparoscopic general surgery procedures (colectomy, cholecystectomy, Nissen fundoplication, inguinal hernia, and gastric bypass) from the ACS-NSQIP 2005–2008 participant use file were identified. Exclusion criteria were defined a priori to identify same-day admission, elective procedures. Operative time was divided into deciles and summary statistics were analyzed. Univariate analyses using a Cochran-Armitage test for trend were completed. The effect of operative time on 30-day morbidity was further analyzed for each procedure type using multivariate regression controlling for case complexity and additional patient factors. Patients within the highest deciles were excluded to reduce outlier effect. Results A total of 76,748 elective general surgical patients who underwent laparoscopic procedures were analyzed. Univariate analyses of deciles of operative time demonstrated a statistically significant trend (p \\ 0.0001) toward increasing odds of complications with increasing operative time for laparoscopic colectomy (n = 10,135), cholecystectomy (n = 37,407), Nissen fundoplication (n = 4,934), and gastric bypass (n = 17,842). The trend was not found to be significant for laparoscopic inguinal hernia repair (n = 6,430; p = 0.14). Multivariate modeling revealed the effect of operative time to remain significant after controlling for additional patient factors. Conclusion Increasing operative time was associated with increased odds of complications and, therefore, it appears that speed may matter in laparoscopic surgery. These analyses are limited in their inability to adjust for all patient factors, potential confounders, and case complexities. Additional hierarchical multivariate analyses at the surgeon level would be important to examine this relationship further. PMID:21298533

Does speed matter? The impact of operative time on outcome in laparoscopic surgery.

PubMed

Jackson, Timothy D; Wannares, Jeffrey J; Lancaster, R Todd; Rattner, David W; Hutter, Matthew M

2011-07-01

Controversy exists concerning the importance of operative time on patient outcomes. It is unclear whether faster is better or haste makes waste or similarly whether slower procedures represent a safe, meticulous approach or inexperienced dawdling. The objective of the present study was to determine the effect of operative time on 30-day outcomes in laparoscopic surgery. Patients who underwent laparoscopic general surgery procedures (colectomy, cholecystectomy, Nissen fundoplication, inguinal hernia, and gastric bypass) from the ACS-NSQIP 2005-2008 participant use file were identified. Exclusion criteria were defined a priori to identify same-day admission, elective procedures. Operative time was divided into deciles and summary statistics were analyzed. Univariate analyses using a Cochran-Armitage test for trend were completed. The effect of operative time on 30-day morbidity was further analyzed for each procedure type using multivariate regression controlling for case complexity and additional patient factors. Patients within the highest deciles were excluded to reduce outlier effect. A total of 76,748 elective general surgical patients who underwent laparoscopic procedures were analyzed. Univariate analyses of deciles of operative time demonstrated a statistically significant trend (p<0.0001) toward increasing odds of complications with increasing operative time for laparoscopic colectomy (n=10,135), cholecystectomy (n=37,407), Nissen fundoplication (n=4,934), and gastric bypass (n=17,842). The trend was not found to be significant for laparoscopic inguinal hernia repair (n=6,430; p=0.14). Multivariate modeling revealed the effect of operative time to remain significant after controlling for additional patient factors. Increasing operative time was associated with increased odds of complications and, therefore, it appears that speed may matter in laparoscopic surgery. These analyses are limited in their inability to adjust for all patient factors, potential confounders, and case complexities. Additional hierarchical multivariate analyses at the surgeon level would be important to examine this relationship further.

Tacrolimus in the treatment of myasthenia gravis in patients with an inadequate response to glucocorticoid therapy: randomized, double-blind, placebo-controlled study conducted in China.

PubMed

Zhou, Lei; Liu, Weibin; Li, Wei; Li, Haifeng; Zhang, Xu; Shang, Huifang; Zhang, Xu; Bu, Bitao; Deng, Hui; Fang, Qi; Li, Jimei; Zhang, Hua; Song, Zhi; Ou, Changyi; Yan, Chuanzhu; Liu, Tao; Zhou, Hongyu; Bao, Jianhong; Lu, Jiahong; Shi, Huawei; Zhao, Chongbo

2017-09-01

To determine the efficacy of low-dose, immediate-release tacrolimus in patients with myasthenia gravis (MG) with inadequate response to glucocorticoid therapy in a randomized, double-blind, placebo-controlled study. Eligible patients had inadequate response to glucocorticoids (GCs) after ⩾6 weeks of treatment with prednisone ⩾0.75 mg/kg/day or 60-100 mg/day. Patients were randomized to receive 3 mg tacrolimus or placebo daily (orally) for 24 weeks. Concomitant glucocorticoids and pyridostigmine were allowed. Patients continued GC therapy from weeks 1-4; from week 5, the dose was decreased at the discretion of the investigator. The primary efficacy outcome measure was a reduction, relative to baseline, in quantitative myasthenia gravis (QMG) score assessed using a generalized linear model; supportive analyses used alternative models. Of 138 patients screened, 83 [tacrolimus ( n = 45); placebo ( n = 38)] were enrolled and treated. The change in adjusted mean QMG score from baseline to week 24 was -4.9 for tacrolimus and -3.3 for placebo (least squares mean difference: -1.7, 95% confidence interval: -3.5, -0.1; p = 0.067). A post-hoc analysis demonstrated a statistically significant difference for QMG score reduction of ⩾4 points in the tacrolimus group (68.2%) versus the placebo group (44.7%; p = 0.044). Adverse event profiles were similar between treatment groups. Tacrolimus 3 mg treatment for patients with MG and inadequate response to GCs did not demonstrate a statistically significant improvement in the primary endpoint versus placebo over 24 weeks; however, a post-hoc analysis demonstrated a statistically significant difference for QMG score reduction of ⩾4 points in the tacrolimus group versus the placebo group. This study was limited by the low number of patients, the absence of testing for acetylcholine receptor antibody and the absence of stratification by disease duration (which led to a disparity between the two groups). ClinicalTrials.gov identifier: NCT01325571.

Implemented Lomb-Scargle periodogram: a valuable tool for improving cyclostratigraphic research on unevenly sampled deep-sea stratigraphic sequences

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2011-12-01

One important handicap when working with stratigraphic sequences is the discontinuous character of the sedimentary record, especially relevant in cyclostratigraphic analysis. Uneven palaeoclimatic/palaeoceanographic time series are common, their cyclostratigraphic analysis being comparatively difficult because most spectral methodologies are appropriate only when working with even sampling. As a means to solve this problem, a program for calculating the smoothed Lomb-Scargle periodogram and cross-periodogram, which additionally evaluates the statistical confidence of the estimated power spectrum through a Monte Carlo procedure (the permutation test), has been developed. The spectral analysis of a short uneven time series calls for assessment of the statistical significance of the spectral peaks, since a periodogram can always be calculated but the main challenge resides in identifying true spectral features. To demonstrate the effectiveness of this program, two case studies are presented: the one deals with synthetic data and the other with paleoceanographic/palaeoclimatic proxies. On a simulated time series of 500 data, two uneven time series (with 100 and 25 data) were generated by selecting data at random. Comparative analysis between the power spectra from the simulated series and from the two uneven time series demonstrates the usefulness of the smoothed Lomb-Scargle periodogram for uneven sequences, making it possible to distinguish between statistically significant and spurious spectral peaks. Fragmentary time series of Cd/Ca ratios and δ18O from core AII107-131 of SPECMAP were analysed as a real case study. The efficiency of the direct and cross Lomb-Scargle periodogram in recognizing Milankovitch and sub-Milankovitch signals related to palaeoclimatic/palaeoceanographic changes is demonstrated. As implemented, the Lomb-Scargle periodogram may be applied to any palaeoclimatic/palaeoceanographic proxies, including those usually recovered from contourites, and it holds special interest in the context of centennial- to millennial-scale climatic changes affecting contouritic currents.

Transfusion Indication Threshold Reduction (TITRe2) randomized controlled trial in cardiac surgery: statistical analysis plan.

PubMed

Pike, Katie; Nash, Rachel L; Murphy, Gavin J; Reeves, Barnaby C; Rogers, Chris A

2015-02-22

The Transfusion Indication Threshold Reduction (TITRe2) trial is the largest randomized controlled trial to date to compare red blood cell transfusion strategies following cardiac surgery. This update presents the statistical analysis plan, detailing how the study will be analyzed and presented. The statistical analysis plan has been written following recommendations from the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, prior to database lock and the final analysis of trial data. Outlined analyses are in line with the Consolidated Standards of Reporting Trials (CONSORT). The study aims to randomize 2000 patients from 17 UK centres. Patients are randomized to either a restrictive (transfuse if haemoglobin concentration <7.5 g/dl) or liberal (transfuse if haemoglobin concentration <9 g/dl) transfusion strategy. The primary outcome is a binary composite outcome of any serious infectious or ischaemic event in the first 3 months following randomization. The statistical analysis plan details how non-adherence with the intervention, withdrawals from the study, and the study population will be derived and dealt with in the analysis. The planned analyses of the trial primary and secondary outcome measures are described in detail, including approaches taken to deal with multiple testing, model assumptions not being met and missing data. Details of planned subgroup and sensitivity analyses and pre-specified ancillary analyses are given, along with potential issues that have been identified with such analyses and possible approaches to overcome such issues. ISRCTN70923932 .

Demonstration of fundamental statistics by studying timing of electronics signals in a physics-based laboratory

NASA Astrophysics Data System (ADS)

Beach, Shaun E.; Semkow, Thomas M.; Remling, David J.; Bradt, Clayton J.

2017-07-01

We have developed accessible methods to demonstrate fundamental statistics in several phenomena, in the context of teaching electronic signal processing in a physics-based college-level curriculum. A relationship between the exponential time-interval distribution and Poisson counting distribution for a Markov process with constant rate is derived in a novel way and demonstrated using nuclear counting. Negative binomial statistics is demonstrated as a model for overdispersion and justified by the effect of electronic noise in nuclear counting. The statistics of digital packets on a computer network are shown to be compatible with the fractal-point stochastic process leading to a power-law as well as generalized inverse Gaussian density distributions of time intervals between packets.

Development of a Self-Report Physical Function Instrument for Disability Assessment: Item Pool Construction and Factor Analysis

PubMed Central

McDonough, Christine M.; Jette, Alan M.; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M.; Rasch, Elizabeth K.

2014-01-01

Objectives To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Design Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. Setting In-person and semi-structured interviews; internet and telephone surveys. Participants A sample of 1,017 SSA claimants, and a normative sample of 999 adults from the US general population. Interventions Not Applicable. Main Outcome Measure Model fit statistics Results The final item pool consisted of 139 items. Within the claimant sample 58.7% were white; 31.8% were black; 46.6% were female; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution which included more items and allowed separate characterization of: 1) Changing and Maintaining Body Position, 2) Whole Body Mobility, 3) Upper Body Function and 4) Upper Extremity Fine Motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples respectively were: Comparative Fit Index = 0.93 and 0.98; Tucker-Lewis Index = 0.92 and 0.98; Root Mean Square Error Approximation = 0.05 and 0.04. Conclusions The factor structure of the Physical Function item pool closely resembled the hypothesized content model. The four scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. PMID:23542402

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin.

PubMed

Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin

2018-10-15

To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs of MSWQVs and MSPs) repeated in at least two out of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods. To find effective MSP factors on MSWQVs, a multivariate linear regression analysis was employed. Then, preliminary equations that estimated MSWQVs were developed. The preliminary equations were modified to adaptive equations to obtain the final models. The final models indicated that a new metric, referred to as hydrological distance, provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Millennium development goals and oral health in cities in Southern Brazil.

PubMed

Bueno, Roberto Eduardo; Moysés, Samuel Jorge; Moysés, Simone Tetu

2010-06-01

To investigate social determinants of oral health, analysing the occurrence of associations between millennium development goals (MDG) indicators and oral health (OH) indicators. An ecological study was performed in two distinct phases. In Phase 1, MDG indicators and related covariates were obtained from the demographic census of the Brazilian Institute of Geography and Statistics, the Ministry of Health database and the 2000 Human Development Atlas, making up the whole set of independent variables. Principal component analysis was carried out for the independent variables showing the correlations among the variables comprising the main components, and generating a synthetic index allowing the performance of the cities to be known with regard to the MDG (MDG index). In Phase 2, the DMFT index (mean number of decay, missing or filled permanent teeth) and the CF index (prevalence of caries-free individuals), in 12 years old were obtained from the epidemiological survey undertaken in 2002-2003, in 49 cities in southern Brazil, and were analysed in relation to the MDG index using Spearman's correlation.   A statistically significant correlation was found for the DMFT and CF indices, respectively, with: the MDG index (R(2)=0.49 and 0.48; P = 0.00); the socioeconomic status of the population (R(2)= 0.12 and 0.12; P = 0.02); the socioenvironmental characteristics (R(2)=0.41 and 0.46; P= 0.00).   The MDG synthetic index of the cities analysed and the respective components relating to their socioeconomic and socioenvironmental status demonstrated a positive correlation with OH indicators. As such, intersectoral public policies based on population strategies that act on social determinants of general and oral health need to be integrated so as to impact on the MDG and OH outcomes. © 2010 John Wiley & Sons A/S.

Development of a self-report physical function instrument for disability assessment: item pool construction and factor analysis.

PubMed

McDonough, Christine M; Jette, Alan M; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M; Rasch, Elizabeth K

2013-09-01

To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. In-person and semistructured interviews and Internet and telephone surveys. Sample of SSA claimants (n=1017) and a normative sample of adults from the U.S. general population (n=999). Not applicable. Model fit statistics. The final item pool consisted of 139 items. Within the claimant sample, 58.7% were white; 31.8% were black; 46.6% were women; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution, which included more items and allowed separate characterization of: (1) changing and maintaining body position, (2) whole body mobility, (3) upper body function, and (4) upper extremity fine motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples, respectively, were: Comparative Fit Index=.93 and .98; Tucker-Lewis Index=.92 and .98; and root mean square error approximation=.05 and .04. The factor structure of the physical function item pool closely resembled the hypothesized content model. The 4 scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

3-D microstructure of olivine in complex geological materials reconstructed by correlative X-ray μ-CT and EBSD analyses.

PubMed

Kahl, W-A; Dilissen, N; Hidas, K; Garrido, C J; López-Sánchez-Vizcaíno, V; Román-Alpiste, M J

2017-11-01

We reconstruct the 3-D microstructure of centimetre-sized olivine crystals in rocks from the Almirez ultramafic massif (SE Spain) using combined X-ray micro computed tomography (μ-CT) and electron backscatter diffraction (EBSD). The semidestructive sample treatment involves geographically oriented drill pressing of rocks and preparation of oriented thin sections for EBSD from the μ-CT scanned cores. The μ-CT results show that the mean intercept length (MIL) analyses provide reliable information on the shape preferred orientation (SPO) of texturally different olivine groups. We show that statistical interpretation of crystal preferred orientation (CPO) and SPO of olivine becomes feasible because the highest densities of the distribution of main olivine crystal axes from EBSD are aligned with the three axes of the 3-D ellipsoid calculated from the MIL analyses from μ-CT. From EBSD data we distinguish multiple CPO groups and by locating the thin sections within the μ-CT volume, we assign SPO to the corresponding olivine crystal aggregates, which confirm the results of statistical comparison. We demonstrate that the limitations of both methods (i.e. no crystal orientation data in μ-CT and no spatial information in EBSD) can be overcome, and the 3-D orientation of the crystallographic axes of olivines from different orientation groups can be successfully correlated with the crystal shapes of representative olivine grains. Through this approach one can establish the link among geological structures, macrostructure, fabric and 3-D SPO-CPO relationship at the hand specimen scale even in complex, coarse-grained geomaterials. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Microbial composition analyses by 16S rRNA sequencing: A proof of concept approach to provenance determination of archaeological ochre.

PubMed

Lenehan, Claire E; Tobe, Shanan S; Smith, Renee J; Popelka-Filcoff, Rachel S

2017-01-01

Many archaeological science studies use the concept of "provenance", where the origins of cultural material can be determined through physical or chemical properties that relate back to the origins of the material. Recent studies using DNA profiling of bacteria have been used for the forensic determination of soils, towards determination of geographic origin. This manuscript presents a novel approach to the provenance of archaeological minerals and related materials through the use of 16S rRNA sequencing analysis of microbial DNA. Through the microbial DNA characterization from ochre and multivariate statistics, we have demonstrated the clear discrimination between four distinct Australian cultural ochre sites.

Automation in high-content flow cytometry screening.

PubMed

Naumann, U; Wand, M P

2009-09-01

High-content flow cytometric screening (FC-HCS) is a 21st Century technology that combines robotic fluid handling, flow cytometric instrumentation, and bioinformatics software, so that relatively large numbers of flow cytometric samples can be processed and analysed in a short period of time. We revisit a recent application of FC-HCS to the problem of cellular signature definition for acute graft-versus-host-disease. Our focus is on automation of the data processing steps using recent advances in statistical methodology. We demonstrate that effective results, on par with those obtained via manual processing, can be achieved using our automatic techniques. Such automation of FC-HCS has the potential to drastically improve diagnosis and biomarker identification.

Improving preschoolers' mathematics achievement with tablets: a randomized controlled trial

NASA Astrophysics Data System (ADS)

Schacter, John; Jo, Booil

2017-09-01

With a randomized field experiment of 433 preschoolers, we tested a tablet mathematics program designed to increase young children's mathematics learning. Intervention students played Math Shelf, a comprehensive iPad preschool and year 1 mathematics app, while comparison children received research-based hands-on mathematics instruction delivered by their classroom teachers. After 22 weeks, there was a large and statistically significant effect on mathematics achievement for Math Shelf students (Cohen's d = .94). Moderator analyses demonstrated an even larger effect for low achieving children (Cohen's d = 1.27). These results suggest that early education teachers can improve their students' mathematics outcomes by integrating experimentally proven tablet software into their daily routines.

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution.

PubMed

van Iterson, Maarten; van Zwet, Erik W; Heijmans, Bastiaan T

2017-01-27

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

PubMed Central

Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

2016-01-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis. PMID:27274911

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

PubMed

Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

2016-04-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

Partners or Partners in Crime? The Relationship Between Criminal Associates and Criminogenic Thinking.

PubMed

Whited, William H; Wagar, Laura; Mandracchia, Jon T; Morgan, Robert D

2017-04-01

Meta-analyses examining the risk factors for recidivism have identified the importance of ties with criminal associates as well as thoughts and attitudes conducive to the continuance of criminal behavior (e.g., criminogenic thinking). Criminologists have theorized that a direct relationship exists between the association with criminal peers and the development of criminogenic thinking. The present study empirically explored the relationship between criminal associates and criminogenic thinking in 595 adult male inmates in the United States. It was hypothesized that the proportion of free time spent with and number of criminal associates would be associated with criminogenic thinking, as measured by two self-report instruments, the Measure of Offender Thinking Styles-Revised (MOTS-R) and the Psychological Inventory of Criminal Thinking Styles (PICTS). Hierarchal linear regression analyses demonstrated that the proportion of free time spent with criminal associates statistically predicted criminogenic thinking when controlling for demographic variables. The implications of these findings on correctional practice (including assessment and intervention) as well as future research are discussed.

Characterization of branch complexity by fractal analyses

USGS Publications Warehouse

Alados, C.L.; Escos, J.; Emlen, J.M.; Freeman, D.C.

1999-01-01

The comparison between complexity in the sense of space occupancy (box-counting fractal dimension D(c) and information dimension D1) and heterogeneity in the sense of space distribution (average evenness index f and evenness variation coefficient J(cv)) were investigated in mathematical fractal objects and natural branch structures. In general, increased fractal dimension was paired with low heterogeneity. Comparisons between branch architecture in Anthyllis cytisoides under different slope exposure and grazing impact revealed that branches were more complex and more homogeneously distributed for plants on northern exposures than southern, while grazing had no impact during a wet year. Developmental instability was also investigated by the statistical noise of the allometric relation between internode length and node order. In conclusion, our study demonstrated that fractal dimension of branch structure can be used to analyze the structural organization of plants, especially if we consider not only fractal dimension but also shoot distribution within the canopy (lacunarity). These indexes together with developmental instability analyses are good indicators of growth responses to the environment.

Characterization of branch complexity by fractal analyses and detect plant functional adaptations

USGS Publications Warehouse

Alados, C.L.; Escos, J.; Emlen, J.M.; Freeman, D.C.

1999-01-01

The comparison between complexity in the sense of space occupancy (box-counting fractal dimension Dc and information dimension DI ) and heterogeneity in the sense of space distribution (average evenness index and evenness variation coefficient JCV) were investigated in mathematical fractal objects and natural branch ¯ J structures. In general, increased fractal dimension was paired with low heterogeneity. Comparisons between branch architecture in Anthyllis cytisoides under different slope exposure and grazing impact revealed that branches were more complex and more homogeneously distributed for plants on northern exposures than southern, while grazing had no impact during a wet year. Developmental instability was also investigated by the statistical noise of the allometric relation between internode length and node order. In conclusion, our study demonstrated that fractal dimension of branch structure can be used to analyze the structural organization of plants, especially if we consider not only fractal dimension but also shoot distribution within the canopy (lacunarity). These indexes together with developmental instability analyses are good indicators of growth responses to the environment.

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms

PubMed Central

Bentz, Christian; Verkerk, Annemarie; Kiela, Douwe; Hill, Felix; Buttery, Paula

2015-01-01

Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language. PMID:26083380

A General Accelerated Degradation Model Based on the Wiener Process.

PubMed

Liu, Le; Li, Xiaoyang; Sun, Fuqiang; Wang, Ning

2016-12-06

Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

Track analysis of laser-illuminated etched track detectors using an opto-digital imaging system

NASA Astrophysics Data System (ADS)

Eghan, Moses J.; Buah-Bassuah, Paul K.; Oppon, Osborne C.

2007-11-01

An opto-digital imaging system for counting and analysing tracks on a LR-115 detector is described. One batch of LR-115 track detectors was irradiated with Am-241 for a determined period and distance for linearity test and another batch was exposed to radon gas. The laser-illuminated etched track detector area was imaged, digitized and analysed by the system. The tracks that were counted on the opto-digital system with the aid of media cybernetics software as well as spark gap counter showed comparable track density results ranging between 1500 and 2750 tracks cm-2 and 65 tracks cm-2 in the two different batch detector samples with 0.5% and 1% track counts, respectively. Track sizes of the incident alpha particles from the radon gas on the LR-115 detector demonstrating different track energies are statistically and graphically represented. The opto-digital imaging system counts and measures other track parameters at an average process time of 3-5 s.

A General Accelerated Degradation Model Based on the Wiener Process

PubMed Central

Liu, Le; Li, Xiaoyang; Sun, Fuqiang; Wang, Ning

2016-01-01

Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses. PMID:28774107

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

PubMed

Barrantes, Gilbert; Sandoval, Luis

2009-09-01

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

Sampling and sensitivity analyses tools (SaSAT) for computational modelling

PubMed Central

Hoare, Alexander; Regan, David G; Wilson, David P

2008-01-01

SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated. PMID:18304361

Does educational status impact adult mortality in Denmark? A twin approach.

PubMed

Madsen, Mia; Andersen, Anne-Marie Nybo; Christensen, Kaare; Andersen, Per Kragh; Osler, Merete

2010-07-15

To disentangle an independent effect of educational status on mortality risk from direct and indirect selection mechanisms, the authors used a discordant twin pair design, which allowed them to isolate the effect of education by means of adjustment for genetic and environmental confounding per design. The study is based on data from the Danish Twin Registry and Statistics Denmark. Using Cox regression, they estimated hazard ratios for mortality according to the highest attained education among 5,260 monozygotic and 11,088 dizygotic same-sex twin pairs born during 1921-1950 and followed during 1980-2008. Both standard cohort and intrapair analyses were conducted separately for zygosity, gender, and birth cohort. Educational differences in mortality were demonstrated in the standard cohort analyses but attenuated in the intrapair analyses in all subgroups but men born during 1921-1935, and no effect modification by zygosity was observed. Hence, the results are most compatible with an effect of early family environment in explaining the educational inequality in mortality. However, large educational differences were still reflected in mortality risk differences within twin pairs, thus supporting some degree of independent effect of education. In addition, the effect of education may be more pronounced in older cohorts of Danish men.

Basic statistical analyses of candidate nickel-hydrogen cells for the Space Station Freedom

NASA Technical Reports Server (NTRS)

Maloney, Thomas M.; Frate, David T.

1993-01-01

Nickel-Hydrogen (Ni/H2) secondary batteries will be implemented as a power source for the Space Station Freedom as well as for other NASA missions. Consequently, characterization tests of Ni/H2 cells from Eagle-Picher, Whittaker-Yardney, and Hughes were completed at the NASA Lewis Research Center. Watt-hour efficiencies of each Ni/H2 cell were measured for regulated charge and discharge cycles as a function of temperature, charge rate, discharge rate, and state of charge. Temperatures ranged from -5 C to 30 C, charge rates ranged from C/10 to 1C, discharge rates ranged from C/10 to 2C, and states of charge ranged from 20 percent to 100 percent. Results from regression analyses and analyses of mean watt-hour efficiencies demonstrated that overall performance was best at temperatures between 10 C and 20 C while the discharge rate correlated most strongly with watt-hour efficiency. In general, the cell with back-to-back electrode arrangement, single stack, 26 percent KOH, and serrated zircar separator and the cell with a recirculating electrode arrangement, unit stack, 31 percent KOH, zircar separators performed best.

Benchmarking Strategies for Measuring the Quality of Healthcare: Problems and Prospects

PubMed Central

Lovaglio, Pietro Giorgio

2012-01-01

Over the last few years, increasing attention has been directed toward the problems inherent to measuring the quality of healthcare and implementing benchmarking strategies. Besides offering accreditation and certification processes, recent approaches measure the performance of healthcare institutions in order to evaluate their effectiveness, defined as the capacity to provide treatment that modifies and improves the patient's state of health. This paper, dealing with hospital effectiveness, focuses on research methods for effectiveness analyses within a strategy comparing different healthcare institutions. The paper, after having introduced readers to the principle debates on benchmarking strategies, which depend on the perspective and type of indicators used, focuses on the methodological problems related to performing consistent benchmarking analyses. Particularly, statistical methods suitable for controlling case-mix, analyzing aggregate data, rare events, and continuous outcomes measured with error are examined. Specific challenges of benchmarking strategies, such as the risk of risk adjustment (case-mix fallacy, underreporting, risk of comparing noncomparable hospitals), selection bias, and possible strategies for the development of consistent benchmarking analyses, are discussed. Finally, to demonstrate the feasibility of the illustrated benchmarking strategies, an application focused on determining regional benchmarks for patient satisfaction (using 2009 Lombardy Region Patient Satisfaction Questionnaire) is proposed. PMID:22666140

Benchmarking strategies for measuring the quality of healthcare: problems and prospects.

PubMed

Lovaglio, Pietro Giorgio

2012-01-01

Over the last few years, increasing attention has been directed toward the problems inherent to measuring the quality of healthcare and implementing benchmarking strategies. Besides offering accreditation and certification processes, recent approaches measure the performance of healthcare institutions in order to evaluate their effectiveness, defined as the capacity to provide treatment that modifies and improves the patient's state of health. This paper, dealing with hospital effectiveness, focuses on research methods for effectiveness analyses within a strategy comparing different healthcare institutions. The paper, after having introduced readers to the principle debates on benchmarking strategies, which depend on the perspective and type of indicators used, focuses on the methodological problems related to performing consistent benchmarking analyses. Particularly, statistical methods suitable for controlling case-mix, analyzing aggregate data, rare events, and continuous outcomes measured with error are examined. Specific challenges of benchmarking strategies, such as the risk of risk adjustment (case-mix fallacy, underreporting, risk of comparing noncomparable hospitals), selection bias, and possible strategies for the development of consistent benchmarking analyses, are discussed. Finally, to demonstrate the feasibility of the illustrated benchmarking strategies, an application focused on determining regional benchmarks for patient satisfaction (using 2009 Lombardy Region Patient Satisfaction Questionnaire) is proposed.

Evaluation of atpB nucleotide sequences for phylogenetic studies of ferns and other pteridophytes.

PubMed

Wolf, P

1997-10-01

Inferring basal relationships among vascular plants poses a major challenge to plant systematists. The divergence events that describe these relationships occurred long ago and considerable homoplasy has since accrued for both molecular and morphological characters. A potential solution is to examine phylogenetic analyses from multiple data sets. Here I present a new source of phylogenetic data for ferns and other pteridophytes. I sequenced the chloroplast gene atpB from 23 pteridophyte taxa and used maximum parsimony to infer relationships. A 588-bp region of the gene appeared to contain a statistically significant amount of phylogenetic signal and the resulting trees were largely congruent with similar analyses of nucleotide sequences from rbcL. However, a combined analysis of atpB plus rbcL produced a better resolved tree than did either data set alone. In the shortest trees, leptosporangiate ferns formed a monophyletic group. Also, I detected a well-supported clade of Psilotaceae (Psilotum and Tmesipteris) plus Ophioglossaceae (Ophioglossum and Botrychium). The demonstrated utility of atpB suggests that sequences from this gene should play a role in phylogenetic analyses that incorporate data from chloroplast genes, nuclear genes, morphology, and fossil data.

Research Pearls: The Significance of Statistics and Perils of Pooling. Part 3: Pearls and Pitfalls of Meta-analyses and Systematic Reviews.

PubMed

Harris, Joshua D; Brand, Jefferson C; Cote, Mark P; Dhawan, Aman

2017-08-01

Within the health care environment, there has been a recent and appropriate trend towards emphasizing the value of care provision. Reduced cost and higher quality improve the value of care. Quality is a challenging, heterogeneous, variably defined concept. At the core of quality is the patient's outcome, quantified by a vast assortment of subjective and objective outcome measures. There has been a recent evolution towards evidence-based medicine in health care, clearly elucidating the role of high-quality evidence across groups of patients and studies. Synthetic studies, such as systematic reviews and meta-analyses, are at the top of the evidence-based medicine hierarchy. Thus, these investigations may be the best potential source of guiding diagnostic, therapeutic, prognostic, and economic medical decision making. Systematic reviews critically appraise and synthesize the best available evidence to provide a conclusion statement (a "take-home point") in response to a specific answerable clinical question. A meta-analysis uses statistical methods to quantitatively combine data from single studies. Meta-analyses should be performed with high methodological quality homogenous studies (Level I or II) or evidence randomized studies, to minimize confounding variable bias. When it is known that the literature is inadequate or a recent systematic review has already been performed with a demonstration of insufficient data, then a new systematic review does not add anything meaningful to the literature. PROSPERO registration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines assist authors in the design and conduct of systematic reviews and should always be used. Complete transparency of the conduct of the review permits reproducibility and improves fidelity of the conclusions. Pooling of data from overly dissimilar investigations should be avoided. This particularly applies to Level IV evidence, that is, noncomparative investigations. With proper technique, systematic reviews and meta-analyses have the potential to be powerful investigations that efficiently assist clinicians in decision making. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Targeting intensive versus conventional glycaemic control for type 1 diabetes mellitus: a systematic review with meta-analyses and trial sequential analyses of randomised clinical trials.

PubMed

Kähler, Pernille; Grevstad, Berit; Almdal, Thomas; Gluud, Christian; Wetterslev, Jørn; Lund, Søren Søgaard; Vaag, Allan; Hemmingsen, Bianca

2014-08-19

To assess the benefits and harms of targeting intensive versus conventional glycaemic control in patients with type 1 diabetes mellitus. A systematic review with meta-analyses and trial sequential analyses of randomised clinical trials. The Cochrane Library, MEDLINE, EMBASE, Science Citation Index Expanded and LILACS to January 2013. Randomised clinical trials that prespecified different targets of glycaemic control in participants at any age with type 1 diabetes mellitus were included. Two authors independently assessed studies for inclusion and extracted data. 18 randomised clinical trials included 2254 participants with type 1 diabetes mellitus. All trials had high risk of bias. There was no statistically significant effect of targeting intensive glycaemic control on all-cause mortality (risk ratio 1.16, 95% CI 0.65 to 2.08) or cardiovascular mortality (0.49, 0.19 to 1.24). Targeting intensive glycaemic control reduced the relative risks for the composite macrovascular outcome (0.63, 0.41 to 0.96; p=0.03), and nephropathy (0.37, 0.27 to 0.50; p<0.00001. The effect estimates of retinopathy, ketoacidosis and retinal photocoagulation were not consistently statistically significant between random and fixed effects models. The risk of severe hypoglycaemia was significantly increased with intensive glycaemic targets (1.40, 1.01 to 1.94). Trial sequential analyses showed that the amount of data needed to demonstrate a relative risk reduction of 10% were, in general, inadequate. There was no significant effect towards improved all-cause mortality when targeting intensive glycaemic control compared with conventional glycaemic control. However, there may be beneficial effects of targeting intensive glycaemic control on the composite macrovascular outcome and on nephropathy, and detrimental effects on severe hypoglycaemia. Notably, the data for retinopathy and ketoacidosis were inconsistent. There was a severe lack of reporting on patient relevant outcomes, and all trials had poor bias control. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

[Clinical research=design*measurements*statistical analyses].

PubMed

Furukawa, Toshiaki

2012-06-01

A clinical study must address true endpoints that matter for the patients and the doctors. A good clinical study starts with a good clinical question. Formulating a clinical question in the form of PECO can sharpen one's original question. In order to perform a good clinical study one must have a knowledge of study design, measurements and statistical analyses: The first is taught by epidemiology, the second by psychometrics and the third by biostatistics.

Reframing Serial Murder Within Empirical Research.

PubMed

Gurian, Elizabeth A

2017-04-01

Empirical research on serial murder is limited due to the lack of consensus on a definition, the continued use of primarily descriptive statistics, and linkage to popular culture depictions. These limitations also inhibit our understanding of these offenders and affect credibility in the field of research. Therefore, this comprehensive overview of a sample of 508 cases (738 total offenders, including partnered groups of two or more offenders) provides analyses of solo male, solo female, and partnered serial killers to elucidate statistical differences and similarities in offending and adjudication patterns among the three groups. This analysis of serial homicide offenders not only supports previous research on offending patterns present in the serial homicide literature but also reveals that empirically based analyses can enhance our understanding beyond traditional case studies and descriptive statistics. Further research based on these empirical analyses can aid in the development of more accurate classifications and definitions of serial murderers.

[Continuity of hospital identifiers in hospital discharge data - Analysis of the nationwide German DRG Statistics from 2005 to 2013].

PubMed

Nimptsch, Ulrike; Wengler, Annelene; Mansky, Thomas

2016-11-01

In Germany, nationwide hospital discharge data (DRG statistics provided by the research data centers of the Federal Statistical Office and the Statistical Offices of the 'Länder') are increasingly used as data source for health services research. Within this data hospitals can be separated via their hospital identifier ([Institutionskennzeichen] IK). However, this hospital identifier primarily designates the invoicing unit and is not necessarily equivalent to one hospital location. Aiming to investigate direction and extent of possible bias in hospital-level analyses this study examines the continuity of the hospital identifier within a cross-sectional and longitudinal approach and compares the results to official hospital census statistics. Within the DRG statistics from 2005 to 2013 the annual number of hospitals as classified by hospital identifiers was counted for each year of observation. The annual number of hospitals derived from DRG statistics was compared to the number of hospitals in the official census statistics 'Grunddaten der Krankenhäuser'. Subsequently, the temporal continuity of hospital identifiers in the DRG statistics was analyzed within cohorts of hospitals. Until 2013, the annual number of hospital identifiers in the DRG statistics fell by 175 (from 1,725 to 1,550). This decline affected only providers with small or medium case volume. The number of hospitals identified in the DRG statistics was lower than the number given in the census statistics (e.g., in 2013 1,550 IK vs. 1,668 hospitals in the census statistics). The longitudinal analyses revealed that the majority of hospital identifiers persisted in the years of observation, while one fifth of hospital identifiers changed. In cross-sectional studies of German hospital discharge data the separation of hospitals via the hospital identifier might lead to underestimating the number of hospitals and consequential overestimation of caseload per hospital. Discontinuities of hospital identifiers over time might impair the follow-up of hospital cohorts. These limitations must be taken into account in analyses of German hospital discharge data focusing on the hospital level. Copyright © 2016. Published by Elsevier GmbH.

Trends in statistical methods in articles published in Archives of Plastic Surgery between 2012 and 2017.

PubMed

Han, Kyunghwa; Jung, Inkyung

2018-05-01

This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.

An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.; Clement, Jessica M.

2014-01-01

Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders. With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, social-value information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems.

Results of Kirari optical communication demonstration experiments with NICT optical ground station (KODEN) aiming for future classical and quantum communications in space

NASA Astrophysics Data System (ADS)

Toyoshima, Morio; Takenaka, Hideki; Shoji, Yozo; Takayama, Yoshihisa; Koyama, Yoshisada; Kunimori, Hiroo

2012-05-01

Bi-directional ground-to-satellite laser communication experiments were successfully performed between the optical ground station developed by the National Institute of Information and Communications Technology (NICT), located in Koganei City in suburban Tokyo, and a low earth orbit (LEO) satellite, the "Kirari" Optical Inter-orbit Communications Engineering Test Satellite (OICETS). The experiments were conducted in cooperation with the Japan Aerospace Exploration Agency (JAXA), and called the Kirari Optical communication Demonstration Experiments with the NICT optical ground station (or KODEN). The ground-to-OICETS laser communication experiment was the first in-orbit demonstration involving the LEO satellite. The laser communication experiment was conducted since March 2006. The polarization characteristics of an artificial laser source in space, such as Stokes parameters, and the degree of polarization were measured through space-to-ground atmospheric transmission paths, which results contribute to the link estimation for quantum key distribution via space and provide the potential for enhancements in quantum cryptography on a global scale in the future. The Phase-5 experiment, international laser communications experiments were also successfully conducted with four optical ground stations located in the United States, Spain, Germany, and Japan from April 2009 to September 2009. The purpose of the Phase-5 experiment was to establish OICETS-to-ground laser communication links from the different optical ground stations and the statistical analyses such as the normalized power, scintillation index, probability density function, auto-covariance function, and power spectral density were performed. Thus the applicability of the satellite laser communications was demonstrated, aiming not only for geostationary earth orbit-LEO links but also for ground-to-LEO optical links. This paper presents the results of the KODEN experiments and mainly introduces the common analyses among the different optical ground stations.

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

PubMed

Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

2016-12-01

: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Pooling sexes when assessing ground reaction forces during walking: Statistical Parametric Mapping versus traditional approach.

PubMed

Castro, Marcelo P; Pataky, Todd C; Sole, Gisela; Vilas-Boas, Joao Paulo

2015-07-16

Ground reaction force (GRF) data from men and women are commonly pooled for analyses. However, it may not be justifiable to pool sexes on the basis of discrete parameters extracted from continuous GRF gait waveforms because this can miss continuous effects. Forty healthy participants (20 men and 20 women) walked at a cadence of 100 steps per minute across two force plates, recording GRFs. Two statistical methods were used to test the null hypothesis of no mean GRF differences between sexes: (i) Statistical Parametric Mapping-using the entire three-component GRF waveform; and (ii) traditional approach-using the first and second vertical GRF peaks. Statistical Parametric Mapping results suggested large sex differences, which post-hoc analyses suggested were due predominantly to higher anterior-posterior and vertical GRFs in early stance in women compared to men. Statistically significant differences were observed for the first GRF peak and similar values for the second GRF peak. These contrasting results emphasise that different parts of the waveform have different signal strengths and thus that one may use the traditional approach to choose arbitrary metrics and make arbitrary conclusions. We suggest that researchers and clinicians consider both the entire gait waveforms and sex-specificity when analysing GRF data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Perceived Effectiveness among College Students of Selected Statistical Measures in Motivating Exercise Behavior

ERIC Educational Resources Information Center

Merrill, Ray M.; Chatterley, Amanda; Shields, Eric C.

2005-01-01

This study explored the effectiveness of selected statistical measures at motivating or maintaining regular exercise among college students. The study also considered whether ease in understanding these statistical measures was associated with perceived effectiveness at motivating or maintaining regular exercise. Analyses were based on a…

Statistical Diversions

ERIC Educational Resources Information Center

Petocz, Peter; Sowey, Eric

2012-01-01

The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…

The Empirical Nature and Statistical Treatment of Missing Data

ERIC Educational Resources Information Center

Tannenbaum, Christyn E.

2009-01-01

Introduction. Missing data is a common problem in research and can produce severely misleading analyses, including biased estimates of statistical parameters, and erroneous conclusions. In its 1999 report, the APA Task Force on Statistical Inference encouraged authors to report complications such as missing data and discouraged the use of…

Statistical Significance Testing in Second Language Research: Basic Problems and Suggestions for Reform

ERIC Educational Resources Information Center

Norris, John M.

2015-01-01

Traditions of statistical significance testing in second language (L2) quantitative research are strongly entrenched in how researchers design studies, select analyses, and interpret results. However, statistical significance tests using "p" values are commonly misinterpreted by researchers, reviewers, readers, and others, leading to…

75 FR 24718 - Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-05

...] Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability AGENCY... Programs and Data Files.'' This guidance is provided to inform study statisticians of recommendations for documenting statistical analyses and data files submitted to the Center for Veterinary Medicine (CVM) for the...

Ethnic differences in thermal pain responses: a comparison of South Asian and White British healthy males.

PubMed

Watson, Paul J; Latif, R Khalid; Rowbotham, David J

2005-11-01

The expression and report of pain is influenced by social environment and culture. Previous studies have suggested ethnically determined differences in report of pain threshold, intensity and affect. The influence of ethnic differences between White British and South Asians has remained unexplored. Twenty age-matched, male volunteers in each group underwent evaluation. Cold and warm perception and cold and heat threshold were assessed using an ascending method of limits. Magnitude estimation of pain unpleasantness and pain intensity were investigated with thermal stimuli of 46, 47, 48 and 49 degrees C. Subjects also completed a pain anxiety questionnaire. Data was analysed using t-test, Mann-Whitney and repeated measures analysis of variance as appropriate. There were no differences in cold and warm perception between the two groups. There was a statistically significant difference between the two groups for heat pain threshold (P=0.006) and heat pain intensity demonstrated a significant effect for ethnicity (F=13.84, P=0.001). Although no group differences emerged for cold pain threshold and heat unpleasantness, South Asians demonstrated lower cold pain threshold and reported more unpleasantness at all temperatures but this was not statistically significant. Our study shows that ethnicity plays an important role in heat pain threshold and pain report, South Asian males demonstrated lower pain thresholds and higher pain report when compared with matched White British males. There were no differences in pain anxiety between the two groups and no correlations were identified between pain and pain anxiety Haemodynamic measures and anthropometry did not explain group differences.

Contrast enhanced dual energy spectral mammogram, an emerging addendum in breast imaging

PubMed Central

Gnanaprakasam, Francis; Anand, Subhapradha; Krishnaswami, Murali; Ramachandran, Madan

2016-01-01

Objective: To assess the role of contrast-enhanced dual-energy spectral mammogram (CEDM) as a problem-solving tool in equivocal cases. Methods: 44 consenting females with equivocal findings on full-field digital mammogram underwent CEDM. All the images were interpreted by two radiologists independently. Confidence of presence was plotted on a three-point Likert scale and probability of cancer was assigned on Breast Imaging Reporting and Data System scoring. Histopathology was taken as the gold standard. Statistical analyses of all variables were performed. Results: 44 breast lesions were included in the study, among which 77.3% lesions were malignant or precancerous and 22.7% lesions were benign or inconclusive. 20% of lesions were identified only on CEDM. True extent of the lesion was made out in 15.9% of cases, multifocality was established in 9.1% of cases and ductal extension was demonstrated in 6.8% of cases. Statistical significance for CEDM was p-value <0.05. Interobserver kappa value was 0.837. Conclusion: CEDM has a useful role in identifying occult lesions in dense breasts and in triaging lesions. In a mammographically visible lesion, CEDM characterizes the lesion, affirms the finding and better demonstrates response to treatment. Hence, we conclude that CEDM is a useful complementary tool to standard mammogram. Advances in knowledge: CEDM can detect and demonstrate lesions even in dense breasts with the advantage of feasibility of stereotactic biopsy in the same setting. Hence, it has the potential to be a screening modality with need for further studies and validation. PMID:27610475

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).

PubMed

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

PubMed

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing

PubMed Central

STAMATE, MIRELA CRISTINA; TODOR, NICOLAE; COSGAREA, MARCEL

2015-01-01

Background and aim The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. Methods The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. Results We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Conclusion Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies. PMID:26733749

ParallABEL: an R library for generalized parallelization of genome-wide association studies.

PubMed

Sangket, Unitsa; Mahasirimongkol, Surakameth; Chantratita, Wasun; Tandayya, Pichaya; Aulchenko, Yurii S

2010-04-29

Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.

Statistical analysis plan for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). A randomized controlled trial

PubMed Central

Damiani, Lucas Petri; Berwanger, Otavio; Paisani, Denise; Laranjeira, Ligia Nasi; Suzumura, Erica Aranha; Amato, Marcelo Britto Passos; Carvalho, Carlos Roberto Ribeiro; Cavalcanti, Alexandre Biasi

2017-01-01

Background The Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) is an international multicenter randomized pragmatic controlled trial with allocation concealment involving 120 intensive care units in Brazil, Argentina, Colombia, Italy, Poland, Portugal, Malaysia, Spain, and Uruguay. The primary objective of ART is to determine whether maximum stepwise alveolar recruitment associated with PEEP titration, adjusted according to the static compliance of the respiratory system (ART strategy), is able to increase 28-day survival in patients with acute respiratory distress syndrome compared to conventional treatment (ARDSNet strategy). Objective To describe the data management process and statistical analysis plan. Methods The statistical analysis plan was designed by the trial executive committee and reviewed and approved by the trial steering committee. We provide an overview of the trial design with a special focus on describing the primary (28-day survival) and secondary outcomes. We describe our data management process, data monitoring committee, interim analyses, and sample size calculation. We describe our planned statistical analyses for primary and secondary outcomes as well as pre-specified subgroup analyses. We also provide details for presenting results, including mock tables for baseline characteristics, adherence to the protocol and effect on clinical outcomes. Conclusion According to best trial practice, we report our statistical analysis plan and data management plan prior to locking the database and beginning analyses. We anticipate that this document will prevent analysis bias and enhance the utility of the reported results. Trial registration ClinicalTrials.gov number, NCT01374022. PMID:28977255

Formalizing the definition of meta-analysis in Molecular Ecology.

PubMed

ArchMiller, Althea A; Bauer, Eric F; Koch, Rebecca E; Wijayawardena, Bhagya K; Anil, Ammu; Kottwitz, Jack J; Munsterman, Amelia S; Wilson, Alan E

2015-08-01

Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first meta-analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's FST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'meta-analyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted meta-analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta-analysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology. © 2015 John Wiley & Sons Ltd.

Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

PubMed Central

Hernández-Morera, Pablo; Castaño-González, Irene; Travieso-González, Carlos M.; Mompeó-Corredera, Blanca; Ortega-Santana, Francisco

2016-01-01

Purpose To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson’s trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained. Methods The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time. Results The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes. Conclusion The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met. PMID:26761643

Statistical analysis of nonmonotonic dose-response relationships: research design and analysis of nasal cell proliferation in rats exposed to formaldehyde.

PubMed

Gaylor, David W; Lutz, Werner K; Conolly, Rory B

2004-01-01

Statistical analyses of nonmonotonic dose-response curves are proposed, experimental designs to detect low-dose effects of J-shaped curves are suggested, and sample sizes are provided. For quantal data such as cancer incidence rates, much larger numbers of animals are required than for continuous data such as biomarker measurements. For example, 155 animals per dose group are required to have at least an 80% chance of detecting a decrease from a 20% incidence in controls to an incidence of 10% at a low dose. For a continuous measurement, only 14 animals per group are required to have at least an 80% chance of detecting a change of the mean by one standard deviation of the control group. Experimental designs based on three dose groups plus controls are discussed to detect nonmonotonicity or to estimate the zero equivalent dose (ZED), i.e., the dose that produces a response equal to the average response in the controls. Cell proliferation data in the nasal respiratory epithelium of rats exposed to formaldehyde by inhalation are used to illustrate the statistical procedures. Statistically significant departures from a monotonic dose response were obtained for time-weighted average labeling indices with an estimated ZED at a formaldehyde dose of 5.4 ppm, with a lower 95% confidence limit of 2.7 ppm. It is concluded that demonstration of a statistically significant bi-phasic dose-response curve, together with estimation of the resulting ZED, could serve as a point-of departure in establishing a reference dose for low-dose risk assessment.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

The Statistical Basis of Chemical Equilibria.

ERIC Educational Resources Information Center

Hauptmann, Siegfried; Menger, Eva

1978-01-01

Describes a machine which demonstrates the statistical bases of chemical equilibrium, and in doing so conveys insight into the connections among statistical mechanics, quantum mechanics, Maxwell Boltzmann statistics, statistical thermodynamics, and transition state theory. (GA)

SEER Cancer Query Systems (CanQues)

Cancer.gov

These applications provide access to cancer statistics including incidence, mortality, survival, prevalence, and probability of developing or dying from cancer. Users can display reports of the statistics or extract them for additional analyses.

Barrett’s oesophagus: Evidence from the current meta-analyses

PubMed Central

Gatenby, Piers; Soon, Yuen

2014-01-01

Guidelines have been published regarding the management of Barrett’s oesophagus (columnar-lined oesophagus). These have examined the role of surveillance in an effort to detect dysplasia and early cancer. The guidelines have provided criteria for enrolment into surveillance and some risk stratification with regard to surveillance interval. The research basis for the decisions reached with regard to cancer risk is weak and this manuscript has examined the available data published from meta-analyses up to 25th April 2013 (much of which has been published since the guidelines and their most recent updates have been written). There were 9 meta-analyses comparing patients with Barrett’s oesophagus to control populations. These have demonstrated that Barrett’s oesophagus is more common in males than females, in subjects who have ever smoked, in subjects with obesity, in subjects with prolonged symptoms of gastro-oesophageal reflux disease, in subjects who do not have infection with Helicobacter pylori and in subjects with hiatus hernia. These findings should inform public health measures in reducing the risk of Barrett’s oesophagus and subsequent surveillance burden and cancer risk. There were 8 meta-analyses comparing different groups of patients with Barrett’s oesophagus with regard to cancer risk. These have demonstrated that there was no statistically significant benefit of antireflux surgery over medical therapy, that endoscopic ablative therapy was effective in reducing cancer risk that there was similar cancer risk in patients with Barrett’s oesophagus independent of geographic origin, that the adenocarcinoma incidence in males is twice the rate in females, that the cancer risk in long segment disease showed a trend to be higher than in short segment disease, that there was a trend for higher cancer risk in low-grade dysplasia over non-dysplastic Barrett’s oesophagus, that there is a lower risk in patients with Helicobacter pylori infection and that there is a significant protective effect of aspirin and statins. There were no meta-analyses examining the role of intestinal metaplasia. These results demonstrate that guidance regarding surveillance based on the presence of intestinal metaplasia, segment length and the presence of low-grade dysplasia has a weak basis, and further consideration should be given to gender and helicobacter status, ablation of the metaplastic segment as well as the chemoprotective role of aspirin and statins. PMID:25133020

Barrett's oesophagus: Evidence from the current meta-analyses.

PubMed

Gatenby, Piers; Soon, Yuen

2014-08-15

Guidelines have been published regarding the management of Barrett's oesophagus (columnar-lined oesophagus). These have examined the role of surveillance in an effort to detect dysplasia and early cancer. The guidelines have provided criteria for enrolment into surveillance and some risk stratification with regard to surveillance interval. The research basis for the decisions reached with regard to cancer risk is weak and this manuscript has examined the available data published from meta-analyses up to 25(th) April 2013 (much of which has been published since the guidelines and their most recent updates have been written). There were 9 meta-analyses comparing patients with Barrett's oesophagus to control populations. These have demonstrated that Barrett's oesophagus is more common in males than females, in subjects who have ever smoked, in subjects with obesity, in subjects with prolonged symptoms of gastro-oesophageal reflux disease, in subjects who do not have infection with Helicobacter pylori and in subjects with hiatus hernia. These findings should inform public health measures in reducing the risk of Barrett's oesophagus and subsequent surveillance burden and cancer risk. There were 8 meta-analyses comparing different groups of patients with Barrett's oesophagus with regard to cancer risk. These have demonstrated that there was no statistically significant benefit of antireflux surgery over medical therapy, that endoscopic ablative therapy was effective in reducing cancer risk that there was similar cancer risk in patients with Barrett's oesophagus independent of geographic origin, that the adenocarcinoma incidence in males is twice the rate in females, that the cancer risk in long segment disease showed a trend to be higher than in short segment disease, that there was a trend for higher cancer risk in low-grade dysplasia over non-dysplastic Barrett's oesophagus, that there is a lower risk in patients with Helicobacter pylori infection and that there is a significant protective effect of aspirin and statins. There were no meta-analyses examining the role of intestinal metaplasia. These results demonstrate that guidance regarding surveillance based on the presence of intestinal metaplasia, segment length and the presence of low-grade dysplasia has a weak basis, and further consideration should be given to gender and helicobacter status, ablation of the metaplastic segment as well as the chemoprotective role of aspirin and statins.

Facilitating the Transition from Bright to Dim Environments

DTIC Science & Technology

2016-03-04

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

Subthalamic deep brain stimulation in Parkinson׳s disease has no significant effect on perceptual timing in the hundreds of milliseconds range

PubMed Central

Cope, Thomas E.; Grube, Manon; Mandal, Arnab; Cooper, Freya E.; Brechany, Una; Burn, David J.; Griffiths, Timothy D.

2014-01-01

Bilateral, high-frequency stimulation of the basal ganglia (STN-DBS) is in widespread use for the treatment of the motor symptoms of Parkinson׳s disease (PD). We present here the first psychophysical investigation of the effect of STN-DBS upon perceptual timing in the hundreds of milliseconds range, with both duration-based (absolute) and beat-based (relative) tasks; 13 patients with PD were assessed with their STN-DBS ‘on’, ‘off’, and then ‘on’ again. Paired parametric analyses revealed no statistically significant differences for any task according to DBS status. We demonstrate, from the examination of confidence intervals, that any functionally relevant effect of STN-DBS on relative perceptual timing is statistically unlikely. For absolute, duration-based timing, we demonstrate that the activation of STN-DBS may either worsen performance or have no effect, but that it is unlikely to lead to significant improvement. Although these results are negative they have important implications for our understanding of perceptual timing and its relationship to motor functions within the timing network of the brain. They imply that the mechanisms involved in the perceptual processing of temporal information are likely to be functionally independent from those that underpin movement. Further, they suggest that the connections between STN and the subtantia nigra and globus pallidus are unlikely to be critical to beat-based perceptual timing. PMID:24613477

Gadobutrol for contrast-enhanced magnetic resonance imaging in elderly patients: review of the safety profile from clinical trial, post-marketing surveillance, and pharmacovigilance data.

PubMed

Endrikat, J; Schwenke, C; Prince, M R

2015-07-01

To assess the safety of gadobutrol administration in elderly patients (≥65 years) by comparing the incidence of adverse drug reactions (ADRs) following gadobutrol-enhanced magnetic resonance imaging (MRI) procedures in elderly patients with that in adults aged 18-64 years. Safety data on gadobutrol administration from clinical trials, post-marketing surveillance (PMS) studies, and pharmacovigilance reports were collected in three databases. In each dataset, absolute and relative frequencies of ADRs between age groups were analysed, along with odds ratios and 95% confidence intervals. Logistic regression was used to identify significant influencing factors on ADRs in the PMS and pharmacovigilance data. Rates of reported ADRs were lower in elderly patients versus adults aged <65 years due to a reduced incidence of non-serious ADRs; this was statistically significant for the clinical trials and pharmacovigilance populations, with a trend in the PMS database. Serious ADRs occurred infrequently in the clinical trials and PMS populations (too low for statistical comparison), and pharmacovigilance data demonstrated a low incidence (<0.005%) in both age groups. This evaluation involving three large databases demonstrated no greater incidence of ADRs following gadobutrol-enhanced MRI in elderly patients (≥65 years) compared with younger adults, with gadobutrol having a favourable safety profile in both age groups. Copyright © 2015 The Royal College of Radiologists. All rights reserved.

Imaging Depression in Adults with ASD

DTIC Science & Technology

2017-10-01

collected temporally close enough to imaging data in Phase 2 to be confidently incorporated in the planned statistical analyses, and (b) not unduly risk...Phase 2 to be confidently incorporated in the planned statistical analyses, and (b) not unduly risk attrition between Phase 1 and 2, we chose to hold...supervision is ongoing (since 9/2014). • Co-l Dr. Lerner’s 2nd year Clinical Psychology PhD students have participated in ADOS- 2 Introductory Clinical

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

PubMed

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Separating Putative Pathogens from Background Contamination with Principal Orthogonal Decomposition: Evidence for Leptospira in the Ugandan Neonatal Septisome

PubMed Central

Schiff, Steven J.; Kiwanuka, Julius; Riggio, Gina; Nguyen, Lan; Mu, Kevin; Sproul, Emily; Bazira, Joel; Mwanga-Amumpaire, Juliet; Tumusiime, Dickson; Nyesigire, Eunice; Lwanga, Nkangi; Bogale, Kaleb T.; Kapur, Vivek; Broach, James R.; Morton, Sarah U.; Warf, Benjamin C.; Poss, Mary

2016-01-01

Neonatal sepsis (NS) is responsible for over 1 million yearly deaths worldwide. In the developing world, NS is often treated without an identified microbial pathogen. Amplicon sequencing of the bacterial 16S rRNA gene can be used to identify organisms that are difficult to detect by routine microbiological methods. However, contaminating bacteria are ubiquitous in both hospital settings and research reagents and must be accounted for to make effective use of these data. In this study, we sequenced the bacterial 16S rRNA gene obtained from blood and cerebrospinal fluid (CSF) of 80 neonates presenting with NS to the Mbarara Regional Hospital in Uganda. Assuming that patterns of background contamination would be independent of pathogenic microorganism DNA, we applied a novel quantitative approach using principal orthogonal decomposition to separate background contamination from potential pathogens in sequencing data. We designed our quantitative approach contrasting blood, CSF, and control specimens and employed a variety of statistical random matrix bootstrap hypotheses to estimate statistical significance. These analyses demonstrate that Leptospira appears present in some infants presenting within 48 h of birth, indicative of infection in utero, and up to 28 days of age, suggesting environmental exposure. This organism cannot be cultured in routine bacteriological settings and is enzootic in the cattle that often live in close proximity to the rural peoples of western Uganda. Our findings demonstrate that statistical approaches to remove background organisms common in 16S sequence data can reveal putative pathogens in small volume biological samples from newborns. This computational analysis thus reveals an important medical finding that has the potential to alter therapy and prevention efforts in a critically ill population. PMID:27379237

Additive scales in degenerative disease--calculation of effect sizes and clinical judgment.

PubMed

Riepe, Matthias W; Wilkinson, David; Förstl, Hans; Brieden, Andreas

2011-12-16

The therapeutic efficacy of an intervention is often assessed in clinical trials by scales measuring multiple diverse activities that are added to produce a cumulative global score. Medical communities and health care systems subsequently use these data to calculate pooled effect sizes to compare treatments. This is done because major doubt has been cast over the clinical relevance of statistically significant findings relying on p values with the potential to report chance findings. Hence in an aim to overcome this pooling the results of clinical studies into a meta-analyses with a statistical calculus has been assumed to be a more definitive way of deciding of efficacy. We simulate the therapeutic effects as measured with additive scales in patient cohorts with different disease severity and assess the limitations of an effect size calculation of additive scales which are proven mathematically. We demonstrate that the major problem, which cannot be overcome by current numerical methods, is the complex nature and neurobiological foundation of clinical psychiatric endpoints in particular and additive scales in general. This is particularly relevant for endpoints used in dementia research. 'Cognition' is composed of functions such as memory, attention, orientation and many more. These individual functions decline in varied and non-linear ways. Here we demonstrate that with progressive diseases cumulative values from multidimensional scales are subject to distortion by the limitations of the additive scale. The non-linearity of the decline of function impedes the calculation of effect sizes based on cumulative values from these multidimensional scales. Statistical analysis needs to be guided by boundaries of the biological condition. Alternatively, we suggest a different approach avoiding the error imposed by over-analysis of cumulative global scores from additive scales.

Causal modelling applied to the risk assessment of a wastewater discharge.

PubMed

Paul, Warren L; Rokahr, Pat A; Webb, Jeff M; Rees, Gavin N; Clune, Tim S

2016-03-01

Bayesian networks (BNs), or causal Bayesian networks, have become quite popular in ecological risk assessment and natural resource management because of their utility as a communication and decision-support tool. Since their development in the field of artificial intelligence in the 1980s, however, Bayesian networks have evolved and merged with structural equation modelling (SEM). Unlike BNs, which are constrained to encode causal knowledge in conditional probability tables, SEMs encode this knowledge in structural equations, which is thought to be a more natural language for expressing causal information. This merger has clarified the causal content of SEMs and generalised the method such that it can now be performed using standard statistical techniques. As it was with BNs, the utility of this new generation of SEM in ecological risk assessment will need to be demonstrated with examples to foster an understanding and acceptance of the method. Here, we applied SEM to the risk assessment of a wastewater discharge to a stream, with a particular focus on the process of translating a causal diagram (conceptual model) into a statistical model which might then be used in the decision-making and evaluation stages of the risk assessment. The process of building and testing a spatial causal model is demonstrated using data from a spatial sampling design, and the implications of the resulting model are discussed in terms of the risk assessment. It is argued that a spatiotemporal causal model would have greater external validity than the spatial model, enabling broader generalisations to be made regarding the impact of a discharge, and greater value as a tool for evaluating the effects of potential treatment plant upgrades. Suggestions are made on how the causal model could be augmented to include temporal as well as spatial information, including suggestions for appropriate statistical models and analyses.

Long-Term Follow-up to a Randomized Controlled Trial Comparing Peroneal Nerve Functional Electrical Stimulation to an Ankle Foot Orthosis for Patients With Chronic Stroke.

PubMed

Bethoux, Francois; Rogers, Helen L; Nolan, Karen J; Abrams, Gary M; Annaswamy, Thiru; Brandstater, Murray; Browne, Barbara; Burnfield, Judith M; Feng, Wuwei; Freed, Mitchell J; Geis, Carolyn; Greenberg, Jason; Gudesblatt, Mark; Ikramuddin, Farha; Jayaraman, Arun; Kautz, Steven A; Lutsep, Helmi L; Madhavan, Sangeetha; Meilahn, Jill; Pease, William S; Rao, Noel; Seetharama, Subramani; Sethi, Pramod; Turk, Margaret A; Wallis, Roi Ann; Kufta, Conrad

2015-01-01

Evidence supports peroneal nerve functional electrical stimulation (FES) as an effective alternative to ankle foot orthoses (AFO) for treatment of foot drop poststroke, but few long-term, randomized controlled comparisons exist. Compare changes in gait quality and function between FES and AFOs in individuals with foot drop poststroke over a 12-month period. Follow-up analysis of an unblinded randomized controlled trial (ClinicalTrials.gov #NCT01087957) conducted at 30 rehabilitation centers comparing FES to AFOs over 6 months. Subjects continued to wear their randomized device for another 6 months to final 12-month assessments. Subjects used study devices for all home and community ambulation. Multiply imputed intention-to-treat analyses were utilized; primary endpoints were tested for noninferiority and secondary endpoints for superiority. Primary endpoints: 10 Meter Walk Test (10MWT) and device-related serious adverse event rate. Secondary endpoints: 6-Minute Walk Test (6MWT), GaitRite Functional Ambulation Profile, and Modified Emory Functional Ambulation Profile (mEFAP). A total of 495 subjects were randomized, and 384 completed the 12-month follow-up. FES proved noninferior to AFOs for all primary endpoints. Both FES and AFO groups showed statistically and clinically significant improvement for 10MWT compared with initial measurement. No statistically significant between-group differences were found for primary or secondary endpoints. The FES group demonstrated statistically significant improvements for 6MWT and mEFAP Stair-time subscore. At 12 months, both FES and AFOs continue to demonstrate equivalent gains in gait speed. Results suggest that long-term FES use may lead to additional improvements in walking endurance and functional ambulation; further research is needed to confirm these findings. © The Author(s) 2015.

Dimensionality of Hallucinogen and Inhalant/Solvent Abuse and Dependence Criteria: Implications for the Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition

PubMed Central

Kerridge, Bradley T.; Saha, Tulshi D.; Smith, Sharon; Chou, Patricia S.; Pickering, Roger P.; Huang, Boji; Ruan, June W.; Pulay, Attila J.

2012-01-01

Background Prior research has demonstrated the dimensionality of Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV) alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria. The purpose of this study was to examine the dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria. In addition, we assessed the impact of elimination of the legal problems abuse criterion on the information value of the aggregate abuse and dependence criteria, another proposed change for DSM- IV currently lacking empirical justification. Methods Factor analyses and item response theory (IRT) analyses were used to explore the unidimisionality and psychometric properties of hallucinogen and inhalant/solvent abuse and dependence criteria using a large representative sample of the United States (U.S.) general population. Results Hallucinogen and inhalant/solvent abuse and dependence criteria formed unidimensional latent traits. For both substances, IRT models without the legal problems abuse criterion demonstrated better fit than the corresponding model with the legal problem abuse criterion. Further, there were no differences in the information value of the IRT models with and without the legal problems abuse criterion, supporting the elimination of that criterion. No bias in the new diagnoses was observed by sex, age and race-ethnicity. Conclusion Consistent with findings for alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria, hallucinogen and inhalant/solvent criteria reflect underlying dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the DSM-V Substance and Related Disorders Workgroup, that is, combining DSM-IV abuse and dependence criteria and eliminating the legal problems abuse criterion. PMID:21621334

Hybrid Diffusion Imaging in Mild Traumatic Brain Injury.

PubMed

Wu, Yu-Chien; Mustafi, Sourajit Mitra; Harezlak, Jaroslaw; Kodiweera, Chandana; Flashman, Laura A; McAllister, Thomas

2018-05-22

Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white-matter alterations in nineteen patients with mTBI and 23 other trauma-control patients. Within 15 days (SD=10) of brain injury, all subjects underwent magnetic-resonance HYDI and were assessed with battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) were used for voxelwise statistical analyses within the white-matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between group interaction effects. The advanced diffusion imaging techniques including neurite orientation dispersion and density imaging (NODDI) and q-space analyses appeared to be more sensitive then classic diffusion tensor imaging (DTI). Only NODDI-derived intra-axonal volume fraction (V_ic) demonstrated significant group differences (i.e., 5% to 9% lower in the injured brain). Within the mTBI group, V_ic and a q-space measure, P₀, correlated with 6 of 10 neuropsychological tests including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between the groups (R² > 0.71 and P_interation < 0.03). Specifically, in the control group, higher V_ic and P₀ were associated with better performances on clinical assessments, whereas in the mTBI group, higher V_ic and P₀ were associated with worse performances with correlation coefficients > 0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white-matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.

Dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria: implications for the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition.

PubMed

Kerridge, Bradley T; Saha, Tulshi D; Smith, Sharon; Chou, Patricia S; Pickering, Roger P; Huang, Boji; Ruan, June W; Pulay, Attila J

2011-09-01

Prior research has demonstrated the dimensionality of Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria. The purpose of this study was to examine the dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria. In addition, we assessed the impact of elimination of the legal problems abuse criterion on the information value of the aggregate abuse and dependence criteria, another proposed change for DSM-IV currently lacking empirical justification. Factor analyses and item response theory (IRT) analyses were used to explore the unidimisionality and psychometric properties of hallucinogen and inhalant/solvent abuse and dependence criteria using a large representative sample of the United States (U.S.) general population. Hallucinogen and inhalant/solvent abuse and dependence criteria formed unidimensional latent traits. For both substances, IRT models without the legal problems abuse criterion demonstrated better fit than the corresponding model with the legal problem abuse criterion. Further, there were no differences in the information value of the IRT models with and without the legal problems abuse criterion, supporting the elimination of that criterion. No bias in the new diagnoses was observed by sex, age and race-ethnicity. Consistent with findings for alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria, hallucinogen and inhalant/solvent criteria reflect underlying dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the DSM-V Substance and Related Disorders Workgroup, that is, combining DSM-IV abuse and dependence criteria and eliminating the legal problems abuse criterion. Published by Elsevier Ltd.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

PubMed

Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-06-01

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography

PubMed Central

Packham, B; Barnes, G; dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-01-01

Abstract Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity. PMID:27203477

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Identifying currents in the gene pool for bacterial populations using an integrative approach.

PubMed

Tang, Jing; Hanage, William P; Fraser, Christophe; Corander, Jukka

2009-08-01

The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html.

Effect of crowd size on patient volume at a large, multipurpose, indoor stadium.

PubMed

De Lorenzo, R A; Gray, B C; Bennett, P C; Lamparella, V J

1989-01-01

A prediction of patient volume expected at "mass gatherings" is desirable in order to provide optimal on-site emergency medical care. While several methods of predicting patient loads have been suggested, a reliable technique has not been established. This study examines the frequency of medical emergencies at the Syracuse University Carrier Dome, a 50,500-seat indoor stadium. Patient volume and level of care at collegiate basketball and football games as well as rock concerts, over a 7-year period were examined and tabulated. This information was analyzed using simple regression and nonparametric statistical methods to determine level of correlation between crowd size and patient volume. These analyses demonstrated no statistically significant increase in patient volume for increasing crowd size for basketball and football events. There was a small but statistically significant increase in patient volume for increasing crowd size for concerts. A comparison of similar crowd size for each of the three events showed that patient frequency is greatest for concerts and smallest for basketball. The study suggests that crowd size alone has only a minor influence on patient volume at any given event. Structuring medical services based solely on expected crowd size and not considering other influences such as event type and duration may give poor results.

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

PubMed

Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi

2016-03-01

Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies.

PubMed

Grimm, Dominik G; Roqueiro, Damian; Salomé, Patrice A; Kleeberger, Stefan; Greshake, Bastian; Zhu, Wangsheng; Liu, Chang; Lippert, Christoph; Stegle, Oliver; Schölkopf, Bernhard; Weigel, Detlef; Borgwardt, Karsten M

2017-01-01

The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana , using flowering and growth-related traits. © 2016 American Society of Plant Biologists. All rights reserved.

Dependence of drivers affects risks associated with compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Seneviratne, Sonia I.

2017-04-01

Compound climate extremes are receiving increasing attention because of their disproportionate impacts on humans and ecosystems. Risks assessments, however, generally focus on univariate statistics even when multiple stressors are considered. Concurrent extreme droughts and heatwaves have been observed to cause a suite of extreme impacts on natural and human systems alike. For example, they can substantially affect vegetation health, prompting tree mortality, and thereby facilitating insect outbreaks and fires. In addition, hot droughts have the potential to trigger and intensify fires and can cause severe economical damage. By promoting disease spread, extremely hot and dry conditions also strongly affect human health. We analyse the co-occurrence of dry and hot summers and show that these are strongly correlated for many regions, inducing a much higher frequency of concurrent hot and dry summers than what would be assumed from the independent combination of the univariate statistics. Our results demonstrate how the dependence structure between variables affects the occurrence frequency of multivariate extremes. Assessments based on univariate statistics can thus strongly underestimate risks associated with given extremes, if impacts depend on multiple (dependent) variables. We conclude that a multivariate perspective is necessary in order to appropriately assess changes in climate extremes and their impacts, and to design adaptation strategies.

A new statistical method for design and analyses of component tolerance

NASA Astrophysics Data System (ADS)

Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam

2017-03-01

Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.

Methods in pharmacoepidemiology: a review of statistical analyses and data reporting in pediatric drug utilization studies.

PubMed

Sequi, Marco; Campi, Rita; Clavenna, Antonio; Bonati, Maurizio

2013-03-01

To evaluate the quality of data reporting and statistical methods performed in drug utilization studies in the pediatric population. Drug utilization studies evaluating all drug prescriptions to children and adolescents published between January 1994 and December 2011 were retrieved and analyzed. For each study, information on measures of exposure/consumption, the covariates considered, descriptive and inferential analyses, statistical tests, and methods of data reporting was extracted. An overall quality score was created for each study using a 12-item checklist that took into account the presence of outcome measures, covariates of measures, descriptive measures, statistical tests, and graphical representation. A total of 22 studies were reviewed and analyzed. Of these, 20 studies reported at least one descriptive measure. The mean was the most commonly used measure (18 studies), but only five of these also reported the standard deviation. Statistical analyses were performed in 12 studies, with the chi-square test being the most commonly performed test. Graphs were presented in 14 papers. Sixteen papers reported the number of drug prescriptions and/or packages, and ten reported the prevalence of the drug prescription. The mean quality score was 8 (median 9). Only seven of the 22 studies received a score of ≥10, while four studies received a score of <6. Our findings document that only a few of the studies reviewed applied statistical methods and reported data in a satisfactory manner. We therefore conclude that the methodology of drug utilization studies needs to be improved.

Quantitative Methods for Analysing Joint Questionnaire Data: Exploring the Role of Joint in Force Design

DTIC Science & Technology

2015-08-01

the nine questions. The Statistical Package for the Social Sciences ( SPSS ) [11] was used to conduct statistical analysis on the sample. Two types...constructs. SPSS was again used to conduct statistical analysis on the sample. This time factor analysis was conducted. Factor analysis attempts to...Business Research Methods and Statistics using SPSS . P432. 11 IBM SPSS Statistics . (2012) 12 Burns, R.B., Burns, R.A. (2008) ‘Business Research

Research Design and Statistical Methods in Indian Medical Journals: A Retrospective Survey

PubMed Central

Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S.; Mayya, Shreemathi S.

2015-01-01

Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were – study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325/490) and interpretation (χ2=25.616, Φ=0.173, p<0.0001), 32.5% (104/320) compared to 17.1% (84/490), though some serious ones were still present. Indian medical research seems to have made no major progress regarding using correct statistical analyses, but error/defects in study designs have decreased significantly. Randomized clinical trials are quite rarely published and have high proportion of methodological problems. PMID:25856194

Research design and statistical methods in Indian medical journals: a retrospective survey.

PubMed

Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S; Mayya, Shreemathi S

2015-01-01

Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were - study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325/490) and interpretation (χ2=25.616, Φ=0.173, p<0.0001), 32.5% (104/320) compared to 17.1% (84/490), though some serious ones were still present. Indian medical research seems to have made no major progress regarding using correct statistical analyses, but error/defects in study designs have decreased significantly. Randomized clinical trials are quite rarely published and have high proportion of methodological problems.

Statistical Literacy in the Data Science Workplace

ERIC Educational Resources Information Center

Grant, Robert

2017-01-01

Statistical literacy, the ability to understand and make use of statistical information including methods, has particular relevance in the age of data science, when complex analyses are undertaken by teams from diverse backgrounds. Not only is it essential to communicate to the consumers of information but also within the team. Writing from the…

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.

Distinct role of the Fas rs1800682 and FasL rs763110 polymorphisms in determining the risk of breast cancer among Han Chinese females.

PubMed

Wang, Meng; Wang, Zheng; Wang, Xi-Jing; Jin, Tian-Bo; Dai, Zhi-Ming; Kang, Hua-Feng; Guan, Hai-Tao; Ma, Xiao-Bin; Liu, Xing-Han; Dai, Zhi-Jun

2016-01-01

In recent years, studies have demonstrated that polymorphisms in the promoters of Fas and FasL are significantly associated with breast cancer risk. However, the results of these studies were inconsistent. This case-control study was performed to explore the associations between Fas rs1800682 and FasL rs763110 polymorphisms and breast cancer. A hospital-based case-control study of 560 Han Chinese females with breast cancer (583 controls) was conducted. The MassARRAY system was used to search for a possible association between the disease risk and the two single nucleotide polymorphisms, Fas rs1800682 and FasL rs763110. Statistical analyses were performed using SNPStats software to conduct Pearson's chi-square tests in five different genetic models. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated after adjustment to age and body mass index. PHASE v2.1 software was used to reconstruct all common haplotypes. A statistically significant association was found between Fas rs1800682 and increased breast cancer risk (AG vs AA: OR =1.37, 95% CI =1.06-1.78; AA+AG vs GG: OR =1.32, 95% CI =1.04-1.66), and also it was found that the FasL rs763110 polymorphism may decrease the risk. Stratified analyses demonstrated that the rs763110 polymorphism was associated with lower breast cancer risk among postmenopausal females (heterozygote model: OR =0.69, 95% CI =0.49-0.97; dominant model: OR =0.70, 95% CI =0.51-0.96). The T allele of rs763110 was also associated with a decreased risk of lymph node metastasis (allele model: OR =0.75, 95% CI =0.57-0.97) and an increased risk of the breast cancer being human epidermal growth factor receptor 2 positive (allele model: OR =1.37, 95% CI =1.03-1.18). Moreover, haplotype analysis showed that Ars1800682Trs763110 was associated to a statistically significant degree with lower risk of breast cancer (OR =0.70, 95% CI =0.53-0.91). These data suggest that the presence of Fas rs1800683 is an important risk factor for breast cancer, whereas FasL rs763110 may exert a protective effect against the onset of breast cancer.

The SPARC Intercomparison of Middle Atmosphere Climatologies

NASA Technical Reports Server (NTRS)

Randel, William; Fleming, Eric; Geller, Marvin; Gelman, Mel; Hamilton, Kevin; Karoly, David; Ortland, Dave; Pawson, Steve; Swinbank, Richard; Udelhofen, Petra

2003-01-01

Our current confidence in 'observed' climatological winds and temperatures in the middle atmosphere (over altitudes approx. 10-80 km) is assessed by detailed intercomparisons of contemporary and historic data sets. These data sets include global meteorological analyses and assimilations, climatologies derived from research satellite measurements, and historical reference atmosphere circulation statistics. We also include comparisons with historical rocketsonde wind and temperature data, and with more recent lidar temperature measurements. The comparisons focus on a few basic circulation statistics, such as temperature, zonal wind, and eddy flux statistics. Special attention is focused on tropical winds and temperatures, where large differences exist among separate analyses. Assimilated data sets provide the most realistic tropical variability, but substantial differences exist among current schemes.

Computer program for prediction of fuel consumption statistical data for an upper stage three-axes stabilized on-off control system

NASA Technical Reports Server (NTRS)

1982-01-01

A FORTRAN coded computer program and method to predict the reaction control fuel consumption statistics for a three axis stabilized rocket vehicle upper stage is described. A Monte Carlo approach is used which is more efficient by using closed form estimates of impulses. The effects of rocket motor thrust misalignment, static unbalance, aerodynamic disturbances, and deviations in trajectory, mass properties and control system characteristics are included. This routine can be applied to many types of on-off reaction controlled vehicles. The pseudorandom number generation and statistical analyses subroutines including the output histograms can be used for other Monte Carlo analyses problems.

Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach.

PubMed

Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H

2017-04-20

Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression analyses, and assessment of associations between HCV clustering and the built environment are needed to expand upon our combined spatial epidemiological and statistical methods.

Implementation and validation of fully relativistic GW calculations: Spin–orbit coupling in molecules, nanocrystals, and solids

DOE PAGES

Scherpelz, Peter; Govoni, Marco; Hamada, Ikutaro; ...

2016-06-22

We present an implementation of G 0W 0 calculations including spin–orbit coupling (SOC) enabling investigations of large systems, with thousands of electrons, and we discuss results for molecules, solids, and nanocrystals. Using a newly developed set of molecules with heavy elements (called GW-SOC81), we find that, when based upon hybrid density functional calculations, fully relativistic (FR) and scalar-relativistic (SR) G 0W 0 calculations of vertical ionization potentials both yield excellent performance compared to experiment, with errors below 1.9%. We demonstrate that while SR calculations have higher random errors, FR calculations systematically underestimate the VIP by 0.1 to 0.2 eV. Wemore » further verify that SOC effects may be well approximated at the FR density functional level and then added to SR G 0W 0 results for a broad class of systems. We also address the use of different root-finding algorithms for the G 0W 0 quasiparticle equation and the significant influence of including d electrons in the valence partition of the pseudopotential for G 0W 0 calculations. Lastly, we present statistical analyses of our data, highlighting the importance of separating definitive improvements from those that may occur by chance due to a limited number of samples. We suggest the statistical analyses used here will be useful in the assessment of the accuracy of a large variety of electronic structure methods« less

Neuroanatomical Characterization of Child Offspring of Bipolar Parents

PubMed Central

Singh, Manpreet K.; DelBello, Melissa P.; Adler, Caleb M.; Stanford, Kevin E.; Strakowski, Stephen M.

2012-01-01

Objectives To examine structural differences in selected anterior limbic brain regions between at-risk children of parents with bipolar I disorder and children with healthy parents. We hypothesized that at-risk children would exhibit abnormalities in brain regions that are involved in mood regulation. Methods Children (8–12 years old) of parents with bipolar I disorder (“at-risk”, AR, N=21) and of parents without any DSM-IV Axis I disorder (health controls, HC, N=24) were evaluated using diagnosticassessments and brain magnetic resonance imaging (MRI). Morphometric analyses were used to examine group differences in the prefrontal cortical, thalamic, striatal, and amygdalar volumes. Results Nine (43%) of the AR children met DSM-IV-TR criteria for a non-bipolar mood disorder at the time of assessment. AR and HC children did not demonstrate statistically significant differences across regions of interest [Wilks Lambda = 0.86, F(4,39)=1.64, p=0.18; effect size, (f)=0.19]. Post-hoc analyses of covariance showed the largest relative effect size was contributed by the prefrontal cortex [(f)=0.26]. Conclusions 8 to 12 year old children with a familial risk for mania do not exhibit any statistically significant volumetric differences in the prefrontal cortex, thalamus, striatum, or amygdala as compared to age matched children of parents without any psychopathology. Longitudinal studies examining whether structural changes over time may be associated with vulnerability for developing subsequent bipolar disorder are needed to clarify the underlying pathophysiology of this disorder. PMID:18356766

Implementation and validation of fully relativistic GW calculations: Spin–orbit coupling in molecules, nanocrystals, and solids

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

Scherpelz, Peter; Govoni, Marco; Hamada, Ikutaro

We present an implementation of G 0W 0 calculations including spin–orbit coupling (SOC) enabling investigations of large systems, with thousands of electrons, and we discuss results for molecules, solids, and nanocrystals. Using a newly developed set of molecules with heavy elements (called GW-SOC81), we find that, when based upon hybrid density functional calculations, fully relativistic (FR) and scalar-relativistic (SR) G 0W 0 calculations of vertical ionization potentials both yield excellent performance compared to experiment, with errors below 1.9%. We demonstrate that while SR calculations have higher random errors, FR calculations systematically underestimate the VIP by 0.1 to 0.2 eV. Wemore » further verify that SOC effects may be well approximated at the FR density functional level and then added to SR G 0W 0 results for a broad class of systems. We also address the use of different root-finding algorithms for the G 0W 0 quasiparticle equation and the significant influence of including d electrons in the valence partition of the pseudopotential for G 0W 0 calculations. Lastly, we present statistical analyses of our data, highlighting the importance of separating definitive improvements from those that may occur by chance due to a limited number of samples. We suggest the statistical analyses used here will be useful in the assessment of the accuracy of a large variety of electronic structure methods« less

SkyGlowNet as a Vehicle for STEM Education

NASA Astrophysics Data System (ADS)

Flurchick, K. M.; Craine, E. R.; Culver, R. B.; Deal, S.; Foster, C.

2013-06-01

SkyGlowNet is an emerging network of internet-enabled sky brightness meters (iSBM) that continuously record and log sky brightness at the zenith of each network node site. Also logged are time and weather information. These data are polled at a user-defined frequency, typically about every 45 seconds. The data are uploaded to the SkyGlowNet website, initially to a proprietary area where the data for each institution are embargoed for one or two semesters as students conduct research projects with their data. When released from embargo, the data are moved to another area where they can be accessed by all SkyGlowNet participants. Some of the data are periodically released to a public area on the website. In this presentation we describe the data formats and provide examples of both data content and the structure of the website. Early data from two nodes in the SkyGlowNet have been characterized, both quantitatively and qualitatively, by undergraduate students at NCAT. A summary of their work is presented here. These analyses are of utility in helping those new to looking at these data to understand how to interpret them. In particular, we demonstrate differences between effects on light at night and sky brightness due to astronomical cycles, atmospheric phenomena, and artificial lighting. Quantitative characterization of the data includes statistical analyses of parsed segments of the temporal data stream. An attempt is made to relate statistical metrics to specific types of phenomena.

Break and trend analysis of EUMETSAT Climate Data Records

NASA Astrophysics Data System (ADS)

Doutriaux-Boucher, Marie; Zeder, Joel; Lattanzio, Alessio; Khlystova, Iryna; Graw, Kathrin

2016-04-01

EUMETSAT reprocessed imagery acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat 8-9. The data covers the period from 2004 to 2012. Climate Data Records (CDRs) of atmospheric parameters such as Atmospheric Motion Vectors (AMV) as well as Clear and All Sky Radiances (CSR and ASR) have been generated. Such CDRs are mainly ingested by ECMWF to produce a reanalysis data. In addition, EUMETSAT produced a long CDR (1982-2004) of land surface albedo exploiting imagery acquired by the Meteosat Visible and Infrared Imager (MVIRI) on board Meteosat 2-7. Such CDR is key information in climate analysis and climate models. Extensive validation has been performed for the surface albedo record and a first validation of the winds and clear sky radiances have been done. All validation results demonstrated that the time series of all parameter appear homogeneous at first sight. Statistical science offers a variety of analyses methods that have been applied to further analyse the homogeneity of the CDRs. Many breakpoint analysis techniques depend on the comparison of two time series which incorporates the issue that both may have breakpoints. This paper will present a quantitative and statistical analysis of eventual breakpoints found in the MVIRI and SEVIRI CDRs that includes attribution of breakpoints to changes of instruments and other events in the data series compared. The value of different methods applied will be discussed with suggestions how to further develop this type of analysis for quality evaluation of CDRs.

Fitness to practise in pharmacy: a study of impairment in professional practice.

PubMed

Mohammad, Annim; Hanrahan, Jane R; Sainsbury, Erica; Chaar, Betty B

2012-04-01

To explore the opinions and knowledge of Australian pharmacists about impairment in the profession, and their awareness of new legislation regarding impairment and mandatory reporting. Pharmacy practice in Australia. Pharmacists' opinions and knowledge were explored using a purposively designed, de-identified survey distributed by an intermediate mailing house to randomly selected pharmacists registered with the Pharmacy Board. Descriptive statistics and thematic analyses were conducted on the data. KEY OUTCOME MEASURES: This being an explorative study, we analysed various items using standard statistical methods and qualitative thematic analysis for responses to open-ended questions. Responses from 370 registered pharmacists were obtained. Of these, nearly 60% were not confident in their knowledge of legislation relating to impairment. The vast majority stated they would consider reporting an impaired colleague in principle, but only after consulting the colleague. Older pharmacists demonstrated increased awareness of new legislation; this was accompanied however, by a marked decrease in confidence regarding knowledge about impairment. Thematic analysis of the qualitative data revealed four main themes: (1) perception of impairment and support systems available (2) stigma related to implications of impairment and whistle-blowing (3) factors affecting reporting of impairment and (4) management of impairment. Australian pharmacists in this study recognised the importance of the issue of impairment, but appeared to lack confidence and/or awareness of legislative requirements regarding impairment in the profession. There is a need for educative programs and accessible, profession-specific rehabilitative programs to be instigated for management of impairment in the profession of pharmacy in Australia.

M-TraCE: a new tool for high-resolution computation and statistical elaboration of backward trajectories on the Italian domain

NASA Astrophysics Data System (ADS)

Vitali, Lina; Righini, Gaia; Piersanti, Antonio; Cremona, Giuseppe; Pace, Giandomenico; Ciancarella, Luisella

2017-12-01

Air backward trajectory calculations are commonly used in a variety of atmospheric analyses, in particular for source attribution evaluation. The accuracy of backward trajectory analysis is mainly determined by the quality and the spatial and temporal resolution of the underlying meteorological data set, especially in the cases of complex terrain. This work describes a new tool for the calculation and the statistical elaboration of backward trajectories. To take advantage of the high-resolution meteorological database of the Italian national air quality model MINNI, a dedicated set of procedures was implemented under the name of M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration) to calculate and process the backward trajectories of air masses reaching a site of interest. Some outcomes from the application of the developed methodology to the Italian Network of Special Purpose Monitoring Stations are shown to assess its strengths for the meteorological characterization of air quality monitoring stations. M-TraCE has demonstrated its capabilities to provide a detailed statistical assessment of transport patterns and region of influence of the site under investigation, which is fundamental for correctly interpreting pollutants measurements and ascertaining the official classification of the monitoring site based on meta-data information. Moreover, M-TraCE has shown its usefulness in supporting other assessments, i.e., spatial representativeness of a monitoring site, focussing specifically on the analysis of the effects due to meteorological variables.

Evaluation of extreme temperature events in northern Spain based on process control charts

NASA Astrophysics Data System (ADS)

Villeta, M.; Valencia, J. L.; Saá, A.; Tarquis, A. M.

2018-02-01

Extreme climate events have recently attracted the attention of a growing number of researchers because these events impose a large cost on agriculture and associated insurance planning. This study focuses on extreme temperature events and proposes a new method for their evaluation based on statistical process control tools, which are unusual in climate studies. A series of minimum and maximum daily temperatures for 12 geographical areas of a Spanish region between 1931 and 2009 were evaluated by applying statistical process control charts to statistically test whether evidence existed for an increase or a decrease of extreme temperature events. Specification limits were determined for each geographical area and used to define four types of extreme anomalies: lower and upper extremes for the minimum and maximum anomalies. A new binomial Markov extended process that considers the autocorrelation between extreme temperature events was generated for each geographical area and extreme anomaly type to establish the attribute control charts for the annual fraction of extreme days and to monitor the occurrence of annual extreme days. This method was used to assess the significance of changes and trends of extreme temperature events in the analysed region. The results demonstrate the effectiveness of an attribute control chart for evaluating extreme temperature events. For example, the evaluation of extreme maximum temperature events using the proposed statistical process control charts was consistent with the evidence of an increase in maximum temperatures during the last decades of the last century.

Associations among selected motor skills and health-related fitness: indirect evidence for Seefeldt's proficiency barrier in young adults?

PubMed

Stodden, David F; True, Larissa K; Langendorfer, Stephen J; Gao, Zan

2013-09-01

This exploratory study examined the notion of Seefeldt's (1980) hypothesized motor skill "proficiency barrier" related to composite levels of health-related physical fitness (HRF) in young adults. A motor skill competence (MSC) index composed of maximum throwing and kicking speed and jumping distance in 187 young adults aged 18 to 25 years old was evaluated against a composite index of 5 health-related fitness (HRF) test scores. MSC (high, moderate, and low) and HRF indexes (good, fair, and poor) were categorized according to normative fitness percentile ranges. 2 separate 3-way chi-square analyses were conducted to determine the probabilities of skill predicting fitness and fitness predicting skill. Most correlations among HRF and MSC variables by gender demonstrated low-to-moderate positive correlations in both men (12/15; r = .23-.58) and women (14/15; r = .21-.53). Chi-square analyses for the total sample, using composite indexes, demonstrated statistically significant predictive models, chi2(1, N = 187) = 66.99, p < .001, Cramer's V = .42. Only 3.1% of low-skilled (2 of 65) individuals were classified as having a "good" HRF. Only 1 participant (out of 65) who demonstrated high MSC was classified as having "poor" HRF (1.5%). Although individual correlations among individual MSC and HRF measures were low to moderate, these data provide indirect evidence for the possibility of a motor skill "proficiency barrier" as indicated by low composite HRF levels. This study may generate future research to address the proficiency barrier hypothesis in youth as well as adults.

Adaptive Evolution and Environmental Durability Jointly Structure Phylodynamic Patterns in Avian Influenza Viruses

PubMed Central

Roche, Benjamin; Drake, John M.; Brown, Justin; Stallknecht, David E.; Bedford, Trevor; Rohani, Pejman

2014-01-01

Avian influenza viruses (AIVs) have been pivotal to the origination of human pandemic strains. Despite their scientific and public health significance, however, there remains much to be understood about the ecology and evolution of AIVs in wild birds, where major pools of genetic diversity are generated and maintained. Here, we present comparative phylodynamic analyses of human and AIVs in North America, demonstrating (i) significantly higher standing genetic diversity and (ii) phylogenetic trees with a weaker signature of immune escape in AIVs than in human viruses. To explain these differences, we performed statistical analyses to quantify the relative contribution of several potential explanations. We found that HA genetic diversity in avian viruses is determined by a combination of factors, predominantly subtype-specific differences in host immune selective pressure and the ecology of transmission (in particular, the durability of subtypes in aquatic environments). Extending this analysis using a computational model demonstrated that virus durability may lead to long-term, indirect chains of transmission that, when coupled with a short host lifespan, can generate and maintain the observed high levels of genetic diversity. Further evidence in support of this novel finding was found by demonstrating an association between subtype-specific environmental durability and predicted phylogenetic signatures: genetic diversity, variation in phylogenetic tree branch lengths, and tree height. The conclusion that environmental transmission plays an important role in the evolutionary biology of avian influenza viruses—a manifestation of the “storage effect”—highlights the potentially unpredictable impact of wildlife reservoirs for future human pandemics and the need for improved understanding of the natural ecology of these viruses. PMID:25116957

The Thurgood Marshall School of Law Empirical Findings: A Report of the Statistical Analysis of the July 2010 TMSL Texas Bar Results

ERIC Educational Resources Information Center

Kadhi, Tau; Holley, D.

2010-01-01

The following report gives the statistical findings of the July 2010 TMSL Bar results. Procedures: Data is pre-existing and was given to the Evaluator by email from the Registrar and Dean. Statistical analyses were run using SPSS 17 to address the following research questions: 1. What are the statistical descriptors of the July 2010 overall TMSL…

A Monte Carlo Analysis of the Thrust Imbalance for the RSRMV Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle

A Monte Carlo Analysis of the Thrust Imbalance for the Space Launch System Booster During Both the Ignition Transient and Steady State Operation

NASA Technical Reports Server (NTRS)

Foster, Winfred A., Jr.; Crowder, Winston; Steadman, Todd E.

2014-01-01

This paper presents the results of statistical analyses performed to predict the thrust imbalance between two solid rocket motor boosters to be used on the Space Launch System (SLS) vehicle. Two legacy internal ballistics codes developed for the Space Shuttle program were coupled with a Monte Carlo analysis code to determine a thrust imbalance envelope for the SLS vehicle based on the performance of 1000 motor pairs. Thirty three variables which could impact the performance of the motors during the ignition transient and thirty eight variables which could impact the performance of the motors during steady state operation of the motor were identified and treated as statistical variables for the analyses. The effects of motor to motor variation as well as variations between motors of a single pair were included in the analyses. The statistical variations of the variables were defined based on data provided by NASA's Marshall Space Flight Center for the upgraded five segment booster and from the Space Shuttle booster when appropriate. The results obtained for the statistical envelope are compared with the design specification thrust imbalance limits for the SLS launch vehicle.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

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

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

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

Boggess, A.

Existing models and simulants of tank disposition media at SRS have presumed the presence of high concentrations of inorganic mercury. However, recent quarterly tank analyses show that mercury is present as organomercurial species at concentrations that may present challenges to remediation and disposition and may exceed the Saltstone Waste Acceptance Criteria (WAC). To-date, methylmercury analysis for Savannah River Remediation (SRR) has been performed off-site by Eurofins Scientific (Lancaster, PA). A series of optimization and validation experiments has been performed at SRNL, which has resulted in the development of on-site organomercury speciation capabilities using purge and trap gas chromatography coupled withmore » thermal desorption cold vapor atomic fluorescence spectroscopy (P&T GC/CVAFS). Speciation has been achieved for methylmercury, with a method reporting limit (MRL) values of 1.42 pg for methylmercury. Results obtained by SRNL from the analysis of past quarterly samples from tanks 21, 40, and 50 have demonstrated statistically indistinguishable concentration values compared with the concentration data obtained from Eurofins, while the data from SRNL has demonstrated significantly improved precision and processing time.« less

Maximising resource allocation in the teaching laboratory: understanding student evaluations of teaching assistants in a team-based teaching format

NASA Astrophysics Data System (ADS)

Nikolic, Sasha; Suesse, Thomas F.; McCarthy, Timothy J.; Goldfinch, Thomas L.

2017-11-01

Minimal research papers have investigated the use of student evaluations on the laboratory, a learning medium usually run by teaching assistants with little control of the content, delivery and equipment. Finding the right mix of teaching assistants for the laboratory can be an onerous task due to the many skills required including theoretical and practical know-how, troubleshooting, safety and class management. Using larger classes with multiple teaching assistants, a team-based teaching (TBT) format may be advantageous. A rigorous three-year study across twenty-five courses over repetitive laboratory classes is analysed using a multi-level statistical model considering students, laboratory classes and courses. The study is used to investigate the effectiveness of the TBT format, and quantify the influence each demonstrator has on the laboratory experience. The study found that TBT is effective and the lead demonstrator most influential, influencing up to 55% of the laboratory experience evaluation.

Distributional Analysis in Educational Evaluation: A Case Study from the New York City Voucher Program

PubMed Central

Domina, Thurston; Penner, Emily; Hoynes, Hilary

2014-01-01

We use quantile treatment effects estimation to examine the consequences of the random-assignment New York City School Choice Scholarship Program (NYCSCSP) across the distribution of student achievement. Our analyses suggest that the program had negligible and statistically insignificant effects across the skill distribution. In addition to contributing to the literature on school choice, the paper illustrates several ways in which distributional effects estimation can enrich educational research: First, we demonstrate that moving beyond a focus on mean effects estimation makes it possible to generate and test new hypotheses about the heterogeneity of educational treatment effects that speak to the justification for many interventions. Second, we demonstrate that distributional effects can uncover issues even with well-studied datasets by forcing analysts to view their data in new ways. Finally, such estimates highlight where in the overall national achievement distribution test scores of children exposed to particular interventions lie; this is important for exploring the external validity of the intervention’s effects. PMID:26207158

Agnotology: learning from mistakes

NASA Astrophysics Data System (ADS)

Benestad, R. E.; Hygen, H. O.; van Dorland, R.; Cook, J.; Nuccitelli, D.

2013-05-01

Replication is an important part of science, and by repeating past analyses, we show that a number of papers in the scientific literature contain severe methodological flaws which can easily be identified through simple tests and demonstrations. In many cases, shortcomings are related to a lack of robustness, leading to results that are not universally valid but rather an artifact of a particular experimental set-up. Some examples presented here have ignored data that do not fit the conclusions, and in several other cases, inappropriate statistical methods have been adopted or conclusions have been based on misconceived physics. These papers may serve as educational case studies for why certain analytical approaches sometimes are unsuitable in providing reliable answers. They also highlight the merit of replication. A lack of common replication has repercussions for the quality of the scientific literature, and may be a reason why some controversial questions remain unanswered even when ignorance could be reduced. Agnotology is the study of such ignorance. A free and open-source software is provided for demonstration purposes.

Additive Interaction between Heterogeneous Environmental Quality Domains (Air, Water, Land, Sociodemographic, and Built Environment) on Preterm Birth.

PubMed

Grabich, Shannon C; Rappazzo, Kristen M; Gray, Christine L; Jagai, Jyotsna S; Jian, Yun; Messer, Lynne C; Lobdell, Danelle T

2016-01-01

Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000 to 2005. The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built, and sociodemographic) using principal component analyses. County-level preterm birth rates ( n  = 3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PDs) and 95% confidence intervals (CIs) comparing worse environmental quality to the better quality for each model for (a) each individual domain main effect, (b) the interaction contrast, and (c) the two main effects plus interaction effect (i.e., the "net effect") to show departure from additivity for the all U.S. counties. Analyses were also performed for subgroupings by four urban/rural strata. We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interactions, between the sociodemographic/air domains [net effect (i.e., the association, including main effects and interaction effects) PD: -0.004 (95% CI: -0.007, 0.000), interaction contrast: -0.013 (95% CI: -0.020, -0.007)] and built/air domains [net effect PD: 0.008 (95% CI 0.004, 0.011), interaction contrast: -0.008 (95% CI: -0.015, -0.002)]. Most interactions were between the air domain and other respective domains. Interactions differed by urbanicity, with more interactions observed in non-metropolitan regions. Observed antagonistic associations may indicate that those living in areas with multiple detrimental domains may have other interfering factors reducing the burden of environmental exposure. This study is the first to explore interactions across different environmental domains and demonstrates the utility of the EQI to examine the relationship between environmental domain interactions and human health. While we did observe some departures from additivity, many observed effects were additive. This study demonstrated that interactions between environmental domains should be considered in future analyses.

The GODAE High Resolution Sea Surface Temperature Pilot Project (GHRSST-PP)

NASA Astrophysics Data System (ADS)

Donlon, C.; Ghrsst-Pp Science Team

2003-04-01

This paper summarises Development and Implementation Plan of the GODAE High Resolution Sea Surface Temperature Pilot Project (GHRSST-PP). The aim of the GHRSST-PP is to coordinate a new generation of global, multi-sensor, high-resolution (better than 10 km and 12 hours) SST products for the benefit of the operational and scientific community and for those with a potential interest in the products of GODAE. The GHRSST-PP project will deliver a demonstration system that integrates data from existing international satellite and in situ data sources using state-of-the-art communications and analysis tools. Primary GHRSST-PP products will be generated by fusing infrared and microwave satellite data obtained from sensors in near polar, geostationary and low earth orbits, constrained by in situ observations. Surface skin SST, sub-surface SST and SST at depth will be produced as both merged and analysed data products. Merged data products have a common grid but all input data retaining their error statistics whereas analysed data products use all data to derive a best estimate data source having one set of error statistics. Merged SST fields will not be interpolated thereby preserving the integrity of the source data as much as possible. Products will be first produced and validated using in situ observations for regional areas by regional data assembly centres (RDAC) and sent to a global data analysis centre (GDAC) for integration with other data to provide global coverage. GDAC and RDAC will be connected together with other data using a virtual dynamic distributed database (DDD). The GDAC will merge and analyse RDAC data together with other data (from the GTS and space agencies) to provide global coverage every 12 hours in real time. In all cases data products will be accurate to better than 0.5 K validated using data collected at globally distributed diagnostic data set (DDS) sites. A user information service (UIS) will work together with user applications and services (AUS) to ensure that the GHRSST-PP is able to respond appropriately to user demands. In addition, the GDAC will provide product validation and dissemination services as well as the means for researchers to test and use the In situ and Satellite Data Integration Processing Model (ISDI-PM) operational demonstration code using a large supercomputer.

Evidence for the Selective Reporting of Analyses and Discrepancies in Clinical Trials: A Systematic Review of Cohort Studies of Clinical Trials

PubMed Central

Dwan, Kerry; Altman, Douglas G.; Clarke, Mike; Gamble, Carrol; Higgins, Julian P. T.; Sterne, Jonathan A. C.; Williamson, Paula R.; Kirkham, Jamie J.

2014-01-01

Background Most publications about selective reporting in clinical trials have focussed on outcomes. However, selective reporting of analyses for a given outcome may also affect the validity of findings. If analyses are selected on the basis of the results, reporting bias may occur. The aims of this study were to review and summarise the evidence from empirical cohort studies that assessed discrepant or selective reporting of analyses in randomised controlled trials (RCTs). Methods and Findings A systematic review was conducted and included cohort studies that assessed any aspect of the reporting of analyses of RCTs by comparing different trial documents, e.g., protocol compared to trial report, or different sections within a trial publication. The Cochrane Methodology Register, Medline (Ovid), PsycInfo (Ovid), and PubMed were searched on 5 February 2014. Two authors independently selected studies, performed data extraction, and assessed the methodological quality of the eligible studies. Twenty-two studies (containing 3,140 RCTs) published between 2000 and 2013 were included. Twenty-two studies reported on discrepancies between information given in different sources. Discrepancies were found in statistical analyses (eight studies), composite outcomes (one study), the handling of missing data (three studies), unadjusted versus adjusted analyses (three studies), handling of continuous data (three studies), and subgroup analyses (12 studies). Discrepancy rates varied, ranging from 7% (3/42) to 88% (7/8) in statistical analyses, 46% (36/79) to 82% (23/28) in adjusted versus unadjusted analyses, and 61% (11/18) to 100% (25/25) in subgroup analyses. This review is limited in that none of the included studies investigated the evidence for bias resulting from selective reporting of analyses. It was not possible to combine studies to provide overall summary estimates, and so the results of studies are discussed narratively. Conclusions Discrepancies in analyses between publications and other study documentation were common, but reasons for these discrepancies were not discussed in the trial reports. To ensure transparency, protocols and statistical analysis plans need to be published, and investigators should adhere to these or explain discrepancies. Please see later in the article for the Editors' Summary PMID:24959719

Fine-structural changes in the midgut of old Drosophila melanogaster

NASA Technical Reports Server (NTRS)

Anton-Erxleben, F.; Miquel, J.; Philpott, D. E.

1983-01-01

Senescent fine-structural changes in the midgut of Drosophila melanogaster are investigated. A large number of midgut mitochondria in old flies exhibit nodular cristae and a tubular system located perpendicular to the normal cristae orientation. Anterior intestinal cells show a senescent accumulation of age pigment, either with a surrounding two-unit membrane or without any membrane. The predominant localization of enlarged mitochondria and pigment in the luminal gut region may be related to the polarized metabolism of the intestinal cells. Findings concur with previous observations of dense-body accumulations and support the theory that mitochondria are involved in the aging of fixed post-mitotic cells. Demonstrated by statistical analyses is that mitochondrial size increase is related to mitochondrial variation increase.

Heterogeneous Risk Perceptions: The Case of Poultry Meat Purchase Intentions in Finland

PubMed Central

Heikkilä, Jaakko; Pouta, Eija; Forsman-Hugg, Sari; Mäkelä, Johanna

2013-01-01

This study focused on the heterogeneity of consumer reactions, measured through poultry meat purchase intentions, when facing three cases of risk. The heterogeneity was analysed by latent class logistic regression that included all three risk cases. Approximately 60% of the respondents belonged to the group of production risk avoiders, in which the intention to purchase risk food was significantly lower than in the second group of risk neutrals. In addition to socio-demographic variables, the purchase intentions were statistically associated with several attitude-based variables. We highlighted some policy implications of the heterogeneity. Overall, the study demonstrated that risk matters to consumers, not all risk is equal, and consumer types react somewhat differently to different types of risk. PMID:24157513

Nodal domains of a non-separable problem—the right-angled isosceles triangle

NASA Astrophysics Data System (ADS)

Aronovitch, Amit; Band, Ram; Fajman, David; Gnutzmann, Sven

2012-03-01

We study the nodal set of eigenfunctions of the Laplace operator on the right-angled isosceles triangle. A local analysis of the nodal pattern provides an algorithm for computing the number νn of nodal domains for any eigenfunction. In addition, an exact recursive formula for the number of nodal domains is found to reproduce all existing data. Eventually, we use the recursion formula to analyse a large sequence of nodal counts statistically. Our analysis shows that the distribution of nodal counts for this triangular shape has a much richer structure than the known cases of regular separable shapes or completely irregular shapes. Furthermore, we demonstrate that the nodal count sequence contains information about the periodic orbits of the corresponding classical ray dynamics.

Design solutions for the solar cell interconnect fatigue fracture problem

NASA Technical Reports Server (NTRS)

Mon, G. R.; Ross, R. G., Jr.

1982-01-01

Mechanical fatigue of solar cell interconnects is a major failure mechanism in photovoltaic arrays. A comprehensive approach to the reliability design of interconnects, together with extensive design data for the fatigue properties of copper interconnects, has been published. This paper extends the previous work, developing failure prediction (fatigue) data for additional interconnect material choices, including aluminum and a variety of copper-Invar and copper-steel claddings. An improved global fatigue function is used to model the probability-of-failure statistics of each material as a function of level and number of cycles of applied strain. Life-cycle economic analyses are used to evaluate the relative merits of each material choce. The copper-Invar clad composites demonstrate superior performance over pure copper. Aluminum results are disappointing.

Phenomenological characteristics, social problems, and the economic impact associated with chronic skin picking.

PubMed

Flessner, Christopher A; Woods, Douglas W

2006-11-01

In this study, the authors collected data on the demographic characteristics, phenomenology, and social and economic impact of skin picking. A total of 92 participants completed an anonymous, Internet-based survey through a link to the Trichotillomania Learning Center's home page. Results indicated that skin pickers experienced social, occupational, and academic impairment, a number of medical or mental health concerns, and financial burdens, which they attributed to skin picking. Results also revealed moderate, statistically significant relationships between skin picking severity and symptoms of depression, anxiety, and experiential avoidance. Subsequent mediational analyses demonstrated that the relationship between skin picking severity and symptoms of anxiety and depression was partially mediated by experiential avoidance. Implications, conclusions, and future areas of research are discussed.

Gender differences in children's problem behaviours in competitive play with friends.

PubMed

Ensor, Rosie; Hart, Martha; Jacobs, Lorna; Hughes, Claire

2011-06-01

Disruptive behaviour disorders are much more common in boys than girls (Office of National Statistics, 1999); in contrast, gender differences in normative problem behaviours are poorly understood. To address this issue, 228 6-year-olds (134 boys, 94 girls) were each observed playing a board game with a same-gender friend. Ratings of aggression, disruption, arousal and negativity were used to index problem behaviours. Multiple-groups confirmatory factor analyses demonstrated that the latent factor had the same metric for boys and girls, but a mean that was approximately half a standard deviation higher for boys than girls. In addition, the association between the latent factor and teachers' ratings of total difficulties was significantly stronger for boys than girls.

Methods to achieve accurate projection of regional and global raster databases

USGS Publications Warehouse

Usery, E. Lynn; Seong, Jeong Chang; Steinwand, Dan

2002-01-01

Modeling regional and global activities of climatic and human-induced change requires accurate geographic data from which we can develop mathematical and statistical tabulations of attributes and properties of the environment. Many of these models depend on data formatted as raster cells or matrices of pixel values. Recently, it has been demonstrated that regional and global raster datasets are subject to significant error from mathematical projection and that these errors are of such magnitude that model results may be jeopardized (Steinwand, et al., 1995; Yang, et al., 1996; Usery and Seong, 2001; Seong and Usery, 2001). There is a need to develop methods of projection that maintain the accuracy of these datasets to support regional and global analyses and modeling

Principal component analysis of the cytokine and chemokine response to human traumatic brain injury.

PubMed

Helmy, Adel; Antoniades, Chrystalina A; Guilfoyle, Mathew R; Carpenter, Keri L H; Hutchinson, Peter J

2012-01-01

There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of Traumatic Brain Injury (TBI). This has led to the search for biomarkers that reflect these underlying inflammatory processes using techniques such as cerebral microdialysis. The interpretation of such biomarker data has been limited by the statistical methods used. When analysing data of this sort the multiple putative interactions between mediators need to be considered as well as the timing of production and high degree of statistical co-variance in levels of these mediators. Here we present a cytokine and chemokine dataset from human brain following human traumatic brain injury and use principal component analysis and partial least squares discriminant analysis to demonstrate the pattern of production following TBI, distinct phases of the humoral inflammatory response and the differing patterns of response in brain and in peripheral blood. This technique has the added advantage of making no assumptions about the Relative Recovery (RR) of microdialysis derived parameters. Taken together these techniques can be used in complex microdialysis datasets to summarise the data succinctly and generate hypotheses for future study.

A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

PubMed

Armour, Cherie; Műllerová, Jana; Elhai, Jon D

2016-03-01

The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.

The exposure-crossover design is a new method for studying sustained changes in recurrent events.

PubMed

Redelmeier, Donald A

2013-09-01

To introduce a new design that explores how an acute exposure might lead to a sustained change in the risk of a recurrent outcome. The exposure-crossover design uses self-matching to control within-person confounding due to genetics, personality, and all other stable patient characteristics. The design is demonstrated using population-based individual-level health data from Ontario, Canada, for three separate medical conditions (n > 100,000 for each) related to the risk of a motor vehicle crash (total outcomes, >2,000 for each). The exposure-crossover design yields numerical risk estimates during the baseline interval before an intervention, the induction interval immediately ahead of the intervention, and the subsequent interval after the intervention. Accompanying graphs summarize results, provide an intuitive display to readers, and show risk comparisons (absolute and relative). Self-matching increases statistical efficiency, reduces selection bias, and yields quantitative analyses. The design has potential limitations related to confounding, artifacts, pragmatics, survivor bias, statistical models, potential misunderstandings, and serendipity. The exposure-crossover design may help in exploring selected questions in epidemiology science. Copyright © 2013 Elsevier Inc. All rights reserved.

Temperature rise, sea level rise and increased radiative forcing - an application of cointegration methods

NASA Astrophysics Data System (ADS)

Schmith, Torben; Thejll, Peter; Johansen, Søren

2016-04-01

We analyse the statistical relationship between changes in global temperature, global steric sea level and radiative forcing in order to reveal causal relationships. There are in this, however, potential pitfalls due to the trending nature of the time series. We therefore apply a statistical method called cointegration analysis, originating from the field of econometrics, which is able to correctly handle the analysis of series with trends and other long-range dependencies. Further, we find a relationship between steric sea level and temperature and find that temperature causally depends on the steric sea level, which can be understood as a consequence of the large heat capacity of the ocean. This result is obtained both when analyzing observed data and data from a CMIP5 historical model run. Finally, we find that in the data from the historical run, the steric sea level, in turn, is driven by the external forcing. Finally, we demonstrate that combining these two results can lead to a novel estimate of radiative forcing back in time based on observations.

Errors in reporting on dissolution research: methodological and statistical implications.

PubMed

Jasińska-Stroschein, Magdalena; Kurczewska, Urszula; Orszulak-Michalak, Daria

2017-02-01

In vitro dissolution testing provides useful information at clinical and preclinical stages of the drug development process. The study includes pharmaceutical papers on dissolution research published in Polish journals between 2010 and 2015. They were analyzed with regard to information provided by authors about chosen methods, performed validation, statistical reporting or assumptions used to properly compare release profiles considering the present guideline documents addressed to dissolution methodology and its validation. Of all the papers included in the study, 23.86% presented at least one set of validation parameters, 63.64% gave the results of the weight uniformity test, 55.68% content determination, 97.73% dissolution testing conditions, and 50% discussed a comparison of release profiles. The assumptions for methods used to compare dissolution profiles were discussed in 6.82% of papers. By means of example analyses, we demonstrate that the outcome can be influenced by the violation of several assumptions or selection of an improper method to compare dissolution profiles. A clearer description of the procedures would undoubtedly increase the quality of papers in this area.

Bayesian correction for covariate measurement error: A frequentist evaluation and comparison with regression calibration.

PubMed

Bartlett, Jonathan W; Keogh, Ruth H

2018-06-01

Bayesian approaches for handling covariate measurement error are well established and yet arguably are still relatively little used by researchers. For some this is likely due to unfamiliarity or disagreement with the Bayesian inferential paradigm. For others a contributory factor is the inability of standard statistical packages to perform such Bayesian analyses. In this paper, we first give an overview of the Bayesian approach to handling covariate measurement error, and contrast it with regression calibration, arguably the most commonly adopted approach. We then argue why the Bayesian approach has a number of statistical advantages compared to regression calibration and demonstrate that implementing the Bayesian approach is usually quite feasible for the analyst. Next, we describe the closely related maximum likelihood and multiple imputation approaches and explain why we believe the Bayesian approach to generally be preferable. We then empirically compare the frequentist properties of regression calibration and the Bayesian approach through simulation studies. The flexibility of the Bayesian approach to handle both measurement error and missing data is then illustrated through an analysis of data from the Third National Health and Nutrition Examination Survey.

More data, less information? Potential for nonmonotonic information growth using GEE.

PubMed

Shoben, Abigail B; Rudser, Kyle D; Emerson, Scott S

2017-01-01

Statistical intuition suggests that increasing the total number of observations available for analysis should increase the precision with which parameters can be estimated. Such monotonic growth of statistical information is of particular importance when data are analyzed sequentially, such as in confirmatory clinical trials. However, monotonic information growth is not always guaranteed, even when using a valid, but inefficient estimator. In this article, we demonstrate the theoretical possibility of nonmonotonic information growth when using generalized estimating equations (GEE) to estimate a slope and provide intuition for why this possibility exists. We use theoretical and simulation-based results to characterize situations that may result in nonmonotonic information growth. Nonmonotonic information growth is most likely to occur when (1) accrual is fast relative to follow-up on each individual, (2) correlation among measurements from the same individual is high, and (3) measurements are becoming more variable further from randomization. In situations that may lead to nonmonotonic information growth, study designers should plan interim analyses to avoid situations most likely to result in nonmonotonic information growth.

Dietary fat intake and risk of epithelial ovarian cancer: a meta-analysis of 6,689 subjects from 8 observational studies.

PubMed

Huncharek, M; Kupelnick, B

2001-01-01

The etiology of epithelial ovarian cancer is unknown. Prior work suggests that high dietary fat intake is associated with an increased risk of this tumor, although this association remains speculative. A meta-analysis was performed to evaluate this suspected relationship. Using previously described methods, a protocol was developed for a meta-analysis examining the association between high vs. low dietary fat intake and the risk of epithelial ovarian cancer. Literature search techniques, study inclusion criteria, and statistical procedures were prospectively defined. Data from observational studies were pooled using a general variance-based meta-analytic method employing confidence intervals (CI) previously described by Greenland. The outcome of interest was a summary relative risk (RRs) reflecting the risk of ovarian cancer associated with high vs. low dietary fat intake. Sensitivity analyses were performed when necessary to evaluate any observed statistical heterogeneity. The literature search yielded 8 observational studies enrolling 6,689 subjects. Data were stratified into three dietary fat intake categories: total fat, animal fat, and saturated fat. Initial tests for statistical homogeneity demonstrated that hospital-based studies accounted for observed heterogeneity possibly because of selection bias. Accounting for this, an RRs was calculated for high vs. low total fat intake, yielding a value of 1.24 (95% CI = 1.07-1.43), a statistically significant result. That is, high total fat intake is associated with a 24% increased risk of ovarian cancer development. The RRs for high saturated fat intake was 1.20 (95% CI = 1.04-1.39), suggesting a 20% increased risk of ovarian cancer among subjects with these dietary habits. High vs. low animal fat diet gave an RRs of 1.70 (95% CI = 1.43-2.03), consistent with a statistically significant 70% increased ovarian cancer risk. High dietary fat intake appears to represent a significant risk factor for the development of ovarian cancer. The magnitude of this risk associated with total fat and saturated fat is rather modest. Ovarian cancer risk associated with high animal fat intake appears significantly greater than that associated with the other types of fat intake studied, although this requires confirmation via larger analyses. Further work is needed to clarify factors that may modify the effects of dietary fat in vivo.

Testing for effects of climate change on competitive relationships and coexistence between two bird species.

PubMed

Stenseth, Nils Chr; Durant, Joël M; Fowler, Mike S; Matthysen, Erik; Adriaensen, Frank; Jonzén, Niclas; Chan, Kung-Sik; Liu, Hai; De Laet, Jenny; Sheldon, Ben C; Visser, Marcel E; Dhondt, André A

2015-05-22

Climate change is expected to have profound ecological effects, yet shifts in competitive abilities among species are rarely studied in this context. Blue tits (Cyanistes caeruleus) and great tits (Parus major) compete for food and roosting sites, yet coexist across much of their range. Climate change might thus change the competitive relationships and coexistence between these two species. Analysing four of the highest-quality, long-term datasets available on these species across Europe, we extend the textbook example of coexistence between competing species to include the dynamic effects of long-term climate variation. Using threshold time-series statistical modelling, we demonstrate that long-term climate variation affects species demography through different influences on density-dependent and density-independent processes. The competitive interaction between blue tits and great tits has shifted in one of the studied sites, creating conditions that alter the relative equilibrium densities between the two species, potentially disrupting long-term coexistence. Our analyses show that long-term climate change can, but does not always, generate local differences in the equilibrium conditions of spatially structured species assemblages. We demonstrate how long-term data can be used to better understand whether (and how), for instance, climate change might change the relationships between coexisting species. However, the studied populations are rather robust against competitive exclusion. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Neuropsychiatry and White Matter Microstructure in Huntington's Disease.

PubMed

Gregory, Sarah; Scahill, Rachael I; Seunarine, Kiran K; Stopford, Cheryl; Zhang, Hui; Zhang, Jiaying; Orth, Michael; Durr, Alexandra; Roos, Raymund A C; Langbehn, Douglas R; Long, Jeffrey D; Johnson, Hans; Rees, Geraint; Tabrizi, Sarah J; Craufurd, David

2015-01-01

Neuropsychiatric symptoms in Huntington's disease (HD) are often evident prior to clinical diagnosis. Apathy is highly correlated with disease progression, while depression and irritability occur at different stages of the disease, both before and after clinical onset. Little is understood about the neural bases of these neuropsychiatric symptoms and to what extent those neural bases are analogous to neuropsychiatric disorders in the general population. We used Diffusion Tensor Imaging (DTI) to investigate structural connectivity between brain regions and any putative microstructural changes associated with depression, apathy and irritability in HD. DTI data were collected from 39 premanifest and 45 early-HD participants in the Track-HD study and analysed using whole-brain Tract-Based Spatial Statistics. We used regression analyses to identify white matter tracts whose structural integrity (as measured by fractional anisotropy, FA) was correlated with HADS-depression, PBA-apathy or PBA-irritability scores in gene-carriers and related to cumulative probability to onset (CPO). For those with the highest CPO, we found significant correlations between depression scores and reduced FA in the splenium of the corpus callosum. In contrast, those with lowest CPO demonstrated significant correlations between irritability scores and widespread FA reductions. There was no significant relationship between apathy and FA throughout the whole brain. We demonstrate that white matter changes associated with both depression and irritability in HD occur at different stages of disease progression concomitant with their clinical presentation.

Microlensing for extrasolar planets : improving the photometry

NASA Astrophysics Data System (ADS)

Bajek, David J.

2013-08-01

Gravitational Microlensing, as a technique for detecting Extrasolar Planets, is recognised for its potential in discovering small-mass planets similar to Earth, at a distance of a few Astronomical Units from their host stars. However, analysing the data from microlensing events (which statistically rarely reveal planets) is complex and requires continued and intensive use of various networks of telescopes working together in order to observe the phenomenon. As such the techniques are constantly being developed and refined; this project outlines some steps of the careful analysis required to model an event and ensure the best quality data is used in the fitting. A quantitative investigation into increasing the quality of the original photometric data available from any microlensing event demonstrates that 'lucky imaging' can lead to a marked improvement in the signal to noise ratio of images over standard imaging techniques, which could result in more accurate models and thus the calculation of more accurate planetary parameters. In addition, a simulation illustrating the effects of atmospheric turbulence on exposures was created, and expanded upon to give an approximation of the lucky imaging technique. This further demonstrated the advantages of lucky images which are shown to potentially approach the quality of those expected from diffraction limited photometry. The simulation may be further developed for potential future use as a 'theoretical lucky imager' in our research group, capable of producing and analysing synthetic exposures through customisable conditions.

Optical eigenmodes for illumination & imaging

NASA Astrophysics Data System (ADS)

Kosmeier, Sebastian

Gravitational Microlensing, as a technique for detecting Extrasolar Planets, is recognised for its potential in discovering small-mass planets similar to Earth, at a distance of a few Astronomical Units from their host stars. However, analysing the data from microlensing events (which statistically rarely reveal planets) is complex and requires continued and intensive use of various networks of telescopes working together in order to observe the phenomenon. As such the techniques are constantly being developed and refined; this project outlines some steps of the careful analysis required to model an event and ensure the best quality data is used in the fitting. A quantitative investigation into increasing the quality of the original photometric data available from any microlensing event demonstrates that 'lucky imaging' can lead to a marked improvement in the signal to noise ratio of images over standard imaging techniques, which could result in more accurate models and thus the calculation of more accurate planetary parameters. In addition, a simulation illustrating the effects of atmospheric turbulence on exposures was created, and expanded upon to give an approximation of the lucky imaging technique. This further demonstrated the advantages of lucky images which are shown to potentially approach the quality of those expected from diffraction limited photometry. The simulation may be further developed for potential future use as a 'theoretical lucky imager' in our research group, capable of producing and analysing synthetic exposures through customisable conditions.

Impact of Exposure to Childhood Maltreatment on Transitions to Alcohol Dependence in Women and Men.

PubMed

Oberleitner, Lindsay M S; Smith, Philip H; Weinberger, Andrea H; Mazure, Carolyn M; McKee, Sherry A

2015-11-01

Childhood maltreatment decreases age of first use and speeds the transition from first use to dependence (i.e., telescoping) for alcohol use, however, it is currently unknown whether this influence is the same for men and women. Analyses were conducted with the National Epidemiologic Survey on Alcohol and Related Conditions (n = 34,653). Outcome variables included age of alcohol initiation and time to onset of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition alcohol dependence. Predictor variables included gender and childhood maltreatment. Linear and Poisson regression analyses were conducted. Results demonstrated that in regard to age of drinking initiation, individuals who experienced childhood maltreatment initiated 1 year earlier than those without maltreatment, however, there was no interaction of this relationship with gender. Regarding the time to dependence, it was found that women who experienced childhood maltreatment demonstrated telescoping (shorter time between onset and dependence) compared to women without maltreatment and men (both with and without maltreatment). Women with a history of childhood maltreatment are particularly vulnerable to an accelerated time from initiation of alcohol use until dependence, a pattern indicative of increased negative alcohol-related outcomes. Findings highlight the need for development of gender-specific prevention efforts and behavioral treatments to aid in early intervention of problematic alcohol use in women. © The Author(s) 2015.

WISARD: workbench for integrated superfast association studies for related datasets.

PubMed

Lee, Sungyoung; Choi, Sungkyoung; Qiao, Dandi; Cho, Michael; Silverman, Edwin K; Park, Taesung; Won, Sungho

2018-04-20

A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies-from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value.