Statistical significance test for transition matrices of atmospheric Markov chains

NASA Technical Reports Server (NTRS)

Vautard, Robert; Mo, Kingtse C.; Ghil, Michael

1990-01-01

Low-frequency variability of large-scale atmospheric dynamics can be represented schematically by a Markov chain of multiple flow regimes. This Markov chain contains useful information for the long-range forecaster, provided that the statistical significance of the associated transition matrix can be reliably tested. Monte Carlo simulation yields a very reliable significance test for the elements of this matrix. The results of this test agree with previously used empirical formulae when each cluster of maps identified as a distinct flow regime is sufficiently large and when they all contain a comparable number of maps. Monte Carlo simulation provides a more reliable way to test the statistical significance of transitions to and from small clusters. It can determine the most likely transitions, as well as the most unlikely ones, with a prescribed level of statistical significance.

Advances in Testing the Statistical Significance of Mediation Effects

ERIC Educational Resources Information Center

Mallinckrodt, Brent; Abraham, W. Todd; Wei, Meifen; Russell, Daniel W.

2006-01-01

P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…

Assessment of statistical significance and clinical relevance.

PubMed

Kieser, Meinhard; Friede, Tim; Gondan, Matthias

2013-05-10

In drug development, it is well accepted that a successful study will demonstrate not only a statistically significant result but also a clinically relevant effect size. Whereas standard hypothesis tests are used to demonstrate the former, it is less clear how the latter should be established. In the first part of this paper, we consider the responder analysis approach and study the performance of locally optimal rank tests when the outcome distribution is a mixture of responder and non-responder distributions. We find that these tests are quite sensitive to their planning assumptions and have therefore not really any advantage over standard tests such as the t-test and the Wilcoxon-Mann-Whitney test, which perform overall well and can be recommended for applications. In the second part, we present a new approach to the assessment of clinical relevance based on the so-called relative effect (or probabilistic index) and derive appropriate sample size formulae for the design of studies aiming at demonstrating both a statistically significant and clinically relevant effect. Referring to recent studies in multiple sclerosis, we discuss potential issues in the application of this approach. Copyright © 2012 John Wiley & Sons, Ltd.

Increasing the statistical significance of entanglement detection in experiments.

PubMed

Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Estimation of the geochemical threshold and its statistical significance

USGS Publications Warehouse

Miesch, A.T.

1981-01-01

A statistic is proposed for estimating the geochemical threshold and its statistical significance, or it may be used to identify a group of extreme values that can be tested for significance by other means. The statistic is the maximum gap between adjacent values in an ordered array after each gap has been adjusted for the expected frequency. The values in the ordered array are geochemical values transformed by either ln(?? - ??) or ln(?? - ??) and then standardized so that the mean is zero and the variance is unity. The expected frequency is taken from a fitted normal curve with unit area. The midpoint of an adjusted gap that exceeds the corresponding critical value may be taken as an estimate of the geochemical threshold, and the associated probability indicates the likelihood that the threshold separates two geochemical populations. The adjusted gap test may fail to identify threshold values if the variation tends to be continuous from background values to the higher values that reflect mineralized ground. However, the test will serve to identify other anomalies that may be too subtle to have been noted by other means. ?? 1981.

Decadal power in land air temperatures: Is it statistically significant?

NASA Astrophysics Data System (ADS)

Thejll, Peter A.

2001-12-01

The geographical distribution and properties of the well-known 10-11 year signal in terrestrial temperature records is investigated. By analyzing the Global Historical Climate Network data for surface air temperatures we verify that the signal is strongest in North America and is similar in nature to that reported earlier by R. G. Currie. The decadal signal is statistically significant for individual stations, but it is not possible to show that the signal is statistically significant globally, using strict tests. In North America, during the twentieth century, the decadal variability in the solar activity cycle is associated with the decadal part of the North Atlantic Oscillation index series in such a way that both of these signals correspond to the same spatial pattern of cooling and warming. A method for testing statistical results with Monte Carlo trials on data fields with specified temporal structure and specific spatial correlation retained is presented.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

DTIC Science & Technology

2016-04-26

REPORT TYPE Final 3. DATES COVERED (From - To) 15 Oct 2014 to 14 Jan 2015 4. TITLE AND SUBTITLE Detecting statistically significant clusters of...extend the work of Perry et al. [6] by developing a statistical framework that supports the detection of triangle motif-based clusters in complex...priori, the need for triangle motif-based clustering . 2. Developed an algorithm for clustering undirected networks, where the triangle con guration was

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Tipping points in the arctic: eyeballing or statistical significance?

PubMed

Carstensen, Jacob; Weydmann, Agata

2012-02-01

Arctic ecosystems have experienced and are projected to experience continued large increases in temperature and declines in sea ice cover. It has been hypothesized that small changes in ecosystem drivers can fundamentally alter ecosystem functioning, and that this might be particularly pronounced for Arctic ecosystems. We present a suite of simple statistical analyses to identify changes in the statistical properties of data, emphasizing that changes in the standard error should be considered in addition to changes in mean properties. The methods are exemplified using sea ice extent, and suggest that the loss rate of sea ice accelerated by factor of ~5 in 1996, as reported in other studies, but increases in random fluctuations, as an early warning signal, were observed already in 1990. We recommend to employ the proposed methods more systematically for analyzing tipping points to document effects of climate change in the Arctic.

Your Chi-Square Test Is Statistically Significant: Now What?

ERIC Educational Resources Information Center

Sharpe, Donald

2015-01-01

Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data…

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…

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

PubMed Central

Goodpaster, Aaron M.; Kennedy, Michael A.

2015-01-01

Currently, no standard metrics are used to quantify cluster separation in PCA or PLS-DA scores plots for metabonomics studies or to determine if cluster separation is statistically significant. Lack of such measures makes it virtually impossible to compare independent or inter-laboratory studies and can lead to confusion in the metabonomics literature when authors putatively identify metabolites distinguishing classes of samples based on visual and qualitative inspection of scores plots that exhibit marginal separation. While previous papers have addressed quantification of cluster separation in PCA scores plots, none have advocated routine use of a quantitative measure of separation that is supported by a standard and rigorous assessment of whether or not the cluster separation is statistically significant. Here quantification and statistical significance of separation of group centroids in PCA and PLS-DA scores plots are considered. The Mahalanobis distance is used to quantify the distance between group centroids, and the two-sample Hotelling's T2 test is computed for the data, related to an F-statistic, and then an F-test is applied to determine if the cluster separation is statistically significant. We demonstrate the value of this approach using four datasets containing various degrees of separation, ranging from groups that had no apparent visual cluster separation to groups that had no visual cluster overlap. Widespread adoption of such concrete metrics to quantify and evaluate the statistical significance of PCA and PLS-DA cluster separation would help standardize reporting of metabonomics data. PMID:26246647

A Note on Comparing the Power of Test Statistics at Low Significance Levels.

PubMed

Morris, Nathan; Elston, Robert

2011-01-01

It is an obvious fact that the power of a test statistic is dependent upon the significance (alpha) level at which the test is performed. It is perhaps a less obvious fact that the relative performance of two statistics in terms of power is also a function of the alpha level. Through numerous personal discussions, we have noted that even some competent statisticians have the mistaken intuition that relative power comparisons at traditional levels such as α = 0.05 will be roughly similar to relative power comparisons at very low levels, such as the level α = 5 × 10 -8 , which is commonly used in genome-wide association studies. In this brief note, we demonstrate that this notion is in fact quite wrong, especially with respect to comparing tests with differing degrees of freedom. In fact, at very low alpha levels the cost of additional degrees of freedom is often comparatively low. Thus we recommend that statisticians exercise caution when interpreting the results of power comparison studies which use alpha levels that will not be used in practice.

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

PubMed Central

Kim, Sung-Min; Choi, Yosoon

2017-01-01

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH), high content with a low z-score (HL), low content with a high z-score (LH), and low content with a low z-score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required. PMID:28629168

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data.

PubMed

Kim, Sung-Min; Choi, Yosoon

2017-06-18

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z -scores: high content with a high z -score (HH), high content with a low z -score (HL), low content with a high z -score (LH), and low content with a low z -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

Statistical significance versus clinical relevance.

PubMed

van Rijn, Marieke H C; Bech, Anneke; Bouyer, Jean; van den Brand, Jan A J G

2017-04-01

In March this year, the American Statistical Association (ASA) posted a statement on the correct use of P-values, in response to a growing concern that the P-value is commonly misused and misinterpreted. We aim to translate these warnings given by the ASA into a language more easily understood by clinicians and researchers without a deep background in statistics. Moreover, we intend to illustrate the limitations of P-values, even when used and interpreted correctly, and bring more attention to the clinical relevance of study findings using two recently reported studies as examples. We argue that P-values are often misinterpreted. A common mistake is saying that P < 0.05 means that the null hypothesis is false, and P ≥0.05 means that the null hypothesis is true. The correct interpretation of a P-value of 0.05 is that if the null hypothesis were indeed true, a similar or more extreme result would occur 5% of the times upon repeating the study in a similar sample. In other words, the P-value informs about the likelihood of the data given the null hypothesis and not the other way around. A possible alternative related to the P-value is the confidence interval (CI). It provides more information on the magnitude of an effect and the imprecision with which that effect was estimated. However, there is no magic bullet to replace P-values and stop erroneous interpretation of scientific results. Scientists and readers alike should make themselves familiar with the correct, nuanced interpretation of statistical tests, P-values and CIs. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation

PubMed Central

Adams, James; Kruger, Uwe; Geis, Elizabeth; Gehn, Eva; Fimbres, Valeria; Pollard, Elena; Mitchell, Jessica; Ingram, Julie; Hellmers, Robert; Quig, David; Hahn, Juergen

2017-01-01

Introduction A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. Methods In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. Results and Discussion Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate

Statistical Significance and Effect Size: Two Sides of a Coin.

ERIC Educational Resources Information Center

Fan, Xitao

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

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.

Significant Statistics: Viewed with a Contextual Lens

ERIC Educational Resources Information Center

Tait-McCutcheon, Sandi

2010-01-01

This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

"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…

Statistical significance of the rich-club phenomenon in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2008-04-01

We propose that the rich-club phenomenon in complex networks should be defined in the spirit of bootstrapping, in which a null model is adopted to assess the statistical significance of the rich-club detected. Our method can serve as a definition of the rich-club phenomenon and is applied to analyze three real networks and three model networks. The results show significant improvement compared with previously reported results. We report a dilemma with an exceptional example, showing that there does not exist an omnipotent definition for the rich-club phenomenon.

Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures

PubMed Central

2013-01-01

Background Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. Methods Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. Results The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. Conclusions The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F > 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r < 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r > 0.9). PMID:23721463

Fostering Students' Statistical Literacy through Significant Learning Experience

ERIC Educational Resources Information Center

Krishnan, Saras

2015-01-01

A major objective of statistics education is to develop students' statistical literacy that enables them to be educated users of data in context. Teaching statistics in today's educational settings is not an easy feat because teachers have a huge task in keeping up with the demands of the new generation of learners. The present day students have…

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.

PubMed

Wilkinson, Michael

2014-03-01

Decisions about support for predictions of theories in light of data are made using statistical inference. The dominant approach in sport and exercise science is the Neyman-Pearson (N-P) significance-testing approach. When applied correctly it provides a reliable procedure for making dichotomous decisions for accepting or rejecting zero-effect null hypotheses with known and controlled long-run error rates. Type I and type II error rates must be specified in advance and the latter controlled by conducting an a priori sample size calculation. The N-P approach does not provide the probability of hypotheses or indicate the strength of support for hypotheses in light of data, yet many scientists believe it does. Outcomes of analyses allow conclusions only about the existence of non-zero effects, and provide no information about the likely size of true effects or their practical/clinical value. Bayesian inference can show how much support data provide for different hypotheses, and how personal convictions should be altered in light of data, but the approach is complicated by formulating probability distributions about prior subjective estimates of population effects. A pragmatic solution is magnitude-based inference, which allows scientists to estimate the true magnitude of population effects and how likely they are to exceed an effect magnitude of practical/clinical importance, thereby integrating elements of subjective Bayesian-style thinking. While this approach is gaining acceptance, progress might be hastened if scientists appreciate the shortcomings of traditional N-P null hypothesis significance testing.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

PubMed

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Mass spectrometry-based protein identification with accurate statistical significance assignment.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2015-03-01

Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Addition of Cryoprotectant Significantly Alters the Epididymal Sperm Proteome

PubMed Central

Yoon, Sung-Jae; Rahman, Md Saidur; Kwon, Woo-Sung; Park, Yoo-Jin; Pang, Myung-Geol

2016-01-01

Although cryopreservation has been developed and optimized over the past decades, it causes various stresses, including cold shock, osmotic stress, and ice crystal formation, thereby reducing fertility. During cryopreservation, addition of cryoprotective agent (CPA) is crucial for protecting spermatozoa from freezing damage. However, the intrinsic toxicity and osmotic stress induced by CPA cause damage to spermatozoa. To identify the effects of CPA addition during cryopreservation, we assessed the motility (%), motion kinematics, capacitation status, and viability of epididymal spermatozoa using computer-assisted sperm analysis and Hoechst 33258/chlortetracycline fluorescence staining. Moreover, the effects of CPA addition were also demonstrated at the proteome level using two-dimensional electrophoresis. Our results demonstrated that CPA addition significantly reduced sperm motility (%), curvilinear velocity, viability (%), and non-capacitated spermatozoa, whereas straightness and acrosome-reacted spermatozoa increased significantly (p < 0.05). Ten proteins were differentially expressed (two decreased and eight increased) (>3 fold, p < 0.05) after CPA, whereas NADH dehydrogenase flavoprotein 2, f-actin-capping protein subunit beta, superoxide dismutase 2, and outer dense fiber protein 2 were associated with several important signaling pathways (p < 0.05). The present study provides a mechanistic basis for specific cryostresses and potential markers of CPA-induced stress. Therefore, these might provide information about the development of safe biomaterials for cryopreservation and basic ground for sperm cryopreservation. PMID:27031703

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

The role of baryons in creating statistically significant planes of satellites around Milky Way-mass galaxies

NASA Astrophysics Data System (ADS)

Ahmed, Sheehan H.; Brooks, Alyson M.; Christensen, Charlotte R.

2017-04-01

We investigate whether the inclusion of baryonic physics influences the formation of thin, coherently rotating planes of satellites such as those seen around the Milky Way and Andromeda. For four Milky Way-mass simulations, each run both as dark matter-only and with baryons included, we are able to identify a planar configuration that significantly maximizes the number of plane satellite members. The maximum plane member satellites are consistently different between the dark matter-only and baryonic versions of the same run due to the fact that satellites are both more likely to be destroyed and to infall later in the baryonic runs. Hence, studying satellite planes in dark matter-only simulations is misleading, because they will be composed of different satellite members than those that would exist if baryons were included. Additionally, the destruction of satellites in the baryonic runs leads to less radially concentrated satellite distributions, a result that is critical to making planes that are statistically significant compared to a random distribution. Since all planes pass through the centre of the galaxy, it is much harder to create a plane of a given height from a random distribution if the satellites have a low radial concentration. We identify Andromeda's low radial satellite concentration as a key reason why the plane in Andromeda is highly significant. Despite this, when corotation is considered, none of the satellite planes identified for the simulated galaxies are as statistically significant as the observed planes around the Milky Way and Andromeda, even in the baryonic runs.

Clinical relevance vs. statistical significance: Using neck outcomes in patients with temporomandibular disorders as an example.

PubMed

Armijo-Olivo, Susan; Warren, Sharon; Fuentes, Jorge; Magee, David J

2011-12-01

Statistical significance has been used extensively to evaluate the results of research studies. Nevertheless, it offers only limited information to clinicians. The assessment of clinical relevance can facilitate the interpretation of the research results into clinical practice. The objective of this study was to explore different methods to evaluate the clinical relevance of the results using a cross-sectional study as an example comparing different neck outcomes between subjects with temporomandibular disorders and healthy controls. Subjects were compared for head and cervical posture, maximal cervical muscle strength, endurance of the cervical flexor and extensor muscles, and electromyographic activity of the cervical flexor muscles during the CranioCervical Flexion Test (CCFT). The evaluation of clinical relevance of the results was performed based on the effect size (ES), minimal important difference (MID), and clinical judgement. The results of this study show that it is possible to have statistical significance without having clinical relevance, to have both statistical significance and clinical relevance, to have clinical relevance without having statistical significance, or to have neither statistical significance nor clinical relevance. The evaluation of clinical relevance in clinical research is crucial to simplify the transfer of knowledge from research into practice. Clinical researchers should present the clinical relevance of their results. Copyright © 2011 Elsevier Ltd. All rights reserved.

Statistical significance of seasonal warming/cooling trends

NASA Astrophysics Data System (ADS)

Ludescher, Josef; Bunde, Armin; Schellnhuber, Hans Joachim

2017-04-01

The question whether a seasonal climate trend (e.g., the increase of summer temperatures in Antarctica in the last decades) is of anthropogenic or natural origin is of great importance for mitigation and adaption measures alike. The conventional significance analysis assumes that (i) the seasonal climate trends can be quantified by linear regression, (ii) the different seasonal records can be treated as independent records, and (iii) the persistence in each of these seasonal records can be characterized by short-term memory described by an autoregressive process of first order. Here we show that assumption ii is not valid, due to strong intraannual correlations by which different seasons are correlated. We also show that, even in the absence of correlations, for Gaussian white noise, the conventional analysis leads to a strong overestimation of the significance of the seasonal trends, because multiple testing has not been taken into account. In addition, when the data exhibit long-term memory (which is the case in most climate records), assumption iii leads to a further overestimation of the trend significance. Combining Monte Carlo simulations with the Holm-Bonferroni method, we demonstrate how to obtain reliable estimates of the significance of the seasonal climate trends in long-term correlated records. For an illustration, we apply our method to representative temperature records from West Antarctica, which is one of the fastest-warming places on Earth and belongs to the crucial tipping elements in the Earth system.

On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis.

PubMed

Li, Bing; Chun, Hyonho; Zhao, Hongyu

2014-09-01

We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis.

The fragility of statistically significant findings from randomized trials in head and neck surgery.

PubMed

Noel, Christopher W; McMullen, Caitlin; Yao, Christopher; Monteiro, Eric; Goldstein, David P; Eskander, Antoine; de Almeida, John R

2018-04-23

The Fragility Index (FI) is a novel tool for evaluating the robustness of statistically significant findings in a randomized control trial (RCT). It measures the number of events upon which statistical significance depends. We sought to calculate the FI scores for RCTs in the head and neck cancer literature where surgery was a primary intervention. Potential articles were identified in PubMed (MEDLINE), Embase, and Cochrane without publication date restrictions. Two reviewers independently screened eligible RCTs reporting at least one dichotomous and statistically significant outcome. The data from each trial were extracted and the FI scores were calculated. Associations between trial characteristics and FI were determined. In total, 27 articles were identified. The median sample size was 67.5 (interquartile range [IQR] = 42-143) and the median number of events per trial was 8 (IQR = 2.25-18.25). The median FI score was 1 (IQR = 0-2.5), meaning that changing one patient from a nonevent to an event in the treatment arm would change the result to a statistically nonsignificant result, or P > .05. The FI score was less than the number of patients lost to follow-up in 71% of cases. The FI score was found to be moderately correlated with P value (ρ = -0.52, P = .007) and with journal impact factor (ρ = 0.49, P = .009) on univariable analysis. On multivariable analysis, only the P value was found to be a predictor of FI score (P = .001). Randomized trials in the head and neck cancer literature where surgery is a primary modality are relatively nonrobust statistically with low FI scores. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.

Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

2016-02-01

Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple `fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Are Mammographically Occult Additional Tumors Identified More Than 2 Cm Away From the Primary Breast Cancer on MRI Clinically Significant?

PubMed

Goodman, Sarah; Mango, Victoria; Friedlander, Lauren; Desperito, Elise; Wynn, Ralph; Ha, Richard

2018-06-08

To evaluate the clinical significance of mammographically occult additional tumors identified more than 2cm away from the primary breast cancer on preoperative magnetic resonance imaging (MRI). An Institutional Review Board approved review of consecutive preoperative breast MRIs performed from 1/1/08 to 12/31/14, yielded 667 patients with breast cancer. These patients underwent further assessment to identify biopsy proven mammographically occult breast tumors located more than 2cm away from the edge of the primary tumor. Additional MRI characteristics of the primary and secondary tumors and pathology were reviewed. Statistical analysis was performed using SPSS (v. 24). Of 667 patients with breast cancer, 129 patients had 150 additional ipsilateral mammographically occult tumors that were more than 2cm away from the edge of the primary tumor. One hundred twelve of 129 (86.8%) patients had one additional tumor and 17/129 (13.2%) had two or more additional tumors. In 71/129 (55.0%), additional tumors were located in a different quadrant and in 58/129 (45.0%) additional tumors were in the same quadrant but ≥2cm away. Overall, primary tumor size was significantly larger (mean 1.87± 1.25 cm) than the additional tumors (mean 0.79 ± 0.61cm, p < 0.001). However, in 20/129 (15.5%) the additional tumor was larger and in 26/129 (20.2%) the additional tumor was ≥1cm. The primary tumor was significantly more likely to be invasive (81.4%, 105/129) compared to additional tumors (70%, 105/150, p = 0.03). In 9/129 (7.0%) patients, additional tumors yielded unsuspected invasive cancer orhigher tumor grade. The additional tumor was more likely to be nonmass lesion type (37.3% vs 24% p = 0.02) and focus lesion type (10% vs 0.08%, p < 0.001) compared to primary tumor. Mammographically occult additional tumors identified more than 2cm away from the primary breast tumor on MRI are unlikely to be surgically treated if undiagnosed and may be clinically significant. Copyright �

Reporting of statistically significant results at ClinicalTrials.gov for completed superiority randomized controlled trials.

PubMed

Dechartres, Agnes; Bond, Elizabeth G; Scheer, Jordan; Riveros, Carolina; Atal, Ignacio; Ravaud, Philippe

2016-11-30

Publication bias and other reporting bias have been well documented for journal articles, but no study has evaluated the nature of results posted at ClinicalTrials.gov. We aimed to assess how many randomized controlled trials (RCTs) with results posted at ClinicalTrials.gov report statistically significant results and whether the proportion of trials with significant results differs when no treatment effect estimate or p-value is posted. We searched ClinicalTrials.gov in June 2015 for all studies with results posted. We included completed RCTs with a superiority hypothesis and considered results for the first primary outcome with results posted. For each trial, we assessed whether a treatment effect estimate and/or p-value was reported at ClinicalTrials.gov and if yes, whether results were statistically significant. If no treatment effect estimate or p-value was reported, we calculated the treatment effect and corresponding p-value using results per arm posted at ClinicalTrials.gov when sufficient data were reported. From the 17,536 studies with results posted at ClinicalTrials.gov, we identified 2823 completed phase 3 or 4 randomized trials with a superiority hypothesis. Of these, 1400 (50%) reported a treatment effect estimate and/or p-value. Results were statistically significant for 844 trials (60%), with a median p-value of 0.01 (Q1-Q3: 0.001-0.26). For the 1423 trials with no treatment effect estimate or p-value posted, we could calculate the treatment effect and corresponding p-value using results reported per arm for 929 (65%). For 494 trials (35%), p-values could not be calculated mainly because of insufficient reporting, censored data, or repeated measurements over time. For the 929 trials we could calculate p-values, we found statistically significant results for 342 (37%), with a median p-value of 0.19 (Q1-Q3: 0.005-0.59). Half of the trials with results posted at ClinicalTrials.gov reported a treatment effect estimate and/or p-value, with significant

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

Intensive inpatient treatment for bulimia nervosa: Statistical and clinical significance of symptom changes.

PubMed

Diedrich, Alice; Schlegl, Sandra; Greetfeld, Martin; Fumi, Markus; Voderholzer, Ulrich

2018-03-01

This study examines the statistical and clinical significance of symptom changes during an intensive inpatient treatment program with a strong psychotherapeutic focus for individuals with severe bulimia nervosa. 295 consecutively admitted bulimic patients were administered the Structured Interview for Anorexic and Bulimic Syndromes-Self-Rating (SIAB-S), the Eating Disorder Inventory-2 (EDI-2), the Brief Symptom Inventory (BSI), and the Beck Depression Inventory-II (BDI-II) at treatment intake and discharge. Results indicated statistically significant symptom reductions with large effect sizes regarding severity of binge eating and compensatory behavior (SIAB-S), overall eating disorder symptom severity (EDI-2), overall psychopathology (BSI), and depressive symptom severity (BDI-II) even when controlling for antidepressant medication. The majority of patients showed either reliable (EDI-2: 33.7%, BSI: 34.8%, BDI-II: 18.1%) or even clinically significant symptom changes (EDI-2: 43.2%, BSI: 33.9%, BDI-II: 56.9%). Patients with clinically significant improvement were less distressed at intake and less likely to suffer from a comorbid borderline personality disorder when compared with those who did not improve to a clinically significant extent. Findings indicate that intensive psychotherapeutic inpatient treatment may be effective in about 75% of severely affected bulimic patients. For the remaining non-responding patients, inpatient treatment might be improved through an even stronger focus on the reduction of comorbid borderline personality traits.

Using the Descriptive Bootstrap to Evaluate Result Replicability (Because Statistical Significance Doesn't)

ERIC Educational Resources Information Center

Spinella, Sarah

2011-01-01

As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Statistical Significance of Optical Map Alignments

PubMed Central

Sarkar, Deepayan; Goldstein, Steve; Schwartz, David C.

2012-01-01

Abstract The Optical Mapping System constructs ordered restriction maps spanning entire genomes through the assembly and analysis of large datasets comprising individually analyzed genomic DNA molecules. Such restriction maps uniquely reveal mammalian genome structure and variation, but also raise computational and statistical questions beyond those that have been solved in the analysis of smaller, microbial genomes. We address the problem of how to filter maps that align poorly to a reference genome. We obtain map-specific thresholds that control errors and improve iterative assembly. We also show how an optimal self-alignment score provides an accurate approximation to the probability of alignment, which is useful in applications seeking to identify structural genomic abnormalities. PMID:22506568

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

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

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.

Statistically significant performance results of a mine detector and fusion algorithm from an x-band high-resolution SAR

NASA Astrophysics Data System (ADS)

Williams, Arnold C.; Pachowicz, Peter W.

2004-09-01

Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

Septic tank additive impacts on microbial populations.

PubMed

Pradhan, S; Hoover, M T; Clark, G H; Gumpertz, M; Wollum, A G; Cobb, C; Strock, J

2008-01-01

Environmental health specialists, other onsite wastewater professionals, scientists, and homeowners have questioned the effectiveness of septic tank additives. This paper describes an independent, third-party, field scale, research study of the effects of three liquid bacterial septic tank additives and a control (no additive) on septic tank microbial populations. Microbial populations were measured quarterly in a field study for 12 months in 48 full-size, functioning septic tanks. Bacterial populations in the 48 septic tanks were statistically analyzed with a mixed linear model. Additive effects were assessed for three septic tank maintenance levels (low, intermediate, and high). Dunnett's t-test for tank bacteria (alpha = .05) indicated that none of the treatments were significantly different, overall, from the control at the statistical level tested. In addition, the additives had no significant effects on septic tank bacterial populations at any of the septic tank maintenance levels. Additional controlled, field-based research iswarranted, however, to address additional additives and experimental conditions.

A systematic review and meta-analysis of acute stroke unit care: What’s beyond the statistical significance?

PubMed Central

2013-01-01

Background The benefits of stroke unit care in terms of reducing death, dependency and institutional care were demonstrated in a 2009 Cochrane review carried out by the Stroke Unit Trialists’ Collaboration. Methods As requested by the Belgian health authorities, a systematic review and meta-analysis of the effect of acute stroke units was performed. Clinical trials mentioned in the original Cochrane review were included. In addition, an electronic database search on Medline, Embase, the Cochrane Central Register of Controlled Trials, and Physiotherapy Evidence Database (PEDro) was conducted to identify trials published since 2006. Trials investigating acute stroke units compared to alternative care were eligible for inclusion. Study quality was appraised according to the criteria recommended by Scottish Intercollegiate Guidelines Network (SIGN) and the GRADE system. In the meta-analysis, dichotomous outcomes were estimated by calculating odds ratios (OR) and continuous outcomes were estimated by calculating standardized mean differences. The weight of a study was calculated based on inverse variance. Results Evidence from eight trials comparing acute stroke unit and conventional care (general medical ward) were retained for the main synthesis and analysis. The findings from this study were broadly in line with the original Cochrane review: acute stroke units can improve survival and independency, as well as reduce the chance of hospitalization and the length of inpatient stay. The improvement with stroke unit care on mortality was less conclusive and only reached borderline level of significance (OR 0.84, 95% CI 0.70 to 1.00, P = 0.05). This improvement became statistically non-significant (OR 0.87, 95% CI 0.74 to 1.03, P = 0.12) when data from two unpublished trials (Goteborg-Ostra and Svendborg) were added to the analysis. After further also adding two additional trials (Beijing, Stockholm) with very short observation periods (until discharge), the

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.

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

Statistical significance estimation of a signal within the GooFit framework on GPUs

NASA Astrophysics Data System (ADS)

Cristella, Leonardo; Di Florio, Adriano; Pompili, Alexis

2017-03-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant.

PubMed

Monsarrat, Paul; Vergnes, Jean-Noel

2018-01-01

In medicine, effect sizes (ESs) allow the effects of independent variables (including risk/protective factors or treatment interventions) on dependent variables (e.g., health outcomes) to be quantified. Given that many public health decisions and health care policies are based on ES estimates, it is important to assess how ESs are used in the biomedical literature and to investigate potential trends in their reporting over time. Through a big data approach, the text mining process automatically extracted 814 120 ESs from 13 322 754 PubMed abstracts. Eligible ESs were risk ratio, odds ratio, and hazard ratio, along with their confidence intervals. Here we show a remarkable decrease of ES values in PubMed abstracts between 1990 and 2015 while, concomitantly, results become more often statistically significant. Medians of ES values have decreased over time for both "risk" and "protective" values. This trend was found in nearly all fields of biomedical research, with the most marked downward tendency in genetics. Over the same period, the proportion of statistically significant ESs increased regularly: among the abstracts with at least 1 ES, 74% were statistically significant in 1990-1995, vs 85% in 2010-2015. whereas decreasing ESs could be an intrinsic evolution in biomedical research, the concomitant increase of statistically significant results is more intriguing. Although it is likely that growing sample sizes in biomedical research could explain these results, another explanation may lie in the "publish or perish" context of scientific research, with the probability of a growing orientation toward sensationalism in research reports. Important provisions must be made to improve the credibility of biomedical research and limit waste of resources. © The Authors 2017. Published by Oxford University Press.

Additive effects in high-voltage layered-oxide cells: A statistics of mixtures approach

DOE PAGES

Sahore, Ritu; Peebles, Cameron; Abraham, Daniel P.; ...

2017-07-20

Li 1.03(Ni 0.5Mn 0.3Co 0.2) 0.97O 2 (NMC)-based coin cells containing the electrolyte additives vinylene carbonate (VC) and tris(trimethylsilyl)phosphite (TMSPi) in the range of 0-2 wt% were cycled between 3.0 and 4.4 V. The changes in capacity at rates of C/10 and C/1 and resistance at 60% state of charge were found to follow linear-with-time kinetic rate laws. Further, the C/10 capacity and resistance data were amenable to modeling by a statistics of mixtures approach. Applying physical meaning to the terms in the empirical models indicated that the interactions between the electrolyte and additives were not simple. For example, theremore » were strong, synergistic interactions between VC and TMSPi affecting C/10 capacity loss, as expected, but there were other, more subtle interactions between the electrolyte components. In conclusion, the interactions between these components controlled the C/10 capacity decline and resistance increase.« less

Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.

PubMed

Xia, Li C; Ai, Dongmei; Cram, Jacob A; Liang, Xiaoyi; Fuhrman, Jed A; Sun, Fengzhu

2015-09-21

Local trend (i.e. shape) analysis of time series data reveals co-changing patterns in dynamics of biological systems. However, slow permutation procedures to evaluate the statistical significance of local trend scores have limited its applications to high-throughput time series data analysis, e.g., data from the next generation sequencing technology based studies. By extending the theories for the tail probability of the range of sum of Markovian random variables, we propose formulae for approximating the statistical significance of local trend scores. Using simulations and real data, we show that the approximate p-value is close to that obtained using a large number of permutations (starting at time points >20 with no delay and >30 with delay of at most three time steps) in that the non-zero decimals of the p-values obtained by the approximation and the permutations are mostly the same when the approximate p-value is less than 0.05. In addition, the approximate p-value is slightly larger than that based on permutations making hypothesis testing based on the approximate p-value conservative. The approximation enables efficient calculation of p-values for pairwise local trend analysis, making large scale all-versus-all comparisons possible. We also propose a hybrid approach by integrating the approximation and permutations to obtain accurate p-values for significantly associated pairs. We further demonstrate its use with the analysis of the Polymouth Marine Laboratory (PML) microbial community time series from high-throughput sequencing data and found interesting organism co-occurrence dynamic patterns. The software tool is integrated into the eLSA software package that now provides accelerated local trend and similarity analysis pipelines for time series data. The package is freely available from the eLSA website: http://bitbucket.org/charade/elsa.

Addition of perfluorocarbons to alginate hydrogels significantly impacts molecular transport and fracture stress.

PubMed

White, Joseph C; Stoppel, Whitney L; Roberts, Susan C; Bhatia, Surita R

2013-02-01

Perfluorocarbons (PFCs) are used in biomaterial formulations to increase oxygen (O(2) ) tension and create a homogeneous O(2) environment in three-dimensional tissue constructs. It is unclear how PFCs affect mechanical and transport properties of the scaffold, which are critical for robustness, intracellular signaling, protein transport, and overall device efficacy. In this study, we investigate composite alginate hydrogels containing a perfluorooctyl bromide (PFOB) emulsion stabilized with Pluronic(®) F68 (F68). We demonstrate that PFC addition significantly affects biomaterial properties and performance. Solution and hydrogel mechanical properties and transport of representative hydrophilic (riboflavin), hydrophobic (methyl and ethyl paraben), and protein (bovine serum albumin, BSA) solutes were compared in alginate/F68 composite hydrogels with or without PFOB. Our results indicate that mechanical properties of the alginate/F68/PFOB hydrogels are not significantly affected under small strains, but a significant decrease fracture stress is observed. The effective diffusivity D(eff) of hydrophobic small molecules decreases with PFOB emulsion addition, yet the D(eff) of hydrophilic small molecules remained unaffected. For BSA, the D(eff) increased and the loading capacity decreased with PFOB emulsion addition. Thus, a trade-off between the desired increased O(2) supply provided by PFCs and the mechanical weakening and change in transport of cellular signals must be carefully considered in the design of biomaterials containing PFCs. Copyright © 2012 Wiley Periodicals, Inc.

Use of Tests of Statistical Significance and Other Analytic Choices in a School Psychology Journal: Review of Practices and Suggested Alternatives.

ERIC Educational Resources Information Center

Snyder, Patricia A.; Thompson, Bruce

The use of tests of statistical significance was explored, first by reviewing some criticisms of contemporary practice in the use of statistical tests as reflected in a series of articles in the "American Psychologist" and in the appointment of a "Task Force on Statistical Inference" by the American Psychological Association…

Consomic mouse strain selection based on effect size measurement, statistical significance testing and integrated behavioral z-scoring: focus on anxiety-related behavior and locomotion.

PubMed

Labots, M; Laarakker, M C; Ohl, F; van Lith, H A

2016-06-29

Selecting chromosome substitution strains (CSSs, also called consomic strains/lines) used in the search for quantitative trait loci (QTLs) consistently requires the identification of the respective phenotypic trait of interest and is simply based on a significant difference between a consomic and host strain. However, statistical significance as represented by P values does not necessarily predicate practical importance. We therefore propose a method that pays attention to both the statistical significance and the actual size of the observed effect. The present paper extends on this approach and describes in more detail the use of effect size measures (Cohen's d, partial eta squared - η p (2) ) together with the P value as statistical selection parameters for the chromosomal assignment of QTLs influencing anxiety-related behavior and locomotion in laboratory mice. The effect size measures were based on integrated behavioral z-scoring and were calculated in three experiments: (A) a complete consomic male mouse panel with A/J as the donor strain and C57BL/6J as the host strain. This panel, including host and donor strains, was analyzed in the modified Hole Board (mHB). The consomic line with chromosome 19 from A/J (CSS-19A) was selected since it showed increased anxiety-related behavior, but similar locomotion compared to its host. (B) Following experiment A, female CSS-19A mice were compared with their C57BL/6J counterparts; however no significant differences and effect sizes close to zero were found. (C) A different consomic mouse strain (CSS-19PWD), with chromosome 19 from PWD/PhJ transferred on the genetic background of C57BL/6J, was compared with its host strain. Here, in contrast with CSS-19A, there was a decreased overall anxiety in CSS-19PWD compared to C57BL/6J males, but not locomotion. This new method shows an improved way to identify CSSs for QTL analysis for anxiety-related behavior using a combination of statistical significance testing and effect

On Interestingness Measures for Mining Statistically Significant and Novel Clinical Associations from EMRs

PubMed Central

Abar, Orhan; Charnigo, Richard J.; Rayapati, Abner

2017-01-01

Association rule mining has received significant attention from both the data mining and machine learning communities. While data mining researchers focus more on designing efficient algorithms to mine rules from large datasets, the learning community has explored applications of rule mining to classification. A major problem with rule mining algorithms is the explosion of rules even for moderate sized datasets making it very difficult for end users to identify both statistically significant and potentially novel rules that could lead to interesting new insights and hypotheses. Researchers have proposed many domain independent interestingness measures using which, one can rank the rules and potentially glean useful rules from the top ranked ones. However, these measures have not been fully explored for rule mining in clinical datasets owing to the relatively large sizes of the datasets often encountered in healthcare and also due to limited access to domain experts for review/analysis. In this paper, using an electronic medical record (EMR) dataset of diagnoses and medications from over three million patient visits to the University of Kentucky medical center and affiliated clinics, we conduct a thorough evaluation of dozens of interestingness measures proposed in data mining literature, including some new composite measures. Using cumulative relevance metrics from information retrieval, we compare these interestingness measures against human judgments obtained from a practicing psychiatrist for association rules involving the depressive disorders class as the consequent. Our results not only surface new interesting associations for depressive disorders but also indicate classes of interestingness measures that weight rule novelty and statistical strength in contrasting ways, offering new insights for end users in identifying interesting rules. PMID:28736771

A randomized trial in a massive online open course shows people don't know what a statistically significant relationship looks like, but they can learn.

PubMed

Fisher, Aaron; Anderson, G Brooke; Peng, Roger; Leek, Jeff

2014-01-01

Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to statistically justify relationships identified between variables. Here we measure the ability to detect statistically significant relationships from scatterplots in a randomized trial of 2,039 students in a statistics massive open online course (MOOC). Each subject was shown a random set of scatterplots and asked to visually determine if the underlying relationships were statistically significant at the P < 0.05 level. Subjects correctly classified only 47.4% (95% CI [45.1%-49.7%]) of statistically significant relationships, and 74.6% (95% CI [72.5%-76.6%]) of non-significant relationships. Adding visual aids such as a best fit line or scatterplot smooth increased the probability a relationship was called significant, regardless of whether the relationship was actually significant. Classification of statistically significant relationships improved on repeat attempts of the survey, although classification of non-significant relationships did not. Our results suggest: (1) that evidence-based data analysis can be used to identify weaknesses in theoretical procedures in the hands of average users, (2) data analysts can be trained to improve detection of statistically significant results with practice, but (3) data analysts have incorrect intuition about what statistically significant relationships look like, particularly for small effects. We have built a web tool for people to compare scatterplots with their corresponding p-values which is available here: http://glimmer.rstudio.com/afisher/EDA/.

A randomized trial in a massive online open course shows people don’t know what a statistically significant relationship looks like, but they can learn

PubMed Central

Fisher, Aaron; Anderson, G. Brooke; Peng, Roger

2014-01-01

Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to statistically justify relationships identified between variables. Here we measure the ability to detect statistically significant relationships from scatterplots in a randomized trial of 2,039 students in a statistics massive open online course (MOOC). Each subject was shown a random set of scatterplots and asked to visually determine if the underlying relationships were statistically significant at the P < 0.05 level. Subjects correctly classified only 47.4% (95% CI [45.1%–49.7%]) of statistically significant relationships, and 74.6% (95% CI [72.5%–76.6%]) of non-significant relationships. Adding visual aids such as a best fit line or scatterplot smooth increased the probability a relationship was called significant, regardless of whether the relationship was actually significant. Classification of statistically significant relationships improved on repeat attempts of the survey, although classification of non-significant relationships did not. Our results suggest: (1) that evidence-based data analysis can be used to identify weaknesses in theoretical procedures in the hands of average users, (2) data analysts can be trained to improve detection of statistically significant results with practice, but (3) data analysts have incorrect intuition about what statistically significant relationships look like, particularly for small effects. We have built a web tool for people to compare scatterplots with their corresponding p-values which is available here: http://glimmer.rstudio.com/afisher/EDA/. PMID:25337457

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

PubMed Central

2010-01-01

Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting.

PubMed

Young, Robin L; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F

2010-07-19

A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. The GAM permutation testing methods provide a regression

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

PubMed Central

Baldi, Pierre

2010-01-01

As repositories of chemical molecules continue to expand and become more open, it becomes increasingly important to develop tools to search them efficiently and assess the statistical significance of chemical similarity scores. Here we develop a general framework for understanding, modeling, predicting, and approximating the distribution of chemical similarity scores and its extreme values in large databases. The framework can be applied to different chemical representations and similarity measures but is demonstrated here using the most common binary fingerprints with the Tanimoto similarity measure. After introducing several probabilistic models of fingerprints, including the Conditional Gaussian Uniform model, we show that the distribution of Tanimoto scores can be approximated by the distribution of the ratio of two correlated Normal random variables associated with the corresponding unions and intersections. This remains true also when the distribution of similarity scores is conditioned on the size of the query molecules in order to derive more fine-grained results and improve chemical retrieval. The corresponding extreme value distributions for the maximum scores are approximated by Weibull distributions. From these various distributions and their analytical forms, Z-scores, E-values, and p-values are derived to assess the significance of similarity scores. In addition, the framework allows one to predict also the value of standard chemical retrieval metrics, such as Sensitivity and Specificity at fixed thresholds, or ROC (Receiver Operating Characteristic) curves at multiple thresholds, and to detect outliers in the form of atypical molecules. Numerous and diverse experiments carried in part with large sets of molecules from the ChemDB show remarkable agreement between theory and empirical results. PMID:20540577

A SIGNIFICANCE TEST FOR THE LASSO1

PubMed Central

Lockhart, Richard; Taylor, Jonathan; Tibshirani, Ryan J.; Tibshirani, Robert

2014-01-01

In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of models visited along the lasso solution path. We propose a simple test statistic based on lasso fitted values, called the covariance test statistic, and show that when the true model is linear, this statistic has an Exp(1) asymptotic distribution under the null hypothesis (the null being that all truly active variables are contained in the current lasso model). Our proof of this result for the special case of the first predictor to enter the model (i.e., testing for a single significant predictor variable against the global null) requires only weak assumptions on the predictor matrix X. On the other hand, our proof for a general step in the lasso path places further technical assumptions on X and the generative model, but still allows for the important high-dimensional case p > n, and does not necessarily require that the current lasso model achieves perfect recovery of the truly active variables. Of course, for testing the significance of an additional variable between two nested linear models, one typically uses the chi-squared test, comparing the drop in residual sum of squares (RSS) to a χ12 distribution. But when this additional variable is not fixed, and has been chosen adaptively or greedily, this test is no longer appropriate: adaptivity makes the drop in RSS stochastically much larger than χ12 under the null hypothesis. Our analysis explicitly accounts for adaptivity, as it must, since the lasso builds an adaptive sequence of linear models as the tuning parameter λ decreases. In this analysis, shrinkage plays a key role: though additional variables are chosen adaptively, the coefficients of lasso active variables are shrunken due to the l1 penalty. Therefore, the test statistic (which is based on lasso fitted values) is in a sense balanced by these two opposing properties—adaptivity and

"Clinical" Significance: "Clinical" Significance and "Practical" Significance are NOT the Same Things

ERIC Educational Resources Information Center

Peterson, Lisa S.

2008-01-01

Clinical significance is an important concept in research, particularly in education and the social sciences. The present article first compares clinical significance to other measures of "significance" in statistics. The major methods used to determine clinical significance are explained and the strengths and weaknesses of clinical significance…

The distribution of P-values in medical research articles suggested selective reporting associated with statistical significance.

PubMed

Perneger, Thomas V; Combescure, Christophe

2017-07-01

Published P-values provide a window into the global enterprise of medical research. The aim of this study was to use the distribution of published P-values to estimate the relative frequencies of null and alternative hypotheses and to seek irregularities suggestive of publication bias. This cross-sectional study included P-values published in 120 medical research articles in 2016 (30 each from the BMJ, JAMA, Lancet, and New England Journal of Medicine). The observed distribution of P-values was compared with expected distributions under the null hypothesis (i.e., uniform between 0 and 1) and the alternative hypothesis (strictly decreasing from 0 to 1). P-values were categorized according to conventional levels of statistical significance and in one-percent intervals. Among 4,158 recorded P-values, 26.1% were highly significant (P < 0.001), 9.1% were moderately significant (P ≥ 0.001 to < 0.01), 11.7% were weakly significant (P ≥ 0.01 to < 0.05), and 53.2% were nonsignificant (P ≥ 0.05). We noted three irregularities: (1) high proportion of P-values <0.001, especially in observational studies, (2) excess of P-values equal to 1, and (3) about twice as many P-values less than 0.05 compared with those more than 0.05. The latter finding was seen in both randomized trials and observational studies, and in most types of analyses, excepting heterogeneity tests and interaction tests. Under plausible assumptions, we estimate that about half of the tested hypotheses were null and the other half were alternative. This analysis suggests that statistical tests published in medical journals are not a random sample of null and alternative hypotheses but that selective reporting is prevalent. In particular, significant results are about twice as likely to be reported as nonsignificant results. Copyright © 2017 Elsevier Inc. All rights reserved.

The thresholds for statistical and clinical significance – a five-step procedure for evaluation of intervention effects in randomised clinical trials

PubMed Central

2014-01-01

Background Thresholds for statistical significance are insufficiently demonstrated by 95% confidence intervals or P-values when assessing results from randomised clinical trials. First, a P-value only shows the probability of getting a result assuming that the null hypothesis is true and does not reflect the probability of getting a result assuming an alternative hypothesis to the null hypothesis is true. Second, a confidence interval or a P-value showing significance may be caused by multiplicity. Third, statistical significance does not necessarily result in clinical significance. Therefore, assessment of intervention effects in randomised clinical trials deserves more rigour in order to become more valid. Methods Several methodologies for assessing the statistical and clinical significance of intervention effects in randomised clinical trials were considered. Balancing simplicity and comprehensiveness, a simple five-step procedure was developed. Results For a more valid assessment of results from a randomised clinical trial we propose the following five-steps: (1) report the confidence intervals and the exact P-values; (2) report Bayes factor for the primary outcome, being the ratio of the probability that a given trial result is compatible with a ‘null’ effect (corresponding to the P-value) divided by the probability that the trial result is compatible with the intervention effect hypothesised in the sample size calculation; (3) adjust the confidence intervals and the statistical significance threshold if the trial is stopped early or if interim analyses have been conducted; (4) adjust the confidence intervals and the P-values for multiplicity due to number of outcome comparisons; and (5) assess clinical significance of the trial results. Conclusions If the proposed five-step procedure is followed, this may increase the validity of assessments of intervention effects in randomised clinical trials. PMID:24588900

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

Lubricant and additive effects on spur gear fatigue life

NASA Technical Reports Server (NTRS)

Townsend, D. P.; Zaretsky, E. V.; Scibbe, H. W.

1985-01-01

Spur gear endurance tests were conducted with six lubricants using a single lot of consumable-electrode vacuum melted (CVM) AISI 9310 spur gears. The sixth lubricant was divided into four batches each of which had a different additive content. Lubricants tested with a phosphorus-type load carrying additive showed a statistically significant improvement in life over lubricants without this type of additive. The presence of sulfur type antiwear additives in the lubricant did not appear to affect the surface fatigue life of the gears. No statistical difference in life was produced with those lubricants of different base stocks but with similar viscosity, pressure-viscosity coefficients and antiwear additives. Gears tested with a 0.1 wt % sulfur and 0.1 wt % phosphorus EP additives in the lubricant had reactive films that were 200 to 400 (0.8 to 1.6 microns) thick.

A Network-Based Method to Assess the Statistical Significance of Mild Co-Regulation Effects

PubMed Central

Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

2013-01-01

Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis. PMID:24039936

Prognostic significance of smoking in addition to established risk factors in patients with Dukes B and C colorectal cancer: a retrospective analysis.

PubMed

Diamantis, N; Xynos, I D; Amptulah, S; Karadima, M; Skopelitis, H; Tsavaris, N

2013-01-01

To investigate the prognostic significance of smoking in addition to established risk factors in patients with Dukes stage B and C colorectal cancer (CRC). 291 consecutive non-selected CRC patients were studied retrospectively. Twenty-three variables were examined using a regression statistical model to identify relevant prognostic factors related to disease free survival (DFS) and overall survival (OS). On multivariate analysis DFS was found to be negatively affected in patients with a smoking history of ≤10 pack-years vs. non-smokers (p<0.016). Additionally, performance status (PS)<90 (p<0.001), Dukes stage C (p<0.001) and elevated tumor markers (p<0.001) at the time of diagnosis were found to adversely affect DFS. Smoking also had a significant association with relapse. Patients with a smoking history of ≤10 pack-years had 2.45 (p<0.018) higher risk of recurrence compared to patients with no smoking history. OS was influenced by Karnofsky performance status (PS), Dukes stage, and elevated tumor markers. In particular patients with PS< 90 had a 4.69-fold higher risk of death (p<0.001) than patients with better PS. Stage C disease was associated with 2.27-fold higher risk of death (p<0.001) than stage B disease, and patients with elevated tumor markers at the time of diagnosis had 2.74-fold higher risk of death (p<0.014) when compared to those whose tumor markers were normal at presentation. Our study associates smoking and relapse incidence in non-clinical- trial CRC patients and reiterates the prognostic significance of PS, stage and tumor markers at the time of diagnosis.

Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence

NASA Astrophysics Data System (ADS)

Keylock, Christopher J.

2017-08-01

A method is presented for deriving random velocity gradient tensors given a source tensor. These synthetic tensors are constrained to lie within mathematical bounds of the non-normality of the source tensor, but we do not impose direct constraints upon scalar quantities typically derived from the velocity gradient tensor and studied in fluid mechanics. Hence, it becomes possible to ask hypotheses of data at a point regarding the statistical significance of these scalar quantities. Having presented our method and the associated mathematical concepts, we apply it to homogeneous, isotropic turbulence to test the utility of the approach for a case where the behavior of the tensor is understood well. We show that, as well as the concentration of data along the Vieillefosse tail, actual turbulence is also preferentially located in the quadrant where there is both excess enstrophy (Q>0 ) and excess enstrophy production (R<0 ). We also examine the topology implied by the strain eigenvalues and find that for the statistically significant results there is a particularly strong relative preference for the formation of disklike structures in the (Q<0 ,R<0 ) quadrant. With the method shown to be useful for a turbulence that is already understood well, it should be of even greater utility for studying complex flows seen in industry and the environment.

Statistical Significance of Periodicity and Log-Periodicity with Heavy-Tailed Correlated Noise

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

We estimate the probability that random noise, of several plausible standard distributions, creates a false alarm that a periodicity (or log-periodicity) is found in a time series. The solution of this problem is already known for independent Gaussian distributed noise. We investigate more general situations with non-Gaussian correlated noises and present synthetic tests on the detectability and statistical significance of periodic components. A periodic component of a time series is usually detected by some sort of Fourier analysis. Here, we use the Lomb periodogram analysis, which is suitable and outperforms Fourier transforms for unevenly sampled time series. We examine the false-alarm probability of the largest spectral peak of the Lomb periodogram in the presence of power-law distributed noises, of short-range and of long-range fractional-Gaussian noises. Increasing heavy-tailness (respectively correlations describing persistence) tends to decrease (respectively increase) the false-alarm probability of finding a large spurious Lomb peak. Increasing anti-persistence tends to decrease the false-alarm probability. We also study the interplay between heavy-tailness and long-range correlations. In order to fully determine if a Lomb peak signals a genuine rather than a spurious periodicity, one should in principle characterize the Lomb peak height, its width and its relations to other peaks in the complete spectrum. As a step towards this full characterization, we construct the joint-distribution of the frequency position (relative to other peaks) and of the height of the highest peak of the power spectrum. We also provide the distributions of the ratio of the highest Lomb peak to the second highest one. Using the insight obtained by the present statistical study, we re-examine previously reported claims of ``log-periodicity'' and find that the credibility for log-periodicity in 2D-freely decaying turbulence is weakened while it is strengthened for fracture, for the

Why publishing everything is more effective than selective publishing of statistically significant results.

PubMed

van Assen, Marcel A L M; van Aert, Robbie C M; Nuijten, Michèle B; Wicherts, Jelte M

2014-01-01

De Winter and Happee examined whether science based on selective publishing of significant results may be effective in accurate estimation of population effects, and whether this is even more effective than a science in which all results are published (i.e., a science without publication bias). Based on their simulation study they concluded that "selective publishing yields a more accurate meta-analytic estimation of the true effect than publishing everything, (and that) publishing nonreplicable results while placing null results in the file drawer can be beneficial for the scientific collective" (p.4). Using their scenario with a small to medium population effect size, we show that publishing everything is more effective for the scientific collective than selective publishing of significant results. Additionally, we examined a scenario with a null effect, which provides a more dramatic illustration of the superiority of publishing everything over selective publishing. Publishing everything is more effective than only reporting significant outcomes.

Why Publishing Everything Is More Effective than Selective Publishing of Statistically Significant Results

PubMed Central

van Assen, Marcel A. L. M.; van Aert, Robbie C. M.; Nuijten, Michèle B.; Wicherts, Jelte M.

2014-01-01

Background De Winter and Happee [1] examined whether science based on selective publishing of significant results may be effective in accurate estimation of population effects, and whether this is even more effective than a science in which all results are published (i.e., a science without publication bias). Based on their simulation study they concluded that “selective publishing yields a more accurate meta-analytic estimation of the true effect than publishing everything, (and that) publishing nonreplicable results while placing null results in the file drawer can be beneficial for the scientific collective” (p.4). Methods and Findings Using their scenario with a small to medium population effect size, we show that publishing everything is more effective for the scientific collective than selective publishing of significant results. Additionally, we examined a scenario with a null effect, which provides a more dramatic illustration of the superiority of publishing everything over selective publishing. Conclusion Publishing everything is more effective than only reporting significant outcomes. PMID:24465448

Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?

NASA Astrophysics Data System (ADS)

Vu, Minh Tue; Aribarg, Thannob; Supratid, Siriporn; Raghavan, Srivatsan V.; Liong, Shie-Yui

2016-11-01

Artificial neural network (ANN) is an established technique with a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data. The present study utilizes ANN as a method of statistically downscaling global climate models (GCMs) during the rainy season at meteorological site locations in Bangkok, Thailand. The study illustrates the applications of the feed forward back propagation using large-scale predictor variables derived from both the ERA-Interim reanalyses data and present day/future GCM data. The predictors are first selected over different grid boxes surrounding Bangkok region and then screened by using principal component analysis (PCA) to filter the best correlated predictors for ANN training. The reanalyses downscaled results of the present day climate show good agreement against station precipitation with a correlation coefficient of 0.8 and a Nash-Sutcliffe efficiency of 0.65. The final downscaled results for four GCMs show an increasing trend of precipitation for rainy season over Bangkok by the end of the twenty-first century. The extreme values of precipitation determined using statistical indices show strong increases of wetness. These findings will be useful for policy makers in pondering adaptation measures due to flooding such as whether the current drainage network system is sufficient to meet the changing climate and to plan for a range of related adaptation/mitigation measures.

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2010-06-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The r-largest annual maxima method provides more reliable predictions of the extreme values especially for small return periods (<100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Natural time analysis and Tsallis non-additive entropy statistical mechanics.

NASA Astrophysics Data System (ADS)

Sarlis, N. V.; Skordas, E. S.; Varotsos, P.

2016-12-01

Upon analyzing the seismic data in natural time and employing a sliding natural time window comprising a number of events that would occur in a few months, it has been recently uncovered[1] that a precursory Seismic Electric Signals activity[2] initiates almost simultaneously with the appearance of a minimum in the fluctuations of the order parameter of seismicity [3]. Such minima have been ascertained [4] during periods of the magnitude time series exhibiting long range correlations [5] a few months before all earthquakes of magnitude 7.6 or larger that occurred in the entire Japanese area from 1 January 1984 to 11 March 2011 (the day of the M9 Tohoku-Oki earthquake). Before and after these minima, characteristic changes of the temporal correlations between earthquake magnitudes are observed which cannot be captured by Tsallis non-additive entropy statistical mechanics in the frame of which it has been suggested that kappa distributions arise [6]. Here, we extend the study concerning the existence of such minima in a large area that includes Aegean Sea and its surrounding area which exhibits in general seismo-tectonics [7] different than that of the entire Japanese area. References P. A. Varotsos et al., Tectonophysics, 589 (2013) 116. P. Varotsos and M. Lazaridou, Tectonophysics 188 (1991) 321. P.A. Varotsos et al., Phys Rev E 72 (2005) 041103. N. V. Sarlis et al., Proc Natl Acad Sci USA 110 (2013) 13734. P. A. Varotsos, N. V. Sarlis, and E. S. Skordas, J Geophys Res Space Physics 119 (2014), 9192, doi: 10.1002/2014JA0205800. G. Livadiotis, and D. J. McComas, J Geophys Res 114 (2009) A11105, doi:10.1029/2009JA014352. S. Uyeda et al., Tectonophysics, 304 (1999) 41.

On the statistical significance of excess events: Remarks of caution and the need for a standard method of calculation

NASA Technical Reports Server (NTRS)

Staubert, R.

1985-01-01

Methods for calculating the statistical significance of excess events and the interpretation of the formally derived values are discussed. It is argued that a simple formula for a conservative estimate should generally be used in order to provide a common understanding of quoted values.

Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

PubMed

Hashim, Muhammad Jawad

2010-09-01

Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

Scalable detection of statistically significant communities and hierarchies, using message passing for modularity

PubMed Central

Zhang, Pan; Moore, Cristopher

2014-01-01

Modularity is a popular measure of community structure. However, maximizing the modularity can lead to many competing partitions, with almost the same modularity, that are poorly correlated with each other. It can also produce illusory ‘‘communities’’ in random graphs where none exist. We address this problem by using the modularity as a Hamiltonian at finite temperature and using an efficient belief propagation algorithm to obtain the consensus of many partitions with high modularity, rather than looking for a single partition that maximizes it. We show analytically and numerically that the proposed algorithm works all of the way down to the detectability transition in networks generated by the stochastic block model. It also performs well on real-world networks, revealing large communities in some networks where previous work has claimed no communities exist. Finally we show that by applying our algorithm recursively, subdividing communities until no statistically significant subcommunities can be found, we can detect hierarchical structure in real-world networks more efficiently than previous methods. PMID:25489096

Impaired Statistical Learning in Developmental Dyslexia

PubMed Central

Thiessen, Erik D.; Holt, Lori L.

2015-01-01

Purpose Developmental dyslexia (DD) is commonly thought to arise from phonological impairments. However, an emerging perspective is that a more general procedural learning deficit, not specific to phonological processing, may underlie DD. The current study examined if individuals with DD are capable of extracting statistical regularities across sequences of passively experienced speech and nonspeech sounds. Such statistical learning is believed to be domain-general, to draw upon procedural learning systems, and to relate to language outcomes. Method DD and control groups were familiarized with a continuous stream of syllables or sine-wave tones, the ordering of which was defined by high or low transitional probabilities across adjacent stimulus pairs. Participants subsequently judged two 3-stimulus test items with either high or low statistical coherence as being the most similar to the sounds heard during familiarization. Results As with control participants, the DD group was sensitive to the transitional probability structure of the familiarization materials as evidenced by above-chance performance. However, the performance of participants with DD was significantly poorer than controls across linguistic and nonlinguistic stimuli. In addition, reading-related measures were significantly correlated with statistical learning performance of both speech and nonspeech material. Conclusion Results are discussed in light of procedural learning impairments among participants with DD. PMID:25860795

Data-driven inference for the spatial scan statistic.

PubMed

Almeida, Alexandre C L; Duarte, Anderson R; Duczmal, Luiz H; Oliveira, Fernando L P; Takahashi, Ricardo H C

2011-08-02

Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

The evidence for clinically significant bias in plasma glucose between liquid and lyophilized citrate buffer additive.

PubMed

Juricic, Gordana; Saracevic, Andrea; Kopcinovic, Lara Milevoj; Bakliza, Ana; Simundic, Ana-Maria

2016-12-01

Citrate buffer additive has been suggested to be of supreme performance in inhibiting glycolysis. However, there is little evidence in the literature regarding the comparability of glucose concentrations in liquid and lyophilized citrate buffer containing tubes. The aim of this study was to compare glucose concentrations in tubes containing liquid (Glucomedics) and lyophilized citrate buffer (Terumo VENOSAFE™ Glycemia) additive, measured immediately after centrifugation. Blood was collected from forty volunteers into both Glucomedics and Venosafe Glycemia tubes. Blood was centrifuged within 15min from venipuncture and glucose concentration was measured immediately after centrifugation, on the Abbott Architect analyzer. Differences between glucose concentrations in Glucomedics and Terumo tubes were tested using the paired t-test. Mean bias was calculated and compared to recommended quality specification for glucose (i.e. 2.2%). Glucose concentration in Terumo tubes was 3.4% lower than in Glucomedics tubes (P<0.001). The mean bias was clinically significant. There is a clinically significant difference between glucose concentrations in liquid and lyophilized citrate buffer additive tubes (Glucomedics vs. Terumo tubes) measured immediately after centrifugation. This difference may affect the patient outcome due to the misclassification of diabetes. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.

PubMed

Wang, Hong-Qiang; Tsai, Chung-Jui

2013-01-01

With the rapid increase of omics data, correlation analysis has become an indispensable tool for inferring meaningful associations from a large number of observations. Pearson correlation coefficient (PCC) and its variants are widely used for such purposes. However, it remains challenging to test whether an observed association is reliable both statistically and biologically. We present here a new method, CorSig, for statistical inference of correlation significance. CorSig is based on a biology-informed null hypothesis, i.e., testing whether the true PCC (ρ) between two variables is statistically larger than a user-specified PCC cutoff (τ), as opposed to the simple null hypothesis of ρ = 0 in existing methods, i.e., testing whether an association can be declared without a threshold. CorSig incorporates Fisher's Z transformation of the observed PCC (r), which facilitates use of standard techniques for p-value computation and multiple testing corrections. We compared CorSig against two methods: one uses a minimum PCC cutoff while the other (Zhu's procedure) controls correlation strength and statistical significance in two discrete steps. CorSig consistently outperformed these methods in various simulation data scenarios by balancing between false positives and false negatives. When tested on real-world Populus microarray data, CorSig effectively identified co-expressed genes in the flavonoid pathway, and discriminated between closely related gene family members for their differential association with flavonoid and lignin pathways. The p-values obtained by CorSig can be used as a stand-alone parameter for stratification of co-expressed genes according to their correlation strength in lieu of an arbitrary cutoff. CorSig requires one single tunable parameter, and can be readily extended to other correlation measures. Thus, CorSig should be useful for a wide range of applications, particularly for network analysis of high-dimensional genomic data. A web server for

2017 Annual Disability Statistics Supplement

ERIC Educational Resources Information Center

Lauer, E. A; Houtenville, A. J.

2018-01-01

The "Annual Disability Statistics Supplement" is a companion report to the "Annual Disability Statistics Compendium." The "Supplement" presents statistics on the same topics as the "Compendium," with additional categorizations by demographic characteristics including age, gender and race/ethnicity. In…

In vitro bioassays reveal that additives are significant contributors to the toxicity of commercial household pesticides.

PubMed

van de Merwe, Jason P; Neale, Peta A; Melvin, Steven D; Leusch, Frederic D L

2018-06-01

Pesticides commonly used around households can contain additives of unknown concentrations and toxicity. Given the likelihood of these chemicals washing into urban waterways, it is important to understand the effects that these additives may have on aquatic organisms. The aim of this study was to compare the toxicity of commercially available household pesticides to that of the active ingredient(s) alone. The toxicity of five household pesticides (three herbicides and two insecticides) was investigated using a bacterial cytotoxicity bioassay and an algal photosynthesis bioassay. The commercial products were up to an order of magnitude more toxic than the active ingredient(s) alone. In addition, two commercial products with the same listed active ingredients in the same ratio had a 600× difference in potency. These results clearly demonstrate that additives in commercial formulations are significant contributors to the toxicity of household pesticides. The toxicity of pesticides in aquatic systems is therefore likely underestimated by conventional chemical monitoring and risk assessment when only the active ingredients are considered. Regulators and customers should require more clarity from pesticide manufacturers about the nature and concentrations of not only the active ingredients, but also additives used in commercial formulations. In addition, monitoring programmes and chemical risk assessments schemes should develop a structured approach to assessing the toxic effects of commercial formulations, including additives, rather than simply those of the listed active ingredients. Copyright © 2018. Published by Elsevier B.V.

Searching for statistically significant regulatory modules.

PubMed

Bailey, Timothy L; Noble, William Stafford

2003-10-01

The regulatory machinery controlling gene expression is complex, frequently requiring multiple, simultaneous DNA-protein interactions. The rate at which a gene is transcribed may depend upon the presence or absence of a collection of transcription factors bound to the DNA near the gene. Locating transcription factor binding sites in genomic DNA is difficult because the individual sites are small and tend to occur frequently by chance. True binding sites may be identified by their tendency to occur in clusters, sometimes known as regulatory modules. We describe an algorithm for detecting occurrences of regulatory modules in genomic DNA. The algorithm, called mcast, takes as input a DNA database and a collection of binding site motifs that are known to operate in concert. mcast uses a motif-based hidden Markov model with several novel features. The model incorporates motif-specific p-values, thereby allowing scores from motifs of different widths and specificities to be compared directly. The p-value scoring also allows mcast to only accept motif occurrences with significance below a user-specified threshold, while still assigning better scores to motif occurrences with lower p-values. mcast can search long DNA sequences, modeling length distributions between motifs within a regulatory module, but ignoring length distributions between modules. The algorithm produces a list of predicted regulatory modules, ranked by E-value. We validate the algorithm using simulated data as well as real data sets from fruitfly and human. http://meme.sdsc.edu/MCAST/paper

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2009-09-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 70's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The study shows the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

SU-F-BRD-05: Dosimetric Comparison of Protocol-Based SBRT Lung Treatment Modalities: Statistically Significant VMAT Advantages Over Fixed- Beam IMRT

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

Best, R; Harrell, A; Geesey, C

2014-06-15

Purpose: The purpose of this study is to inter-compare and find statistically significant differences between flattened field fixed-beam (FB) IMRT with flattening-filter free (FFF) volumetric modulated arc therapy (VMAT) for stereotactic body radiation therapy SBRT. Methods: SBRT plans using FB IMRT and FFF VMAT were generated for fifteen SBRT lung patients using 6 MV beams. For each patient, both IMRT and VMAT plans were created for comparison. Plans were generated utilizing RTOG 0915 (peripheral, 10 patients) and RTOG 0813 (medial, 5 patients) lung protocols. Target dose, critical structure dose, and treatment time were compared and tested for statistical significance. Parametersmore » of interest included prescription isodose surface coverage, target dose heterogeneity, high dose spillage (location and volume), low dose spillage (location and volume), lung dose spillage, and critical structure maximum- and volumetric-dose limits. Results: For all criteria, we found equivalent or higher conformality with VMAT plans as well as reduced critical structure doses. Several differences passed a Student's t-test of significance: VMAT reduced the high dose spillage, evaluated with conformality index (CI), by an average of 9.4%±15.1% (p=0.030) compared to IMRT. VMAT plans reduced the lung volume receiving 20 Gy by 16.2%±15.0% (p=0.016) compared with IMRT. For the RTOG 0915 peripheral lesions, the volumes of lung receiving 12.4 Gy and 11.6 Gy were reduced by 27.0%±13.8% and 27.5%±12.6% (for both, p<0.001) in VMAT plans. Of the 26 protocol pass/fail criteria, VMAT plans were able to achieve an average of 0.2±0.7 (p=0.026) more constraints than the IMRT plans. Conclusions: FFF VMAT has dosimetric advantages over fixed beam IMRT for lung SBRT. Significant advantages included increased dose conformity, and reduced organs-at-risk doses. The overall improvements in terms of protocol pass/fail criteria were more modest and will require more patient data to establish

Funding source and primary outcome changes in clinical trials registered on ClinicalTrials.gov are associated with the reporting of a statistically significant primary outcome: a cross-sectional study.

PubMed

Ramagopalan, Sreeram V; Skingsley, Andrew P; Handunnetthi, Lahiru; Magnus, Daniel; Klingel, Michelle; Pakpoor, Julia; Goldacre, Ben

2015-01-01

We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3%) had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome .  Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Teaching Biology through Statistics: Application of Statistical Methods in Genetics and Zoology Courses

PubMed Central

Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.

2011-01-01

Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math–biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology. PMID:21885822

Teaching biology through statistics: application of statistical methods in genetics and zoology courses.

PubMed

Colon-Berlingeri, Migdalisel; Burrowes, Patricia A

2011-01-01

Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math-biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology.

Significant lexical relationships

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

Pedersen, T.; Kayaalp, M.; Bruce, R.

Statistical NLP inevitably deals with a large number of rare events. As a consequence, NLP data often violates the assumptions implicit in traditional statistical procedures such as significance testing. We describe a significance test, an exact conditional test, that is appropriate for NLP data and can be performed using freely available software. We apply this test to the study of lexical relationships and demonstrate that the results obtained using this test are both theoretically more reliable and different from the results obtained using previously applied tests.

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

NASA Technical Reports Server (NTRS)

Sharma, Manali; Das, Kamalika; Bilgic, Mustafa; Matthews, Bryan; Nielsen, David Lynn; Oza, Nikunj C.

2016-01-01

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

Sodium-Reduced Meat and Poultry Products Contain a Significant Amount of Potassium from Food Additives.

PubMed

Parpia, Arti Sharma; Goldstein, Marc B; Arcand, JoAnne; Cho, France; L'Abbé, Mary R; Darling, Pauline B

2018-05-01

-sodium-reduced counterparts (mean difference [95% CI]: 486 [334-638]; P<0.001). The amounts of phosphorus and protein, as well as the frequency of phosphorus additives appearing on the product label ingredient list, did not significantly differ between the two groups. Potassium additives are frequently added to sodium-reduced MPPs in amounts that significantly contribute to the potassium load for patients with impaired renal handling of potassium caused by chronic kidney disease and certain medications. Patients requiring potassium restriction should be counseled to be cautious regarding the potassium content of sodium-reduced MPPs and encouraged to make food choices accordingly. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Primarily Statistics: Developing an Introductory Statistics Course for Pre-Service Elementary Teachers

ERIC Educational Resources Information Center

Green, Jennifer L.; Blankenship, Erin E.

2013-01-01

We developed an introductory statistics course for pre-service elementary teachers. In this paper, we describe the goals and structure of the course, as well as the assessments we implemented. Additionally, we use example course work to demonstrate pre-service teachers' progress both in learning statistics and as novice teachers. Overall, the…

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in amore » stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

PubMed

Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis.

PubMed

Langan, Dean; Higgins, Julian P T; Gregory, Walter; Sutton, Alexander J

2012-05-01

We aim to illustrate the potential impact of a new study on a meta-analysis, which gives an indication of the robustness of the meta-analysis. A number of augmentations are proposed to one of the most widely used of graphical displays, the funnel plot. Namely, 1) statistical significance contours, which define regions of the funnel plot in which a new study would have to be located to change the statistical significance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis. Several other features are also described, and the use of multiple features simultaneously is considered. The statistical significance contours suggest that one additional study, no matter how large, may have a very limited impact on the statistical significance of a meta-analysis. The heterogeneity contours illustrate that one outlying study can increase the level of heterogeneity dramatically. The additional features of the funnel plot have applications including 1) informing sample size calculations for the design of future studies eligible for inclusion in the meta-analysis; and 2) informing the updating prioritization of a portfolio of meta-analyses such as those prepared by the Cochrane Collaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Time series, periodograms, and significance

NASA Astrophysics Data System (ADS)

Hernandez, G.

1999-05-01

The geophysical literature shows a wide and conflicting usage of methods employed to extract meaningful information on coherent oscillations from measurements. This makes it difficult, if not impossible, to relate the findings reported by different authors. Therefore, we have undertaken a critical investigation of the tests and methodology used for determining the presence of statistically significant coherent oscillations in periodograms derived from time series. Statistical significance tests are only valid when performed on the independent frequencies present in a measurement. Both the number of possible independent frequencies in a periodogram and the significance tests are determined by the number of degrees of freedom, which is the number of true independent measurements, present in the time series, rather than the number of sample points in the measurement. The number of degrees of freedom is an intrinsic property of the data, and it must be determined from the serial coherence of the time series. As part of this investigation, a detailed study has been performed which clearly illustrates the deleterious effects that the apparently innocent and commonly used processes of filtering, de-trending, and tapering of data have on periodogram analysis and the consequent difficulties in the interpretation of the statistical significance thus derived. For the sake of clarity, a specific example of actual field measurements containing unevenly-spaced measurements, gaps, etc., as well as synthetic examples, have been used to illustrate the periodogram approach, and pitfalls, leading to the (statistical) significance tests for the presence of coherent oscillations. Among the insights of this investigation are: (1) the concept of a time series being (statistically) band limited by its own serial coherence and thus having a critical sampling rate which defines one of the necessary requirements for the proper statistical design of an experiment; (2) the design of a critical

Statistical Literacy as a Function of Online versus Hybrid Course Delivery Format for an Introductory Graduate Statistics Course

ERIC Educational Resources Information Center

Hahs-Vaughn, Debbie L.; Acquaye, Hannah; Griffith, Matthew D.; Jo, Hang; Matthews, Ken; Acharya, Parul

2017-01-01

Statistical literacy refers to understanding fundamental statistical concepts. Assessment of statistical literacy can take the forms of tasks that require students to identify, translate, compute, read, and interpret data. In addition, statistical instruction can take many forms encompassing course delivery format such as face-to-face, hybrid,…

Statistical Modeling of Zr/Hf Extraction using TBP-D2EHPA Mixtures

NASA Astrophysics Data System (ADS)

Rezaeinejhad Jirandehi, Vahid; Haghshenas Fatmehsari, Davoud; Firoozi, Sadegh; Taghizadeh, Mohammad; Keshavarz Alamdari, Eskandar

2012-12-01

In the present work, response surface methodology was employed for the study and prediction of Zr/Hf extraction curves in a solvent extraction system using D2EHPA-TBP mixtures. The effect of change in the levels of temperature, nitric acid concentration, and TBP/D2EHPA ratio (T/D) on the Zr/Hf extraction/separation was studied by the use of central composite design. The results showed a statistically significant effect of T/D, nitric acid concentration, and temperature on the extraction percentage of Zr and Hf. In the case of Zr, a statistically significant interaction was found between T/D and nitric acid, whereas for Hf, both interactive terms between temperature and T/D and nitric acid were significant. Additionally, the extraction curves were profitably predicted applying the developed statistical regression equations; this approach is faster and more economical compared with experimentally obtained curves.

Statistical Analysis of Compressive and Flexural Test Results on the Sustainable Adobe Reinforced with Steel Wire Mesh

NASA Astrophysics Data System (ADS)

Jokhio, Gul A.; Syed Mohsin, Sharifah M.; Gul, Yasmeen

2018-04-01

It has been established that Adobe provides, in addition to being sustainable and economic, a better indoor air quality without spending extensive amounts of energy as opposed to the modern synthetic materials. The material, however, suffers from weak structural behaviour when subjected to adverse loading conditions. A wide range of mechanical properties has been reported in literature owing to lack of research and standardization. The present paper presents the statistical analysis of the results that were obtained through compressive and flexural tests on Adobe samples. Adobe specimens with and without wire mesh reinforcement were tested and the results were reported. The statistical analysis of these results presents an interesting read. It has been found that the compressive strength of adobe increases by about 43% after adding a single layer of wire mesh reinforcement. This increase is statistically significant. The flexural response of Adobe has also shown improvement with the addition of wire mesh reinforcement, however, the statistical significance of the same cannot be established.

Efficiently Identifying Significant Associations in Genome-wide Association Studies

PubMed Central

Eskin, Eleazar

2013-01-01

Abstract Over the past several years, genome-wide association studies (GWAS) have implicated hundreds of genes in common disease. More recently, the GWAS approach has been utilized to identify regions of the genome that harbor variation affecting gene expression or expression quantitative trait loci (eQTLs). Unlike GWAS applied to clinical traits, where only a handful of phenotypes are analyzed per study, in eQTL studies, tens of thousands of gene expression levels are measured, and the GWAS approach is applied to each gene expression level. This leads to computing billions of statistical tests and requires substantial computational resources, particularly when applying novel statistical methods such as mixed models. We introduce a novel two-stage testing procedure that identifies all of the significant associations more efficiently than testing all the single nucleotide polymorphisms (SNPs). In the first stage, a small number of informative SNPs, or proxies, across the genome are tested. Based on their observed associations, our approach locates the regions that may contain significant SNPs and only tests additional SNPs from those regions. We show through simulations and analysis of real GWAS datasets that the proposed two-stage procedure increases the computational speed by a factor of 10. Additionally, efficient implementation of our software increases the computational speed relative to the state-of-the-art testing approaches by a factor of 75. PMID:24033261

Antecedents of students' achievement in statistics

NASA Astrophysics Data System (ADS)

Awaludin, Izyan Syazana; Razak, Ruzanna Ab; Harris, Hezlin; Selamat, Zarehan

2015-02-01

The applications of statistics in most fields have been vast. Many degree programmes at local universities require students to enroll in at least one statistics course. The standard of these courses varies across different degree programmes. This is because of students' diverse academic backgrounds in which some comes far from the field of statistics. The high failure rate in statistics courses for non-science stream students had been concerning every year. The purpose of this research is to investigate the antecedents of students' achievement in statistics. A total of 272 students participated in the survey. Multiple linear regression was applied to examine the relationship between the factors and achievement. We found that statistics anxiety was a significant predictor of students' achievement. We also found that students' age has significant effect to achievement. Older students are more likely to achieve lowers scores in statistics. Student's level of study also has a significant impact on their achievement in statistics.

Sb2Te3 and Its Superlattices: Optimization by Statistical Design.

PubMed

Behera, Jitendra K; Zhou, Xilin; Ranjan, Alok; Simpson, Robert E

2018-05-02

The objective of this work is to demonstrate the usefulness of fractional factorial design for optimizing the crystal quality of chalcogenide van der Waals (vdW) crystals. We statistically analyze the growth parameters of highly c axis oriented Sb 2 Te 3 crystals and Sb 2 Te 3 -GeTe phase change vdW heterostructured superlattices. The statistical significance of the growth parameters of temperature, pressure, power, buffer materials, and buffer layer thickness was found by fractional factorial design and response surface analysis. Temperature, pressure, power, and their second-order interactions are the major factors that significantly influence the quality of the crystals. Additionally, using tungsten rather than molybdenum as a buffer layer significantly enhances the crystal quality. Fractional factorial design minimizes the number of experiments that are necessary to find the optimal growth conditions, resulting in an order of magnitude improvement in the crystal quality. We highlight that statistical design of experiment methods, which is more commonly used in product design, should be considered more broadly by those designing and optimizing materials.

Censored data treatment using additional information in intelligent medical systems

NASA Astrophysics Data System (ADS)

Zenkova, Z. N.

2015-11-01

Statistical procedures are a very important and significant part of modern intelligent medical systems. They are used for proceeding, mining and analysis of different types of the data about patients and their diseases; help to make various decisions, regarding the diagnosis, treatment, medication or surgery, etc. In many cases the data can be censored or incomplete. It is a well-known fact that censorship considerably reduces the efficiency of statistical procedures. In this paper the author makes a brief review of the approaches which allow improvement of the procedures using additional information, and describes a modified estimation of an unknown cumulative distribution function involving additional information about a quantile which is known exactly. The additional information is used by applying a projection of a classical estimator to a set of estimators with certain properties. The Kaplan-Meier estimator is considered as an estimator of the unknown cumulative distribution function, the properties of the modified estimator are investigated for a case of a single right censorship by means of simulations.

Worry, Intolerance of Uncertainty, and Statistics Anxiety

ERIC Educational Resources Information Center

Williams, Amanda S.

2013-01-01

Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were…

Reducing statistics anxiety and enhancing statistics learning achievement: effectiveness of a one-minute strategy.

PubMed

Chiou, Chei-Chang; Wang, Yu-Min; Lee, Li-Tze

2014-08-01

Statistical knowledge is widely used in academia; however, statistics teachers struggle with the issue of how to reduce students' statistics anxiety and enhance students' statistics learning. This study assesses the effectiveness of a "one-minute paper strategy" in reducing students' statistics-related anxiety and in improving students' statistics-related achievement. Participants were 77 undergraduates from two classes enrolled in applied statistics courses. An experiment was implemented according to a pretest/posttest comparison group design. The quasi-experimental design showed that the one-minute paper strategy significantly reduced students' statistics anxiety and improved students' statistics learning achievement. The strategy was a better instructional tool than the textbook exercise for reducing students' statistics anxiety and improving students' statistics achievement.

Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

USGS Publications Warehouse

Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

1999-01-01

Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

Do perfume additives termed human pheromones warrant being termed pheromones?

PubMed

Winman, Anders

2004-09-30

Two studies of the effects of perfume additives, termed human pheromones by the authors, have conveyed the message that these substances can promote an increase in human sociosexual behaviour [Physiol. Behav. 75 (2003) R1; Arch. Sex. Behav. 27 (1998) R2]. The present paper presents an extended analysis of this data. It is shown that in neither study is there a statistically significant increase in any of the sociosexual behaviours for the experimental groups. In the control groups of both studies, there are, however, moderate but statistically significant decreases in the corresponding behaviour. Most notably, there is no support in data for the claim that the substances increase the attractiveness of the wearers of the substances to the other sex. It is concluded that more research using matched homogenous groups of participants is needed. Copyright 2004 Elsevier Inc.

Course Format Effects on Learning Outcomes in an Introductory Statistics Course

ERIC Educational Resources Information Center

Sami, Fary

2011-01-01

The purpose of this study was to determine if course format significantly impacted student learning and course completion rates in an introductory statistics course taught at Harford Community College. In addition to the traditional lecture format, the College offers an online, and a hybrid (blend of traditional and online) version of this class.…

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.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

PubMed

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

Null-space and statistical significance of first-arrival traveltime inversion

NASA Astrophysics Data System (ADS)

Morozov, Igor B.

2004-03-01

The strong uncertainty inherent in the traveltime inversion of first arrivals from surface sources is usually removed by using a priori constraints or regularization. This leads to the null-space (data-independent model variability) being inadequately sampled, and consequently, model uncertainties may be underestimated in traditional (such as checkerboard) resolution tests. To measure the full null-space model uncertainties, we use unconstrained Monte Carlo inversion and examine the statistics of the resulting model ensembles. In an application to 1-D first-arrival traveltime inversion, the τ-p method is used to build a set of models that are equivalent to the IASP91 model within small, ~0.02 per cent, time deviations. The resulting velocity variances are much larger, ~2-3 per cent within the regions above the mantle discontinuities, and are interpreted as being due to the null-space. Depth-variant depth averaging is required for constraining the velocities within meaningful bounds, and the averaging scalelength could also be used as a measure of depth resolution. Velocity variances show structure-dependent, negative correlation with the depth-averaging scalelength. Neither the smoothest (Herglotz-Wiechert) nor the mean velocity-depth functions reproduce the discontinuities in the IASP91 model; however, the discontinuities can be identified by the increased null-space velocity (co-)variances. Although derived for a 1-D case, the above conclusions also relate to higher dimensions.

Statistical tests for power-law cross-correlated processes

NASA Astrophysics Data System (ADS)

Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

2011-12-01

For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

Additional Guidance on Prevention of Significant Deterioration (PSD) Regulations

EPA Pesticide Factsheets

This document may be of assistance in applying the New Source Review (NSR) air permitting regulations including the Prevention of Significant Deterioration (PSD) requirements. This document is part of the NSR Policy and Guidance Database. Some documents in the database are a scanned or retyped version of a paper photocopy of the original. Although we have taken considerable effort to quality assure the documents, some may contain typographical errors. Contact the office that issued the document if you need a copy of the original.

Statistics for People Who (Think They) Hate Statistics. Third Edition

ERIC Educational Resources Information Center

Salkind, Neil J.

2007-01-01

This text teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. The author takes students through various statistical procedures, beginning with correlation and graphical representation of data and ending with inferential techniques and analysis of variance. In addition, the text covers SPSS, and…

Use of statistical procedures in Brazilian and international dental journals.

PubMed

Ambrosano, Gláucia Maria Bovi; Reis, André Figueiredo; Giannini, Marcelo; Pereira, Antônio Carlos

2004-01-01

A descriptive survey was performed in order to assess the statistical content and quality of Brazilian and international dental journals, and compare their evolution throughout the last decades. The authors identified the reporting and accuracy of statistical techniques in 1000 papers published from 1970 to 2000 in seven dental journals: three Brazilian (Brazilian Dental Journal, Revista de Odontologia da Universidade de Sao Paulo and Revista de Odontologia da UNESP) and four international journals (Journal of the American Dental Association, Journal of Dental Research, Caries Research and Journal of Periodontology). Papers were divided into two time periods: from 1970 to 1989, and from 1990 to 2000. A slight increase in the number of articles that presented some form of statistical technique was noticed for Brazilian journals (from 61.0 to 66.7%), whereas for international journals, a significant increase was observed (65.8 to 92.6%). In addition, a decrease in the number of statistical errors was verified. The most commonly used statistical tests as well as the most frequent errors found in dental journals were assessed. Hopefully, this investigation will encourage dental educators to better plan the teaching of biostatistics, and to improve the statistical quality of submitted manuscripts.

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

PubMed

Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

2015-01-01

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data.

PubMed

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M; Wolters, Lidewij H; Huizenga, Hilde M

2015-03-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a data-analytic method to analyze univariate (i.e., one symptom) single-case data using the common package SPSS. This method can help the clinical researcher to investigate whether an intervention works as compared with a baseline period or another intervention type, and to determine whether symptom improvement is clinically significant. First, we describe the statistical method in a conceptual way and show how it can be implemented in SPSS. Simulation studies were performed to determine the number of observation points required per intervention phase. Second, to illustrate this method and its implications, we present a case study of an adolescent with anxiety disorders treated with cognitive-behavioral therapy techniques in an outpatient psychotherapy clinic, whose symptoms were regularly assessed before each session. We provide a description of the data analyses and results of this case study. Finally, we discuss the advantages and shortcomings of the proposed method. Copyright © 2014. Published by Elsevier Ltd.

Performance studies of GooFit on GPUs vs RooFit on CPUs while estimating the statistical significance of a new physical signal

NASA Astrophysics Data System (ADS)

Di Florio, Adriano

2017-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B + → J/ψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

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 ...

A Study to Determine if Addition of Palatal Petechiae to Centor Criteria Adds More Significance to Clinical Diagnosis of Acute Strep Pharyngitis in Children.

PubMed

Nibhanipudi, Kumara V

2016-01-01

Objective. A study to determine if addition of palatal petechiae to Centor criteria adds more value for clinical diagnosis of acute strep pharyngitis in children. Hypothesis. In children, Centor Criteria does not cover all the symptoms and signs of acute strep pharyngitis. We hypothesize that addition of palatal petechiae to Centor Criteria will increase the possibility of clinical diagnosis of group A streptococcal pharyngitis in children. Methods. One hundred patients with a complaint of sore throat were enrolled in the study. All the patients were examined clinically using the Centor Criteria. They were also examined for other signs and symptoms like petechial lesions over the palate, abdominal pain, and skin rash. All the patients were given rapid strep tests, and throat cultures were sent. No antibiotics were given until culture results were obtained. Results. The sample size was 100 patients. All 100 had fever, sore throat, and erythema of tonsils. Twenty of the 100 patients had tonsillar exudates, 85/100 had tender anterior cervical lymph nodes, and 86/100 had no cough. In total, 9 out of the 100 patients had positive throat cultures. We observed that petechiae over the palate, a very significant sign, is not included in the Centor Criteria. Palatal petechiae were present in 8 out of the 100 patients. Six out of these 8 with palatal petechiae had positive throat culture for strep (75%). Only 7 out of 20 with exudates had positive strep culture. Sixteen out of the 100 patients had rapid strep test positive. Those 84/100 who had negative rapid strep also had negative throat culture. Statistics. We used Fisher's exact test, comparing throat culture positive and negative versus presence of exudates and palatal hemorrhages with positive and negative throat cultures and the resultant P value <.0001. Conclusion. Our study concludes that addition of petechiae over the palate to Centor Criteria will increase the possibility of diagnosing acute group A streptococcal

SOCR: Statistics Online Computational Resource

PubMed Central

Dinov, Ivo D.

2011-01-01

The need for hands-on computer laboratory experience in undergraduate and graduate statistics education has been firmly established in the past decade. As a result a number of attempts have been undertaken to develop novel approaches for problem-driven statistical thinking, data analysis and result interpretation. In this paper we describe an integrated educational web-based framework for: interactive distribution modeling, virtual online probability experimentation, statistical data analysis, visualization and integration. Following years of experience in statistical teaching at all college levels using established licensed statistical software packages, like STATA, S-PLUS, R, SPSS, SAS, Systat, etc., we have attempted to engineer a new statistics education environment, the Statistics Online Computational Resource (SOCR). This resource performs many of the standard types of statistical analysis, much like other classical tools. In addition, it is designed in a plug-in object-oriented architecture and is completely platform independent, web-based, interactive, extensible and secure. Over the past 4 years we have tested, fine-tuned and reanalyzed the SOCR framework in many of our undergraduate and graduate probability and statistics courses and have evidence that SOCR resources build student’s intuition and enhance their learning. PMID:21451741

Titanic: A Statistical Exploration.

ERIC Educational Resources Information Center

Takis, Sandra L.

1999-01-01

Uses the available data about the Titanic's passengers to interest students in exploring categorical data and the chi-square distribution. Describes activities incorporated into a statistics class and gives additional resources for collecting information about the Titanic. (ASK)

Statistical Significance and Baseline Monitoring.

DTIC Science & Technology

1984-07-01

impacted at once........................... 24 6 Observed versus nominal a levels for multivariate tests of data sets (50 runs of 4 groups each...cumulative proportion of the observations found for each nominal level. The results of the comparisons of the observed versus nominal a levels for the...a values are always higher than nominal levels. Virtual- . .,ly all nominal a levels are below 0.20. In other words, the discriminant analysis models

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

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

PubMed Central

2008-01-01

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

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

PubMed

Metz, Anneke M

2008-01-01

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

Anaerobic sludge digestion with a biocatalytic additive

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

Ghosh, S.; Henry, M.P.; Fedde, P.A.

1982-01-01

The objective of this research was to evaluate the effects of a lactobacillus additive an anaerobic sludge digestion under normal, variable, and overload operating conditions. The additive was a whey fermentation product of an acid-tolerant strain of Lactobacillus acidophilus fortified with CaCO/sub 3/, (NH/sub 4/)/sub 2/HPO/sub 4/, ferrous lactate, and lactic acid. The lactobacillus additive is multifunctional in nature and provides growth factors, metabolic intermediates, and enzymes needed for substrate degradation and cellular synthesis. The experimental work consisted of several pairs of parallel mesophilic (35/sup 0/C) digestion runs (control and test) conducted in five experimental phases. Baseline runs without themore » additive showed that the two experimental digesters had the same methane content, gas production rate (GPR), and ethane yield. The effect of the additive was to increase methane yield and GPR by about 5% (which was statistically significant) during digester operation at a loading rate (LR) of 3.2 kg VS/m/sup 3/-day and a hydraulic retention time (HRT) of 14 days. Data collected from the various experimental phases showed that the biochemical additive increased methane yield, gas production rate, and VS reduction, and decreased volatile acids accumulation. In addition, it enhanced digester buffer capacity and improved the fertilizer value and dewatering characteristics of the digested residue.« less

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.

Prognostic Significance of POLE Proofreading Mutations in Endometrial Cancer

PubMed Central

Church, David N.; Stelloo, Ellen; Nout, Remi A.; Valtcheva, Nadejda; Depreeuw, Jeroen; ter Haar, Natalja; Noske, Aurelia; Amant, Frederic; Wild, Peter J.; Lambrechts, Diether; Jürgenliemk-Schulz, Ina M.; Jobsen, Jan J.; Smit, Vincent T. H. B. M.; Creutzberg, Carien L.; Bosse, Tjalling

2015-01-01

Background: Current risk stratification in endometrial cancer (EC) results in frequent over- and underuse of adjuvant therapy, and may be improved by novel biomarkers. We examined whether POLE proofreading mutations, recently reported in about 7% of ECs, predict prognosis. Methods: We performed targeted POLE sequencing in ECs from the PORTEC-1 and -2 trials (n = 788), and analyzed clinical outcome according to POLE status. We combined these results with those from three additional series (n = 628) by meta-analysis to generate multivariable-adjusted, pooled hazard ratios (HRs) for recurrence-free survival (RFS) and cancer-specific survival (CSS) of POLE-mutant ECs. All statistical tests were two-sided. Results: POLE mutations were detected in 48 of 788 (6.1%) ECs from PORTEC-1 and-2 and were associated with high tumor grade (P < .001). Women with POLE-mutant ECs had fewer recurrences (6.2% vs 14.1%) and EC deaths (2.3% vs 9.7%), though, in the total PORTEC cohort, differences in RFS and CSS were not statistically significant (multivariable-adjusted HR = 0.43, 95% CI = 0.13 to 1.37, P = .15; HR = 0.19, 95% CI = 0.03 to 1.44, P = .11 respectively). However, of 109 grade 3 tumors, 0 of 15 POLE-mutant ECs recurred, compared with 29 of 94 (30.9%) POLE wild-type cancers; reflected in statistically significantly greater RFS (multivariable-adjusted HR = 0.11, 95% CI = 0.001 to 0.84, P = .03). In the additional series, there were no EC-related events in any of 33 POLE-mutant ECs, resulting in a multivariable-adjusted, pooled HR of 0.33 for RFS (95% CI = 0.12 to 0.91, P = .03) and 0.26 for CSS (95% CI = 0.06 to 1.08, P = .06). Conclusion: POLE proofreading mutations predict favorable EC prognosis, independently of other clinicopathological variables, with the greatest effect seen in high-grade tumors. This novel biomarker may help to reduce overtreatment in EC. PMID:25505230

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Meteor trail footprint statistics

NASA Astrophysics Data System (ADS)

Mui, S. Y.; Ellicott, R. C.

Footprint statistics derived from field-test data are presented. The statistics are the probability that two receivers will lie in the same footprint. The dependence of the footprint statistics on the transmitter range, link orientation, and antenna polarization are examined. Empirical expressions for the footprint statistics are presented. The need to distinguish the instantaneous footprint, which is the area illuminated at a particular instant, from the composite footprint, which is the total area illuminated during the lifetime of the meteor trail, is explained. The statistics for the instantaneous and composite footprints have been found to be similar. The only significant difference lies in the parameter that represents the probability of two colocated receivers being in the same footprint. The composite footprint statistics can be used to calculate the space diversity gain of a multiple-receiver system. The instantaneous footprint statistics are useful in the evaluation of the interference probability in a network of meteor burst communication nodes.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

The additivity model assumed that field-scale reaction properties in a sediment including surface area, reactive site concentration, and reaction rate can be predicted from field-scale grain-size distribution by linearly adding reaction properties estimated in laboratory for individual grain-size fractions. This study evaluated the additivity model in scaling mass transfer-limited, multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of the rate constants for individual grain-size fractions, which were then used to predict rate-limited U(VI) desorption in the composite sediment. The resultmore » indicated that the additivity model with respect to the rate of U(VI) desorption provided a good prediction of U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel-size fraction (2 to 8 mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

Comparison of fatty acid profile in the chicken meat after feeding with narasin, nicarbazin and salinomycin sodium and phyto-additive substances.

PubMed

Angelovičová, Mária; Kunová, Simona; Čapla, Jozef; Zajac, Peter; Bučko, Ondřej; Angelovič, Marek

2016-01-01

The purpose of this study was an experimental investigation and a statistical evaluation of the influence of various additives in feed mixtures of broiler chickens on fatty acids content and their ratio in breast and thigh muscles. First feed additive consisted of narasin, nicarbasin and salinomycin sodium, and other five additives were of phytogenic origin. In vivo experiment was realized on the poultry experimental station with deep litter breeding system. A total of 300 one-day-old hybrid chickens Cobb 500 divided into six groups were used for the experiment. The experimental period was divided into four phases, i.e. Starter, Grower 1, Grower 2 and Final, according to the application of commercial feed mixture of soy cereal type. Additive substances used in feed mixtures were different for each group. Basic feed mixtures were equal for all groups. Fatty acid profile of breast and thigh muscles was measured by the method of FT IR Nicolet 6700. Investigated additive substances in the feed mixtures did not have statistically significant effect on fatty acid content and omega-6/omega-3 polyunsaturated fatty acid (PUFA) ratio in breast and thigh muscles. Strong statistically significant relation between omega-6 PUFAs and total PUFAs were proved by experiment. A relation between omega-3 PUFAs and total PUFAs was found only in the group with Biocitro additive.

Statistical lamb wave localization based on extreme value theory

NASA Astrophysics Data System (ADS)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

Physical and genetic-interaction density reveals functional organization and informs significance cutoffs in genome-wide screens

PubMed Central

Dittmar, John C.; Pierce, Steven; Rothstein, Rodney; Reid, Robert J. D.

2013-01-01

Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed “CLIK” (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality, determining screen cutoffs, and comparing results between screens. Furthermore, because CLIK uses previously annotated interaction data to determine biologically informed cutoffs, it provides additional insights into screen results, which supplement traditional statistical approaches. PMID:23589890

A Technology-Based Statistical Reasoning Assessment Tool in Descriptive Statistics for Secondary School Students

ERIC Educational Resources Information Center

Chan, Shiau Wei; Ismail, Zaleha

2014-01-01

The focus of assessment in statistics has gradually shifted from traditional assessment towards alternative assessment where more attention has been paid to the core statistical concepts such as center, variability, and distribution. In spite of this, there are comparatively few assessments that combine the significant three types of statistical…

How to read a paper. Statistics for the non-statistician. II: "Significant" relations and their pitfalls.

PubMed

Greenhalgh, T

1997-08-16

It is possible to be seriously misled by taking the statistical competence (and/or the intellectual honesty) of authors for granted. Some common errors committed (deliberately or inadvertently) by the authors of papers are given in the final box.

Effects of wall curvature on turbulence statistics

NASA Technical Reports Server (NTRS)

Moser, R. D.; Moin, P.

1985-01-01

A three-dimensional, time-dependent, direct numerical simulation of low-Reynolds number turbulent flow in a mildly curved channel was performed, and the results examined to determine the mechanism by which curvature affects wall-bounded turbulent shear flows. A spectral numerical method with about one-million modes was employed, and no explicit subgrid scale model was used. The effects of curvature on this flow were determined by comparing the concave and convex sides of the channel. The observed effects are consistent with experimental observations for mild curvature. The most significant difference in the turbulence statistics between the concave and convex sides is in the Reynolds shear stress. This is accompanied by significant differences in the terms of the Reynolds shear stress balance equations. In addition, it was found that stationary Taylor-Goertler vortices were present and that they had a significant effect on the flow by contributing to the mean Reynolds shear stress, and by enhancing the difference between the wall shear stresses.

How to read a paper. Statistics for the non-statistician. II: "Significant" relations and their pitfalls.

PubMed Central

Greenhalgh, T.

1997-01-01

It is possible to be seriously misled by taking the statistical competence (and/or the intellectual honesty) of authors for granted. Some common errors committed (deliberately or inadvertently) by the authors of papers are given in the final box. PMID:9277611

Factors related to student performance in statistics courses in Lebanon

NASA Astrophysics Data System (ADS)

Naccache, Hiba Salim

The purpose of the present study was to identify factors that may contribute to business students in Lebanese universities having difficulty in introductory and advanced statistics courses. Two statistics courses are required for business majors at Lebanese universities. Students are not obliged to be enrolled in any math courses prior to taking statistics courses. Drawing on recent educational research, this dissertation attempted to identify the relationship between (1) students’ scores on Lebanese university math admissions tests; (2) students’ scores on a test of very basic mathematical concepts; (3) students’ scores on the survey of attitude toward statistics (SATS); (4) course performance as measured by students’ final scores in the course; and (5) their scores on the final exam. Data were collected from 561 students enrolled in multiple sections of two courses: 307 students in the introductory statistics course and 260 in the advanced statistics course in seven campuses across Lebanon over one semester. The multiple regressions results revealed four significant relationships at the introductory level: between students’ scores on the math quiz with their (1) final exam scores; (2) their final averages; (3) the Cognitive subscale of the SATS with their final exam scores; and (4) their final averages. These four significant relationships were also found at the advanced level. In addition, two more significant relationships were found between students’ final average and the two subscales of Effort (5) and Affect (6). No relationship was found between students’ scores on the admission math tests and both their final exam scores and their final averages in both the introductory and advanced level courses. On the other hand, there was no relationship between students’ scores on Lebanese admissions tests and their final achievement. Although these results were consistent across course formats and instructors, they may encourage Lebanese universities

Perception of ensemble statistics requires attention.

PubMed

Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A

2017-02-01

To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Effect of Internet-Based Cognitive Apprenticeship Model (i-CAM) on Statistics Learning among Postgraduate Students.

PubMed

Saadati, Farzaneh; Ahmad Tarmizi, Rohani; Mohd Ayub, Ahmad Fauzi; Abu Bakar, Kamariah

2015-01-01

Because students' ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is 'value added' because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM) in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students' problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students.

Whole-genome scan reveals significant non-additive effects for sire conception rate in Holstein cattle.

PubMed

Nicolini, Paula; Amorín, Rocío; Han, Yi; Peñagaricano, Francisco

2018-02-27

Service sire has a considerable impact on reproductive success in dairy cattle. Most gene mapping studies for bull fertility have focused on additive effects, while non-additive effects have been largely ignored. The main goal of this study was to assess the relevance of non-additive effects on Sire Conception Rate (SCR) in Holstein dairy cattle. The analysis included 7.5 k Holstein bulls with both SCR records and 57.8 k single nucleotide polymorphism (SNP) markers spanning the entire genome. The importance of non-additive effects was evaluated using an efficient two-step mixed model-based approach. Four genomic regions located on chromosomes BTA8, BTA9, BTA13 and BTA17 showed marked dominance and/or recessive effects. Most of these regions harbor genes, such as ADAM28, DNAJA1, TBC1D20, SPO11, PIWIL3 and TMEM119, that are directly implicated in testis development, male germ line maintenance, and sperm maturation. This study provides further evidence for the relevance of non-additive effects in fitness-related traits, such as male fertility. In addition, these findings may point out new strategies for improving service sire fertility in dairy cattle via marker-assisted selection.

Unpolarized infrared emissivity with shadow from anisotropic rough sea surfaces with non-Gaussian statistics.

PubMed

Bourlier, Christophe

2005-07-10

The emissivity of two-dimensional anisotropic rough sea surfaces with non-Gaussian statistics is investigated. The emissivity derivation is of importance for retrieval of the sea-surface temperature or equivalent temperature of a rough sea surface by infrared thermal imaging. The well-known Cox-Munk slope probability-density function, considered non-Gaussian, is used for the emissivity derivation, in which the skewness and the kurtosis (related to the third- and fourth-order statistics, respectively) are included. The shadowing effect, which is significant for grazing angles, is also taken into account. The geometric optics approximation is assumed to be valid, which means that the rough surface is modeled as a collection of facets reflecting locally the light in the specular direction. In addition, multiple reflections are ignored. Numerical results of the emissivity are presented for Gaussian and non-Gaussian statistics, for moderate wind speeds, for near-infrared wavelengths, for emission angles ranging from 0 degrees (nadir) to 90 degrees (horizon), and according to the wind direction. In addition, the emissivity is compared with both measurements and a Monte Carlo ray-tracing method.

Statistical considerations for agroforestry studies

Treesearch

James A. Baldwin

1993-01-01

Statistical topics that related to agroforestry studies are discussed. These included study objectives, populations of interest, sampling schemes, sample sizes, estimation vs. hypothesis testing, and P-values. In addition, a relatively new and very much improved histogram display is described.

Pedagogical Utilization and Assessment of the Statistic Online Computational Resource in Introductory Probability and Statistics Courses.

PubMed

Dinov, Ivo D; Sanchez, Juana; Christou, Nicolas

2008-01-01

Technology-based instruction represents a new recent pedagogical paradigm that is rooted in the realization that new generations are much more comfortable with, and excited about, new technologies. The rapid technological advancement over the past decade has fueled an enormous demand for the integration of modern networking, informational and computational tools with classical pedagogical instruments. Consequently, teaching with technology typically involves utilizing a variety of IT and multimedia resources for online learning, course management, electronic course materials, and novel tools of communication, engagement, experimental, critical thinking and assessment.The NSF-funded Statistics Online Computational Resource (SOCR) provides a number of interactive tools for enhancing instruction in various undergraduate and graduate courses in probability and statistics. These resources include online instructional materials, statistical calculators, interactive graphical user interfaces, computational and simulation applets, tools for data analysis and visualization. The tools provided as part of SOCR include conceptual simulations and statistical computing interfaces, which are designed to bridge between the introductory and the more advanced computational and applied probability and statistics courses. In this manuscript, we describe our designs for utilizing SOCR technology in instruction in a recent study. In addition, present the results of the effectiveness of using SOCR tools at two different course intensity levels on three outcome measures: exam scores, student satisfaction and choice of technology to complete assignments. Learning styles assessment was completed at baseline. We have used three very different designs for three different undergraduate classes. Each course included a treatment group, using the SOCR resources, and a control group, using classical instruction techniques. Our findings include marginal effects of the SOCR treatment per individual

Pedagogical Utilization and Assessment of the Statistic Online Computational Resource in Introductory Probability and Statistics Courses

PubMed Central

Dinov, Ivo D.; Sanchez, Juana; Christou, Nicolas

2009-01-01

Technology-based instruction represents a new recent pedagogical paradigm that is rooted in the realization that new generations are much more comfortable with, and excited about, new technologies. The rapid technological advancement over the past decade has fueled an enormous demand for the integration of modern networking, informational and computational tools with classical pedagogical instruments. Consequently, teaching with technology typically involves utilizing a variety of IT and multimedia resources for online learning, course management, electronic course materials, and novel tools of communication, engagement, experimental, critical thinking and assessment. The NSF-funded Statistics Online Computational Resource (SOCR) provides a number of interactive tools for enhancing instruction in various undergraduate and graduate courses in probability and statistics. These resources include online instructional materials, statistical calculators, interactive graphical user interfaces, computational and simulation applets, tools for data analysis and visualization. The tools provided as part of SOCR include conceptual simulations and statistical computing interfaces, which are designed to bridge between the introductory and the more advanced computational and applied probability and statistics courses. In this manuscript, we describe our designs for utilizing SOCR technology in instruction in a recent study. In addition, present the results of the effectiveness of using SOCR tools at two different course intensity levels on three outcome measures: exam scores, student satisfaction and choice of technology to complete assignments. Learning styles assessment was completed at baseline. We have used three very different designs for three different undergraduate classes. Each course included a treatment group, using the SOCR resources, and a control group, using classical instruction techniques. Our findings include marginal effects of the SOCR treatment per individual

Statistics Anxiety among Postgraduate Students

ERIC Educational Resources Information Center

Koh, Denise; Zawi, Mohd Khairi

2014-01-01

Most postgraduate programmes, that have research components, require students to take at least one course of research statistics. Not all postgraduate programmes are science based, there are a significant number of postgraduate students who are from the social sciences that will be taking statistics courses, as they try to complete their…

Statistics Using Just One Formula

ERIC Educational Resources Information Center

Rosenthal, Jeffrey S.

2018-01-01

This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…

Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science.

PubMed

Veldkamp, Coosje L S; Nuijten, Michèle B; Dominguez-Alvarez, Linda; van Assen, Marcel A L M; Wicherts, Jelte M

2014-01-01

Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this 'co-piloting' currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors.

Statistics 101 for Radiologists.

PubMed

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Mechanical and Electrical Properties of a Polyimide Film Significantly Enhanced by the Addition of Single-Wall Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Meador, Michael A.

2005-01-01

Single-wall carbon nanotubes have been shown to possess a combination of outstanding mechanical, electrical, and thermal properties. The use of carbon nanotubes as an additive to improve the mechanical properties of polymers and/or enhance their thermal and electrical conductivity has been a topic of intense interest. Nanotube-modified polymeric materials could find a variety of applications in NASA missions including large-area antennas, solar arrays, and solar sails; radiation shielding materials for vehicles, habitats, and extravehicular activity suits; and multifunctional materials for vehicle structures and habitats. Use of these revolutionary materials could reduce vehicle weight significantly and improve vehicle performance and capabilities.

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.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Forest statistics of western Kentucky

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1950-01-01

This Survey Release presents the more significant preliminary statistics on the forest area and timber volume for the western region of Kentucky. Similar reports for the remainder of the state will be published as soon as statistical tabulations are completed. Later, an analytical report for the state will be published which will interpret forest area, timber volume,...

Forest statistics of southern Indiana

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1951-01-01

This Survey Release presents the more significant preliminary statistics on the forest area and timber volume for each of the three regions of southern Indiana. A similar report will be published for the two northern Indiana regions. Later, an analytical report for the state will be published which will interpret statistics on forest area, timber- volume, growth, and...

The Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing.

PubMed

Lash, Timothy L

2017-09-15

In the last few years, stakeholders in the scientific community have raised alarms about a perceived lack of reproducibility of scientific results. In reaction, guidelines for journals have been promulgated and grant applicants have been asked to address the rigor and reproducibility of their proposed projects. Neither solution addresses a primary culprit, which is the culture of null hypothesis significance testing that dominates statistical analysis and inference. In an innovative research enterprise, selection of results for further evaluation based on null hypothesis significance testing is doomed to yield a low proportion of reproducible results and a high proportion of effects that are initially overestimated. In addition, the culture of null hypothesis significance testing discourages quantitative adjustments to account for systematic errors and quantitative incorporation of prior information. These strategies would otherwise improve reproducibility and have not been previously proposed in the widely cited literature on this topic. Without discarding the culture of null hypothesis significance testing and implementing these alternative methods for statistical analysis and inference, all other strategies for improving reproducibility will yield marginal gains at best. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Additivity of nonlinear biomass equations

Treesearch

Bernard R. Parresol

2001-01-01

Two procedures that guarantee the property of additivity among the components of tree biomass and total tree biomass utilizing nonlinear functions are developed. Procedure 1 is a simple combination approach, and procedure 2 is based on nonlinear joint-generalized regression (nonlinear seemingly unrelated regressions) with parameter restrictions. Statistical theory is...

Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies.

PubMed

Lyons-Weiler, James; Pelikan, Richard; Zeh, Herbert J; Whitcomb, David C; Malehorn, David E; Bigbee, William L; Hauskrecht, Milos

2005-01-01

Peptide profiles generated using SELDI/MALDI time of flight mass spectrometry provide a promising source of patient-specific information with high potential impact on the early detection and classification of cancer and other diseases. The new profiling technology comes, however, with numerous challenges and concerns. Particularly important are concerns of reproducibility of classification results and their significance. In this work we describe a computational validation framework, called PACE (Permutation-Achieved Classification Error), that lets us assess, for a given classification model, the significance of the Achieved Classification Error (ACE) on the profile data. The framework compares the performance statistic of the classifier on true data samples and checks if these are consistent with the behavior of the classifier on the same data with randomly reassigned class labels. A statistically significant ACE increases our belief that a discriminative signal was found in the data. The advantage of PACE analysis is that it can be easily combined with any classification model and is relatively easy to interpret. PACE analysis does not protect researchers against confounding in the experimental design, or other sources of systematic or random error. We use PACE analysis to assess significance of classification results we have achieved on a number of published data sets. The results show that many of these datasets indeed possess a signal that leads to a statistically significant ACE.

Application of addition-cured silicone denture relining materials to adjust mouthguards.

PubMed

Fukasawa, Shintaro; Churei, Hiroshi; Chowdhury, Ruman Uddin; Shirako, Takahiro; Shahrin, Sharika; Shrestha, Abhishekhi; Wada, Takahiro; Uo, Motohiro; Takahashi, Hidekazu; Ueno, Toshiaki

2016-01-01

The purposes of this study were to examine the shock absorption capability of addition-cured silicone denture relining materials and the bonding strength of addition-cured silicone denture relining materials and a commercial mouthguard material to determine its applicability to mouthguard adjustment. Two addition-cured silicone denture relining materials and eleven commercial mouthguard materials were selected as test materials. The impact test was applied by a free-falling steel ball. On the other hand, bonding strength was determined by a delamination test. After prepared surface treatments using acrylic resin on MG sheet surface, 2 types of addition-cured silicone denture relining materials were glued to MG surface. The peak intensity, the time to peak intensity from the onset of the transmitted force and bonding strength were statistically analyzed using ANOVA and Tukey's honest significant difference post hoc test (p<0.05). These results suggest that the silicone denture relining materials could be clinically applicable as a mouthguard adjustment material.

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Statistical models and NMR analysis of polymer microstructure

USDA-ARS?s Scientific Manuscript database

Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...

Statistics of Statisticians: Critical Mass of Statistics and Operational Research Groups

NASA Astrophysics Data System (ADS)

Kenna, Ralph; Berche, Bertrand

Using a recently developed model, inspired by mean field theory in statistical physics, and data from the UK's Research Assessment Exercise, we analyse the relationship between the qualities of statistics and operational research groups and the quantities of researchers in them. Similar to other academic disciplines, we provide evidence for a linear dependency of quality on quantity up to an upper critical mass, which is interpreted as the average maximum number of colleagues with whom a researcher can communicate meaningfully within a research group. The model also predicts a lower critical mass, which research groups should strive to achieve to avoid extinction. For statistics and operational research, the lower critical mass is estimated to be 9 ± 3. The upper critical mass, beyond which research quality does not significantly depend on group size, is 17 ± 6.

BETTER STATISTICS FOR BETTER DECISIONS: REJECTING NULL HYPOTHESES STATISTICAL TESTS IN FAVOR OF REPLICATION STATISTICS

PubMed Central

SANABRIA, FEDERICO; KILLEEN, PETER R.

2008-01-01

Despite being under challenge for the past 50 years, null hypothesis significance testing (NHST) remains dominant in the scientific field for want of viable alternatives. NHST, along with its significance level p, is inadequate for most of the uses to which it is put, a flaw that is of particular interest to educational practitioners who too often must use it to sanctify their research. In this article, we review the failure of NHST and propose prep, the probability of replicating an effect, as a more useful statistic for evaluating research and aiding practical decision making. PMID:19122766

Effect of Internet-Based Cognitive Apprenticeship Model (i-CAM) on Statistics Learning among Postgraduate Students

PubMed Central

Saadati, Farzaneh; Ahmad Tarmizi, Rohani

2015-01-01

Because students’ ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is ‘value added’ because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM) in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students’ problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students. PMID:26132553

Lessons from Inferentialism for Statistics Education

ERIC Educational Resources Information Center

Bakker, Arthur; Derry, Jan

2011-01-01

This theoretical paper relates recent interest in informal statistical inference (ISI) to the semantic theory termed inferentialism, a significant development in contemporary philosophy, which places inference at the heart of human knowing. This theory assists epistemological reflection on challenges in statistics education encountered when…

Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science

PubMed Central

Veldkamp, Coosje L. S.; Nuijten, Michèle B.; Dominguez-Alvarez, Linda; van Assen, Marcel A. L. M.; Wicherts, Jelte M.

2014-01-01

Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this ‘co-piloting’ currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors. PMID:25493918

Pisces did not have increased heart failure: data-driven comparisons of binary proportions between levels of a categorical variable can result in incorrect statistical significance levels.

PubMed

Austin, Peter C; Goldwasser, Meredith A

2008-03-01

We examined the impact on statistical inference when a chi(2) test is used to compare the proportion of successes in the level of a categorical variable that has the highest observed proportion of successes with the proportion of successes in all other levels of the categorical variable combined. Monte Carlo simulations and a case study examining the association between astrological sign and hospitalization for heart failure. A standard chi(2) test results in an inflation of the type I error rate, with the type I error rate increasing as the number of levels of the categorical variable increases. Using a standard chi(2) test, the hospitalization rate for Pisces was statistically significantly different from that of the other 11 astrological signs combined (P=0.026). After accounting for the fact that the selection of Pisces was based on it having the highest observed proportion of heart failure hospitalizations, subjects born under the sign of Pisces no longer had a significantly higher rate of heart failure hospitalization compared to the other residents of Ontario (P=0.152). Post hoc comparisons of the proportions of successes across different levels of a categorical variable can result in incorrect inferences.

The Statistical Power of Planned Comparisons.

ERIC Educational Resources Information Center

Benton, Roberta L.

Basic principles underlying statistical power are examined; and issues pertaining to effect size, sample size, error variance, and significance level are highlighted via the use of specific hypothetical examples. Analysis of variance (ANOVA) and related methods remain popular, although other procedures sometimes have more statistical power against…

Illinois crash facts and statistics, 2002

DOT National Transportation Integrated Search

2002-01-01

This publication, Illinois Traffic Crash Facts : and Statistics for 2002, is designed to provide an : overview of motor vehicle crash experience in : Illinois. In addition to a plethora of crash data, the : publication includes key events in th...

Illinois crash facts and statistics, 2001

DOT National Transportation Integrated Search

2001-01-01

This publication, Illinois Traffic Crash Facts : and Statistics for 2001, is designed to provide an : overview of motor vehicle crash experience in : Illinois. In addition to a plethora of crash data, the : publication includes key events in th...

Illinois crash facts and statistics, 2003

DOT National Transportation Integrated Search

2003-01-01

This publication, Illinois Traffic Crash Facts : and Statistics for 2003, is designed to provide an : overview of motor vehicle crash experience in : Illinois. In addition to a plethora of crash data, the : publication includes key events in th...

Adjusted scaling of FDG positron emission tomography images for statistical evaluation in patients with suspected Alzheimer's disease.

PubMed

Buchert, Ralph; Wilke, Florian; Chakrabarti, Bhismadev; Martin, Brigitte; Brenner, Winfried; Mester, Janos; Clausen, Malte

2005-10-01

Statistical parametric mapping (SPM) gained increasing acceptance for the voxel-based statistical evaluation of brain positron emission tomography (PET) with the glucose analog 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) in patients with suspected Alzheimer's disease (AD). To increase the sensitivity for detection of local changes, individual differences of total brain FDG uptake are usually compensated for by proportional scaling. However, in cases of extensive hypometabolic areas, proportional scaling overestimates scaled uptake. This may cause significant underestimation of the extent of hypometabolic areas by the statistical test. To detect this problem, the authors tested for hypermetabolism. In patients with no visual evidence of true focal hypermetabolism, significant clusters of hypermetabolism in the presence of extended hypometabolism were interpreted as false-positive findings, indicating relevant overestimation of scaled uptake. In this case, scaled uptake was reduced step by step until there were no more significant clusters of hypermetabolism. In 22 consecutive patients with suspected AD, proportional scaling resulted in relevant overestimation of scaled uptake in 9 patients. Scaled uptake had to be reduced by 11.1% +/- 5.3% in these cases to eliminate the artifacts. Adjusted scaling resulted in extension of existing and appearance of new clusters of hypometabolism. Total volume of the additional voxels with significant hypometabolism depended linearly on the extent of the additional scaling and was 202 +/- 118 mL on average. Adjusted scaling helps to identify characteristic metabolic patterns in patients with suspected AD. It is expected to increase specificity of FDGPET in this group of patients.

Understanding Statistics - Cancer Statistics

Cancer.gov

Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

P-Value Club: Teaching Significance Level on the Dance Floor

ERIC Educational Resources Information Center

Gray, Jennifer

2010-01-01

Courses: Beginning research methods and statistics courses, as well as advanced communication courses that require reading research articles and completing research projects involving statistics. Objective: Students will understand the difference between significant and nonsignificant statistical results based on p-value.

[Cause-of-death statistics and ICD, quo vadis?

PubMed

Eckert, Olaf; Vogel, Ulrich

2018-07-01

The International Statistical Classification of Diseases and Related Health Problems (ICD) is the worldwide binding standard for generating underlying cause-of-death statistics. What are the effects of former revisions of the ICD on underlying cause-of-death statistics and which opportunities and challenges are becoming apparent in a possible transition process from ICD-10 to ICD-11?This article presents the calculation of the exploitation grade of ICD-9 and ICD-10 in the German cause-of-death statistics and quality of documentation. Approximately 67,000 anonymized German death certificates are processed by Iris/MUSE and official German cause-of-death statistics are analyzed.In addition to substantial changes in the exploitation grade in the transition from ICD-9 to ICD-10, regional effects become visible. The rate of so-called "ill-defined" conditions exceeds 10%.Despite substantial improvement of ICD revisions there are long-known deficits in the coroner's inquest, filling death certificates and quality of coding. To make better use of the ICD as a methodological framework for mortality statistics and health reporting in Germany, the following measures are necessary: 1. General use of Iris/MUSE, 2. Establishing multiple underlying cause-of-death statistics, 3. Introduction of an electronic death certificate, 4. Improvement of the medical assessment of cause of death.Within short time the WHO will release the 11th revision of the ICD that will provide additional opportunities for the development of underlying cause-of-death statistics and their use in science, public health and politics. A coordinated effort including participants in the process and users is necessary to meet the related challenges.

Assessment of corneal properties based on statistical modeling of OCT speckle.

PubMed

Jesus, Danilo A; Iskander, D Robert

2017-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike's Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence.

Assessment of corneal properties based on statistical modeling of OCT speckle

PubMed Central

Jesus, Danilo A.; Iskander, D. Robert

2016-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike’s Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence. PMID:28101409

Performance evaluation of spectral vegetation indices using a statistical sensitivity function

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2007-01-01

A great number of spectral vegetation indices (VIs) have been developed to estimate biophysical parameters of vegetation. Traditional techniques for evaluating the performance of VIs are regression-based statistics, such as the coefficient of determination and root mean square error. These statistics, however, are not capable of quantifying the detailed relationship between VIs and biophysical parameters because the sensitivity of a VI is usually a function of the biophysical parameter instead of a constant. To better quantify this relationship, we developed a “sensitivity function” for measuring the sensitivity of a VI to biophysical parameters. The sensitivity function is defined as the first derivative of the regression function, divided by the standard error of the dependent variable prediction. The function elucidates the change in sensitivity over the range of the biophysical parameter. The Student's t- or z-statistic can be used to test the significance of VI sensitivity. Additionally, we developed a “relative sensitivity function” that compares the sensitivities of two VIs when the biophysical parameters are unavailable.

Robot Trajectories Comparison: A Statistical Approach

PubMed Central

Ansuategui, A.; Arruti, A.; Susperregi, L.; Yurramendi, Y.; Jauregi, E.; Lazkano, E.; Sierra, B.

2014-01-01

The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners. PMID:25525618

Study Designs and Statistical Analyses for Biomarker Research

PubMed Central

Gosho, Masahiko; Nagashima, Kengo; Sato, Yasunori

2012-01-01

Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research. PMID:23012528

Confounding and Statistical Significance of Indirect Effects: Childhood Adversity, Education, Smoking, and Anxious and Depressive Symptomatology.

PubMed

Sheikh, Mashhood Ahmed

2017-01-01

association between childhood adversity and ADS in adulthood. However, when education was excluded as a mediator-response confounding variable, the indirect effect of childhood adversity on ADS in adulthood was statistically significant ( p < 0.05). This study shows that a careful inclusion of potential confounding variables is important when assessing mediation.

Confounding and Statistical Significance of Indirect Effects: Childhood Adversity, Education, Smoking, and Anxious and Depressive Symptomatology

PubMed Central

Sheikh, Mashhood Ahmed

2017-01-01

association between childhood adversity and ADS in adulthood. However, when education was excluded as a mediator-response confounding variable, the indirect effect of childhood adversity on ADS in adulthood was statistically significant (p < 0.05). This study shows that a careful inclusion of potential confounding variables is important when assessing mediation. PMID:28824498

The choice of statistical methods for comparisons of dosimetric data in radiotherapy.

PubMed

Chaikh, Abdulhamid; Giraud, Jean-Yves; Perrin, Emmanuel; Bresciani, Jean-Pierre; Balosso, Jacques

2014-09-18

Novel irradiation techniques are continuously introduced in radiotherapy to optimize the accuracy, the security and the clinical outcome of treatments. These changes could raise the question of discontinuity in dosimetric presentation and the subsequent need for practice adjustments in case of significant modifications. This study proposes a comprehensive approach to compare different techniques and tests whether their respective dose calculation algorithms give rise to statistically significant differences in the treatment doses for the patient. Statistical investigation principles are presented in the framework of a clinical example based on 62 fields of radiotherapy for lung cancer. The delivered doses in monitor units were calculated using three different dose calculation methods: the reference method accounts the dose without tissues density corrections using Pencil Beam Convolution (PBC) algorithm, whereas new methods calculate the dose with tissues density correction for 1D and 3D using Modified Batho (MB) method and Equivalent Tissue air ratio (ETAR) method, respectively. The normality of the data and the homogeneity of variance between groups were tested using Shapiro-Wilks and Levene test, respectively, then non-parametric statistical tests were performed. Specifically, the dose means estimated by the different calculation methods were compared using Friedman's test and Wilcoxon signed-rank test. In addition, the correlation between the doses calculated by the three methods was assessed using Spearman's rank and Kendall's rank tests. The Friedman's test showed a significant effect on the calculation method for the delivered dose of lung cancer patients (p <0.001). The density correction methods yielded to lower doses as compared to PBC by on average (-5 ± 4.4 SD) for MB and (-4.7 ± 5 SD) for ETAR. Post-hoc Wilcoxon signed-rank test of paired comparisons indicated that the delivered dose was significantly reduced using density-corrected methods

Perception in statistical graphics

NASA Astrophysics Data System (ADS)

VanderPlas, Susan Ruth

There has been quite a bit of research on statistical graphics and visualization, generally focused on new types of graphics, new software to create graphics, interactivity, and usability studies. Our ability to interpret and use statistical graphics hinges on the interface between the graph itself and the brain that perceives and interprets it, and there is substantially less research on the interplay between graph, eye, brain, and mind than is sufficient to understand the nature of these relationships. The goal of the work presented here is to further explore the interplay between a static graph, the translation of that graph from paper to mental representation (the journey from eye to brain), and the mental processes that operate on that graph once it is transferred into memory (mind). Understanding the perception of statistical graphics should allow researchers to create more effective graphs which produce fewer distortions and viewer errors while reducing the cognitive load necessary to understand the information presented in the graph. Taken together, these experiments should lay a foundation for exploring the perception of statistical graphics. There has been considerable research into the accuracy of numerical judgments viewers make from graphs, and these studies are useful, but it is more effective to understand how errors in these judgments occur so that the root cause of the error can be addressed directly. Understanding how visual reasoning relates to the ability to make judgments from graphs allows us to tailor graphics to particular target audiences. In addition, understanding the hierarchy of salient features in statistical graphics allows us to clearly communicate the important message from data or statistical models by constructing graphics which are designed specifically for the perceptual system.

[Big data in official statistics].

PubMed

Zwick, Markus

2015-08-01

The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

Introductory Statistics and Fish Management.

ERIC Educational Resources Information Center

Jardine, Dick

2002-01-01

Describes how fisheries research and management data (available on a website) have been incorporated into an Introductory Statistics course. In addition to the motivation gained from seeing the practical relevance of the course, some students have participated in the data collection and analysis for the New Hampshire Fish and Game Department. (MM)

Statistical Reviewers Improve Reporting in Biomedical Articles: A Randomized Trial

PubMed Central

Cobo, Erik; Selva-O'Callagham, Albert; Ribera, Josep-Maria; Cardellach, Francesc; Dominguez, Ruth; Vilardell, Miquel

2007-01-01

Background Although peer review is widely considered to be the most credible way of selecting manuscripts and improving the quality of accepted papers in scientific journals, there is little evidence to support its use. Our aim was to estimate the effects on manuscript quality of either adding a statistical peer reviewer or suggesting the use of checklists such as CONSORT or STARD to clinical reviewers or both. Methodology and Principal Findings Interventions were defined as 1) the addition of a statistical reviewer to the clinical peer review process, and 2) suggesting reporting guidelines to reviewers; with “no statistical expert” and “no checklist” as controls. The two interventions were crossed in a 2×2 balanced factorial design including original research articles consecutively selected, between May 2004 and March 2005, by the Medicina Clinica (Barc) editorial committee. We randomized manuscripts to minimize differences in terms of baseline quality and type of study (intervention, longitudinal, cross-sectional, others). Sample-size calculations indicated that 100 papers provide an 80% power to test a 55% standardized difference. We specified the main outcome as the increment in quality of papers as measured on the Goodman Scale. Two blinded evaluators rated the quality of manuscripts at initial submission and final post peer review version. Of the 327 manuscripts submitted to the journal, 131 were accepted for further review, and 129 were randomized. Of those, 14 that were lost to follow-up showed no differences in initial quality to the followed-up papers. Hence, 115 were included in the main analysis, with 16 rejected for publication after peer review. 21 (18.3%) of the 115 included papers were interventions, 46 (40.0%) were longitudinal designs, 28 (24.3%) cross-sectional and 20 (17.4%) others. The 16 (13.9%) rejected papers had a significantly lower initial score on the overall Goodman scale than accepted papers (difference 15.0, 95% CI: 4.6–24

Simple Statistics: - Summarized!

ERIC Educational Resources Information Center

Blai, Boris, Jr.

Statistics are an essential tool for making proper judgement decisions. It is concerned with probability distribution models, testing of hypotheses, significance tests and other means of determining the correctness of deductions and the most likely outcome of decisions. Measures of central tendency include the mean, median and mode. A second…

Exponential order statistic models of software reliability growth

NASA Technical Reports Server (NTRS)

Miller, D. R.

1985-01-01

Failure times of a software reliabilty growth process are modeled as order statistics of independent, nonidentically distributed exponential random variables. The Jelinsky-Moranda, Goel-Okumoto, Littlewood, Musa-Okumoto Logarithmic, and Power Law models are all special cases of Exponential Order Statistic Models, but there are many additional examples also. Various characterizations, properties and examples of this class of models are developed and presented.

Bayesian approach to inverse statistical mechanics.

PubMed

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Bayesian approach to inverse statistical mechanics

NASA Astrophysics Data System (ADS)

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Statistical Modeling for Radiation Hardness Assurance

NASA Technical Reports Server (NTRS)

Ladbury, Raymond L.

2014-01-01

We cover the models and statistics associated with single event effects (and total ionizing dose), why we need them, and how to use them: What models are used, what errors exist in real test data, and what the model allows us to say about the DUT will be discussed. In addition, how to use other sources of data such as historical, heritage, and similar part and how to apply experience, physics, and expert opinion to the analysis will be covered. Also included will be concepts of Bayesian statistics, data fitting, and bounding rates.

DASS-GUI: a user interface for identification and analysis of significant patterns in non-sequential data.

PubMed

Hollunder, Jens; Friedel, Maik; Kuiper, Martin; Wilhelm, Thomas

2010-04-01

Many large 'omics' datasets have been published and many more are expected in the near future. New analysis methods are needed for best exploitation. We have developed a graphical user interface (GUI) for easy data analysis. Our discovery of all significant substructures (DASS) approach elucidates the underlying modularity, a typical feature of complex biological data. It is related to biclustering and other data mining approaches. Importantly, DASS-GUI also allows handling of multi-sets and calculation of statistical significances. DASS-GUI contains tools for further analysis of the identified patterns: analysis of the pattern hierarchy, enrichment analysis, module validation, analysis of additional numerical data, easy handling of synonymous names, clustering, filtering and merging. Different export options allow easy usage of additional tools such as Cytoscape. Source code, pre-compiled binaries for different systems, a comprehensive tutorial, case studies and many additional datasets are freely available at http://www.ifr.ac.uk/dass/gui/. DASS-GUI is implemented in Qt.

Development and Assessment of a Preliminary Randomization-Based Introductory Statistics Curriculum

ERIC Educational Resources Information Center

Tintle, Nathan; VanderStoep, Jill; Holmes, Vicki-Lynn; Quisenberry, Brooke; Swanson, Todd

2011-01-01

The algebra-based introductory statistics course is the most popular undergraduate course in statistics. While there is a general consensus for the content of the curriculum, the recent Guidelines for Assessment and Instruction in Statistics Education (GAISE) have challenged the pedagogy of this course. Additionally, some arguments have been made…

34 CFR 668.49 - Institutional fire safety policies and fire statistics.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false Institutional fire safety policies and fire statistics... fire statistics. (a) Additional definitions that apply to this section. Cause of fire: The factor or... statistics described in paragraph (c) of this section. (2) A description of each on-campus student housing...

A statistical approach to selecting and confirming validation targets in -omics experiments

PubMed Central

2012-01-01

Background Genomic technologies are, by their very nature, designed for hypothesis generation. In some cases, the hypotheses that are generated require that genome scientists confirm findings about specific genes or proteins. But one major advantage of high-throughput technology is that global genetic, genomic, transcriptomic, and proteomic behaviors can be observed. Manual confirmation of every statistically significant genomic result is prohibitively expensive. This has led researchers in genomics to adopt the strategy of confirming only a handful of the most statistically significant results, a small subset chosen for biological interest, or a small random subset. But there is no standard approach for selecting and quantitatively evaluating validation targets. Results Here we present a new statistical method and approach for statistically validating lists of significant results based on confirming only a small random sample. We apply our statistical method to show that the usual practice of confirming only the most statistically significant results does not statistically validate result lists. We analyze an extensively validated RNA-sequencing experiment to show that confirming a random subset can statistically validate entire lists of significant results. Finally, we analyze multiple publicly available microarray experiments to show that statistically validating random samples can both (i) provide evidence to confirm long gene lists and (ii) save thousands of dollars and hundreds of hours of labor over manual validation of each significant result. Conclusions For high-throughput -omics studies, statistical validation is a cost-effective and statistically valid approach to confirming lists of significant results. PMID:22738145

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

Statistics for X-chromosome associations.

PubMed

Özbek, Umut; Lin, Hui-Min; Lin, Yan; Weeks, Daniel E; Chen, Wei; Shaffer, John R; Purcell, Shaun M; Feingold, Eleanor

2018-06-13

In a genome-wide association study (GWAS), association between genotype and phenotype at autosomal loci is generally tested by regression models. However, X-chromosome data are often excluded from published analyses of autosomes because of the difference between males and females in number of X chromosomes. Failure to analyze X-chromosome data at all is obviously less than ideal, and can lead to missed discoveries. Even when X-chromosome data are included, they are often analyzed with suboptimal statistics. Several mathematically sensible statistics for X-chromosome association have been proposed. The optimality of these statistics, however, is based on very specific simple genetic models. In addition, while previous simulation studies of these statistics have been informative, they have focused on single-marker tests and have not considered the types of error that occur even under the null hypothesis when the entire X chromosome is scanned. In this study, we comprehensively tested several X-chromosome association statistics using simulation studies that include the entire chromosome. We also considered a wide range of trait models for sex differences and phenotypic effects of X inactivation. We found that models that do not incorporate a sex effect can have large type I error in some cases. We also found that many of the best statistics perform well even when there are modest deviations, such as trait variance differences between the sexes or small sex differences in allele frequencies, from assumptions. © 2018 WILEY PERIODICALS, INC.

NASA Pocket Statistics

NASA Technical Reports Server (NTRS)

1996-01-01

This booklet of pocket statistics includes the 1996 NASA Major Launch Record, NASA Procurement, Financial, and Workforce data. The NASA Major Launch Record includes all launches of Scout class and larger vehicles. Vehicle and spacecraft development flights are also included in the Major Luanch Record. Shuttle missions are counted as one launch and one payload, where free flying payloads are not involved. Satellites deployed from the cargo bay of the Shuttle and placed in a separate orbit or trajectory are counted as an additional payload.

A Statistics Curriculum for the Undergraduate Chemistry Major

ERIC Educational Resources Information Center

Schlotter, Nicholas E.

2013-01-01

Our ability to statistically analyze data has grown significantly with the maturing of computer hardware and software. However, the evolution of our statistics capabilities has taken place without a corresponding evolution in the curriculum for the undergraduate chemistry major. Most faculty understands the need for a statistical educational…

Statistical properties of Chinese phonemic networks

NASA Astrophysics Data System (ADS)

Yu, Shuiyuan; Liu, Haitao; Xu, Chunshan

2011-04-01

The study of properties of speech sound systems is of great significance in understanding the human cognitive mechanism and the working principles of speech sound systems. Some properties of speech sound systems, such as the listener-oriented feature and the talker-oriented feature, have been unveiled with the statistical study of phonemes in human languages and the research of the interrelations between human articulatory gestures and the corresponding acoustic parameters. With all the phonemes of speech sound systems treated as a coherent whole, our research, which focuses on the dynamic properties of speech sound systems in operation, investigates some statistical parameters of Chinese phoneme networks based on real text and dictionaries. The findings are as follows: phonemic networks have high connectivity degrees and short average distances; the degrees obey normal distribution and the weighted degrees obey power law distribution; vowels enjoy higher priority than consonants in the actual operation of speech sound systems; the phonemic networks have high robustness against targeted attacks and random errors. In addition, for investigating the structural properties of a speech sound system, a statistical study of dictionaries is conducted, which shows the higher frequency of shorter words and syllables and the tendency that the longer a word is, the shorter the syllables composing it are. From these structural properties and dynamic properties one can derive the following conclusion: the static structure of a speech sound system tends to promote communication efficiency and save articulation effort while the dynamic operation of this system gives preference to reliable transmission and easy recognition. In short, a speech sound system is an effective, efficient and reliable communication system optimized in many aspects.

On sufficient statistics of least-squares superposition of vector sets.

PubMed

Konagurthu, Arun S; Kasarapu, Parthan; Allison, Lloyd; Collier, James H; Lesk, Arthur M

2015-06-01

The problem of superposition of two corresponding vector sets by minimizing their sum-of-squares error under orthogonal transformation is a fundamental task in many areas of science, notably structural molecular biology. This problem can be solved exactly using an algorithm whose time complexity grows linearly with the number of correspondences. This efficient solution has facilitated the widespread use of the superposition task, particularly in studies involving macromolecular structures. This article formally derives a set of sufficient statistics for the least-squares superposition problem. These statistics are additive. This permits a highly efficient (constant time) computation of superpositions (and sufficient statistics) of vector sets that are composed from its constituent vector sets under addition or deletion operation, where the sufficient statistics of the constituent sets are already known (that is, the constituent vector sets have been previously superposed). This results in a drastic improvement in the run time of the methods that commonly superpose vector sets under addition or deletion operations, where previously these operations were carried out ab initio (ignoring the sufficient statistics). We experimentally demonstrate the improvement our work offers in the context of protein structural alignment programs that assemble a reliable structural alignment from well-fitting (substructural) fragment pairs. A C++ library for this task is available online under an open-source license.

Statistics of high-level scene context

PubMed Central

Greene, Michelle R.

2013-01-01

Context is critical for recognizing environments and for searching for objects within them: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed “things” in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by

Statistics of high-level scene context.

PubMed

Greene, Michelle R

2013-01-01

CONTEXT IS CRITICAL FOR RECOGNIZING ENVIRONMENTS AND FOR SEARCHING FOR OBJECTS WITHIN THEM: contextual associations have been shown to modulate reaction time and object recognition accuracy, as well as influence the distribution of eye movements and patterns of brain activations. However, we have not yet systematically quantified the relationships between objects and their scene environments. Here I seek to fill this gap by providing descriptive statistics of object-scene relationships. A total of 48, 167 objects were hand-labeled in 3499 scenes using the LabelMe tool (Russell et al., 2008). From these data, I computed a variety of descriptive statistics at three different levels of analysis: the ensemble statistics that describe the density and spatial distribution of unnamed "things" in the scene; the bag of words level where scenes are described by the list of objects contained within them; and the structural level where the spatial distribution and relationships between the objects are measured. The utility of each level of description for scene categorization was assessed through the use of linear classifiers, and the plausibility of each level for modeling human scene categorization is discussed. Of the three levels, ensemble statistics were found to be the most informative (per feature), and also best explained human patterns of categorization errors. Although a bag of words classifier had similar performance to human observers, it had a markedly different pattern of errors. However, certain objects are more useful than others, and ceiling classification performance could be achieved using only the 64 most informative objects. As object location tends not to vary as a function of category, structural information provided little additional information. Additionally, these data provide valuable information on natural scene redundancy that can be exploited for machine vision, and can help the visual cognition community to design experiments guided by statistics

A Tablet-PC Software Application for Statistics Classes

ERIC Educational Resources Information Center

Probst, Alexandre C.

2014-01-01

A significant deficiency in the area of introductory statistics education exists: Student performance on standardized assessments after a full semester statistics course is poor and students report a very low desire to learn statistics. Research on the current generation of students indicates an affinity for technology and for multitasking.…

Tsallis statistics and neurodegenerative disorders

NASA Astrophysics Data System (ADS)

Iliopoulos, Aggelos C.; Tsolaki, Magdalini; Aifantis, Elias C.

2016-08-01

In this paper, we perform statistical analysis of time series deriving from four neurodegenerative disorders, namely epilepsy, amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD). The time series are concerned with electroencephalograms (EEGs) of healthy and epileptic states, as well as gait dynamics (in particular stride intervals) of the ALS, PD and HDs. We study data concerning one subject for each neurodegenerative disorder and one healthy control. The analysis is based on Tsallis non-extensive statistical mechanics and in particular on the estimation of Tsallis q-triplet, namely {qstat, qsen, qrel}. The deviation of Tsallis q-triplet from unity indicates non-Gaussian statistics and long-range dependencies for all time series considered. In addition, the results reveal the efficiency of Tsallis statistics in capturing differences in brain dynamics between healthy and epileptic states, as well as differences between ALS, PD, HDs from healthy control subjects. The results indicate that estimations of Tsallis q-indices could be used as possible biomarkers, along with others, for improving classification and prediction of epileptic seizures, as well as for studying the gait complex dynamics of various diseases providing new insights into severity, medications and fall risk, improving therapeutic interventions.

Basic statistics (the fundamental concepts).

PubMed

Lim, Eric

2014-12-01

An appreciation and understanding of statistics is import to all practising clinicians, not simply researchers. This is because mathematics is the fundamental basis to which we base clinical decisions, usually with reference to the benefit in relation to risk. Unless a clinician has a basic understanding of statistics, he or she will never be in a position to question healthcare management decisions that have been handed down from generation to generation, will not be able to conduct research effectively nor evaluate the validity of published evidence (usually making an assumption that most published work is either all good or all bad). This article provides a brief introduction to basic statistical methods and illustrates its use in common clinical scenarios. In addition, pitfalls of incorrect usage have been highlighted. However, it is not meant to be a substitute for formal training or consultation with a qualified and experienced medical statistician prior to starting any research project.

Evaluation of bond strength of resin cements using different general-purpose statistical software packages for two-parameter Weibull statistics.

PubMed

Roos, Malgorzata; Stawarczyk, Bogna

2012-07-01

This study evaluated and compared Weibull parameters of resin bond strength values using six different general-purpose statistical software packages for two-parameter Weibull distribution. Two-hundred human teeth were randomly divided into 4 groups (n=50), prepared and bonded on dentin according to the manufacturers' instructions using the following resin cements: (i) Variolink (VAN, conventional resin cement), (ii) Panavia21 (PAN, conventional resin cement), (iii) RelyX Unicem (RXU, self-adhesive resin cement) and (iv) G-Cem (GCM, self-adhesive resin cement). Subsequently, all specimens were stored in water for 24h at 37°C. Shear bond strength was measured and the data were analyzed using Anderson-Darling goodness-of-fit (MINITAB 16) and two-parameter Weibull statistics with the following statistical software packages: Excel 2011, SPSS 19, MINITAB 16, R 2.12.1, SAS 9.1.3. and STATA 11.2 (p≤0.05). Additionally, the three-parameter Weibull was fitted using MNITAB 16. Two-parameter Weibull calculated with MINITAB and STATA can be compared using an omnibus test and using 95% CI. In SAS only 95% CI were directly obtained from the output. R provided no estimates of 95% CI. In both SAS and R the global comparison of the characteristic bond strength among groups is provided by means of the Weibull regression. EXCEL and SPSS provided no default information about 95% CI and no significance test for the comparison of Weibull parameters among the groups. In summary, conventional resin cement VAN showed the highest Weibull modulus and characteristic bond strength. There are discrepancies in the Weibull statistics depending on the software package and the estimation method. The information content in the default output provided by the software packages differs to very high extent. Copyright © 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Influence of disinfection with peracetic acid and hypochlorite in dimensional alterations of casts obtained from addition silicone and polyether impressions.

PubMed

Queiroz, Daher Antonio; Peçanha, Marcelo Massaroni; Neves, Ana Christina Claro; Frizzera, Fausto; Tonetto, Mateus Rodrigues; Silva-Concílio, Laís Regiane

2013-11-01

Dental impressions disinfection is important to reduce the risk of cross contamination but this process may produce dimensional distortions. Peracetic acid is a disinfectant agent with several favorable characteristics yet underutilized in Dentistry. The aim of this paper is to compare the dimensional stability of casts obtained from addition silicone and polyether impressions that were immersed for 10 minutes in a solution of 0.2% peracetic acid or 1% sodium hypochlorite. Sixty samples in type IV gypsum were produced after a master cast that simulated a full crown preparation of a maxillary premolar. Samples were divided in 6 groups (n = 10) according to the impression material and disinfection agent: Group AC--addition silicone control (without disinfectant); Group APA--addition silicone + 0.2% peracetic acid; Group AH--addition silicone + 1% sodium hypochlorite; Group PC--polyether control (without disinfectant); Group PPA--polyether + 0.2% peracetic acid; Group PH--polyether + 1% sodium hypochlorite. Cast height, base and top diameter were measured and a mean value was obtained for each sample and group all data was statistically analyzed (ANOVA, p < 0.05). There was not a significant statistical difference between addition silicone and polyether impressions regardless of the disinfectant materials. It can be concluded that disinfection with the proposed agents did not produce significant alterations of the impressions and the peracetic acid could be considered a reliable material to disinfect dental molds.

Evaluation of Evidence of Statistical Support and Corroboration of Subgroup Claims in Randomized Clinical Trials.

PubMed

Wallach, Joshua D; Sullivan, Patrick G; Trepanowski, John F; Sainani, Kristin L; Steyerberg, Ewout W; Ioannidis, John P A

2017-04-01

Many published randomized clinical trials (RCTs) make claims for subgroup differences. To evaluate how often subgroup claims reported in the abstracts of RCTs are actually supported by statistical evidence (P < .05 from an interaction test) and corroborated by subsequent RCTs and meta-analyses. This meta-epidemiological survey examines data sets of trials with at least 1 subgroup claim, including Subgroup Analysis of Trials Is Rarely Easy (SATIRE) articles and Discontinuation of Randomized Trials (DISCO) articles. We used Scopus (updated July 2016) to search for English-language articles citing each of the eligible index articles with at least 1 subgroup finding in the abstract. Articles with a subgroup claim in the abstract with or without evidence of statistical heterogeneity (P < .05 from an interaction test) in the text and articles attempting to corroborate the subgroup findings. Study characteristics of trials with at least 1 subgroup claim in the abstract were recorded. Two reviewers extracted the data necessary to calculate subgroup-level effect sizes, standard errors, and the P values for interaction. For individual RCTs and meta-analyses that attempted to corroborate the subgroup findings from the index articles, trial characteristics were extracted. Cochran Q test was used to reevaluate heterogeneity with the data from all available trials. The number of subgroup claims in the abstracts of RCTs, the number of subgroup claims in the abstracts of RCTs with statistical support (subgroup findings), and the number of subgroup findings corroborated by subsequent RCTs and meta-analyses. Sixty-four eligible RCTs made a total of 117 subgroup claims in their abstracts. Of these 117 claims, only 46 (39.3%) in 33 articles had evidence of statistically significant heterogeneity from a test for interaction. In addition, out of these 46 subgroup findings, only 16 (34.8%) ensured balance between randomization groups within the subgroups (eg, through stratified

The Statistical Consulting Center for Astronomy (SCCA)

NASA Technical Reports Server (NTRS)

Akritas, Michael

2001-01-01

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to

An operational definition of a statistically meaningful trend.

PubMed

Bryhn, Andreas C; Dimberg, Peter H

2011-04-28

Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r(2) and p values are calculated from regressions concerning time and interval mean values. If r(2) ≥ 0.65 at p ≤ 0.05 in any of these regressions, then the trend is regarded as statistically meaningful. Out of ten investigated time series from different scientific disciplines, five displayed statistically meaningful trends. A Microsoft Excel application (add-in) was developed which can perform statistical meaningfulness tests and which may increase the operationality of the test. The presented method for distinguishing statistically meaningful trends should be reasonably uncomplicated for researchers with basic statistics skills and may thus be useful for determining which trends are worth analysing further, for instance with respect to causal factors. The method can also be used for determining which segments of a time trend may be particularly worthwhile to focus on.

HYPE: a WFD tool for the identification of significant and sustained upward trends in groundwater time series

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Croiset, Nolwenn; Laurence, Gourcy

2014-05-01

The Water Framework Directive 2006/11/CE (WFD) on the protection of groundwater against pollution and deterioration asks Member States to identify significant and sustained upward trends in all bodies or groups of bodies of groundwater that are characterised as being at risk in accordance with Annex II to Directive 2000/60/EC. The Directive indicates that the procedure for the identification of significant and sustained upward trends must be based on a statistical method. Moreover, for significant increases of concentrations of pollutants, trend reversals are identified as being necessary. This means to be able to identify significant trend reversals. A specific tool, named HYPE, has been developed in order to help stakeholders working on groundwater trend assessment. The R encoded tool HYPE provides statistical analysis of groundwater time series. It follows several studies on the relevancy of the use of statistical tests on groundwater data series (Lopez et al., 2011) and other case studies on the thematic (Bourgine et al., 2012). It integrates the most powerful and robust statistical tests for hydrogeological applications. HYPE is linked to the French national database on groundwater data (ADES). So monitoring data gathered by the Water Agencies can be directly processed. HYPE has two main modules: - a characterisation module, which allows to visualize time series. HYPE calculates the main statistical characteristics and provides graphical representations; - a trend module, which identifies significant breaks, trends and trend reversals in time series, providing result table and graphical representation (cf figure). Additional modules are also implemented to identify regional and seasonal trends and to sample time series in a relevant way. HYPE has been used successfully in 2012 by the French Water Agencies to satisfy requirements of the WFD, concerning characterization of groundwater bodies' qualitative status and evaluation of the risk of non-achievement of

Statistical wave climate projections for coastal impact assessments

NASA Astrophysics Data System (ADS)

Camus, P.; Losada, I. J.; Izaguirre, C.; Espejo, A.; Menéndez, M.; Pérez, J.

2017-09-01

Global multimodel wave climate projections are obtained at 1.0° × 1.0° scale from 30 Coupled Model Intercomparison Project Phase 5 (CMIP5) global circulation model (GCM) realizations. A semi-supervised weather-typing approach based on a characterization of the ocean wave generation areas and the historical wave information from the recent GOW2 database are used to train the statistical model. This framework is also applied to obtain high resolution projections of coastal wave climate and coastal impacts as port operability and coastal flooding. Regional projections are estimated using the collection of weather types at spacing of 1.0°. This assumption is feasible because the predictor is defined based on the wave generation area and the classification is guided by the local wave climate. The assessment of future changes in coastal impacts is based on direct downscaling of indicators defined by empirical formulations (total water level for coastal flooding and number of hours per year with overtopping for port operability). Global multimodel projections of the significant wave height and peak period are consistent with changes obtained in previous studies. Statistical confidence of expected changes is obtained due to the large number of GCMs to construct the ensemble. The proposed methodology is proved to be flexible to project wave climate at different spatial scales. Regional changes of additional variables as wave direction or other statistics can be estimated from the future empirical distribution with extreme values restricted to high percentiles (i.e., 95th, 99th percentiles). The statistical framework can also be applied to evaluate regional coastal impacts integrating changes in storminess and sea level rise.

Mutual interference between statistical summary perception and statistical learning.

PubMed

Zhao, Jiaying; Ngo, Nhi; McKendrick, Ryan; Turk-Browne, Nicholas B

2011-09-01

The visual system is an efficient statistician, extracting statistical summaries over sets of objects (statistical summary perception) and statistical regularities among individual objects (statistical learning). Although these two kinds of statistical processing have been studied extensively in isolation, their relationship is not yet understood. We first examined how statistical summary perception influences statistical learning by manipulating the task that participants performed over sets of objects containing statistical regularities (Experiment 1). Participants who performed a summary task showed no statistical learning of the regularities, whereas those who performed control tasks showed robust learning. We then examined how statistical learning influences statistical summary perception by manipulating whether the sets being summarized contained regularities (Experiment 2) and whether such regularities had already been learned (Experiment 3). The accuracy of summary judgments improved when regularities were removed and when learning had occurred in advance. In sum, calculating summary statistics impeded statistical learning, and extracting statistical regularities impeded statistical summary perception. This mutual interference suggests that statistical summary perception and statistical learning are fundamentally related.

Statistical comparison of coherent structures in fully developed turbulent pipe flow with and without drag reduction

NASA Astrophysics Data System (ADS)

Sogaro, Francesca; Poole, Robert; Dennis, David

2014-11-01

High-speed stereoscopic particle image velocimetry has been performed in fully developed turbulent pipe flow at moderate Reynolds numbers with and without a drag-reducing additive (an aqueous solution of high molecular weight polyacrylamide). Three-dimensional large and very large-scale motions (LSM and VLSM) are extracted from the flow fields by a detection algorithm and the characteristics for each case are statistically compared. The results show that the three-dimensional extent of VLSMs in drag reduced (DR) flow appears to increase significantly compared to their Newtonian counterparts. A statistical increase in azimuthal extent of DR VLSM is observed by means of two-point spatial autocorrelation of the streamwise velocity fluctuation in the radial-azimuthal plane. Furthermore, a remarkable increase in length of these structures is observed by three-dimensional two-point spatial autocorrelation. These results are accompanied by an analysis of the swirling strength in the flow field that shows a significant reduction in strength and number of the vortices for the DR flow. The findings suggest that the damping of the small scales due to polymer addition results in the undisturbed development of longer flow structures.

Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb-Scargle periodogram and Monte Carlo evaluation of statistical significance

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2012-12-01

Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and

Erratum to: Application of addition-cured silicone denture relining materials to adjust mouthguards.

PubMed

Fukasawa, Shintaro; Churei, Hiroshi; Chowdhury, Ruman Uddin; Shirako, Takahiro; Shahrin, Sharika; Shrestha, Abhishekhi; Wada, Takahiro; Uo, Motohiro; Takahashi, Hidekazu; Ueno, Toshiaki

2016-01-01

The purposes of this study were to examine the shock absorption capability of addition-cured silicone denture relining materials and the bonding strength of addition-cured silicone denture relining materials and a commercial mouthguard material to determine its applicability to mouthguard adjustment. Two addition-cured silicone denture relining materials were selected as test materials. The impact test was applied by a free-falling steel ball. On the other hand, bonding strength was determined by a delamination test. After prepared surface treatments using acrylic resin on MG sheet surface, 2 types of addition-cured silicone denture relining materials were glued to MG surface. The peak intensity, the time to peak intensity from the onset of the transmitted force and bonding strength were statistically analyzed using ANOVA and Tukey's honest significant difference post hoc test (p<0.05). These results suggest that the silicone denture relining materials could be clinically applicable as a mouthguard adjustment material.

Determining significant material properties: A discovery approach

NASA Technical Reports Server (NTRS)

Karplus, Alan K.

1992-01-01

The following is a laboratory experiment designed to further understanding of materials science. The experiment itself can be informative for persons of any age past elementary school, and even for some in elementary school. The preparation of the plastic samples is readily accomplished by persons with resonable dexterity in the cutting of paper designs. The completion of the statistical Design of Experiments, which uses Yates' Method, requires basic math (addition and subtraction). Interpretive work requires plotting of data and making observations. Knowledge of statistical methods would be helpful. The purpose of this experiment is to acquaint students with the seven classes of recyclable plastics, and provide hands-on learning about the response of these plastics to mechanical tensile loading.

US Geological Survey nutrient preservation experiment : experimental design, statistical analysis, and interpretation of analytical results

USGS Publications Warehouse

Patton, Charles J.; Gilroy, Edward J.

1999-01-01

Data on which this report is based, including nutrient concentrations in synthetic reference samples determined concurrently with those in real samples, are extensive (greater than 20,000 determinations) and have been published separately. In addition to confirming the well-documented instability of nitrite in acidified samples, this study also demonstrates that when biota are removed from samples at collection sites by 0.45-micrometer membrane filtration, subsequent preservation with sulfuric acid or mercury (II) provides no statistically significant improvement in nutrient concentration stability during storage at 4 degrees Celsius for 30 days. Biocide preservation had no statistically significant effect on the 30-day stability of phosphorus concentrations in whole-water splits from any of the 15 stations, but did stabilize Kjeldahl nitrogen concentrations in whole-water splits from three data-collection stations where ammonium accounted for at least half of the measured Kjeldahl nitrogen.

Statistically Modeling Individual Students' Learning over Successive Collaborative Practice Opportunities

ERIC Educational Resources Information Center

Olsen, Jennifer; Aleven, Vincent; Rummel, Nikol

2017-01-01

Within educational data mining, many statistical models capture the learning of students working individually. However, not much work has been done to extend these statistical models of individual learning to a collaborative setting, despite the effectiveness of collaborative learning activities. We extend a widely used model (the additive factors…

[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.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

Statistical power analysis in wildlife research

USGS Publications Warehouse

Steidl, R.J.; Hayes, J.P.

1997-01-01

Statistical power analysis can be used to increase the efficiency of research efforts and to clarify research results. Power analysis is most valuable in the design or planning phases of research efforts. Such prospective (a priori) power analyses can be used to guide research design and to estimate the number of samples necessary to achieve a high probability of detecting biologically significant effects. Retrospective (a posteriori) power analysis has been advocated as a method to increase information about hypothesis tests that were not rejected. However, estimating power for tests of null hypotheses that were not rejected with the effect size observed in the study is incorrect; these power estimates will always be a??0.50 when bias adjusted and have no relation to true power. Therefore, retrospective power estimates based on the observed effect size for hypothesis tests that were not rejected are misleading; retrospective power estimates are only meaningful when based on effect sizes other than the observed effect size, such as those effect sizes hypothesized to be biologically significant. Retrospective power analysis can be used effectively to estimate the number of samples or effect size that would have been necessary for a completed study to have rejected a specific null hypothesis. Simply presenting confidence intervals can provide additional information about null hypotheses that were not rejected, including information about the size of the true effect and whether or not there is adequate evidence to 'accept' a null hypothesis as true. We suggest that (1) statistical power analyses be routinely incorporated into research planning efforts to increase their efficiency, (2) confidence intervals be used in lieu of retrospective power analyses for null hypotheses that were not rejected to assess the likely size of the true effect, (3) minimum biologically significant effect sizes be used for all power analyses, and (4) if retrospective power estimates are to

A statistical analysis of the impact of advertising signs on road safety.

PubMed

Yannis, George; Papadimitriou, Eleonora; Papantoniou, Panagiotis; Voulgari, Chrisoula

2013-01-01

This research aims to investigate the impact of advertising signs on road safety. An exhaustive review of international literature was carried out on the effect of advertising signs on driver behaviour and safety. Moreover, a before-and-after statistical analysis with control groups was applied on several road sites with different characteristics in the Athens metropolitan area, in Greece, in order to investigate the correlation between the placement or removal of advertising signs and the related occurrence of road accidents. Road accident data for the 'before' and 'after' periods on the test sites and the control sites were extracted from the database of the Hellenic Statistical Authority, and the selected 'before' and 'after' periods vary from 2.5 to 6 years. The statistical analysis shows no statistical correlation between road accidents and advertising signs in none of the nine sites examined, as the confidence intervals of the estimated safety effects are non-significant at 95% confidence level. This can be explained by the fact that, in the examined road sites, drivers are overloaded with information (traffic signs, directions signs, labels of shops, pedestrians and other vehicles, etc.) so that the additional information load from advertising signs may not further distract them.

2016 Workplace and Gender Relations Survey of Active Duty Members: Statistical Methodology Report

DTIC Science & Technology

2017-03-01

2016 Workplace and Gender Relations Survey of Active Duty Members Statistical Methodology Report Additional copies of this report may be...MEMBERS: STATISTICAL METHODOLOGY REPORT Office of People Analytics (OPA) Defense Research, Surveys, and Statistics Center 4800 Mark Center Drive...20 1 2016 WORKPLACE AND GENDER RELATIONS SURVEY OF ACTIVE DUTY MEMBERS: STATISTICAL METHODOLOGY REPORT

Optimal allocation of testing resources for statistical simulations

NASA Astrophysics Data System (ADS)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

[Statistics for statistics?--Thoughts about psychological tools].

PubMed

Berger, Uwe; Stöbel-Richter, Yve

2007-12-01

Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.

Additive Manufacturing Infrared Inspection

NASA Technical Reports Server (NTRS)

Gaddy, Darrell

2014-01-01

Additive manufacturing is a rapid prototyping technology that allows parts to be built in a series of thin layers from plastic, ceramics, and metallics. Metallic additive manufacturing is an emerging form of rapid prototyping that allows complex structures to be built using various metallic powders. Significant time and cost savings have also been observed using the metallic additive manufacturing compared with traditional techniques. Development of the metallic additive manufacturing technology has advanced significantly over the last decade, although many of the techniques to inspect parts made from these processes have not advanced significantly or have limitations. Several external geometry inspection techniques exist such as Coordinate Measurement Machines (CMM), Laser Scanners, Structured Light Scanning Systems, or even traditional calipers and gages. All of the aforementioned techniques are limited to external geometry and contours or must use a contact probe to inspect limited internal dimensions. This presentation will document the development of a process for real-time dimensional inspection technique and digital quality record of the additive manufacturing process using Infrared camera imaging and processing techniques.

Tools for Basic Statistical Analysis

NASA Technical Reports Server (NTRS)

Luz, Paul L.

2005-01-01

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

Statistical inference for the additive hazards model under outcome-dependent sampling.

PubMed

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Extreme-value statistics reveal rare failure-critical defects in additive manufacturing

DOE PAGES

Boyce, Brad L.; Salzbrenner, Bradley C.; Rodelas, Jeffrey M.; ...

2017-04-21

Additive manufacturing enables the rapid, cost effective production of large populations of material test coupons such as tensile bars. By adopting streamlined test methods including ‘drop-in’ grips and non-contact extensometry, testing these large populations becomes more efficient. Unlike hardness tests, the tensile test provides a direct measure of yield strength, flow properties, and ductility, which can be directly incorporated into solid mechanics simulations. In the present work, over 1000 nominally identical tensile tests were used to explore the effect of process variability on the mechanical property distributions of a precipitation hardened stainless steel, 17-4PH, produced by a laser powder bedmore » fusion process, also known as direct metal laser sintering. With this large dataset, rare defects are revealed that affect only ~2% of the population, stemming from a single build lot of material. Lastly, the rare defects caused a substantial loss in ductility and were associated with an interconnected network of porosity.« less

Statistical inference for the additive hazards model under outcome-dependent sampling

PubMed Central

Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

2015-01-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

Statistical mechanics of economics I

NASA Astrophysics Data System (ADS)

Kusmartsev, F. V.

2011-02-01

We show that statistical mechanics is useful in the description of financial crisis and economics. Taking a large amount of instant snapshots of a market over an interval of time we construct their ensembles and study their statistical interference. This results in a probability description of the market and gives capital, money, income, wealth and debt distributions, which in the most cases takes the form of the Bose-Einstein distribution. In addition, statistical mechanics provides the main market equations and laws which govern the correlations between the amount of money, debt, product, prices and number of retailers. We applied the found relations to a study of the evolution of the economics in USA between the years 1996 to 2008 and observe that over that time the income of a major population is well described by the Bose-Einstein distribution which parameters are different for each year. Each financial crisis corresponds to a peak in the absolute activity coefficient. The analysis correctly indicates the past crises and predicts the future one.

Semi-Poisson statistics in quantum chaos.

PubMed

García-García, Antonio M; Wang, Jiao

2006-03-01

We investigate the quantum properties of a nonrandom Hamiltonian with a steplike singularity. It is shown that the eigenfunctions are multifractals and, in a certain range of parameters, the level statistics is described exactly by semi-Poisson statistics (SP) typical of pseudointegrable systems. It is also shown that our results are universal, namely, they depend exclusively on the presence of the steplike singularity and are not modified by smooth perturbations of the potential or the addition of a magnetic flux. Although the quantum properties of our system are similar to those of a disordered conductor at the Anderson transition, we report important quantitative differences in both the level statistics and the multifractal dimensions controlling the transition. Finally, the study of quantum transport properties suggests that the classical singularity induces quantum anomalous diffusion. We discuss how these findings may be experimentally corroborated by using ultracold atoms techniques.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Additional Value of Transluminal Attenuation Gradient in CT Angiography to Predict Hemodynamic Significance of Coronary Artery Stenosis

PubMed Central

Stuijfzand, Wynand J.; Danad, Ibrahim; Raijmakers, Pieter G.; Marcu, C. Bogdan; Heymans, Martijn W.; van Kuijk, Cornelis C.; van Rossum, Albert C.; Nieman, Koen; Min, James K.; Leipsic, Jonathon; van Royen, Niels; Knaapen, Paul

2015-01-01

OBJECTIVES The current study evaluates the incremental value of transluminal attenuation gradient (TAG), TAG with corrected contrast opacification (CCO), and TAG with exclusion of calcified coronary segments (ExC) over coronary computed tomography angiogram (CTA) alone using fractional flow reserve (FFR) as the gold standard. BACKGROUND TAG is defined as the contrast opacification gradient along the length of a coronary artery on a coronary CTA. Preliminary data suggest that TAG provides additional functional information. Interpretation of TAG is hampered by multiple heartbeat acquisition algorithms and coronary calcifications. Two correction models have been proposed based on either dephasing of contrast delivery by relating coronary density to corresponding descending aortic opacification (TAG-CCO) or excluding calcified coronary segments (TAG-ExC). METHODS Eighty-five patients with intermediate probability of coronary artery disease were prospectively included. All patients underwent step-and-shoot 256-slice coronary CTA. TAG, TAG-CCO, and TAG-ExC analyses were performed followed by invasive coronary angiography in conjunction with FFR measurements of all major coronary branches. RESULTS Thirty-four patients (40%) were diagnosed with hemodynamically-significant coronary artery disease (i.e., FFR ≤0.80). On a per-vessel basis (n = 253), 59 lesions (23%) were graded as hemodynamically significant, and the diagnostic accuracy of coronary CTA (diameter stenosis ≥50%) was 95%, 75%, 98%, and 54% for sensitivity, specificity, negative predictive value, and positive predictive value, respectively. TAG and TAG-ExC did not discriminate between vessels with or without hemodynamically significant lesions (−13.5 ± 17.1 HU [Hounsfield units] × 10 mm−1 vs. −11.6 ± 13.3 HU × 10 mm−1, p = 0.36; and 13.1 ± 15.9 HU × 10 mm−1 vs. −11.4 ± 11.7 HU × 10 mm−1, p = 0.77, respectively). TAG-CCO was lower in vessels with a hemodynamically-significant lesion (−0

Tables of Significance Points for the Variance-Weighted Kolmogorov-Smirnov Statistics.

DTIC Science & Technology

1981-02-19

neN x; 1; ( := 0 for all z Vo0 For the values of a function V: N0 IR we use both notations V(i) and vi " ii Tables of Significance Points for the...satisfying 0 < V0 < 10 and v, < Vi -i ¥i IN,* The following functions define a 4-Sheffer sequence (see (A.12)) for the derivative operator D: d i if x ɘ f(,c...S U(i ) < Ii ¥ Vi l,...,M)IMl 7 i7- 1.2. Recursions. For this section we assume p’ 1 without loss of generality.M With qn-k(x)- x n-k/(n-k)! in (A.13

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.

PubMed

Hu, Ting; Pan, Qinxin; Andrew, Angeline S; Langer, Jillian M; Cole, Michael D; Tomlinson, Craig R; Karagas, Margaret R; Moore, Jason H

2014-04-11

Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types. The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.

Assay optimization: a statistical design of experiments approach.

PubMed

Altekar, Maneesha; Homon, Carol A; Kashem, Mohammed A; Mason, Steven W; Nelson, Richard M; Patnaude, Lori A; Yingling, Jeffrey; Taylor, Paul B

2007-03-01

With the transition from manual to robotic HTS in the last several years, assay optimization has become a significant bottleneck. Recent advances in robotic liquid handling have made it feasible to reduce assay optimization timelines with the application of statistically designed experiments. When implemented, they can efficiently optimize assays by rapidly identifying significant factors, complex interactions, and nonlinear responses. This article focuses on the use of statistically designed experiments in assay optimization.

Whither Statistics Education Research?

ERIC Educational Resources Information Center

Watson, Jane

2016-01-01

This year marks the 25th anniversary of the publication of a "National Statement on Mathematics for Australian Schools", which was the first curriculum statement this country had including "Chance and Data" as a significant component. It is hence an opportune time to survey the history of the related statistics education…

Clinical significance in nursing research: A discussion and descriptive analysis.

PubMed

Polit, Denise F

2017-08-01

It is widely understood that statistical significance should not be equated with clinical significance, but the topic of clinical significance has not received much attention in the nursing literature. By contrast, interest in conceptualizing and operationalizing clinical significance has been a "hot topic" in other health care fields for several decades. The major purpose of this paper is to briefly describe recent advances in defining and quantifying clinical significance. The overview covers both group-level indicators of clinical significance (e.g., effect size indexes), and individual-level benchmarks (e.g., the minimal important change index). A secondary purpose is to describe the extent to which developments in clinical significance have penetrated the nursing literature. A descriptive analysis of a sample of primary research articles published in three high-impact nursing research journals in 2016 was undertaken. A total of 362 articles were electronically searched for terms relating to statistical and clinical significance. Of the 362 articles, 261 were reports of quantitative studies, the vast majority of which (93%) included a formal evaluation of the statistical significance of the results. By contrast, the term "clinical significance" or related surrogate terms were found in only 33 papers, and most often the term was used informally, without explicit definition or assessment. Raising consciousness about clinical significance should be an important priority among nurse researchers. Several recommendations are offered to improve the visibility and salience of clinical significance in nursing science. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

PubMed

Wu, Johnny C; Gardner, David P; Ozer, Stuart; Gutell, Robin R; Ren, Pengyu

2009-08-28

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.

Serious fighting-related injuries produce a significant reduction in intelligence.

PubMed

Schwartz, Joseph A; Beaver, Kevin M

2013-10-01

Fighting-related injuries are common among adolescents within the United States, but how such injuries relate to subsequent cognitive functioning remains unclear. In particular, the long-term effect of fighting-related injuries suffered during important developmental periods, such as adolescence, on subsequent cognitive functioning has been overlooked by previous studies. The purpose of this study is to examine the association between sustaining serious fighting-related injuries and changes in verbal intelligence (IQ) over a 5- to 6-year time period. Longitudinal multivariate statistical models were used to analyze data from the National Longitudinal Study of Adolescent Health collected between 1994 and 2002 and analyzed in 2013. Even a single fighting-related injury resulted in a significant reduction in IQ over time even after controlling for age, race, sex, and changes in socioeconomic status (SES) over the study period. Additionally, females experienced a significantly greater reduction in IQ from each fighting-related injury than males. Fighting-related injuries have a significant impact on subsequent cognitive functioning and intelligence. The implications for future policies and research are discussed in more detail. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Non-additive genetic variation in growth, carcass and fertility traits of beef cattle.

PubMed

Bolormaa, Sunduimijid; Pryce, Jennie E; Zhang, Yuandan; Reverter, Antonio; Barendse, William; Hayes, Ben J; Goddard, Michael E

2015-04-02

A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were

Compositional differences among Chinese soy sauce types studied by (13)C NMR spectroscopy coupled with multivariate statistical analysis.

PubMed

Kamal, Ghulam Mustafa; Wang, Xiaohua; Bin Yuan; Wang, Jie; Sun, Peng; Zhang, Xu; Liu, Maili

2016-09-01

Soy sauce a well known seasoning all over the world, especially in Asia, is available in global market in a wide range of types based on its purpose and the processing methods. Its composition varies with respect to the fermentation processes and addition of additives, preservatives and flavor enhancers. A comprehensive (1)H NMR based study regarding the metabonomic variations of soy sauce to differentiate among different types of soy sauce available on the global market has been limited due to the complexity of the mixture. In present study, (13)C NMR spectroscopy coupled with multivariate statistical data analysis like principle component analysis (PCA), and orthogonal partial least square-discriminant analysis (OPLS-DA) was applied to investigate metabonomic variations among different types of soy sauce, namely super light, super dark, red cooking and mushroom soy sauce. The main additives in soy sauce like glutamate, sucrose and glucose were easily distinguished and quantified using (13)C NMR spectroscopy which were otherwise difficult to be assigned and quantified due to serious signal overlaps in (1)H NMR spectra. The significantly higher concentration of sucrose in dark, red cooking and mushroom flavored soy sauce can directly be linked to the addition of caramel in soy sauce. Similarly, significantly higher level of glutamate in super light as compared to super dark and mushroom flavored soy sauce may come from the addition of monosodium glutamate. The study highlights the potentiality of (13)C NMR based metabonomics coupled with multivariate statistical data analysis in differentiating between the types of soy sauce on the basis of level of additives, raw materials and fermentation procedures. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical comparison of leaching behavior of incineration bottom ash using seawater and deionized water: Significant findings based on several leaching methods.

PubMed

Yin, Ke; Dou, Xiaomin; Ren, Fei; Chan, Wei-Ping; Chang, Victor Wei-Chung

2018-02-15

Bottom ashes generated from municipal solid waste incineration have gained increasing popularity as alternative construction materials, however, they contains elevated heavy metals posing a challenge for its free usage. Different leaching methods are developed to quantify leaching potential of incineration bottom ashes meanwhile guide its environmentally friendly application. Yet, there are diverse IBA applications while the in situ environment is always complicated, challenging its legislation. In this study, leaching tests were conveyed using batch and column leaching methods with seawater as opposed to deionized water, to unveil the metal leaching potential of IBA subjected to salty environment, which is commonly encountered when using IBA in land reclamation yet not well understood. Statistical analysis for different leaching methods suggested disparate performance between seawater and deionized water primarily ascribed to ionic strength. Impacts of leachant are metal-specific dependent on leaching methods and have a function of intrinsic characteristics of incineration bottom ashes. Leaching performances were further compared on additional perspectives, e.g. leaching approach and liquid to solid ratio, indicating sophisticated leaching potentials dominated by combined geochemistry. It is necessary to develop application-oriented leaching methods with corresponding leaching criteria to preclude discriminations between different applications, e.g., terrestrial applications vs. land reclamation. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical significance of hair analysis of clenbuterol to discriminate therapeutic use from contamination.

PubMed

Krumbholz, Aniko; Anielski, Patricia; Gfrerer, Lena; Graw, Matthias; Geyer, Hans; Schänzer, Wilhelm; Dvorak, Jiri; Thieme, Detlef

2014-01-01

Clenbuterol is a well-established β2-agonist, which is prohibited in sports and strictly regulated for use in the livestock industry. During the last few years clenbuterol-positive results in doping controls and in samples from residents or travellers from a high-risk country were suspected to be related the illegal use of clenbuterol for fattening. A sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to detect low clenbuterol residues in hair with a detection limit of 0.02 pg/mg. A sub-therapeutic application study and a field study with volunteers, who have a high risk of contamination, were performed. For the application study, a total dosage of 30 µg clenbuterol was applied to 20 healthy volunteers on 5 subsequent days. One month after the beginning of the application, clenbuterol was detected in the proximal hair segment (0-1 cm) in concentrations between 0.43 and 4.76 pg/mg. For the second part, samples of 66 Mexican soccer players were analyzed. In 89% of these volunteers, clenbuterol was detectable in their hair at concentrations between 0.02 and 1.90 pg/mg. A comparison of both parts showed no statistical difference between sub-therapeutic application and contamination. In contrast, discrimination to a typical abuse of clenbuterol is apparently possible. Due to these findings results of real doping control samples can be evaluated. Copyright © 2014 John Wiley & Sons, Ltd.

Interpreting “statistical hypothesis testing” results in clinical research

PubMed Central

Sarmukaddam, Sanjeev B.

2012-01-01

Difference between “Clinical Significance and Statistical Significance” should be kept in mind while interpreting “statistical hypothesis testing” results in clinical research. This fact is already known to many but again pointed out here as philosophy of “statistical hypothesis testing” is sometimes unnecessarily criticized mainly due to failure in considering such distinction. Randomized controlled trials are also wrongly criticized similarly. Some scientific method may not be applicable in some peculiar/particular situation does not mean that the method is useless. Also remember that “statistical hypothesis testing” is not for decision making and the field of “decision analysis” is very much an integral part of science of statistics. It is not correct to say that “confidence intervals have nothing to do with confidence” unless one understands meaning of the word “confidence” as used in context of confidence interval. Interpretation of the results of every study should always consider all possible alternative explanations like chance, bias, and confounding. Statistical tests in inferential statistics are, in general, designed to answer the question “How likely is the difference found in random sample(s) is due to chance” and therefore limitation of relying only on statistical significance in making clinical decisions should be avoided. PMID:22707861

Estimating order statistics of network degrees

NASA Astrophysics Data System (ADS)

Chu, J.; Nadarajah, S.

2018-01-01

We model the order statistics of network degrees of big data sets by a range of generalised beta distributions. A three parameter beta distribution due to Libby and Novick (1982) is shown to give the best overall fit for at least four big data sets. The fit of this distribution is significantly better than the fit suggested by Olhede and Wolfe (2012) across the whole range of order statistics for all four data sets.

Statistical aspects of solar flares

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1987-01-01

A survey of the statistical properties of 850 H alpha solar flares during 1975 is presented. Comparison of the results found here with those reported elsewhere for different epochs is accomplished. Distributions of rise time, decay time, and duration are given, as are the mean, mode, median, and 90th percentile values. Proportions by selected groupings are also determined. For flares in general, mean values for rise time, decay time, and duration are 5.2 + or - 0.4 min, and 18.1 + or 1.1 min, respectively. Subflares, accounting for nearly 90 percent of the flares, had mean values lower than those found for flares of H alpha importance greater than 1, and the differences are statistically significant. Likewise, flares of bright and normal relative brightness have mean values of decay time and duration that are significantly longer than those computed for faint flares, and mass-motion related flares are significantly longer than non-mass-motion related flares. Seventy-three percent of the mass-motion related flares are categorized as being a two-ribbon flare and/or being accompanied by a high-speed dark filament. Slow rise time flares (rise time greater than 5 min) have a mean value for duration that is significantly longer than that computed for fast rise time flares, and long-lived duration flares (duration greater than 18 min) have a mean value for rise time that is significantly longer than that computed for short-lived duration flares, suggesting a positive linear relationship between rise time and duration for flares. Monthly occurrence rates for flares in general and by group are found to be linearly related in a positive sense to monthly sunspot number. Statistical testing reveals the association between sunspot number and numbers of flares to be significant at the 95 percent level of confidence, and the t statistic for slope is significant at greater than 99 percent level of confidence. Dependent upon the specific fit, between 58 percent and 94 percent of

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

Robustness of statistical tests for multiplicative terms in the additive main effects and multiplicative interaction model for cultivar trials.

PubMed

Piepho, H P

1995-03-01

The additive main effects multiplicative interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the multiplicative interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, F GH1, FGH2, FR)to departures from these assumptions. It is concluded that, because of its better robustness, the F Rtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.

Childhood-compared to adolescent-onset bipolar disorder has more statistically significant clinical correlates.

PubMed

Holtzman, Jessica N; Miller, Shefali; Hooshmand, Farnaz; Wang, Po W; Chang, Kiki D; Hill, Shelley J; Rasgon, Natalie L; Ketter, Terence A

2015-07-01

The strengths and limitations of considering childhood-and adolescent-onset bipolar disorder (BD) separately versus together remain to be established. We assessed this issue. BD patients referred to the Stanford Bipolar Disorder Clinic during 2000-2011 were assessed with the Systematic Treatment Enhancement Program for BD Affective Disorders Evaluation. Patients with childhood- and adolescent-onset were compared to those with adult-onset for 7 unfavorable bipolar illness characteristics with replicated associations with early-onset patients. Among 502 BD outpatients, those with childhood- (<13 years, N=110) and adolescent- (13-18 years, N=218) onset had significantly higher rates for 4/7 unfavorable illness characteristics, including lifetime comorbid anxiety disorder, at least ten lifetime mood episodes, lifetime alcohol use disorder, and prior suicide attempt, than those with adult-onset (>18 years, N=174). Childhood- but not adolescent-onset BD patients also had significantly higher rates of first-degree relative with mood disorder, lifetime substance use disorder, and rapid cycling in the prior year. Patients with pooled childhood/adolescent - compared to adult-onset had significantly higher rates for 5/7 of these unfavorable illness characteristics, while patients with childhood- compared to adolescent-onset had significantly higher rates for 4/7 of these unfavorable illness characteristics. Caucasian, insured, suburban, low substance abuse, American specialty clinic-referred sample limits generalizability. Onset age is based on retrospective recall. Childhood- compared to adolescent-onset BD was more robustly related to unfavorable bipolar illness characteristics, so pooling these groups attenuated such relationships. Further study is warranted to determine the extent to which adolescent-onset BD represents an intermediate phenotype between childhood- and adult-onset BD. Copyright © 2015 Elsevier B.V. All rights reserved.

On Statistical Analysis of Neuroimages with Imperfect Registration

PubMed Central

Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

2016-01-01

A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

Illustrating the practice of statistics

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

Hamada, Christina A; Hamada, Michael S

2009-01-01

The practice of statistics involves analyzing data and planning data collection schemes to answer scientific questions. Issues often arise with the data that must be dealt with and can lead to new procedures. In analyzing data, these issues can sometimes be addressed through the statistical models that are developed. Simulation can also be helpful in evaluating a new procedure. Moreover, simulation coupled with optimization can be used to plan a data collection scheme. The practice of statistics as just described is much more than just using a statistical package. In analyzing the data, it involves understanding the scientific problem andmore » incorporating the scientist's knowledge. In modeling the data, it involves understanding how the data were collected and accounting for limitations of the data where possible. Moreover, the modeling is likely to be iterative by considering a series of models and evaluating the fit of these models. Designing a data collection scheme involves understanding the scientist's goal and staying within hislher budget in terms of time and the available resources. Consequently, a practicing statistician is faced with such tasks and requires skills and tools to do them quickly. We have written this article for students to provide a glimpse of the practice of statistics. To illustrate the practice of statistics, we consider a problem motivated by some precipitation data that our relative, Masaru Hamada, collected some years ago. We describe his rain gauge observational study in Section 2. We describe modeling and an initial analysis of the precipitation data in Section 3. In Section 4, we consider alternative analyses that address potential issues with the precipitation data. In Section 5, we consider the impact of incorporating additional infonnation. We design a data collection scheme to illustrate the use of simulation and optimization in Section 6. We conclude this article in Section 7 with a discussion.« less

The Relationship between Statistics Self-Efficacy, Statistics Anxiety, and Performance in an Introductory Graduate Statistics Course

ERIC Educational Resources Information Center

Schneider, William R.

2011-01-01

The purpose of this study was to determine the relationship between statistics self-efficacy, statistics anxiety, and performance in introductory graduate statistics courses. The study design compared two statistics self-efficacy measures developed by Finney and Schraw (2003), a statistics anxiety measure developed by Cruise and Wilkins (1980),…

Chi-squared and C statistic minimization for low count per bin data

NASA Astrophysics Data System (ADS)

Nousek, John A.; Shue, David R.

1989-07-01

Results are presented from a computer simulation comparing two statistical fitting techniques on data samples with large and small counts per bin; the results are then related specifically to X-ray astronomy. The Marquardt and Powell minimization techniques are compared by using both to minimize the chi-squared statistic. In addition, Cash's C statistic is applied, with Powell's method, and it is shown that the C statistic produces better fits in the low-count regime than chi-squared.

Statistical Control Paradigm for Aerospace Structures Under Impulsive Disturbances

DTIC Science & Technology

2006-08-03

attitude control system with an innovative and robust statistical controller design shows significant promise for use in attitude hold mode operation...indicate that the existing attitude control system with an innovative and robust statistical controller design shows significant promise for use in...and three thrusters are for use in controlling the attitude of the satellite. Then the angular momentum of the satellite with three thrusters and a

Investigating the cognitive structure of stereotypes: Generic beliefs about groups predict social judgments better than statistical beliefs.

PubMed

Hammond, Matthew D; Cimpian, Andrei

2017-05-01

Stereotypes are typically defined as beliefs about groups, but this definition is underspecified. Beliefs about groups can be generic or statistical. Generic beliefs attribute features to entire groups (e.g., men are strong), whereas statistical beliefs encode the perceived prevalence of features (e.g., how common it is for men to be strong). In the present research, we sought to determine which beliefs-generic or statistical-are more central to the cognitive structure of stereotypes. Specifically, we tested whether generic or statistical beliefs are more influential in people's social judgments, on the assumption that greater functional importance indicates greater centrality in stereotype structure. Relative to statistical beliefs, generic beliefs about social groups were significantly stronger predictors of expectations (Studies 1-3) and explanations (Study 4) for unfamiliar individuals' traits. In addition, consistent with prior evidence that generic beliefs are cognitively simpler than statistical beliefs, generic beliefs were particularly predictive of social judgments for participants with more intuitive (vs. analytic) cognitive styles and for participants higher (vs. lower) in authoritarianism, who tend to view outgroups in simplistic, all-or-none terms. The present studies suggest that generic beliefs about groups are more central than statistical beliefs to the cognitive structure of stereotypes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

NASA Pocket Statistics

NASA Technical Reports Server (NTRS)

1995-01-01

NASA Pocket Statistics is published for the use of NASA managers and their staff. Included herein is Administrative and Organizational information, summaries of Space Flight Activity including the NASA Major Launch Record, and NASA Procurement, Financial, and Manpower data. The NASA Major Launch Record includes all launches of Scout class and larger vehicles. Vehicle and spacecraft development flights are also included in the Major Launch Record. Shuttle missions are counted as one launch and one payload, where free flying payloads are not involved. Satellites deployed from the cargo bay of the Shuttle and placed in a separate orbit or trajectory are counted as an additional payload.

NASA Pocket Statistics

NASA Technical Reports Server (NTRS)

1994-01-01

Pocket Statistics is published for the use of NASA managers and their staff. Included herein is Administrative and Organizational information, summaries of Space Flight Activity including the NASA Major Launch Record, and NASA Procurement, Financial, and Manpower data. The NASA Major Launch Record includes all launches of Scout class and larger vehicles. Vehicle and spacecraft development flights are also included in the Major Launch Record. Shuttle missions are counted as one launch and one payload, where free flying payloads are not involved. Satellites deployed from the cargo bay of the Shuttle and placed in a separate orbit or trajectory are counted as an additional payload.

Simulating statistics of lightning-induced and man made fires

NASA Astrophysics Data System (ADS)

Krenn, R.; Hergarten, S.

2009-04-01

The frequency-area distributions of forest fires show power-law behavior with scaling exponents α in a quite narrow range, relating wildfire research to the theoretical framework of self-organized criticality. Examples of self-organized critical behavior can be found in computer simulations of simple cellular automata. The established self-organized critical Drossel-Schwabl forest fire model (DS-FFM) is one of the most widespread models in this context. Despite its qualitative agreement with event-size statistics from nature, its applicability is still questioned. Apart from general concerns that the DS-FFM apparently oversimplifies the complex nature of forest dynamics, it significantly overestimates the frequency of large fires. We present a straightforward modification of the model rules that increases the scaling exponent α by approximately 1•3 and brings the simulated event-size statistics close to those observed in nature. In addition, combined simulations of both the original and the modified model predict a dependence of the overall distribution on the ratio of lightning induced and man made fires as well as a difference between their respective event-size statistics. The increase of the scaling exponent with decreasing lightning probability as well as the splitting of the partial distributions are confirmed by the analysis of the Canadian Large Fire Database. As a consequence, lightning induced and man made forest fires cannot be treated separately in wildfire modeling, hazard assessment and forest management.

[Comment on] Statistical discrimination

NASA Astrophysics Data System (ADS)

Chinn, Douglas

In the December 8, 1981, issue of Eos, a news item reported the conclusion of a National Research Council study that sexual discrimination against women with Ph.D.'s exists in the field of geophysics. Basically, the item reported that even when allowances are made for motherhood the percentage of female Ph.D.'s holding high university and corporate positions is significantly lower than the percentage of male Ph.D.'s holding the same types of positions. The sexual discrimination conclusion, based only on these statistics, assumes that there are no basic psychological differences between men and women that might cause different populations in the employment group studied. Therefore, the reasoning goes, after taking into account possible effects from differences related to anatomy, such as women stopping their careers in order to bear and raise children, the statistical distributions of positions held by male and female Ph.D.'s ought to be very similar to one another. Any significant differences between the distributions must be caused primarily by sexual discrimination.

Polyphenols content, phenolics profile and antioxidant activity of organic red wines produced without sulfur dioxide/sulfites addition in comparison to conventional red wines.

PubMed

Garaguso, Ivana; Nardini, Mirella

2015-07-15

Wine exerts beneficial effects on human health when it is drunk with moderation. Nevertheless, wine may also contain components negatively affecting human health. Among these, sulfites may induce adverse effects after ingestion. We examined total polyphenols and flavonoids content, phenolics profile and antioxidant activity of eight organic red wines produced without sulfur dioxide/sulfites addition in comparison to those of eight conventional red wines. Polyphenols and flavonoids content were slightly higher in organic wines in respect to conventional wines, however differences did not reach statistical significance. The phenolic acids profile was quite similar in both groups of wines. Antioxidant activity was higher in organic wines compared to conventional wines, although differences were not statistically significant. Our results indicate that organic red wines produced without sulfur dioxide/sulfites addition are comparable to conventional red wines with regard to the total polyphenols and flavonoids content, the phenolics profile and the antioxidant activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Relationship between Graduate Students' Statistics Self-Efficacy, Statistics Anxiety, Attitude toward Statistics, and Social Support

ERIC Educational Resources Information Center

Perepiczka, Michelle; Chandler, Nichelle; Becerra, Michael

2011-01-01

Statistics plays an integral role in graduate programs. However, numerous intra- and interpersonal factors may lead to successful completion of needed coursework in this area. The authors examined the extent of the relationship between self-efficacy to learn statistics and statistics anxiety, attitude towards statistics, and social support of 166…

Empirical Bayes scan statistics for detecting clusters of disease risk variants in genetic studies.

PubMed

McCallum, Kenneth J; Ionita-Laza, Iuliana

2015-12-01

Recent developments of high-throughput genomic technologies offer an unprecedented detailed view of the genetic variation in various human populations, and promise to lead to significant progress in understanding the genetic basis of complex diseases. Despite this tremendous advance in data generation, it remains very challenging to analyze and interpret these data due to their sparse and high-dimensional nature. Here, we propose novel applications and new developments of empirical Bayes scan statistics to identify genomic regions significantly enriched with disease risk variants. We show that the proposed empirical Bayes methodology can be substantially more powerful than existing scan statistics methods especially so in the presence of many non-disease risk variants, and in situations when there is a mixture of risk and protective variants. Furthermore, the empirical Bayes approach has greater flexibility to accommodate covariates such as functional prediction scores and additional biomarkers. As proof-of-concept we apply the proposed methods to a whole-exome sequencing study for autism spectrum disorders and identify several promising candidate genes. © 2015, The International Biometric Society.

Additive interaction between heterogeneous environmental ...

EPA Pesticide Factsheets

BACKGROUND 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 2000-2005.METHODS: 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 (PD) and 95% confidence intervals (CI) 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 additive interaction for the all U.S counties. Analyses were also performed for subgroupings by four urban/rural strata. RESULTS: 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 interac

On an additive partial correlation operator and nonparametric estimation of graphical models.

PubMed

Lee, Kuang-Yao; Li, Bing; Zhao, Hongyu

2016-09-01

We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance.

On an additive partial correlation operator and nonparametric estimation of graphical models

PubMed Central

Li, Bing; Zhao, Hongyu

2016-01-01

Abstract We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance. PMID:29422689

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

PubMed

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

2009-03-01

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

Forest statistics of Indiana

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1953-01-01

The Forest Survey is conducted in the various regions by the forest experiment stations of the Forest Service. In Indiana the project is directed by the Central States Forest Experiment Station with headquarters in Columbus, Ohio. This Survey Release presents the more significant preliminary statistics on the forest area timber volume, timber growth, and timber drain...

Forest statistics of Kentucky

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1952-01-01

The Forest Survey is conducted in the various regions by the forest experiment stations of the Forest Service. In Kentucky the project is directed by the Central States Forest Experiment Station with headquarters in Columbus, Ohio. This Survey Release presents the more significant preliminary statistics on the forest area, timber volume, timber growth, and timber drain...

Plant extracts as phytogenic additives considering intake, digestibility, and feeding behavior of sheep.

PubMed

da Silva, Camila Sousa; de Souza, Evaristo Jorge Oliveira; Pereira, Gerfesson Felipe Cavalcanti; Cavalcante, Edwilka Oliveira; de Lima, Ewerton Ivo Martins; Torres, Thaysa Rodrigues; da Silva, José Ricardo Coelho; da Silva, Daniel Cézar

2017-02-01

The objective was to evaluate the intake, digestibility, and ingestive sheep behavior with feeding phytogenic additives derived from plant extracts. Five non-emasculated sheep without defined breed at 28 ± 1.81 kg initial body weight and 6 months age were used. Treatments consisted of administering four phytogenic additives from the garlic extracts, coriander seed, oregano, and pods of mesquite, plus a control treatment (without additive). The ration was composed of Tifton 85 hay grass, corn, soybean meal, and mineral salt. As experimental design, we used a 5 × 5 Latin square design (five treatments and five periods). The data were analyzed through the mixed model through the procedure PROC MIXED of software Systems Statistical Analysis version 9.1, with comparation analysis between the treatment without additive (control) with phytogenic additives produced from vegetable extracts of mesquite pod, of coriander seed, the bulb of garlic, and the oregano leaves. There were no significant differences for the nutrient intake and ingestive behavior patterns. However, the additive intake derived from mesquite pods and coriander extracts provided an increase in digestibility. Extracts from garlic, coriander, and mesquite pods can be used as phytogenic additives in feeding sheep.

A simulation study of the strength of evidence in the recommendation of medications based on two trials with statistically significant results

PubMed Central

Ioannidis, John P. A.

2017-01-01

A typical rule that has been used for the endorsement of new medications by the Food and Drug Administration is to have two trials, each convincing on its own, demonstrating effectiveness. “Convincing” may be subjectively interpreted, but the use of p-values and the focus on statistical significance (in particular with p < .05 being coined significant) is pervasive in clinical research. Therefore, in this paper, we calculate with simulations what it means to have exactly two trials, each with p < .05, in terms of the actual strength of evidence quantified by Bayes factors. Our results show that different cases where two trials have a p-value below .05 have wildly differing Bayes factors. Bayes factors of at least 20 in favor of the alternative hypothesis are not necessarily achieved and they fail to be reached in a large proportion of cases, in particular when the true effect size is small (0.2 standard deviations) or zero. In a non-trivial number of cases, evidence actually points to the null hypothesis, in particular when the true effect size is zero, when the number of trials is large, and when the number of participants in both groups is low. We recommend use of Bayes factors as a routine tool to assess endorsement of new medications, because Bayes factors consistently quantify strength of evidence. Use of p-values may lead to paradoxical and spurious decision-making regarding the use of new medications. PMID:28273140

Statistical Exposé of a Multiple-Compartment Anaerobic Reactor Treating Domestic Wastewater.

PubMed

Pfluger, Andrew R; Hahn, Martha J; Hering, Amanda S; Munakata-Marr, Junko; Figueroa, Linda

2018-06-01

  Mainstream anaerobic treatment of domestic wastewater is a promising energy-generating treatment strategy; however, such reactors operated in colder regions are not well characterized. Performance data from a pilot-scale, multiple-compartment anaerobic reactor taken over 786 days were subjected to comprehensive statistical analyses. Results suggest that chemical oxygen demand (COD) was a poor proxy for organics in anaerobic systems as oxygen demand from dissolved inorganic material, dissolved methane, and colloidal material influence dissolved and particulate COD measurements. Additionally, univariate and functional boxplots were useful in visualizing variability in contaminant concentrations and identifying statistical outliers. Further, significantly different dissolved organic removal and methane production was observed between operational years, suggesting that anaerobic reactor systems may not achieve steady-state performance within one year. Last, modeling multiple-compartment reactor systems will require data collected over at least two years to capture seasonal variations of the major anaerobic microbial functions occurring within each reactor compartment.

Testing for significance of phase synchronisation dynamics in the EEG.

PubMed

Daly, Ian; Sweeney-Reed, Catherine M; Nasuto, Slawomir J

2013-06-01

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

Effects of the food additive, citric acid, on kidney cells of mice.

PubMed

Chen, Xg; Lv, Qx; Liu, Ym; Deng, W

2015-01-01

Citric acid is a food additive that is widely used in the food and drink industry. We investigated the effects of citric acid injection on mouse kidney. Forty healthy mice were divided into four groups of 10 including one control group and three citric acid-treated groups. Low dose, middle dose and high dose groups were given doses of 120, 240 and 480 mg/kg of citric acid, respectively. On day 7, kidney tissues were collected for histological, biochemical and molecular biological examination. We observed shrinkage of glomeruli, widened urinary spaces and capillary congestion, narrowing of the tubule lumen, edema and cytoplasmic vacuolated tubule cells, and appearance of pyknotic nuclei. The relation between histopathological changes and citric acid was dose dependent. Compared to the control, T-SOD and GSH-Px activities in the treated groups decreased with increasing doses of citric acid, NOS activity tended to increase, and H2O2 and MDA contents gradually decreased, but the differences between any treated group and the control were not statistically significant. The apoptosis assay showed a dose-dependent increase of caspase-3 activity after administering citrate that was statistically significant. DNA ladder formation occurred after treatment with any dose of citric acid. We concluded that administration of citric acid may cause renal toxicity in mice.

Survey of Attitudes Toward Statistics: Factor Structure Invariance by Gender and by Administration Time

ERIC Educational Resources Information Center

Hilton, Sterling C.; Schau, Candace; Olsen, Joseph A.

2004-01-01

In addition to student learning, positive student attitudes have become an important course outcome for many introductory statistics instructors. To adequately assess changes in mean attitudes across introductory statistics courses, the attitude instruments used should be invariant by administration time. Attitudes toward statistics from 4,910…

The Effect Size Statistic: Overview of Various Choices.

ERIC Educational Resources Information Center

Mahadevan, Lakshmi

Over the years, methodologists have been recommending that researchers use magnitude of effect estimates in result interpretation to highlight the distinction between statistical and practical significance (cf. R. Kirk, 1996). A magnitude of effect statistic (i.e., effect size) tells to what degree the dependent variable can be controlled,…

2017 Workplace and Gender Relations Survey of Reserve Component Members: Statistical Methodology Report

DTIC Science & Technology

2018-04-30

2017 Workplace and Gender Relations Survey of Reserve Component Members Statistical Methodology Report Additional copies of this report...Survey of Reserve Component Members Statistical Methodology Report Office of People Analytics (OPA) 4800 Mark Center Drive, Suite...RESERVE COMPONENT MEMBERS STATISTICAL METHODOLOGY REPORT Introduction The Office of People Analytics’ Center for Health and Resilience (OPA[H&R

Why significant variables aren't automatically good predictors.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2015-11-10

Thus far, genome-wide association studies (GWAS) have been disappointing in the inability of investigators to use the results of identified, statistically significant variants in complex diseases to make predictions useful for personalized medicine. Why are significant variables not leading to good prediction of outcomes? We point out that this problem is prevalent in simple as well as complex data, in the sciences as well as the social sciences. We offer a brief explanation and some statistical insights on why higher significance cannot automatically imply stronger predictivity and illustrate through simulations and a real breast cancer example. We also demonstrate that highly predictive variables do not necessarily appear as highly significant, thus evading the researcher using significance-based methods. We point out that what makes variables good for prediction versus significance depends on different properties of the underlying distributions. If prediction is the goal, we must lay aside significance as the only selection standard. We suggest that progress in prediction requires efforts toward a new research agenda of searching for a novel criterion to retrieve highly predictive variables rather than highly significant variables. We offer an alternative approach that was not designed for significance, the partition retention method, which was very effective predicting on a long-studied breast cancer data set, by reducing the classification error rate from 30% to 8%.

Harmonic statistics

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-05-01

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.

A simulations approach for meta-analysis of genetic association studies based on additive genetic model.

PubMed

John, Majnu; Lencz, Todd; Malhotra, Anil K; Correll, Christoph U; Zhang, Jian-Ping

2018-06-01

Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.

Statistical process control in nursing research.

PubMed

Polit, Denise F; Chaboyer, Wendy

2012-02-01

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. Copyright © 2011 Wiley Periodicals, Inc.

The Probabilistic Admissible Region with Additional Constraints

NASA Astrophysics Data System (ADS)

Roscoe, C.; Hussein, I.; Wilkins, M.; Schumacher, P.

The admissible region, in the space surveillance field, is defined as the set of physically acceptable orbits (e.g., orbits with negative energies) consistent with one or more observations of a space object. Given additional constraints on orbital semimajor axis, eccentricity, etc., the admissible region can be constrained, resulting in the constrained admissible region (CAR). Based on known statistics of the measurement process, one can replace hard constraints with a probabilistic representation of the admissible region. This results in the probabilistic admissible region (PAR), which can be used for orbit initiation in Bayesian tracking and prioritization of tracks in a multiple hypothesis tracking framework. The PAR concept was introduced by the authors at the 2014 AMOS conference. In that paper, a Monte Carlo approach was used to show how to construct the PAR in the range/range-rate space based on known statistics of the measurement, semimajor axis, and eccentricity. An expectation-maximization algorithm was proposed to convert the particle cloud into a Gaussian Mixture Model (GMM) representation of the PAR. This GMM can be used to initialize a Bayesian filter. The PAR was found to be significantly non-uniform, invalidating an assumption frequently made in CAR-based filtering approaches. Using the GMM or particle cloud representations of the PAR, orbits can be prioritized for propagation in a multiple hypothesis tracking (MHT) framework. In this paper, the authors focus on expanding the PAR methodology to allow additional constraints, such as a constraint on perigee altitude, to be modeled in the PAR. This requires re-expressing the joint probability density function for the attributable vector as well as the (constrained) orbital parameters and range and range-rate. The final PAR is derived by accounting for any interdependencies between the parameters. Noting that the concepts presented are general and can be applied to any measurement scenario, the idea

Statistics Anxiety and Business Statistics: The International Student

ERIC Educational Resources Information Center

Bell, James A.

2008-01-01

Does the international student suffer from statistics anxiety? To investigate this, the Statistics Anxiety Rating Scale (STARS) was administered to sixty-six beginning statistics students, including twelve international students and fifty-four domestic students. Due to the small number of international students, nonparametric methods were used to…

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

TAGCNA: A Method to Identify Significant Consensus Events of Copy Number Alterations in Cancer

PubMed Central

Yuan, Xiguo; Zhang, Junying; Yang, Liying; Zhang, Shengli; Chen, Baodi; Geng, Yaojun; Wang, Yue

2012-01-01

Somatic copy number alteration (CNA) is a common phenomenon in cancer genome. Distinguishing significant consensus events (SCEs) from random background CNAs in a set of subjects has been proven to be a valuable tool to study cancer. In order to identify SCEs with an acceptable type I error rate, better computational approaches should be developed based on reasonable statistics and null distributions. In this article, we propose a new approach named TAGCNA for identifying SCEs in somatic CNAs that may encompass cancer driver genes. TAGCNA employs a peel-off permutation scheme to generate a reasonable null distribution based on a prior step of selecting tag CNA markers from the genome being considered. We demonstrate the statistical power of TAGCNA on simulated ground truth data, and validate its applicability using two publicly available cancer datasets: lung and prostate adenocarcinoma. TAGCNA identifies SCEs that are known to be involved with proto-oncogenes (e.g. EGFR, CDK4) and tumor suppressor genes (e.g. CDKN2A, CDKN2B), and provides many additional SCEs with potential biological relevance in these data. TAGCNA can be used to analyze the significance of CNAs in various cancers. It is implemented in R and is freely available at http://tagcna.sourceforge.net/. PMID:22815924

Changing world extreme temperature statistics

NASA Astrophysics Data System (ADS)

Finkel, J. M.; Katz, J. I.

2018-04-01

We use the Global Historical Climatology Network--daily database to calculate a nonparametric statistic that describes the rate at which all-time daily high and low temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid-20th Century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all-time high records were set at a rate significantly (at least $3\\sigma$) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all-time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all-time highs increased suddenly in the 1990's, suggesting a change in regional climate regime; in most other regions there was a steadier increase.

Statistical Seismology and Induced Seismicity

NASA Astrophysics Data System (ADS)

Tiampo, K. F.; González, P. J.; Kazemian, J.

2014-12-01

While seismicity triggered or induced by natural resources production such as mining or water impoundment in large dams has long been recognized, the recent increase in the unconventional production of oil and gas has been linked to rapid rise in seismicity in many places, including central North America (Ellsworth et al., 2012; Ellsworth, 2013). Worldwide, induced events of M~5 have occurred and, although rare, have resulted in both damage and public concern (Horton, 2012; Keranen et al., 2013). In addition, over the past twenty years, the increase in both number and coverage of seismic stations has resulted in an unprecedented ability to precisely record the magnitude and location of large numbers of small magnitude events. The increase in the number and type of seismic sequences available for detailed study has revealed differences in their statistics that previously difficult to quantify. For example, seismic swarms that produce significant numbers of foreshocks as well as aftershocks have been observed in different tectonic settings, including California, Iceland, and the East Pacific Rise (McGuire et al., 2005; Shearer, 2012; Kazemian et al., 2014). Similarly, smaller events have been observed prior to larger induced events in several occurrences from energy production. The field of statistical seismology has long focused on the question of triggering and the mechanisms responsible (Stein et al., 1992; Hill et al., 1993; Steacy et al., 2005; Parsons, 2005; Main et al., 2006). For example, in most cases the associated stress perturbations are much smaller than the earthquake stress drop, suggesting an inherent sensitivity to relatively small stress changes (Nalbant et al., 2005). Induced seismicity provides the opportunity to investigate triggering and, in particular, the differences between long- and short-range triggering. Here we investigate the statistics of induced seismicity sequences from around the world, including central North America and Spain, and

Neurotoxicological and statistical analyses of a mixture of five organophosphorus pesticides using a ray design.

PubMed

Moser, V C; Casey, M; Hamm, A; Carter, W H; Simmons, J E; Gennings, C

2005-07-01

Environmental exposures generally involve chemical mixtures instead of single chemicals. Statistical models such as the fixed-ratio ray design, wherein the mixing ratio (proportions) of the chemicals is fixed across increasing mixture doses, allows for the detection and characterization of interactions among the chemicals. In this study, we tested for interaction(s) in a mixture of five organophosphorus (OP) pesticides (chlorpyrifos, diazinon, dimethoate, acephate, and malathion). The ratio of the five pesticides (full ray) reflected the relative dietary exposure estimates of the general population as projected by the US EPA Dietary Exposure Evaluation Model (DEEM). A second mixture was tested using the same dose levels of all pesticides, but excluding malathion (reduced ray). The experimental approach first required characterization of dose-response curves for the individual OPs to build a dose-additivity model. A series of behavioral measures were evaluated in adult male Long-Evans rats at the time of peak effect following a single oral dose, and then tissues were collected for measurement of cholinesterase (ChE) activity. Neurochemical (blood and brain cholinesterase [ChE] activity) and behavioral (motor activity, gait score, tail-pinch response score) endpoints were evaluated statistically for evidence of additivity. The additivity model constructed from the single chemical data was used to predict the effects of the pesticide mixture along the full ray (10-450 mg/kg) and the reduced ray (1.75-78.8 mg/kg). The experimental mixture data were also modeled and statistically compared to the additivity models. Analysis of the 5-OP mixture (the full ray) revealed significant deviation from additivity for all endpoints except tail-pinch response. Greater-than-additive responses (synergism) were observed at the lower doses of the 5-OP mixture, which contained non-effective dose levels of each of the components. The predicted effective doses (ED20, ED50) were about half

Effect of lubricant extreme-pressure additives on surface fatigue life of AISI 9310 spur gears

NASA Technical Reports Server (NTRS)

Scibbe, H. W.; Townsend, D. P.; Aron, P. R.

1984-01-01

Surface fatigue tests were conducted with AISI 9310 spur gears using a formulated synthetic tetraester oil (conforming to MIL-L-23699 specifications) as the lubricant containing either sulfur or phosphorus as the EP additive. Four groups of gears were tested. One group of gears tested without an additive in the lubricant acted as the reference oil. In the other three groups either a 0.1 wt % sulfur or phosphorus additive was added to the tetraester oil to enhance gear surface fatigue life. Test conditions included a gear temperature of 334 K (160 F), a maximum Hertz stress of 1.71 GPa (248 000 psi), and a speed of 10,000 rpm. The gears tested with a 0.1 wt % phosphorus additive showed pitting fatigue life 2.6 times the life of gears tested with the reference tetraester based oil. Although fatigue lives of two groups of gears tested with the sulfur additive in the oil showed improvement over the control group gear life, the results, unlike those obtained with the phosphorus oil, were not considered to be statistically significant.

Validation of Reverse-Engineered and Additive-Manufactured Microsurgical Instrument Prototype.

PubMed

Singh, Ramandeep; Suri, Ashish; Anand, Sneh; Baby, Britty

2016-12-01

With advancements in imaging techniques, neurosurgical procedures are becoming highly precise and minimally invasive, thus demanding development of new ergonomically aesthetic instruments. Conventionally, neurosurgical instruments are manufactured using subtractive manufacturing methods. Such a process is complex, time-consuming, and impractical for prototype development and validation of new designs. Therefore, an alternative design process has been used utilizing blue light scanning, computer-aided designing, and additive manufacturing direct metal laser sintering (DMLS) for microsurgical instrument prototype development. Deviations of DMLS-fabricated instrument were studied by superimposing scan data of fabricated instrument with the computer-aided designing model. Content and concurrent validity of the fabricated prototypes was done by a group of 15 neurosurgeons by performing sciatic nerve anastomosis in small laboratory animals. Comparative scoring was obtained for the control and study instrument. T test was applied to the individual parameters and P values for force (P < .0001) and surface roughness (P < .01) were found to be statistically significant. These 2 parameters were further analyzed using objective measures. Results depicts that additive manufacturing by DMLS provides an effective method for prototype development. However, direct application of these additive-manufactured instruments in the operating room requires further validation. © The Author(s) 2016.

Software Used to Generate Cancer Statistics - SEER Cancer Statistics

Cancer.gov

Videos that highlight topics and trends in cancer statistics and definitions of statistical terms. Also software tools for analyzing and reporting cancer statistics, which are used to compile SEER's annual reports.

Marker-Based Estimates Reveal Significant Non-additive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties.

PubMed

Wolfe, Marnin D; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

2016-08-31

In clonally propagated crops, non-additive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of non-additive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and non-additive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus non-additive) genetic value. We confirmed previous findings based on diallel populations, that non-additive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in CMD resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species. Copyright © 2016 Author et al.

Understanding Statistics and Statistics Education: A Chinese Perspective

ERIC Educational Resources Information Center

Shi, Ning-Zhong; He, Xuming; Tao, Jian

2009-01-01

In recent years, statistics education in China has made great strides. However, there still exists a fairly large gap with the advanced levels of statistics education in more developed countries. In this paper, we identify some existing problems in statistics education in Chinese schools and make some proposals as to how they may be overcome. We…

Design of order statistics filters using feedforward neural networks

NASA Astrophysics Data System (ADS)

Maslennikova, Yu. S.; Bochkarev, V. V.

2016-08-01

In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

Detailed Spectral Analysis of the 260 ks XMM-Newton Data of 1E 1207.4-5209 and Significance of a 2.1 keV Absorption Feature

NASA Astrophysics Data System (ADS)

Mori, Kaya; Chonko, James C.; Hailey, Charles J.

2005-10-01

We have reanalyzed the 260 ks XMM-Newton observation of 1E 1207.4-5209. There are several significant improvements over previous work. First, a much broader range of physically plausible spectral models was used. Second, we have used a more rigorous statistical analysis. The standard F-distribution was not employed, but rather the exact finite statistics F-distribution was determined by Monte Carlo simulations. This approach was motivated by the recent work of Protassov and coworkers and Freeman and coworkers. They demonstrated that the standard F-distribution is not even asymptotically correct when applied to assess the significance of additional absorption features in a spectrum. With our improved analysis we do not find a third and fourth spectral feature in 1E 1207.4-5209 but only the two broad absorption features previously reported. Two additional statistical tests, one line model dependent and the other line model independent, confirmed our modified F-test analysis. For all physically plausible continuum models in which the weak residuals are strong enough to fit, the residuals occur at the instrument Au M edge. As a sanity check we confirmed that the residuals are consistent in strength and position with the instrument Au M residuals observed in 3C 273.

Directory of Michigan Library Statistics. 1994 Edition. Reporting 1992 and 1993 Statistical Activities including: Public Library Statistics, Library Cooperative Statistics, Regional/Subregional Statistics.

ERIC Educational Resources Information Center

Leaf, Donald C., Comp.; Neely, Linda, Comp.

This edition focuses on statistical data supplied by Michigan public libraries, public library cooperatives, and those public libraries which serve as regional or subregional outlets for blind and physically handicapped services. Since statistics in Michigan academic libraries are typically collected in odd-numbered years, they are not included…

A note on generalized Genome Scan Meta-Analysis statistics

PubMed Central

Koziol, James A; Feng, Anne C

2005-01-01

Background Wise et al. introduced a rank-based statistical technique for meta-analysis of genome scans, the Genome Scan Meta-Analysis (GSMA) method. Levinson et al. recently described two generalizations of the GSMA statistic: (i) a weighted version of the GSMA statistic, so that different studies could be ascribed different weights for analysis; and (ii) an order statistic approach, reflecting the fact that a GSMA statistic can be computed for each chromosomal region or bin width across the various genome scan studies. Results We provide an Edgeworth approximation to the null distribution of the weighted GSMA statistic, and, we examine the limiting distribution of the GSMA statistics under the order statistic formulation, and quantify the relevance of the pairwise correlations of the GSMA statistics across different bins on this limiting distribution. We also remark on aggregate criteria and multiple testing for determining significance of GSMA results. Conclusion Theoretical considerations detailed herein can lead to clarification and simplification of testing criteria for generalizations of the GSMA statistic. PMID:15717930

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

Statistics of Low-Mass Companions to Stars: Implications for Their Origin

NASA Technical Reports Server (NTRS)

Stepinski, T. F.; Black, D. C.

2001-01-01

One of the more significant results from observational astronomy over the past few years has been the detection, primarily via radial velocity studies, of low-mass companions (LMCs) to solar-like stars. The commonly held interpretation of these is that the majority are "extrasolar planets" whereas the rest are brown dwarfs, the distinction made on the basis of apparent discontinuity in the distribution of M sin i for LMCs as revealed by a histogram. We report here results from statistical analysis of M sin i, as well as of the orbital elements data for available LMCs, to rest the assertion that the LMCs population is heterogeneous. The outcome is mixed. Solely on the basis of the distribution of M sin i a heterogeneous model is preferable. Overall, we find that a definitive statement asserting that LMCs population is heterogeneous is, at present, unjustified. In addition we compare statistics of LMCs with a comparable sample of stellar binaries. We find a remarkable statistical similarity between these two populations. This similarity coupled with marked populational dissimilarity between LMCs and acknowledged planets motivates us to suggest a common origin hypothesis for LMCs and stellar binaries as an alternative to the prevailing interpretation. We discuss merits of such a hypothesis and indicate a possible scenario for the formation of LMCs.

A comparative study of additive and subtractive manufacturing for dental restorations.

PubMed

Bae, Eun-Jeong; Jeong, Il-Do; Kim, Woong-Chul; Kim, Ji-Hwan

2017-08-01

Digital systems have recently found widespread application in the fabrication of dental restorations. For the clinical assessment of dental restorations fabricated digitally, it is necessary to evaluate their accuracy. However, studies of the accuracy of inlay restorations fabricated with additive manufacturing are lacking. The purpose of this in vitro study was to evaluate and compare the accuracy of inlay restorations fabricated by using recently introduced additive manufacturing with the accuracy of subtractive methods. The inlay (distal occlusal cavity) shape was fabricated using 3-dimensional image (reference data) software. Specimens were fabricated using 4 different methods (each n=10, total N=40), including 2 additive manufacturing methods, stereolithography apparatus and selective laser sintering; and 2 subtractive methods, wax and zirconia milling. Fabricated specimens were scanned using a dental scanner and then compared by overlapping reference data. The results were statistically analyzed using a 1-way analysis of variance (α=.05). Additionally, the surface morphology of 1 randomly (the first of each specimen) selected specimen from each group was evaluated using a digital microscope. The results of the overlap analysis of the dental restorations indicated that the root mean square (RMS) deviation observed in the restorations fabricated using the additive manufacturing methods were significantly different from those fabricated using the subtractive methods (P<.05). However, no significant differences were found between restorations fabricated using stereolithography apparatus and selective laser sintering, the additive manufacturing methods (P=.466). Similarly, no significant differences were found between wax and zirconia, the subtractive methods (P=.986). The observed RMS values were 106 μm for stereolithography apparatus, 113 μm for selective laser sintering, 116 μm for wax, and 119 μm for zirconia. Microscopic evaluation of the surface

Cardiovascular risk assessment: addition of CKD and race to the Framingham equation

PubMed Central

Drawz, Paul E.; Baraniuk, Sarah; Davis, Barry R.; Brown, Clinton D.; Colon, Pedro J.; Cujyet, Aloysius B.; Dart, Richard A.; Graumlich, James F.; Henriquez, Mario A.; Moloo, Jamaluddin; Sakalayen, Mohammed G.; Simmons, Debra L.; Stanford, Carol; Sweeney, Mary Ellen; Wong, Nathan D.; Rahman, Mahboob

2012-01-01

Background/Aims The value of the Framingham equation in predicting cardiovascular risk in African Americans and patients with chronic kidney disease (CKD) is unclear. The purpose of the study was to evaluate whether the addition of CKD and race to the Framingham equation improves risk stratification in hypertensive patients. Methods Participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) were studied. Those randomized to doxazosin, age greater than 74 years, and those with a history of coronary heart disease (CHD) were excluded. Two risk stratification models were developed using Cox proportional hazards models in a two-thirds developmental sample. The first model included the traditional Framingham risk factors. The second model included the traditional risk factors plus CKD, defined by eGFR categories, and stratification by race (Black vs. Non-Black). The primary outcome was a composite of fatal CHD, nonfatal MI, coronary revascularization, and hospitalized angina. Results There were a total of 19,811 eligible subjects. In the validation cohort, there was no difference in C-statistics between the Framingham equation and the ALLHAT model including CKD and race. This was consistent across subgroups by race and gender and among those with CKD. One exception was among Non-Black women where the C-statistic was higher for the Framingham equation (0.68 vs 0.65, P=0.02). Additionally, net reclassification improvement was not significant for any subgroup based on race and gender, ranging from −5.5% to 4.4%. Conclusion The addition of CKD status and stratification by race does not improve risk prediction in high-risk hypertensive patients. PMID:23194494

VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS

PubMed Central

Huang, Jian; Horowitz, Joel L.; Wei, Fengrong

2010-01-01

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is “small” relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method. PMID:21127739

Spectral-domain Optical Coherence Tomography in Manifest Glaucoma: Its Additive Role in Structural Diagnosis.

PubMed

Kim, Ko Eun; Oh, Sohee; Jeoung, Jin Wook; Suh, Min Hee; Seo, Je Hyun; Kim, Martha; Park, Ki Ho; Kim, Dong Myung; Kim, Seok Hwan

2016-11-01

To investigate the additive role of spectral-domain optical coherence tomography (SDOCT) in the structural diagnosis in glaucoma. Reliability and validity analysis. Structural examinations from 109 eyes of 109 healthy individuals and 151 eyes of 151 glaucoma patients with different severities were included. Four structural-diagnostic examination sets were prepared using stereo-optic disc photography (SDP), red-free retinal nerve fiber layer photography (RNFLP), and SDOCT: (1) SDP (S), (2) SDP and SDOCT (SO), (3) SDP and RNFLP (SR), and (4) SDP, RNFLP, and SDOCT (SRO). Five glaucoma specialists were instructed to classify subjects as normal or glaucoma using each of the 4 diagnostic sets in the order S, SO, SR, and SRO, with a 1-month interval. The interobserver agreement was evaluated using kappa (κ) statistics. The additive effect of SDOCT on the diagnostic performance of the specialists was evaluated using the generalized estimating equation. Five glaucoma specialists showed an excellent level of interobserver agreement on the diagnostic assessments based on the 4 sets. In the comparison of the collective diagnostic performance of the specialists, addition of SDOCT to SDP showed an approximately 2-fold significant increase in the diagnostic accuracy. Adding SDOCT to SDP significantly enhanced the specialists' structural-diagnostic ability with respect to the moderate glaucoma, though not mild or advanced glaucoma. SDOCT significantly enhanced the diagnostic accuracy of the glaucoma specialists' performance, showing its additive diagnostic value in judging glaucomatous structural damage, especially in the moderate stage of glaucoma. Copyright © 2016 Elsevier Inc. All rights reserved.

Statistical Symbolic Execution with Informed Sampling

NASA Technical Reports Server (NTRS)

Filieri, Antonio; Pasareanu, Corina S.; Visser, Willem; Geldenhuys, Jaco

2014-01-01

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

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

Asymmetric statistical features of the Chinese domestic and international gold price fluctuation

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhao, Yingchao; Han, Yan

2015-05-01

Analyzing the statistical features of fluctuation is remarkably significant for financial risk identification and measurement. In this study, the asymmetric detrended fluctuation analysis (A-DFA) method was applied to evaluate asymmetric multifractal scaling behaviors in the Shanghai and New York gold markets. Our findings showed that the multifractal features of the Chinese and international gold spot markets were asymmetric. The gold return series persisted longer in an increasing trend than in a decreasing trend. Moreover, the asymmetric degree of multifractals in the Chinese and international gold markets decreased with the increase in fluctuation range. In addition, the empirical analysis using sliding window technology indicated that multifractal asymmetry in the Chinese and international gold markets was characterized by its time-varying feature. However, the Shanghai and international gold markets basically shared a similar asymmetric degree evolution pattern. The American subprime mortgage crisis (2008) and the European debt crisis (2010) enhanced the asymmetric degree of the multifractal features of the Chinese and international gold markets. Furthermore, we also make statistical tests for the results of multifractatity and asymmetry, and discuss the origin of them. Finally, results of the empirical analysis using the threshold autoregressive conditional heteroskedasticity (TARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models exhibited that good news had a more significant effect on the cyclical fluctuation of the gold market than bad news. Moreover, good news exerted a more significant effect on the Chinese gold market than on the international gold market.

Expression of thymidylate synthase (TS) and its prognostic significance in patients with cutaneous angiosarcoma.

PubMed

Shimizu, A; Kaira, K; Okubo, Y; Utsumi, D; Bolag, A; Yasuda, M; Takahashi, K; Ishikawa, O

2017-01-01

Cutaneous angiosarcoma (CA) is extremely rare, and little is known about the biological significance of possible biomarkers for chemotherapeutic agents. Thymidylate synthase (TS) is an attractive target for cancer treatment in various human neoplasms. It remains unclear whether the expression of TS is associated with the clinicopathological features of CA patients. The aim of this study was to elucidate the relationship between TS expression and the clinicopathological significance in CA patients. Fifty-one patients with CA were included in this study. TS expression and Ki-67 labeling index were examined using immunohistochemical analysis. TS was positively expressed in 39% (20/51) of CA patients. No statistically significant prognostic factor was identified as a predictor of overall survival (OS) for all patients by univariate analysis, whereas a significant prognostic variable for progression free survival (PFS) was found to be the clinical stage. In addition, both univariate and multivariate analyses confirmed that positive expression of TS was a significant predictor of worse PFS in CA patients of clinical stage 1. Positive TS expression in CA was identified as a significant predictor of worse outcome in patients of clinical stage 1.

Further developments in cloud statistics for computer simulations

NASA Technical Reports Server (NTRS)

Chang, D. T.; Willand, J. H.

1972-01-01

This study is a part of NASA's continued program to provide global statistics of cloud parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of cloud types and cloud layers and their applications in the simulation of the vertical distributions of in-cloud parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary cloud climatological regions defined in previous studies of cloud statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of cloud regions, the latitudinal dependence of cloud-type distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in cloud simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.

Effects of quantum coherence on work statistics

NASA Astrophysics Data System (ADS)

Xu, Bao-Ming; Zou, Jian; Guo, Li-Sha; Kong, Xiang-Mu

2018-05-01

In the conventional two-point measurement scheme of quantum thermodynamics, quantum coherence is destroyed by the first measurement. But as we know the coherence really plays an important role in the quantum thermodynamics process, and how to describe the work statistics for a quantum coherent process is still an open question. In this paper, we use the full counting statistics method to investigate the effects of quantum coherence on work statistics. First, we give a general discussion and show that for a quantum coherent process, work statistics is very different from that of the two-point measurement scheme, specifically the average work is increased or decreased and the work fluctuation can be decreased by quantum coherence, which strongly depends on the relative phase, the energy level structure, and the external protocol. Then, we concretely consider a quenched one-dimensional transverse Ising model and show that quantum coherence has a more significant influence on work statistics in the ferromagnetism regime compared with that in the paramagnetism regime, so that due to the presence of quantum coherence the work statistics can exhibit the critical phenomenon even at high temperature.

Statistical learning and selective inference.

PubMed

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

Environmental Health Practice: Statistically Based Performance Measurement

PubMed Central

Enander, Richard T.; Gagnon, Ronald N.; Hanumara, R. Choudary; Park, Eugene; Armstrong, Thomas; Gute, David M.

2007-01-01

Objectives. State environmental and health protection agencies have traditionally relied on a facility-by-facility inspection-enforcement paradigm to achieve compliance with government regulations. We evaluated the effectiveness of a new approach that uses a self-certification random sampling design. Methods. Comprehensive environmental and occupational health data from a 3-year statewide industry self-certification initiative were collected from representative automotive refinishing facilities located in Rhode Island. Statistical comparisons between baseline and postintervention data facilitated a quantitative evaluation of statewide performance. Results. The analysis of field data collected from 82 randomly selected automotive refinishing facilities showed statistically significant improvements (P<.05, Fisher exact test) in 4 major performance categories: occupational health and safety, air pollution control, hazardous waste management, and wastewater discharge. Statistical significance was also shown when a modified Bonferroni adjustment for multiple comparisons was performed. Conclusions. Our findings suggest that the new self-certification approach to environmental and worker protection is effective and can be used as an adjunct to further enhance state and federal enforcement programs. PMID:17267709

New scanning technique using Adaptive Statistical Iterative Reconstruction (ASIR) significantly reduced the radiation dose of cardiac CT.

PubMed

Tumur, Odgerel; Soon, Kean; Brown, Fraser; Mykytowycz, Marcus

2013-06-01

The aims of our study were to evaluate the effect of application of Adaptive Statistical Iterative Reconstruction (ASIR) algorithm on the radiation dose of coronary computed tomography angiography (CCTA) and its effects on image quality of CCTA and to evaluate the effects of various patient and CT scanning factors on the radiation dose of CCTA. This was a retrospective study that included 347 consecutive patients who underwent CCTA at a tertiary university teaching hospital between 1 July 2009 and 20 September 2011. Analysis was performed comparing patient demographics, scan characteristics, radiation dose and image quality in two groups of patients in whom conventional Filtered Back Projection (FBP) or ASIR was used for image reconstruction. There were 238 patients in the FBP group and 109 patients in the ASIR group. There was no difference between the groups in the use of prospective gating, scan length or tube voltage. In ASIR group, significantly lower tube current was used compared with FBP group, 550 mA (450-600) vs. 650 mA (500-711.25) (median (interquartile range)), respectively, P < 0.001. There was 27% effective radiation dose reduction in the ASIR group compared with FBP group, 4.29 mSv (2.84-6.02) vs. 5.84 mSv (3.88-8.39) (median (interquartile range)), respectively, P < 0.001. Although ASIR was associated with increased image noise compared with FBP (39.93 ± 10.22 vs. 37.63 ± 18.79 (mean ± standard deviation), respectively, P < 0.001), it did not affect the signal intensity, signal-to-noise ratio, contrast-to-noise ratio or the diagnostic quality of CCTA. Application of ASIR reduces the radiation dose of CCTA without affecting the image quality. © 2013 The Authors. Journal of Medical Imaging and Radiation Oncology © 2013 The Royal Australian and New Zealand College of Radiologists.

Method for Expressing Clinical and Statistical Significance of Ocular and Corneal Wavefront Error Aberrations

PubMed Central

Smolek, Michael K.

2011-01-01

Purpose The significance of ocular or corneal aberrations may be subject to misinterpretation whenever eyes with different pupil sizes or the application of different Zernike expansion orders are compared. A method is shown that uses simple mathematical interpolation techniques based on normal data to rapidly determine the clinical significance of aberrations, without concern for pupil and expansion order. Methods Corneal topography (Tomey, Inc.; Nagoya, Japan) from 30 normal corneas was collected and the corneal wavefront error analyzed by Zernike polynomial decomposition into specific aberration types for pupil diameters of 3, 5, 7, and 10 mm and Zernike expansion orders of 6, 8, 10 and 12. Using this 4×4 matrix of pupil sizes and fitting orders, best-fitting 3-dimensional functions were determined for the mean and standard deviation of the RMS error for specific aberrations. The functions were encoded into software to determine the significance of data acquired from non-normal cases. Results The best-fitting functions for 6 types of aberrations were determined: defocus, astigmatism, prism, coma, spherical aberration, and all higher-order aberrations. A clinical screening method of color-coding the significance of aberrations in normal, postoperative LASIK, and keratoconus cases having different pupil sizes and different expansion orders is demonstrated. Conclusions A method to calibrate wavefront aberrometry devices by using a standard sample of normal cases was devised. This method could be potentially useful in clinical studies involving patients with uncontrolled pupil sizes or in studies that compare data from aberrometers that use different Zernike fitting-order algorithms. PMID:22157570

Computationally efficient statistical differential equation modeling using homogenization

USGS Publications Warehouse

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Further evidence for addition and numerical competence by a Grey parrot (Psittacus erithacus).

PubMed

Pepperberg, Irene M

2012-07-01

A Grey parrot (Psittacus erithacus), able to quantify sets of eight or fewer items (including heterogeneous subsets), to sum two sequentially presented sets of 0–6 items (up to 6), and to identify and serially order Arabic numerals (1–8), all by using English labels (Pepperberg in J Comp Psychol 108:36–44, 1994; J CompPsychol 120:1–11, 2006a; J Comp Psychol 120:205–216,2006b; Pepperberg and Carey submitted), was tested on addition of two Arabic numerals or three sequentially presented collections (e.g., of variously sized jelly beans or nuts). He was, without explicit training and in the absence of the previously viewed addends, asked, "How many total?" and required to answer with a vocal English number label. In a few trials on the Arabic numeral addition, he was also shown variously colored Arabic numerals while the addends were hidden and asked "What color number (is the) total?" Although his death precluded testing on all possible arrays, his accuracy was statistically significant and suggested addition abilities comparable with those of nonhuman primates.

Statistical reporting inconsistencies in experimental philosophy

PubMed Central

Colombo, Matteo; Duev, Georgi; Nuijten, Michèle B.; Sprenger, Jan

2018-01-01

Experimental philosophy (x-phi) is a young field of research in the intersection of philosophy and psychology. It aims to make progress on philosophical questions by using experimental methods traditionally associated with the psychological and behavioral sciences, such as null hypothesis significance testing (NHST). Motivated by recent discussions about a methodological crisis in the behavioral sciences, questions have been raised about the methodological standards of x-phi. Here, we focus on one aspect of this question, namely the rate of inconsistencies in statistical reporting. Previous research has examined the extent to which published articles in psychology and other behavioral sciences present statistical inconsistencies in reporting the results of NHST. In this study, we used the R package statcheck to detect statistical inconsistencies in x-phi, and compared rates of inconsistencies in psychology and philosophy. We found that rates of inconsistencies in x-phi are lower than in the psychological and behavioral sciences. From the point of view of statistical reporting consistency, x-phi seems to do no worse, and perhaps even better, than psychological science. PMID:29649220

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

Analysis of statistical misconception in terms of statistical reasoning

NASA Astrophysics Data System (ADS)

Maryati, I.; Priatna, N.

2018-05-01

Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.

Addition of sodium caseinate to skim milk increases nonsedimentable casein and causes significant changes in rennet-induced gelation, heat stability, and ethanol stability.

PubMed

Lin, Yingchen; Kelly, Alan L; O'Mahony, James A; Guinee, Timothy P

2017-02-01

The protein content of skim milk was increased from 3.3 to 4.1% (wt/wt) by the addition of a blend of skim milk powder and sodium caseinate (NaCas), in which the weight ratio of skim milk powder to NaCas was varied from 0.8:0.0 to 0.0:0.8. Addition of NaCas increased the levels of nonsedimentable casein (from ∼6 to 18% of total casein) and calcium (from ∼36 to 43% of total calcium) and reduced the turbidity of the fortified milk, to a degree depending on level of NaCas added. Rennet gelation was adversely affected by the addition of NaCas at 0.2% (wt/wt) and completely inhibited at NaCas ≥0.4% (wt/wt). Rennet-induced hydrolysis was not affected by added NaCas. The proportion of total casein that was nonsedimentable on centrifugation (3,000 × g, 1 h, 25°C) of the rennet-treated milk after incubation for 1 h at 31°C increased significantly on addition of NaCas at ≥0.4% (wt/wt). Heat stability in the pH range 6.7 to 7.2 and ethanol stability at pH 6.4 were enhanced by the addition of NaCas. It is suggested that the negative effect of NaCas on rennet gelation is due to the increase in nonsedimentable casein, which upon hydrolysis by chymosin forms into small nonsedimentable particles that physically come between, and impede the aggregation of, rennet-altered para-casein micelles, and thereby inhibit the development of a gel network. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Statistical Inference at Work: Statistical Process Control as an Example

ERIC Educational Resources Information Center

Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia

2008-01-01

To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…

What can we learn from noise? - Mesoscopic nonequilibrium statistical physics.

PubMed

Kobayashi, Kensuke

2016-01-01

Mesoscopic systems - small electric circuits working in quantum regime - offer us a unique experimental stage to explorer quantum transport in a tunable and precise way. The purpose of this Review is to show how they can contribute to statistical physics. We introduce the significance of fluctuation, or equivalently noise, as noise measurement enables us to address the fundamental aspects of a physical system. The significance of the fluctuation theorem (FT) in statistical physics is noted. We explain what information can be deduced from the current noise measurement in mesoscopic systems. As an important application of the noise measurement to statistical physics, we describe our experimental work on the current and current noise in an electron interferometer, which is the first experimental test of FT in quantum regime. Our attempt will shed new light in the research field of mesoscopic quantum statistical physics.

Statistical characteristics of MST radar echoes and its interpretation

NASA Technical Reports Server (NTRS)

Woodman, Ronald F.

1989-01-01

Two concepts of fundamental importance are reviewed: the autocorrelation function and the frequency power spectrum. In addition, some turbulence concepts, the relationship between radar signals and atmospheric medium statistics, partial reflection, and the characteristics of noise and clutter interference are discussed.

2015 QuickCompass of Sexual Assult-Related Responders: Statistical Methodology Report

DTIC Science & Technology

2016-02-01

2015 QuickCompass of Sexual Assault Prevention and Response- Related Responders Statistical Methodology Report Additional copies of this report...from: http://www.dtic.mil/ Ask for report by ADA630235 DMDC Report No. 2015-039 February 2016 2015 QUICKCOMPASS OF SEXUAL ASSAULT PREVENTION...Defense Research, Surveys, and Statistics Center (RSSC) 4800 Mark Center Drive , Suite 04E25-01, Alexandria, VA 22350-4000 ii Acknowledgments

Frog Statistics

Science.gov Websites

Whole Frog Project and Virtual Frog Dissection Statistics wwwstats output for January 1 through duplicate or extraneous accesses. For example, in these statistics, while a POST requesting an image is as well. Note that this under-represents the bytes requested. Starting date for following statistics

Fast, Statistical Model of Surface Roughness for Ion-Solid Interaction Simulations and Efficient Code Coupling

NASA Astrophysics Data System (ADS)

Drobny, Jon; Curreli, Davide; Ruzic, David; Lasa, Ane; Green, David; Canik, John; Younkin, Tim; Blondel, Sophie; Wirth, Brian

2017-10-01

Surface roughness greatly impacts material erosion, and thus plays an important role in Plasma-Surface Interactions. Developing strategies for efficiently introducing rough surfaces into ion-solid interaction codes will be an important step towards whole-device modeling of plasma devices and future fusion reactors such as ITER. Fractal TRIDYN (F-TRIDYN) is an upgraded version of the Monte Carlo, BCA program TRIDYN developed for this purpose that includes an explicit fractal model of surface roughness and extended input and output options for file-based code coupling. Code coupling with both plasma and material codes has been achieved and allows for multi-scale, whole-device modeling of plasma experiments. These code coupling results will be presented. F-TRIDYN has been further upgraded with an alternative, statistical model of surface roughness. The statistical model is significantly faster than and compares favorably to the fractal model. Additionally, the statistical model compares well to alternative computational surface roughness models and experiments. Theoretical links between the fractal and statistical models are made, and further connections to experimental measurements of surface roughness are explored. This work was supported by the PSI-SciDAC Project funded by the U.S. Department of Energy through contract DOE-DE-SC0008658.

Descriptive and inferential statistical methods used in burns research.

PubMed

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

2010-05-01

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

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

George, Brandon J.; Beasley, T. Mark; Brown, Andrew W.; Dawson, John; Dimova, Rositsa; Divers, Jasmin; Goldsby, TaShauna U.; Heo, Moonseong; Kaiser, Kathryn A.; Keith, Scott; Kim, Mimi Y.; Li, Peng; Mehta, Tapan; Oakes, J. Michael; Skinner, Asheley; Stuart, Elizabeth; Allison, David B.

2015-01-01

We identify 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “p-value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. We hope that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician. PMID:27028280

Focus in High School Mathematics: Statistics and Probability

ERIC Educational Resources Information Center

National Council of Teachers of Mathematics, 2009

2009-01-01

Reasoning about and making sense of statistics and probability are essential to students' future success. This volume belongs to a series that supports National Council of Teachers of Mathematics' (NCTM's) "Focus in High School Mathematics: Reasoning and Sense Making" by providing additional guidance for making reasoning and sense making part of…

Statistical process control charts for monitoring military injuries.

PubMed

Schuh, Anna; Canham-Chervak, Michelle; Jones, Bruce H

2017-12-01

An essential aspect of an injury prevention process is surveillance, which quantifies and documents injury rates in populations of interest and enables monitoring of injury frequencies, rates and trends. To drive progress towards injury reduction goals, additional tools are needed. Statistical process control charts, a methodology that has not been previously applied to Army injury monitoring, capitalise on existing medical surveillance data to provide information to leadership about injury trends necessary for prevention planning and evaluation. Statistical process control Shewhart u-charts were created for 49 US Army installations using quarterly injury medical encounter rates, 2007-2015, for active duty soldiers obtained from the Defense Medical Surveillance System. Injuries were defined according to established military injury surveillance recommendations. Charts display control limits three standard deviations (SDs) above and below an installation-specific historical average rate determined using 28 data points, 2007-2013. Charts are available in Army strategic management dashboards. From 2007 to 2015, Army injury rates ranged from 1254 to 1494 unique injuries per 1000 person-years. Installation injury rates ranged from 610 to 2312 injuries per 1000 person-years. Control charts identified four installations with injury rates exceeding the upper control limits at least once during 2014-2015, rates at three installations exceeded the lower control limit at least once and 42 installations had rates that fluctuated around the historical mean. Control charts can be used to drive progress towards injury reduction goals by indicating statistically significant increases and decreases in injury rates. Future applications to military subpopulations, other health outcome metrics and chart enhancements are suggested. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri

USGS Publications Warehouse

Southard, Rodney E.

2013-01-01

located in Region 1, 120 were located in Region 2, and 10 were located in Region 3. Streamgages located outside of Missouri were selected to extend the range of data used for the independent variables in the regression analyses. Streamgages included in the regression analyses had 10 or more years of record and were considered to be affected minimally by anthropogenic activities or trends. Regional regression analyses identified three characteristics as statistically significant for the development of regional equations. For Region 1, drainage area, longest flow path, and streamflow-variability index were statistically significant. The range in the standard error of estimate for Region 1 is 79.6 to 94.2 percent. For Region 2, drainage area and streamflow variability index were statistically significant, and the range in the standard error of estimate is 48.2 to 72.1 percent. For Region 3, drainage area and streamflow-variability index also were statistically significant with a range in the standard error of estimate of 48.1 to 96.2 percent. Limitations on the use of estimating low-flow frequency statistics at ungaged locations are dependent on the method used. The first method outlined for use in Missouri, power curve equations, were developed to estimate the selected statistics for ungaged locations on 28 selected streams with multiple streamgages located on the same stream. A second method uses a drainage-area ratio to compute statistics at an ungaged location using data from a single streamgage on the same stream with 10 or more years of record. Ungaged locations on these streams may use the ratio of the drainage area at an ungaged location to the drainage area at a streamgage location to scale the selected statistic value from the streamgage location to the ungaged location. This method can be used if the drainage area of the ungaged location is within 40 to 150 percent of the streamgage drainage area. The third method is the use of the regional regression equations

MQSA National Statistics

MedlinePlus

... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2018 Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard ...

The Development of Statistical Models for Predicting Surgical Site Infections in Japan: Toward a Statistical Model-Based Standardized Infection Ratio.

PubMed

Fukuda, Haruhisa; Kuroki, Manabu

2016-03-01

To develop and internally validate a surgical site infection (SSI) prediction model for Japan. Retrospective observational cohort study. We analyzed surveillance data submitted to the Japan Nosocomial Infections Surveillance system for patients who had undergone target surgical procedures from January 1, 2010, through December 31, 2012. Logistic regression analyses were used to develop statistical models for predicting SSIs. An SSI prediction model was constructed for each of the procedure categories by statistically selecting the appropriate risk factors from among the collected surveillance data and determining their optimal categorization. Standard bootstrapping techniques were applied to assess potential overfitting. The C-index was used to compare the predictive performances of the new statistical models with those of models based on conventional risk index variables. The study sample comprised 349,987 cases from 428 participant hospitals throughout Japan, and the overall SSI incidence was 7.0%. The C-indices of the new statistical models were significantly higher than those of the conventional risk index models in 21 (67.7%) of the 31 procedure categories (P<.05). No significant overfitting was detected. Japan-specific SSI prediction models were shown to generally have higher accuracy than conventional risk index models. These new models may have applications in assessing hospital performance and identifying high-risk patients in specific procedure categories.

Forest statistics of eastern Kentucky

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1952-01-01

The Forest Survey is conducted in the various regions by the forest experiment stations of the Forest Service. In Kentucky the project is directed by the Central States Forest Experiment Station with headquarters in Columbus, Ohio. This Survey Release presents the more significant preliminary statistics on the forest area and timber volume for the Eastern Kentucky...

Evidence-Based Medicine as a Tool for Undergraduate Probability and Statistics Education

PubMed Central

Masel, J.; Humphrey, P. T.; Blackburn, B.; Levine, J. A.

2015-01-01

Most students have difficulty reasoning about chance events, and misconceptions regarding probability can persist or even strengthen following traditional instruction. Many biostatistics classes sidestep this problem by prioritizing exploratory data analysis over probability. However, probability itself, in addition to statistics, is essential both to the biology curriculum and to informed decision making in daily life. One area in which probability is particularly important is medicine. Given the preponderance of pre health students, in addition to more general interest in medicine, we capitalized on students’ intrinsic motivation in this area to teach both probability and statistics. We use the randomized controlled trial as the centerpiece of the course, because it exemplifies the most salient features of the scientific method, and the application of critical thinking to medicine. The other two pillars of the course are biomedical applications of Bayes’ theorem and science and society content. Backward design from these three overarching aims was used to select appropriate probability and statistics content, with a focus on eliciting and countering previously documented misconceptions in their medical context. Pretest/posttest assessments using the Quantitative Reasoning Quotient and Attitudes Toward Statistics instruments are positive, bucking several negative trends previously reported in statistics education. PMID:26582236

Corroborating tomographic defect metrics with mechanical response in an additively manufactured precipitation-hardened stainless steel

NASA Astrophysics Data System (ADS)

Madison, Jonathan D.; Underwood, Olivia D.; Swiler, Laura P.; Boyce, Brad L.; Jared, Bradley H.; Rodelas, Jeff M.; Salzbrenner, Bradley C.

2018-04-01

The intrinsic relation between structure and performance is a foundational tenant of most all materials science investigations. While the specific form of this relation is dictated by material system, processing route and performance metric of interest, it is widely agreed that appropriate characterization of a material allows for greater accuracy in understanding and/or predicting material response. However, in the context of additive manufacturing, prior models and expectations of material performance must be revisited as performance often diverges from traditional values, even among well explored material systems. This work utilizes micro-computed tomography to quantify porosity and lack of fusion defects in an additively manufactured stainless steel and relates these metrics to performance across a statistically significant population using high-throughput mechanical testing. The degree to which performance in additively manufactured stainless steel can and cannot be correlated to detectable porosity will be presented and suggestions for performing similar experiments will be provided.

Stromal p16 expression is significantly increased in endometrial carcinoma

PubMed Central

Yoon, Nara; Kim, Ji-Ye; Kim, Hyun-Soo

2017-01-01

p16 is a negative regulator of cell proliferation and is considered a tumor suppressor protein. Alterations in p16 protein expression are associated with tumor development and progression. However, the p16 expression status in the peritumoral stroma has not been investigated in the endometrium. Therefore, we evaluated stromal p16 expression in different types of endometrial lesions using immunohistochemistry. Differences in the p16 expression status according to the degree of malignancy and histological type were analyzed. This study included 62, 26, and 36 cases of benign, precancerous, and malignant endometrial lesions, respectively. Most benign lesions showed negative or weak expression, whereas precancerous lesions showed a variable degree of staining proportion and intensity. Atypical hyperplasia/endometrial intraepithelial neoplasia (AH/EIN) and serous endometrial intraepithelial carcinoma (SEIC) had significantly higher stromal p16 expression levels than benign lesions. Endometrioid carcinoma (EC), serous carcinoma (SC), and carcinosarcoma showed significantly elevated stromal p16 expression levels compared with benign and precancerous lesions. In addition, there were significant differences in stromal p16 expression between AH/EIN and SEIC and between EC and SC. In contrast, differences in stromal p16 expression among nonpathological endometrium, atrophic endometrium, endometrial polyp, and hyperplasia without atypia were not statistically significant. Our observations suggest that stromal p16 expression is involved in the development and progression of endometrial carcinoma, and raise the possibility that p16 overexpression in the peritumoral stroma is associated with aggressive oncogenic behavior of endometrial SC. PMID:27902476

Statistical Diversions

ERIC Educational Resources Information Center

Petocz, Peter; Sowey, Eric

2008-01-01

As a branch of knowledge, Statistics is ubiquitous and its applications can be found in (almost) every field of human endeavour. In this article, the authors track down the possible source of the link between the "Siren song" and applications of Statistics. Answers to their previous five questions and five new questions on Statistics are presented.

Statistical learning of action: the role of conditional probability.

PubMed

Meyer, Meredith; Baldwin, Dare

2011-12-01

Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.

Effect of polymerization technique and glass fiber addition on the surface roughness and hardness of PMMA denture base material.

PubMed

Gad, Mohammed M; Rahoma, Ahmed; Al-Thobity, Ahmad M

2018-06-20

The current study evaluated the effects of autoclave polymerization both with and without glass fiber (GF) reinforcement on the surface roughness and hardness of acrylic denture base material. Ninety disc specimens (30×2.5 mm) were prepared from Vertex resin and divided according to polymerization techniques into a water bath, short and long autoclave polymerization groups. Tested groups were divided into three subgroups according to the GF concentration (0, 2.5, and 5 wt%). Profilometer and Vickers hardness tests were performed to measure surface roughness and hardness. ANOVA and Tukey-Kramer multiple comparison tests analyzed the results, and p≤0.05 was considered statistically significant. Autoclave polymerization significantly decreased the surface roughness and increased the hardness of acrylic resin without GF reinforcement (p<0.05). However, 5 wt% GF addition significantly increased surface roughness and decreased hardness of the autoclave polymerized denture base resin (p<0.05). Surface properties of Polymethyl methacrylate (PMMA) denture base material improved with autoclave polymerization and negatively affected with GFs addition.

Nitrite addition to acidified sludge significantly improves digestibility, toxic metal removal, dewaterability and pathogen reduction

NASA Astrophysics Data System (ADS)

Du, Fangzhou; Keller, Jürg; Yuan, Zhiguo; Batstone, Damien J.; Freguia, Stefano; Pikaar, Ilje

2016-12-01

Sludge management is a major issue for water utilities globally. Poor digestibility and dewaterability are the main factors determining the cost for sludge management, whereas pathogen and toxic metal concentrations limit beneficial reuse. In this study, the effects of low level nitrite addition to acidified sludge to simultaneously enhance digestibility, toxic metal removal, dewaterability and pathogen reduction were investigated. Waste activated sludge (WAS) from a full-scale waste water treatment plant was treated at pH 2 with 10 mg NO2--N/L for 5 h. Biochemical methane potential tests showed an increase in the methane production of 28%, corresponding to an improvement from 247 ± 8 L CH4/kg VS to 317 ± 1 L CH4/kg VS. The enhanced removal of toxic metals further increased the methane production by another 18% to 360 ± 6 L CH4/kg VS (a total increase of 46%). The solids content of dewatered sludge increased from 14.6 ± 1.4% in the control to 18.2 ± 0.8%. A 4-log reduction for both total coliforms and E. coli was achieved. Overall, this study highlights the potential of acidification with low level nitrite addition as an effective and simple method achieving multiple improvements in terms of sludge management.

Nitrite addition to acidified sludge significantly improves digestibility, toxic metal removal, dewaterability and pathogen reduction

PubMed Central

Du, Fangzhou; Keller, Jürg; Yuan, Zhiguo; Batstone, Damien J.; Freguia, Stefano; Pikaar, Ilje

2016-01-01

Sludge management is a major issue for water utilities globally. Poor digestibility and dewaterability are the main factors determining the cost for sludge management, whereas pathogen and toxic metal concentrations limit beneficial reuse. In this study, the effects of low level nitrite addition to acidified sludge to simultaneously enhance digestibility, toxic metal removal, dewaterability and pathogen reduction were investigated. Waste activated sludge (WAS) from a full-scale waste water treatment plant was treated at pH 2 with 10 mg NO2−-N/L for 5 h. Biochemical methane potential tests showed an increase in the methane production of 28%, corresponding to an improvement from 247 ± 8 L CH4/kg VS to 317 ± 1 L CH4/kg VS. The enhanced removal of toxic metals further increased the methane production by another 18% to 360 ± 6 L CH4/kg VS (a total increase of 46%). The solids content of dewatered sludge increased from 14.6 ± 1.4% in the control to 18.2 ± 0.8%. A 4-log reduction for both total coliforms and E. coli was achieved. Overall, this study highlights the potential of acidification with low level nitrite addition as an effective and simple method achieving multiple improvements in terms of sludge management. PMID:28004811

Descriptive statistics.

PubMed

Nick, Todd G

2007-01-01

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

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

Statistical methods to detect novel genetic variants using publicly available GWAS summary data.

PubMed

Guo, Bin; Wu, Baolin

2018-03-01

We propose statistical methods to detect novel genetic variants using only genome-wide association studies (GWAS) summary data without access to raw genotype and phenotype data. With more and more summary data being posted for public access in the post GWAS era, the proposed methods are practically very useful to identify additional interesting genetic variants and shed lights on the underlying disease mechanism. We illustrate the utility of our proposed methods with application to GWAS meta-analysis results of fasting glucose from the international MAGIC consortium. We found several novel genome-wide significant loci that are worth further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Additions and deletions to the known cerambycidae (Coleoptera) of Bolivia

USDA-ARS?s Scientific Manuscript database

An additional 137 species and two tribes are added to the known cerambycid fauna of Bolivia while 12 species are deleted. Comments and statistics regarding the growth of knowledge on the Bolivian Cerambycid fauna and species endemicity are included....

Inverse statistics and information content

NASA Astrophysics Data System (ADS)

Ebadi, H.; Bolgorian, Meysam; Jafari, G. R.

2010-12-01

Inverse statistics analysis studies the distribution of investment horizons to achieve a predefined level of return. This distribution provides a maximum investment horizon which determines the most likely horizon for gaining a specific return. There exists a significant difference between inverse statistics of financial market data and a fractional Brownian motion (fBm) as an uncorrelated time-series, which is a suitable criteria to measure information content in financial data. In this paper we perform this analysis for the DJIA and S&P500 as two developed markets and Tehran price index (TEPIX) as an emerging market. We also compare these probability distributions with fBm probability, to detect when the behavior of the stocks are the same as fBm.

Statistical inference for template aging

NASA Astrophysics Data System (ADS)

Schuckers, Michael E.

2006-04-01

A change in classification error rates for a biometric device is often referred to as template aging. Here we offer two methods for determining whether the effect of time is statistically significant. The first of these is the use of a generalized linear model to determine if these error rates change linearly over time. This approach generalizes previous work assessing the impact of covariates using generalized linear models. The second approach uses of likelihood ratio tests methodology. The focus here is on statistical methods for estimation not the underlying cause of the change in error rates over time. These methodologies are applied to data from the National Institutes of Standards and Technology Biometric Score Set Release 1. The results of these applications are discussed.

Testing statistical self-similarity in the topology of river networks

USGS Publications Warehouse

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2010-01-01

Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.

Land use statistics for West Virginia, Part I

USGS Publications Warehouse

Erwin, Robert B.; ,; ,

1979-01-01

The West Virginia Geological and Economic Survey and the United States Geological Survey have completed a cooperative program to provide land-use and land-cover maps and data for the State. This program begins to satisfy a longstanding need for a consistent level of detail, standardization in categorization, and scale of compilation for land-use and land-cover maps and data. The statistical information contained in this Bulletin provides land-use acreage tabulations for the first 20 counties that have been completed. Statistics are being compiled for the remaining counties and will be published shortly. This information has been derived from the recently completed Land-Use Map of West Virginia (on open file at the West Virginia Geological and Economic Survey - Environmental Section). In addition to land-use acreage, we have also included land-use percent. All statistics throughout this Bulletin are in the same format for ease of comparison.

The longevity of statistical learning: When infant memory decays, isolated words come to the rescue.

PubMed

Karaman, Ferhat; Hay, Jessica F

2018-02-01

Research over the past 2 decades has demonstrated that infants are equipped with remarkable computational abilities that allow them to find words in continuous speech. Infants can encode information about the transitional probability (TP) between syllables to segment words from artificial and natural languages. As previous research has tested infants immediately after familiarization, infants' ability to retain sequential statistics beyond the immediate familiarization context remains unknown. Here, we examine infants' memory for statistically defined words 10 min after familiarization with an Italian corpus. Eight-month-old English-learning infants were familiarized with Italian sentences that contained 4 embedded target words-2 words had high internal TP (HTP, TP = 1.0) and 2 had low TP (LTP, TP = .33)-and were tested on their ability to discriminate HTP from LTP words using the Headturn Preference Procedure. When tested after a 10-min delay, infants failed to discriminate HTP from LTP words, suggesting that memory for statistical information likely decays over even short delays (Experiment 1). Experiments 2-4 were designed to test whether experience with isolated words selectively reinforces memory for statistically defined (i.e., HTP) words. When 8-month-olds were given additional experience with isolated tokens of both HTP and LTP words immediately after familiarization, they looked significantly longer on HTP than LTP test trials 10 min later. Although initial representations of statistically defined words may be fragile, our results suggest that experience with isolated words may reinforce the output of statistical learning by helping infants create more robust memories for words with strong versus weak co-occurrence statistics. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Incomplete Lineage Sorting and Hybridization Statistics for Large-Scale Retroposon Insertion Data

PubMed Central

Kuritzin, Andrej; Kischka, Tabea

2016-01-01

Ancient retroposon insertions can be used as virtually homoplasy-free markers to reconstruct the phylogenetic history of species. Inherited, orthologous insertions in related species offer reliable signals of a common origin of the given species. One prerequisite for such a phylogenetically informative insertion is that the inserted element was fixed in the ancestral population before speciation; if not, polymorphically inserted elements may lead to random distributions of presence/absence states during speciation and possibly to apparently conflicting reconstructions of their ancestry. Fortunately, such misleading fixed cases are relatively rare but nevertheless, need to be considered. Here, we present novel, comprehensive statistical models applicable for (1) analyzing any pattern of rare genomic changes, (2) testing and differentiating conflicting phylogenetic reconstructions based on rare genomic changes caused by incomplete lineage sorting or/and ancestral hybridization, and (3) differentiating between search strategies involving genome information from one or several lineages. When the new statistics are applied, in non-conflicting cases a minimum of three elements present in both of two species and absent in a third group are considered significant support (p<0.05) for the branching of the third from the other two, if all three of the given species are screened equally for genome or experimental data. Five elements are necessary for significant support (p<0.05) if a diagnostic locus derived from only one of three species is screened, and no conflicting markers are detected. Most potentially conflicting patterns can be evaluated for their significance and ancestral hybridization can be distinguished from incomplete lineage sorting by considering symmetric or asymmetric distribution of rare genomic changes among possible tree configurations. Additionally, we provide an R-application to make the new KKSC insertion significance test available for the scientific

The American Arts Industry: Size and Significance.

ERIC Educational Resources Information Center

Chartrand, Harry Hillman

In this study, the U.S. arts industry is conceptually defined and measured with respect to statistical size. The contribution and significance of the arts industry to the economy is then assessed within the context of national competitiveness and the emerging knowledge economy. Study findings indicate that the arts industry contributes between 5%…

[Variation trend and significance of adult tonsil size and tongue position].

PubMed

Bin, X; Zhou, Y

2016-08-05

Objective: The aim of this study is to explore the changing trend and significance of adult tonsil size and tongue position by observing adults in different age groups. Method: Oropharyngeal cavities of 1 060 adults who undergoing health examination and had no history of tonsil surgery were observed. Friedman tongue position (FTP) and tonsil size (TS) were scored according to Friedman's criteria and results were statistic analyzed to evaluate their changing law and significance. Result: Mean FTP scores increased with age significantly（ P <0.01）; FTP score in male was lower than that in female（ P <0.01）. TS score significantly decreased with age（ P <0.05）.The average score of TS had no statistical significance in different gender. Although there was no statistical significance, total score of FTP show an increasing trend with age（ P >0.05）;Total scores of FTP were different between sexes（male 4.12±0.67，female 4.23±0.68， P <0.05）.BMI was not found to be statistically different when FTP scores, TS scores and total scores changed ( P >0.05); but it showed an increasing trend with age（ P <0.01）. Conclusion: Width of pharyngeal cavity in normal adults is always kept in certain stability, while it proves to be narrower in obese people. TS score and FTP score, which appear the opposite trend with age, can be thought as a major factor to keep a stable width of oral pharyngeal cavity. Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy.

PubMed

Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne

2017-01-01

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee

Efforts to improve international migration statistics: a historical perspective.

PubMed

Kraly, E P; Gnanasekaran, K S

1987-01-01

During the past decade, the international statistical community has made several efforts to develop standards for the definition, collection and publication of statistics on international migration. This article surveys the history of official initiatives to standardize international migration statistics by reviewing the recommendations of the International Statistical Institute, International Labor Organization, and the UN, and reports a recently proposed agenda for moving toward comparability among national statistical systems. Heightening awareness of the benefits of exchange and creating motivation to implement international standards requires a 3-pronged effort from the international statistical community. 1st, it is essential to continue discussion about the significance of improvement, specifically standardization, of international migration statistics. The move from theory to practice in this area requires ongoing focus by migration statisticians so that conformity to international standards itself becomes a criterion by which national statistical practices are examined and assessed. 2nd, the countries should be provided with technical documentation to support and facilitate the implementation of the recommended statistical systems. Documentation should be developed with an understanding that conformity to international standards for migration and travel statistics must be achieved within existing national statistical programs. 3rd, the call for statistical research in this area requires more efforts by the community of migration statisticians, beginning with the mobilization of bilateral and multilateral resources to undertake the preceding list of activities.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Pitfalls in statistical landslide susceptibility modelling

NASA Astrophysics Data System (ADS)

Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut

2010-05-01

The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible

Re-analysis of survival data of cancer patients utilizing additive homeopathy.

PubMed

Gleiss, Andreas; Frass, Michael; Gaertner, Katharina

2016-08-01

In this short communication we present a re-analysis of homeopathic patient data in comparison to control patient data from the same Outpatient´s Unit "Homeopathy in malignant diseases" of the Medical University of Vienna. In this analysis we took account of a probable immortal time bias. For patients suffering from advanced stages of cancer and surviving the first 6 or 12 months after diagnosis, respectively, the results show that utilizing homeopathy gives a statistically significant (p<0.001) advantage over control patients regarding survival time. In conclusion, bearing in mind all limitations, the results of this retrospective study suggest that patients with advanced stages of cancer might benefit from additional homeopathic treatment until a survival time of up to 12 months after diagnosis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stan: Statistical inference

NASA Astrophysics Data System (ADS)

Stan Development Team

2018-01-01

Stan facilitates statistical inference at the frontiers of applied statistics and provides both a modeling language for specifying complex statistical models and a library of statistical algorithms for computing inferences with those models. These components are exposed through interfaces in environments such as R, Python, and the command line.

Fabrication of Hyperbranched Block-Statistical Copolymer-Based Prodrug with Dual Sensitivities for Controlled Release.

PubMed

Zheng, Luping; Wang, Yunfei; Zhang, Xianshuo; Ma, Liwei; Wang, Baoyan; Ji, Xiangling; Wei, Hua

2018-01-17

Dendrimer with hyperbranched structure and multivalent surface is regarded as one of the most promising candidates close to the ideal drug delivery systems, but the clinical translation and scale-up production of dendrimer has been hampered significantly by the synthetic difficulties. Therefore, there is considerable scope for the development of novel hyperbranched polymer that can not only address the drawbacks of dendrimer but maintain its advantages. The reversible addition-fragmentation chain transfer self-condensing vinyl polymerization (RAFT-SCVP) technique has enabled facile preparation of segmented hyperbranched polymer (SHP) by using chain transfer monomer (CTM)-based double-head agent during the past decade. Meanwhile, the design and development of block-statistical copolymers has been proven in our recent studies to be a simple yet effective way to address the extracellular stability vs intracellular high delivery efficacy dilemma. To integrate the advantages of both hyperbranched and block-statistical structures, we herein reported the fabrication of hyperbranched block-statistical copolymer-based prodrug with pH and reduction dual sensitivities using RAFT-SCVP and post-polymerization click coupling. The external homo oligo(ethylene glycol methyl ether methacrylate) (OEGMA) block provides sufficient extracellularly colloidal stability for the nanocarriers by steric hindrance, and the interior OEGMA units incorporated by the statistical copolymerization promote intracellular drug release by facilitating the permeation of GSH and H + for the cleavage of the reduction-responsive disulfide bond and pH-liable carbonate link as well as weakening the hydrophobic encapsulation of drug molecules. The delivery efficacy of the target hyperbranched block-statistical copolymer-based prodrug was evaluated in terms of in vitro drug release and cytotoxicity studies, which confirms both acidic pH and reduction-triggered drug release for inhibiting proliferation of He

Gluten-free dough-making of specialty breads: Significance of blended starches, flours and additives on dough behaviour.

PubMed

Collar, Concha; Conte, Paola; Fadda, Costantino; Piga, Antonio

2015-10-01

The capability of different gluten-free (GF) basic formulations made of flour (rice, amaranth and chickpea) and starch (corn and cassava) blends, to make machinable and viscoelastic GF-doughs in absence/presence of single hydrocolloids (guar gum, locust bean and psyllium fibre), proteins (milk and egg white) and surfactants (neutral, anionic and vegetable oil) have been investigated. Macroscopic (high deformation) and macromolecular (small deformation) mechanical, viscometric (gelatinization, pasting, gelling) and thermal (gelatinization, melting, retrogradation) approaches were performed on the different matrices in order to (a) identify similarities and differences in GF-doughs in terms of a small number of rheological and thermal analytical parameters according to the formulations and (b) to assess single and interactive effects of basic ingredients and additives on GF-dough performance to achieve GF-flat breads. Larger values for the static and dynamic mechanical characteristics and higher viscometric profiles during both cooking and cooling corresponded to doughs formulated with guar gum and Psyllium fibre added to rice flour/starch and rice flour/corn starch/chickpea flour, while surfactant- and protein-formulated GF-doughs added to rice flour/starch/amaranth flour based GF-doughs exhibited intermediate and lower values for the mechanical parameters and poorer viscometric profiles. In addition, additive-free formulations exhibited higher values for the temperature of both gelatinization and retrogradation and lower enthalpies for the thermal transitions. Single addition of 10% of either chickpea flour or amaranth flour to rice flour/starch blends provided a large GF-dough hardening effect in presence of corn starch and an intermediate effect in presence of cassava starch (chickpea), and an intermediate reinforcement of GF-dough regardless the source of starch (amaranth). At macromolecular level, both chickpea and amaranth flours, singly added, determined

Forest statistics of central Kentucky

Treesearch

The Forest Survey Organization Central States Forest Experiment Station

1950-01-01

This Survey Release presents the more significant preliminary statistics on the forest area and timber volume for each of the four regions of Central Kentucky. A similar report has been published for the Western Kentucky region and a release for the eastern region will be issued as soon as field work and tabulations are completed. Later an analytical report for the...

Cluster Size Statistic and Cluster Mass Statistic: Two Novel Methods for Identifying Changes in Functional Connectivity Between Groups or Conditions

PubMed Central

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods – the cluster size statistic (CSS) and cluster mass statistic (CMS) – are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity. PMID:24906136

Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

PubMed

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

Statistical learning and auditory processing in children with music training: An ERP study.

PubMed

Mandikal Vasuki, Pragati Rao; Sharma, Mridula; Ibrahim, Ronny; Arciuli, Joanne

2017-07-01

The question whether musical training is associated with enhanced auditory and cognitive abilities in children is of considerable interest. In the present study, we compared children with music training versus those without music training across a range of auditory and cognitive measures, including the ability to detect implicitly statistical regularities in input (statistical learning). Statistical learning of regularities embedded in auditory and visual stimuli was measured in musically trained and age-matched untrained children between the ages of 9-11years. In addition to collecting behavioural measures, we recorded electrophysiological measures to obtain an online measure of segmentation during the statistical learning tasks. Musically trained children showed better performance on melody discrimination, rhythm discrimination, frequency discrimination, and auditory statistical learning. Furthermore, grand-averaged ERPs showed that triplet onset (initial stimulus) elicited larger responses in the musically trained children during both auditory and visual statistical learning tasks. In addition, children's music skills were associated with performance on auditory and visual behavioural statistical learning tasks. Our data suggests that individual differences in musical skills are associated with children's ability to detect regularities. The ERP data suggest that musical training is associated with better encoding of both auditory and visual stimuli. Although causality must be explored in further research, these results may have implications for developing music-based remediation strategies for children with learning impairments. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Views of medical students: what, when and how do they want statistics taught?

PubMed

Fielding, S; Poobalan, A; Prescott, G J; Marais, D; Aucott, L

2015-11-01

A key skill for a practising clinician is being able to do research, understand the statistical analyses and interpret results in the medical literature. Basic statistics has become essential within medical education, but when, what and in which format is uncertain. To inform curriculum design/development we undertook a quantitative survey of fifth year medical students and followed them up with a series of focus groups to obtain their opinions as to what statistics teaching they want, when and how. A total of 145 students undertook the survey and five focus groups were held with between 3 and 9 participants each. Previous statistical training varied and students recognised their knowledge was inadequate and keen to see additional training implemented. Students were aware of the importance of statistics to their future careers, but apprehensive about learning. Face-to-face teaching supported by online resources was popular. Focus groups indicated the need for statistical training early in their degree and highlighted their lack of confidence and inconsistencies in support. The study found that the students see the importance of statistics training in the medical curriculum but that timing and mode of delivery are key. The findings have informed the design of a new course to be implemented in the third undergraduate year. Teaching will be based around published studies aiming to equip students with the basics required with additional resources available through a virtual learning environment. © The Author(s) 2015.

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

The statistics of Pearce element diagrams and the Chayes closure problem

NASA Astrophysics Data System (ADS)

Nicholls, J.

1988-05-01

Pearce element ratios are defined as having a constituent in their denominator that is conserved in a system undergoing change. The presence of a conserved element in the denominator simplifies the statistics of such ratios and renders them subject to statistical tests, especially tests of significance of the correlation coefficient between Pearce element ratios. Pearce element ratio diagrams provide unambigous tests of petrologic hypotheses because they are based on the stoichiometry of rock-forming minerals. There are three ways to recognize a conserved element: 1. The petrologic behavior of the element can be used to select conserved ones. They are usually the incompatible elements. 2. The ratio of two conserved elements will be constant in a comagmatic suite. 3. An element ratio diagram that is not constructed with a conserved element in the denominator will have a trend with a near zero intercept. The last two criteria can be tested statistically. The significance of the slope, intercept and correlation coefficient can be tested by estimating the probability of obtaining the observed values from a random population of arrays. This population of arrays must satisfy two criteria: 1. The population must contain at least one array that has the means and variances of the array of analytical data for the rock suite. 2. Arrays with the means and variances of the data must not be so abundant in the population that nearly every array selected at random has the properties of the data. The population of random closed arrays can be obtained from a population of open arrays whose elements are randomly selected from probability distributions. The means and variances of these probability distributions are themselves selected from probability distributions which have means and variances equal to a hypothetical open array that would give the means and variances of the data on closure. This hypothetical open array is called the Chayes array. Alternatively, the population of

Statistical Reference Datasets

National Institute of Standards and Technology Data Gateway

Statistical Reference Datasets (Web, free access)   The Statistical Reference Datasets is also supported by the Standard Reference Data Program. The purpose of this project is to improve the accuracy of statistical software by providing reference datasets with certified computational results that enable the objective evaluation of statistical software.

Clinicopathological significance of c-MYC in esophageal squamous cell carcinoma.

PubMed

Lian, Yu; Niu, Xiangdong; Cai, Hui; Yang, Xiaojun; Ma, Haizhong; Ma, Shixun; Zhang, Yupeng; Chen, Yifeng

2017-07-01

Esophageal squamous cell carcinoma is one of the most common malignant tumors. The oncogene c-MYC is thought to be important in the initiation, promotion, and therapy resistance of cancer. In this study, we aim to investigate the clinicopathologic roles of c-MYC in esophageal squamous cell carcinoma tissue. This study is aimed at discovering and analyzing c-MYC expression in a series of human esophageal tissues. A total of 95 esophageal squamous cell carcinoma samples were analyzed by the western blotting and immunohistochemistry techniques. Then, correlation of c-MYC expression with clinicopathological features of esophageal squamous cell carcinoma patients was statistically analyzed. In most esophageal squamous cell carcinoma cases, the c-MYC expression was positive in tumor tissues. The positive rate of c-MYC expression in tumor tissues was 61.05%, obviously higher than the adjacent normal tissues (8.42%, 8/92) and atypical hyperplasia tissues (19.75%, 16/95). There was a statistical difference among adjacent normal tissues, atypical hyperplasia tissues, and tumor tissues. Overexpression of the c-MYC was detected in 61.05% (58/95) esophageal squamous cell carcinomas, which was significantly correlated with the degree of differentiation (p = 0.004). The positive rate of c-MYC expression was 40.0% in well-differentiated esophageal tissues, with a significantly statistical difference (p = 0.004). The positive rate of c-MYC was 41.5% in T1 + T2 esophageal tissues and 74.1% in T3 + T4 esophageal tissues, with a significantly statistical difference (p = 0.001). The positive rate of c-MYC was 45.0% in I + II esophageal tissues and 72.2% in III + IV esophageal tissues, with a significantly statistical difference (p = 0.011). The c-MYC expression strongly correlated with clinical staging (p = 0.011), differentiation degree (p = 0.004), lymph node metastasis (p = 0.003), and invasion depth (p = 0.001) of patients with esophageal squamous cell carcinoma. The c-MYC was

Pocket Profile of Community Colleges: Trends & Statistics, 1995-1996.

ERIC Educational Resources Information Center

Association of Community College Trustees, Washington, DC.

Using data from the National Center for Education Statistics, Bureau of the Census, and other sources, this pamphlet presents current information on community college students; college outcomes and impact; community college staff, governance, and expenditures; and tuition and financial aid. In addition, trends in enrollments, numbers of…

Mechanical Unloading of Mouse Bone in Microgravity Significantly Alters Cell Cycle Gene Set Expression

NASA Astrophysics Data System (ADS)

Blaber, Elizabeth; Dvorochkin, Natalya; Almeida, Eduardo; Kaplan, Warren; Burns, Brnedan

2012-07-01

unloading in spaceflight, we conducted genome wide microarray analysis of total RNA isolated from the mouse pelvis. Specifically, 16 week old mice were subjected to 15 days spaceflight onboard NASA's STS-131 space shuttle mission. The pelvis of the mice was dissected, the bone marrow was flushed and the bones were briefly stored in RNAlater. The pelvii were then homogenized, and RNA was isolated using TRIzol. RNA concentration and quality was measured using a Nanodrop spectrometer, and 0.8% agarose gel electrophoresis. Samples of cDNA were analyzed using an Affymetrix GeneChip\\S Gene 1.0 ST (Sense Target) Array System for Mouse and GenePattern Software. We normalized the ST gene arrays using Robust Multichip Average (RMA) normalization, which summarizes perfectly matched spots on the array through the median polish algorithm, rather than normalizing according to mismatched spots. We also used Limma for statistical analysis, using the BioConductor Limma Library by Gordon Smyth, and differential expression analysis to identify genes with significant changes in expression between the two experimental conditions. Finally we used GSEApreRanked for Gene Set Enrichment Analysis (GSEA), with Kolmogorov-Smirnov style statistics to identify groups of genes that are regulated together using the t-statistics derived from Limma. Preliminary results show that 6,603 genes expressed in pelvic bone had statistically significant alterations in spaceflight compared to ground controls. These prominently included cell cycle arrest molecules p21, and p18, cell survival molecule Crbp1, and cell cycle molecules cyclin D1, and Cdk1. Additionally, GSEA results indicated alterations in molecular targets of cyclin D1 and Cdk4, senescence pathways resulting from abnormal laminin maturation, cell-cell contacts via E-cadherin, and several pathways relating to protein translation and metabolism. In total 111 gene sets out of 2,488, about 4%, showed statistically significant set alterations. These

Comparing identified and statistically significant lipids and polar metabolites in 15-year old serum and dried blood spot samples for longitudinal studies: Comparing lipids and metabolites in serum and DBS samples

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

Kyle, Jennifer E.; Casey, Cameron P.; Stratton, Kelly G.

The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as smaller blood volume required, storage at room temperature, and ability for sampling in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. Here we analyzed DBS samples collected in 2000-2001 and stored at room temperature and compared them to matched serum samples stored at -80°C to determine if they could be effectively used as specific time points in a longitudinal study following metabolic disease. Four hundred small molecules weremore » identified in both the serum and DBS samples using gas chromatograph-mass spectrometry (GC-MS), liquid chromatography-MS (LC-MS) and LC-ion mobility spectrometry-MS (LC-IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant polar metabolite in a case-control study was conserved, indicating degradation occurs in the DBS samples affecting quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, thirty-six statistically significant lipids correlated in both sample types indicating that lipid quantitation was more stable across the sample types.« less

Diurnal fluctuations in brain volume: Statistical analyses of MRI from large populations.

PubMed

Nakamura, Kunio; Brown, Robert A; Narayanan, Sridar; Collins, D Louis; Arnold, Douglas L

2015-09-01

We investigated fluctuations in brain volume throughout the day using statistical modeling of magnetic resonance imaging (MRI) from large populations. We applied fully automated image analysis software to measure the brain parenchymal fraction (BPF), defined as the ratio of the brain parenchymal volume and intracranial volume, thus accounting for variations in head size. The MRI data came from serial scans of multiple sclerosis (MS) patients in clinical trials (n=755, 3269 scans) and from subjects participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n=834, 6114 scans). The percent change in BPF was modeled with a linear mixed effect (LME) model, and the model was applied separately to the MS and ADNI datasets. The LME model for the MS datasets included random subject effects (intercept and slope over time) and fixed effects for the time-of-day, time from the baseline scan, and trial, which accounted for trial-related effects (for example, different inclusion criteria and imaging protocol). The model for ADNI additionally included the demographics (baseline age, sex, subject type [normal, mild cognitive impairment, or Alzheimer's disease], and interaction between subject type and time from baseline). There was a statistically significant effect of time-of-day on the BPF change in MS clinical trial datasets (-0.180 per day, that is, 0.180% of intracranial volume, p=0.019) as well as the ADNI dataset (-0.438 per day, that is, 0.438% of intracranial volume, p<0.0001), showing that the brain volume is greater in the morning. Linearly correcting the BPF values with the time-of-day reduced the required sample size to detect a 25% treatment effect (80% power and 0.05 significance level) on change in brain volume from 2 time-points over a period of 1year by 2.6%. Our results have significant implications for future brain volumetric studies, suggesting that there is a potential acquisition time bias that should be randomized or statistically controlled to

Statistics, Computation, and Modeling in Cosmology

NASA Astrophysics Data System (ADS)

Jewell, Jeff; Guiness, Joe; SAMSI 2016 Working Group in Cosmology

2017-01-01

Current and future ground and space based missions are designed to not only detect, but map out with increasing precision, details of the universe in its infancy to the present-day. As a result we are faced with the challenge of analyzing and interpreting observations from a wide variety of instruments to form a coherent view of the universe. Finding solutions to a broad range of challenging inference problems in cosmology is one of the goals of the “Statistics, Computation, and Modeling in Cosmology” workings groups, formed as part of the year long program on ‘Statistical, Mathematical, and Computational Methods for Astronomy’, hosted by the Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation funded institute. Two application areas have emerged for focused development in the cosmology working group involving advanced algorithmic implementations of exact Bayesian inference for the Cosmic Microwave Background, and statistical modeling of galaxy formation. The former includes study and development of advanced Markov Chain Monte Carlo algorithms designed to confront challenging inference problems including inference for spatial Gaussian random fields in the presence of sources of galactic emission (an example of a source separation problem). Extending these methods to future redshift survey data probing the nonlinear regime of large scale structure formation is also included in the working group activities. In addition, the working group is also focused on the study of ‘Galacticus’, a galaxy formation model applied to dark matter-only cosmological N-body simulations operating on time-dependent halo merger trees. The working group is interested in calibrating the Galacticus model to match statistics of galaxy survey observations; specifically stellar mass functions, luminosity functions, and color-color diagrams. The group will use subsampling approaches and fractional factorial designs to statistically and

Peer-Assisted Learning in Research Methods and Statistics

ERIC Educational Resources Information Center

Stone, Anna; Meade, Claire; Watling, Rosamond

2012-01-01

Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…

The Content of Statistical Requirements for Authors in Biomedical Research Journals

PubMed Central

Liu, Tian-Yi; Cai, Si-Yu; Nie, Xiao-Lu; Lyu, Ya-Qi; Peng, Xiao-Xia; Feng, Guo-Shuang

2016-01-01

Background: Robust statistical designing, sound statistical analysis, and standardized presentation are important to enhance the quality and transparency of biomedical research. This systematic review was conducted to summarize the statistical reporting requirements introduced by biomedical research journals with an impact factor of 10 or above so that researchers are able to give statistical issues’ serious considerations not only at the stage of data analysis but also at the stage of methodological design. Methods: Detailed statistical instructions for authors were downloaded from the homepage of each of the included journals or obtained from the editors directly via email. Then, we described the types and numbers of statistical guidelines introduced by different press groups. Items of statistical reporting guideline as well as particular requirements were summarized in frequency, which were grouped into design, method of analysis, and presentation, respectively. Finally, updated statistical guidelines and particular requirements for improvement were summed up. Results: Totally, 21 of 23 press groups introduced at least one statistical guideline. More than half of press groups can update their statistical instruction for authors gradually relative to issues of new statistical reporting guidelines. In addition, 16 press groups, covering 44 journals, address particular statistical requirements. The most of the particular requirements focused on the performance of statistical analysis and transparency in statistical reporting, including “address issues relevant to research design, including participant flow diagram, eligibility criteria, and sample size estimation,” and “statistical methods and the reasons.” Conclusions: Statistical requirements for authors are becoming increasingly perfected. Statistical requirements for authors remind researchers that they should make sufficient consideration not only in regards to statistical methods during the research

The Content of Statistical Requirements for Authors in Biomedical Research Journals.

PubMed

Liu, Tian-Yi; Cai, Si-Yu; Nie, Xiao-Lu; Lyu, Ya-Qi; Peng, Xiao-Xia; Feng, Guo-Shuang

2016-10-20

Robust statistical designing, sound statistical analysis, and standardized presentation are important to enhance the quality and transparency of biomedical research. This systematic review was conducted to summarize the statistical reporting requirements introduced by biomedical research journals with an impact factor of 10 or above so that researchers are able to give statistical issues' serious considerations not only at the stage of data analysis but also at the stage of methodological design. Detailed statistical instructions for authors were downloaded from the homepage of each of the included journals or obtained from the editors directly via email. Then, we described the types and numbers of statistical guidelines introduced by different press groups. Items of statistical reporting guideline as well as particular requirements were summarized in frequency, which were grouped into design, method of analysis, and presentation, respectively. Finally, updated statistical guidelines and particular requirements for improvement were summed up. Totally, 21 of 23 press groups introduced at least one statistical guideline. More than half of press groups can update their statistical instruction for authors gradually relative to issues of new statistical reporting guidelines. In addition, 16 press groups, covering 44 journals, address particular statistical requirements. The most of the particular requirements focused on the performance of statistical analysis and transparency in statistical reporting, including "address issues relevant to research design, including participant flow diagram, eligibility criteria, and sample size estimation," and "statistical methods and the reasons." Statistical requirements for authors are becoming increasingly perfected. Statistical requirements for authors remind researchers that they should make sufficient consideration not only in regards to statistical methods during the research design, but also standardized statistical reporting

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

EPA Science Inventory

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...

The discrimination of sea ice types using SAR backscatter statistics

NASA Technical Reports Server (NTRS)

Shuchman, Robert A.; Wackerman, Christopher C.; Maffett, Andrew L.; Onstott, Robert G.; Sutherland, Laura L.

1989-01-01

X-band (HH) synthetic aperture radar (SAR) data of sea ice collected during the Marginal Ice Zone Experiment in March and April of 1987 was statistically analyzed with respect to discriminating open water, first-year ice, multiyear ice, and Odden. Odden are large expanses of nilas ice that rapidly form in the Greenland Sea and transform into pancake ice. A first-order statistical analysis indicated that mean versus variance can segment out open water and first-year ice, and skewness versus modified skewness can segment the Odden and multilayer categories. In additions to first-order statistics, a model has been generated for the distribution function of the SAR ice data. Segmentation of ice types was also attempted using textural measurements. In this case, the general co-occurency matrix was evaluated. The textural method did not generate better results than the first-order statistical approach.

Are studies reporting significant results more likely to be published?

PubMed

Koletsi, Despina; Karagianni, Anthi; Pandis, Nikolaos; Makou, Margarita; Polychronopoulou, Argy; Eliades, Theodore

2009-11-01

Our objective was to assess the hypothesis that there are variations of the proportion of articles reporting a significant effect, with a higher percentage of those articles published in journals with impact factors. The contents of 5 orthodontic journals (American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontist, European Journal of Orthodontics, Journal of Orthodontics, and Orthodontics and Craniofacial Research), published between 2004 and 2008, were hand-searched. Articles with statistical analysis of data were included in the study and classified into 4 categories: behavior and psychology, biomaterials and biomechanics, diagnostic procedures and treatment, and craniofacial growth, morphology, and genetics. In total, 2622 articles were examined, with 1785 included in the analysis. Univariate and multivariate logistic regression analyses were applied with statistical significance as the dependent variable, and whether the journal had an impact factor, the subject, and the year were the independent predictors. A higher percentage of articles showed significant results relative to those without significant associations (on average, 88% vs 12%) for those journals. Overall, these journals published significantly more studies with significant results, ranging from 75% to 90% (P = 0.02). Multivariate modeling showed that journals with impact factors had a 100% increased probability of publishing a statistically significant result compared with journals with no impact factor (odds ratio [OR], 1.99; 95% CI, 1.19-3.31). Compared with articles on biomaterials and biomechanics, all other subject categories showed lower probabilities of significant results. Nonsignificant findings in behavior and psychology and diagnosis and treatment were 1.8 (OR, 1.75; 95% CI, 1.51-2.67) and 3.5 (OR, 3.50; 95% CI, 2.27-5.37) times more likely to be published, respectively. Journals seem to prefer reporting significant results; this might be because of authors

Forensic detection of noise addition in digital images

NASA Astrophysics Data System (ADS)

Cao, Gang; Zhao, Yao; Ni, Rongrong; Ou, Bo; Wang, Yongbin

2014-03-01

We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and recover the image processing history, which is the goal of general forensics techniques. Specifically, the special image blocks, including constant and strip ones, are used to construct the features for identifying noise addition manipulation. The influence of noising on blockwise pixel value distribution is formulated and analyzed formally. The methodology of detectability recognition followed by binary decision is proposed to ensure the applicability and reliability of noising detection. Extensive experimental results demonstrate the efficacy of our proposed noising detector.

CORSSA: Community Online Resource for Statistical Seismicity Analysis

NASA Astrophysics Data System (ADS)

Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.

2011-12-01

Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.

Statistical Analysis of the Polarimetric Cloud Analysis and Seeding Test (POLCAST) Field Projects

NASA Astrophysics Data System (ADS)

Ekness, Jamie Lynn

The North Dakota farming industry brings in more than $4.1 billion annually in cash receipts. Unfortunately, agriculture sales vary significantly from year to year, which is due in large part to weather events such as hail storms and droughts. One method to mitigate drought is to use hygroscopic seeding to increase the precipitation efficiency of clouds. The North Dakota Atmospheric Research Board (NDARB) sponsored the Polarimetric Cloud Analysis and Seeding Test (POLCAST) research project to determine the effectiveness of hygroscopic seeding in North Dakota. The POLCAST field projects obtained airborne and radar observations, while conducting randomized cloud seeding. The Thunderstorm Identification Tracking and Nowcasting (TITAN) program is used to analyze radar data (33 usable cases) in determining differences in the duration of the storm, rain rate and total rain amount between seeded and non-seeded clouds. The single ratio of seeded to non-seeded cases is 1.56 (0.28 mm/0.18 mm) or 56% increase for the average hourly rainfall during the first 60 minutes after target selection. A seeding effect is indicated with the lifetime of the storms increasing by 41 % between seeded and non-seeded clouds for the first 60 minutes past seeding decision. A double ratio statistic, a comparison of radar derived rain amount of the last 40 minutes of a case (seed/non-seed), compared to the first 20 minutes (seed/non-seed), is used to account for the natural variability of the cloud system and gives a double ratio of 1.85. The Mann-Whitney test on the double ratio of seeded to non-seeded cases (33 cases) gives a significance (p-value) of 0.063. Bootstrapping analysis of the POLCAST set indicates that 50 cases would provide statistically significant results based on the Mann-Whitney test of the double ratio. All the statistical analysis conducted on the POLCAST data set show that hygroscopic seeding in North Dakota does increase precipitation. While an additional POLCAST field

Can Money Buy Happiness? A Statistical Analysis of Predictors for User Satisfaction

ERIC Educational Resources Information Center

Hunter, Ben; Perret, Robert

2011-01-01

2007 data from LibQUAL+[TM] and the ACRL Library Trends and Statistics database were analyzed to determine if there is a statistically significant correlation between library expenditures and usage statistics and library patron satisfaction across 73 universities. The results show that users of larger, better funded libraries have higher…

[Influence of autoclave sterilization on dimensional stability and detail reproduction of 5 additional silicone impression materials].

PubMed

Xu, Tong-kai; Sun, Zhi-hui; Jiang, Yong

2012-03-01

To evaluate the dimensional stability and detail reproduction of five additional silicone impression materials after autoclave sterilization. Impressions were made on the ISO 4823 standard mold containing several marking lines, in five kinds of additional silicone. All the impressions were sterilized by high temperature and pressure (135 °C, 212.8 kPa) for 25 min. Linear measurements of pre-sterilization and post-sterilization were made with a measuring microscope. Statistical analysis utilized single-factor analysis with pair-wise comparison of mean values when appropriate. Hypothesis testing was conducted at alpha = 0.05. No significant difference was found between the pre-sterilization and post-sterilization conditions for all locations, and all the absolute valuse of linear rate of change less than 8%. All the sterilization by the autoclave did not affect the surfuce detail reproduction of the 5 impression materials. The dimensional stability and detail reproduction of the five additional silicone impression materials in the study was unaffected by autoclave sterilization.

IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies.

PubMed

Dai, Mingwei; Ming, Jingsi; Cai, Mingxuan; Liu, Jin; Yang, Can; Wan, Xiang; Xu, Zongben

2017-09-15

Results from genome-wide association studies (GWAS) suggest that a complex phenotype is often affected by many variants with small effects, known as 'polygenicity'. Tens of thousands of samples are often required to ensure statistical power of identifying these variants with small effects. However, it is often the case that a research group can only get approval for the access to individual-level genotype data with a limited sample size (e.g. a few hundreds or thousands). Meanwhile, summary statistics generated using single-variant-based analysis are becoming publicly available. The sample sizes associated with the summary statistics datasets are usually quite large. How to make the most efficient use of existing abundant data resources largely remains an open question. In this study, we propose a statistical approach, IGESS, to increasing statistical power of identifying risk variants and improving accuracy of risk prediction by i ntegrating individual level ge notype data and s ummary s tatistics. An efficient algorithm based on variational inference is developed to handle the genome-wide analysis. Through comprehensive simulation studies, we demonstrated the advantages of IGESS over the methods which take either individual-level data or summary statistics data as input. We applied IGESS to perform integrative analysis of Crohns Disease from WTCCC and summary statistics from other studies. IGESS was able to significantly increase the statistical power of identifying risk variants and improve the risk prediction accuracy from 63.2% ( ±0.4% ) to 69.4% ( ±0.1% ) using about 240 000 variants. The IGESS software is available at https://github.com/daviddaigithub/IGESS . zbxu@xjtu.edu.cn or xwan@comp.hkbu.edu.hk or eeyang@hkbu.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies

PubMed Central

Zhu, Zheng-Ming

2017-01-01

Background Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. Results The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52–2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45–2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30–3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. Materials and methods A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Conclusions Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers. PMID:28380443

The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies.

PubMed

Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming

2017-06-20

Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.

Rhythmic grouping biases constrain infant statistical learning

PubMed Central

Hay, Jessica F.; Saffran, Jenny R.

2012-01-01

Linguistic stress and sequential statistical cues to word boundaries interact during speech segmentation in infancy. However, little is known about how the different acoustic components of stress constrain statistical learning. The current studies were designed to investigate whether intensity and duration each function independently as cues to initial prominence (trochaic-based hypothesis) or whether, as predicted by the Iambic-Trochaic Law (ITL), intensity and duration have characteristic and separable effects on rhythmic grouping (ITL-based hypothesis) in a statistical learning task. Infants were familiarized with an artificial language (Experiments 1 & 3) or a tone stream (Experiment 2) in which there was an alternation in either intensity or duration. In addition to potential acoustic cues, the familiarization sequences also contained statistical cues to word boundaries. In speech (Experiment 1) and non-speech (Experiment 2) conditions, 9-month-old infants demonstrated discrimination patterns consistent with an ITL-based hypothesis: intensity signaled initial prominence and duration signaled final prominence. The results of Experiment 3, in which 6.5-month-old infants were familiarized with the speech streams from Experiment 1, suggest that there is a developmental change in infants’ willingness to treat increased duration as a cue to word offsets in fluent speech. Infants’ perceptual systems interact with linguistic experience to constrain how infants learn from their auditory environment. PMID:23730217

Additional standing balance circuit classes during inpatient rehabilitation improved balance outcomes: an assessor-blinded randomised controlled trial.

PubMed

Treacy, Daniel; Schurr, Karl; Lloyd, Bradley; Sherrington, Catherine

2015-07-01

to evaluate the impact on balance (postural control) of six 1-h circuit classes that targeted balance in addition to usual therapy for rehabilitation inpatients. a randomised controlled trial with 2-week and 3-month follow-up. one hundred and sixty-two general rehabilitation inpatients, Bankstown-Lidcombe Hospital, Australia. intervention group participants received six 1-h circuit classes over a 2-week period in addition to usual therapy. Control group participants received usual therapy. standing balance performance (primary outcome) was better in the intervention group than in the control group at 2 weeks (between-group difference after adjusting for baseline values 3.3 s; 95% confidence interval (CI) 0.84 to 5.7, P = 0.009), but the between-group difference was not statistically significant at 3 months (3.4 s; 95% CI -0.56 to 7.38, P = 0.092). Intervention group outcomes were significantly better than the control groups for mobility performance (Short Physical Performance Battery) at 2 weeks (1.19, 95% CI 0.52 to 1.87, P <0.01) and 3 months (1.00, 95% CI 0.00 to 2.00, P < 0.049) and self-reported functioning (AM-PAC) at 2 weeks (5.39, 95% CI 1.20 to 9.57, P = 0.012). The intervention group had a 4.1-day shorter rehabilitation unit stay (95% CI -8.3 to 0.16, P = 0.059) and a lower risk of readmission in the 3 months after randomisation (incidence rate ratio 0.70, 95% CI 0.42 to 1.18, P = 0.184), but these differences were not statistically significant. two weeks of standing balance circuit classes in addition to usual therapy improved balance in general rehabilitation inpatients at 2 weeks. © The Author 2015. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

CHOICE OF INDICATOR DETERMINES THE SIGNIFICANCE AND RISK OBTAINED FROM THE STATISTICAL ASSOCIATION BETWEN FINE PARTICULATE MATTER MASS AND CARDIOVASCULAR MORTALITY

EPA Science Inventory

Minor changes in the indicator used to measure fine PM, which cause only modest changes in Mass concentrations, can lead to dramatic changes in the statistical relationship of fine PM mass with cardiovascular mortality. An epidemiologic study in Phoenix (Mar et al., 2000), augme...

Lidocaine spray in addition to paracervical block reduces pain during first-trimester surgical abortion: a placebo-controlled clinical trial.

PubMed

Karasahin, Kazim Emre; Alanbay, Ibrahim; Ercan, C Mutlu; Mesten, Zeki; Simsek, Canan; Başer, Iskender

2011-04-01

A variety of anesthetic and analgesic techniques have been used for uterine aspiration, and most clinicians use a paracervical block with or without additional analgesia. We intended to evaluate whether the addition of 10% lidocaine spray to a paracervical block decreases pain during cervical dilation and uterine aspiration. Seventy-seven patients were divided into two groups: paracervical blocks (PCB) (n = 30) and PCB plus 10% lidocaine spray (n = 47). Anticipated and overall perceived pain scores were measured with a standard Visual Analog Scale (VAS). Anticipated pain VAS scores of two groups were similar, however overall perceived pain VAS scores demonstrated a significant difference. PCB with Lidocaine only group had 6.56 ± 1.43 cm mean VAS score, whereas lidocaine plus lidocaine spray group had 2.35 ± 1.39 cm, the difference being statistically significant (p < .01). We found that 10% lidocaine spray safely decreases perceived pain during first-trimester surgical abortion, when used in addition to PCB with lidocaine HCl. Copyright © 2011 Elsevier Inc. All rights reserved.

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

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

PubMed Central

Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

2014-01-01

Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874

Neuroendocrine Tumor: Statistics