The potential for increased power from combining P-values testing the same hypothesis.

PubMed

Ganju, Jitendra; Julie Ma, Guoguang

2017-02-01

The conventional approach to hypothesis testing for formal inference is to prespecify a single test statistic thought to be optimal. However, we usually have more than one test statistic in mind for testing the null hypothesis of no treatment effect but we do not know which one is the most powerful. Rather than relying on a single p-value, combining p-values from prespecified multiple test statistics can be used for inference. Combining functions include Fisher's combination test and the minimum p-value. Using randomization-based tests, the increase in power can be remarkable when compared with a single test and Simes's method. The versatility of the method is that it also applies when the number of covariates exceeds the number of observations. The increase in power is large enough to prefer combined p-values over a single p-value. The limitation is that the method does not provide an unbiased estimator of the treatment effect and does not apply to situations when the model includes treatment by covariate interaction.

Experimental design, power and sample size for animal reproduction experiments.

PubMed

Chapman, Phillip L; Seidel, George E

2008-01-01

The present paper concerns statistical issues in the design of animal reproduction experiments, with emphasis on the problems of sample size determination and power calculations. We include examples and non-technical discussions aimed at helping researchers avoid serious errors that may invalidate or seriously impair the validity of conclusions from experiments. Screen shots from interactive power calculation programs and basic SAS power calculation programs are presented to aid in understanding statistical power and computing power in some common experimental situations. Practical issues that are common to most statistical design problems are briefly discussed. These include one-sided hypothesis tests, power level criteria, equality of within-group variances, transformations of response variables to achieve variance equality, optimal specification of treatment group sizes, 'post hoc' power analysis and arguments for the increased use of confidence intervals in place of hypothesis tests.

The influence of the Tribulus terrestris extract on the parameters of the functional preparedness and athletes' organism homeostasis.

PubMed

Milasius, K; Dadeliene, R; Skernevicius, Ju

2009-01-01

The influence of the Tribulus terrestris extract on the parameters of the functional preparadness and athletes' organism homeostase was investigated. It was established the positive impact of dietary supplement "Tribulus" (Optimum Nutrition, U.S.A.) using per 1 capsule 3 times a day during 20 days on athletes' physical power in various energy producing zones: anaerobic alactic muscular power and anaerobic alactic glycolytic power statistically reliable increased. Tribulus terrestris extract, after 20 days of consuming it, did not have essential effect on erythrocytes, haemoglobin and thrombocytes indices. During the experimental period statistically importantly increased percentage of granulocytes and decreased percentage of leucocytes show negative impact of this food supplement on changes of leucocytes formula in athletes' blood. Creatinkinase concentration in athletes' blood statistically importantly has increased and creatinine amount has had a tendency to decline during 20 days period of consuming Tribulus terrestris extract. The declining tendency of urea, cholesterol and bilirubin concentrations has appeared. The concentration of blood testosterone increased statistically reliable during the first half (10 days) of the experiment; it did not grow during the next 10 days while consuming Tribulus still.

Effect size and statistical power in the rodent fear conditioning literature - A systematic review.

PubMed

Carneiro, Clarissa F D; Moulin, Thiago C; Macleod, Malcolm R; Amaral, Olavo B

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.

Effect size and statistical power in the rodent fear conditioning literature – A systematic review

PubMed Central

Macleod, Malcolm R.

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science. PMID:29698451

Statistical power as a function of Cronbach alpha of instrument questionnaire items.

PubMed

Heo, Moonseong; Kim, Namhee; Faith, Myles S

2015-10-14

In countless number of clinical trials, measurements of outcomes rely on instrument questionnaire items which however often suffer measurement error problems which in turn affect statistical power of study designs. The Cronbach alpha or coefficient alpha, here denoted by C(α), can be used as a measure of internal consistency of parallel instrument items that are developed to measure a target unidimensional outcome construct. Scale score for the target construct is often represented by the sum of the item scores. However, power functions based on C(α) have been lacking for various study designs. We formulate a statistical model for parallel items to derive power functions as a function of C(α) under several study designs. To this end, we assume fixed true score variance assumption as opposed to usual fixed total variance assumption. That assumption is critical and practically relevant to show that smaller measurement errors are inversely associated with higher inter-item correlations, and thus that greater C(α) is associated with greater statistical power. We compare the derived theoretical statistical power with empirical power obtained through Monte Carlo simulations for the following comparisons: one-sample comparison of pre- and post-treatment mean differences, two-sample comparison of pre-post mean differences between groups, and two-sample comparison of mean differences between groups. It is shown that C(α) is the same as a test-retest correlation of the scale scores of parallel items, which enables testing significance of C(α). Closed-form power functions and samples size determination formulas are derived in terms of C(α), for all of the aforementioned comparisons. Power functions are shown to be an increasing function of C(α), regardless of comparison of interest. The derived power functions are well validated by simulation studies that show that the magnitudes of theoretical power are virtually identical to those of the empirical power. Regardless of research designs or settings, in order to increase statistical power, development and use of instruments with greater C(α), or equivalently with greater inter-item correlations, is crucial for trials that intend to use questionnaire items for measuring research outcomes. Further development of the power functions for binary or ordinal item scores and under more general item correlation strutures reflecting more real world situations would be a valuable future study.

An Independent Filter for Gene Set Testing Based on Spectral Enrichment.

PubMed

Frost, H Robert; Li, Zhigang; Asselbergs, Folkert W; Moore, Jason H

2015-01-01

Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.

Power in randomized group comparisons: the value of adding a single intermediate time point to a traditional pretest-posttest design.

PubMed

Venter, Anre; Maxwell, Scott E; Bolig, Erika

2002-06-01

Adding a pretest as a covariate to a randomized posttest-only design increases statistical power, as does the addition of intermediate time points to a randomized pretest-posttest design. Although typically 5 waves of data are required in this instance to produce meaningful gains in power, a 3-wave intensive design allows the evaluation of the straight-line growth model and may reduce the effect of missing data. The authors identify the statistically most powerful method of data analysis in the 3-wave intensive design. If straight-line growth is assumed, the pretest-posttest slope must assume fairly extreme values for the intermediate time point to increase power beyond the standard analysis of covariance on the posttest with the pretest as covariate, ignoring the intermediate time point.

Statistical Power of Alternative Structural Models for Comparative Effectiveness Research: Advantages of Modeling Unreliability.

PubMed

Coman, Emil N; Iordache, Eugen; Dierker, Lisa; Fifield, Judith; Schensul, Jean J; Suggs, Suzanne; Barbour, Russell

2014-05-01

The advantages of modeling the unreliability of outcomes when evaluating the comparative effectiveness of health interventions is illustrated. Adding an action-research intervention component to a regular summer job program for youth was expected to help in preventing risk behaviors. A series of simple two-group alternative structural equation models are compared to test the effect of the intervention on one key attitudinal outcome in terms of model fit and statistical power with Monte Carlo simulations. Some models presuming parameters equal across the intervention and comparison groups were underpowered to detect the intervention effect, yet modeling the unreliability of the outcome measure increased their statistical power and helped in the detection of the hypothesized effect. Comparative Effectiveness Research (CER) could benefit from flexible multi-group alternative structural models organized in decision trees, and modeling unreliability of measures can be of tremendous help for both the fit of statistical models to the data and their statistical power.

Output power fluctuations due to different weights of macro particles used in particle-in-cell simulations of Cerenkov devices

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

Bao, Rong; Li, Yongdong; Liu, Chunliang

2016-07-15

The output power fluctuations caused by weights of macro particles used in particle-in-cell (PIC) simulations of a backward wave oscillator and a travelling wave tube are statistically analyzed. It is found that the velocities of electrons passed a specific slow-wave structure form a specific electron velocity distribution. The electron velocity distribution obtained in PIC simulation with a relative small weight of macro particles is considered as an initial distribution. By analyzing this initial distribution with a statistical method, the estimations of the output power fluctuations caused by different weights of macro particles are obtained. The statistical method is verified bymore » comparing the estimations with the simulation results. The fluctuations become stronger with increasing weight of macro particles, which can also be determined reversely from estimations of the output power fluctuations. With the weights of macro particles optimized by the statistical method, the output power fluctuations in PIC simulations are relatively small and acceptable.« less

Wind energy in electric power production, preliminary study

NASA Astrophysics Data System (ADS)

Lento, R.; Peltola, E.

1984-01-01

The wind speed conditions in Finland have been studied with the aid of the existing statistics of the Finnish Meteorological Institute. With the aid of the statistics estimates on the available wind energy were also made. Eight hundred wind power plants, 1.5 MW each, on the windiest west coast would produce about 2 TWh energy per year. Far more information on the temporal, geographical and vertical distribution of the wind speed than the present statistics included is needed when the available wind energy is estimated, when wind power plants are dimensioned optimally, and when suitable locations are chosen for them. The investment costs of a wind power plant increase when the height of the tower or the diameter of the rotor is increased, but the energy production increases, too. Thus, overdimensioning the wind power plant in view of energy needs or the wind conditions caused extra costs. The cost of energy produced by wind power can not yet compete with conventional energy, but the situation changes to the advantage of wind energy, if the real price of the plants decreases (among other things due to large series production and increasing experience), or if the real price of fuels rises. The inconvinience on the environment caused by the wind power plants is considered insignificant. The noise caused by the plant attenuates rapidly with distance. No harmful effects to birds and other animals caused by the wind power plants have been observed in the studies made abroad. Parts of the plant getting loose during an accident, or ice forming on the blades are estimated to fly even from a large plant only a few hundred meters.

Statistical model specification and power: recommendations on the use of test-qualified pooling in analysis of experimental data

PubMed Central

Colegrave, Nick

2017-01-01

A common approach to the analysis of experimental data across much of the biological sciences is test-qualified pooling. Here non-significant terms are dropped from a statistical model, effectively pooling the variation associated with each removed term with the error term used to test hypotheses (or estimate effect sizes). This pooling is only carried out if statistical testing on the basis of applying that data to a previous more complicated model provides motivation for this model simplification; hence the pooling is test-qualified. In pooling, the researcher increases the degrees of freedom of the error term with the aim of increasing statistical power to test their hypotheses of interest. Despite this approach being widely adopted and explicitly recommended by some of the most widely cited statistical textbooks aimed at biologists, here we argue that (except in highly specialized circumstances that we can identify) the hoped-for improvement in statistical power will be small or non-existent, and there is likely to be much reduced reliability of the statistical procedures through deviation of type I error rates from nominal levels. We thus call for greatly reduced use of test-qualified pooling across experimental biology, more careful justification of any use that continues, and a different philosophy for initial selection of statistical models in the light of this change in procedure. PMID:28330912

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 be reported, then the I?-level, effect sizes, and sample sizes used in calculations must also be reported.

When the Test of Mediation is More Powerful than the Test of the Total Effect

PubMed Central

O'Rourke, Holly P.; MacKinnon, David P.

2014-01-01

Although previous research has studied power in mediation models, the extent to which the inclusion of a mediator will increase power has not been investigated. First, a study compared analytical power of the mediated effect to the total effect in a single mediator model to identify the situations in which the inclusion of one mediator increased statistical power. Results from the first study indicated that including a mediator increased statistical power in small samples with large coefficients and in large samples with small coefficients, and when coefficients were non-zero and equal across models. Next, a study identified conditions where power was greater for the test of the total mediated effect compared to the test of the total effect in the parallel two mediator model. Results indicated that including two mediators increased power in small samples with large coefficients and in large samples with small coefficients, the same pattern of results found in the first study. Finally, a study assessed analytical power for a sequential (three-path) two mediator model and compared power to detect the three-path mediated effect to power to detect both the test of the total effect and the test of the mediated effect for the single mediator model. Results indicated that the three-path mediated effect had more power than the mediated effect from the single mediator model and the test of the total effect. Practical implications of these results for researchers are then discussed. PMID:24903690

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.

PubMed

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

2018-03-01

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

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

PubMed

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

2015-03-01

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

Alignment-free sequence comparison (II): theoretical power of comparison statistics.

PubMed

Wan, Lin; Reinert, Gesine; Sun, Fengzhu; Waterman, Michael S

2010-11-01

Rapid methods for alignment-free sequence comparison make large-scale comparisons between sequences increasingly feasible. Here we study the power of the statistic D2, which counts the number of matching k-tuples between two sequences, as well as D2*, which uses centralized counts, and D2S, which is a self-standardized version, both from a theoretical viewpoint and numerically, providing an easy to use program. The power is assessed under two alternative hidden Markov models; the first one assumes that the two sequences share a common motif, whereas the second model is a pattern transfer model; the null model is that the two sequences are composed of independent and identically distributed letters and they are independent. Under the first alternative model, the means of the tuple counts in the individual sequences change, whereas under the second alternative model, the marginal means are the same as under the null model. Using the limit distributions of the count statistics under the null and the alternative models, we find that generally, asymptotically D2S has the largest power, followed by D2*, whereas the power of D2 can even be zero in some cases. In contrast, even for sequences of length 140,000 bp, in simulations D2* generally has the largest power. Under the first alternative model of a shared motif, the power of D2*approaches 100% when sufficiently many motifs are shared, and we recommend the use of D2* for such practical applications. Under the second alternative model of pattern transfer,the power for all three count statistics does not increase with sequence length when the sequence is sufficiently long, and hence none of the three statistics under consideration canbe recommended in such a situation. We illustrate the approach on 323 transcription factor binding motifs with length at most 10 from JASPAR CORE (October 12, 2009 version),verifying that D2* is generally more powerful than D2. The program to calculate the power of D2, D2* and D2S can be downloaded from http://meta.cmb.usc.edu/d2. Supplementary Material is available at www.liebertonline.com/cmb.

When the test of mediation is more powerful than the test of the total effect.

PubMed

O'Rourke, Holly P; MacKinnon, David P

2015-06-01

Although previous research has studied power in mediation models, the extent to which the inclusion of a mediator will increase power has not been investigated. To address this deficit, in a first study we compared the analytical power values of the mediated effect and the total effect in a single-mediator model, to identify the situations in which the inclusion of one mediator increased statistical power. The results from this first study indicated that including a mediator increased statistical power in small samples with large coefficients and in large samples with small coefficients, and when coefficients were nonzero and equal across models. Next, we identified conditions under which power was greater for the test of the total mediated effect than for the test of the total effect in the parallel two-mediator model. These results indicated that including two mediators increased power in small samples with large coefficients and in large samples with small coefficients, the same pattern of results that had been found in the first study. Finally, we assessed the analytical power for a sequential (three-path) two-mediator model and compared the power to detect the three-path mediated effect to the power to detect both the test of the total effect and the test of the mediated effect for the single-mediator model. The results indicated that the three-path mediated effect had more power than the mediated effect from the single-mediator model and the test of the total effect. Practical implications of these results for researchers are then discussed.

Modeling the complexity of acoustic emission during intermittent plastic deformation: Power laws and multifractal spectra

NASA Astrophysics Data System (ADS)

Kumar, Jagadish; Ananthakrishna, G.

2018-01-01

Scale-invariant power-law distributions for acoustic emission signals are ubiquitous in several plastically deforming materials. However, power-law distributions for acoustic emission energies are reported in distinctly different plastically deforming situations such as hcp and fcc single and polycrystalline samples exhibiting smooth stress-strain curves and in dilute metallic alloys exhibiting discontinuous flow. This is surprising since the underlying dislocation mechanisms in these two types of deformations are very different. So far, there have been no models that predict the power-law statistics for discontinuous flow. Furthermore, the statistics of the acoustic emission signals in jerky flow is even more complex, requiring multifractal measures for a proper characterization. There has been no model that explains the complex statistics either. Here we address the problem of statistical characterization of the acoustic emission signals associated with the three types of the Portevin-Le Chatelier bands. Following our recently proposed general framework for calculating acoustic emission, we set up a wave equation for the elastic degrees of freedom with a plastic strain rate as a source term. The energy dissipated during acoustic emission is represented by the Rayleigh-dissipation function. Using the plastic strain rate obtained from the Ananthakrishna model for the Portevin-Le Chatelier effect, we compute the acoustic emission signals associated with the three Portevin-Le Chatelier bands and the Lüders-like band. The so-calculated acoustic emission signals are used for further statistical characterization. Our results show that the model predicts power-law statistics for all the acoustic emission signals associated with the three types of Portevin-Le Chatelier bands with the exponent values increasing with increasing strain rate. The calculated multifractal spectra corresponding to the acoustic emission signals associated with the three band types have a maximum spread for the type C bands and decreasing with types B and A. We further show that the acoustic emission signals associated with Lüders-like band also exhibit a power-law distribution and multifractality.

Modeling the complexity of acoustic emission during intermittent plastic deformation: Power laws and multifractal spectra.

PubMed

Kumar, Jagadish; Ananthakrishna, G

2018-01-01

Scale-invariant power-law distributions for acoustic emission signals are ubiquitous in several plastically deforming materials. However, power-law distributions for acoustic emission energies are reported in distinctly different plastically deforming situations such as hcp and fcc single and polycrystalline samples exhibiting smooth stress-strain curves and in dilute metallic alloys exhibiting discontinuous flow. This is surprising since the underlying dislocation mechanisms in these two types of deformations are very different. So far, there have been no models that predict the power-law statistics for discontinuous flow. Furthermore, the statistics of the acoustic emission signals in jerky flow is even more complex, requiring multifractal measures for a proper characterization. There has been no model that explains the complex statistics either. Here we address the problem of statistical characterization of the acoustic emission signals associated with the three types of the Portevin-Le Chatelier bands. Following our recently proposed general framework for calculating acoustic emission, we set up a wave equation for the elastic degrees of freedom with a plastic strain rate as a source term. The energy dissipated during acoustic emission is represented by the Rayleigh-dissipation function. Using the plastic strain rate obtained from the Ananthakrishna model for the Portevin-Le Chatelier effect, we compute the acoustic emission signals associated with the three Portevin-Le Chatelier bands and the Lüders-like band. The so-calculated acoustic emission signals are used for further statistical characterization. Our results show that the model predicts power-law statistics for all the acoustic emission signals associated with the three types of Portevin-Le Chatelier bands with the exponent values increasing with increasing strain rate. The calculated multifractal spectra corresponding to the acoustic emission signals associated with the three band types have a maximum spread for the type C bands and decreasing with types B and A. We further show that the acoustic emission signals associated with Lüders-like band also exhibit a power-law distribution and multifractality.

Standardized seawater rearing of chinook salmon smolts to evaluate hatchery practices showed low statistical power

USGS Publications Warehouse

Palmisano, Aldo N.; Elder, N.E.

2001-01-01

We examined, under standardized conditions, seawater survival of chinook salmon Oncorhynchus tshawytscha at the smolt stage to evaluate the experimental hatchery practices applied to their rearing. The experimental rearing practices included rearing fish at different densities; attempting to control bacterial kidney disease with broodstock segregation, erythromycin injection, and an experimental diet; rearing fish on different water sources; and freeze branding the fish. After application of experimental rearing practices in hatcheries, smolts were transported to a rearing facility for about 2-3 months of seawater rearing. Of 16 experiments, 4 yielded statistically significant differences in seawater survival. In general we found that high variability among replicates, plus the low numbers of replicates available, resulted in low statistical power. We recommend including four or five replicates and using ?? = 0.10 in 1-tailed tests of hatchery experiments to try to increase the statistical power to 0.80.

Precipitation Cluster Distributions: Current Climate Storm Statistics and Projected Changes Under Global Warming

NASA Astrophysics Data System (ADS)

Quinn, Kevin Martin

The total amount of precipitation integrated across a precipitation cluster (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released, i.e. the power of the disturbance. Probability distributions of cluster power are examined during boreal summer (May-September) and winter (January-March) using satellite-retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) 3B42 and Special Sensor Microwave Imager and Sounder (SSM/I and SSMIS) programs, model output from the High Resolution Atmospheric Model (HIRAM, roughly 0.25-0.5 0 resolution), seven 1-2° resolution members of the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiment, and National Center for Atmospheric Research Large Ensemble (NCAR LENS). Spatial distributions of precipitation-weighted centroids are also investigated in observations (TRMM-3B42) and climate models during winter as a metric for changes in mid-latitude storm tracks. Observed probability distributions for both seasons are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability density drops rapidly. When low rain rates are excluded by choosing a minimum rain rate threshold in defining clusters, the models accurately reproduce observed cluster power statistics and winter storm tracks. Changes in behavior in the tail of the distribution, above the cutoff, are important for impacts since these quantify the frequency of the most powerful storms. End-of-century cluster power distributions and storm track locations are investigated in these models under a "business as usual" global warming scenario. The probability of high cluster power events increases by end-of-century across all models, by up to an order of magnitude for the highest-power events for which statistics can be computed. For the three models in the suite with continuous time series of high resolution output, there is substantial variability on when these probability increases for the most powerful precipitation clusters become detectable, ranging from detectable within the observational period to statistically significant trends emerging only after 2050. A similar analysis of National Centers for Environmental Prediction (NCEP) Reanalysis 2 and SSM/I-SSMIS rain rate retrievals in the recent observational record does not yield reliable evidence of trends in high-power cluster probabilities at this time. Large impacts to mid-latitude storm tracks are projected over the West Coast and eastern North America, with no less than 8 of the 9 models examined showing large increases by end-of-century in the probability density of the most powerful storms, ranging up to a factor of 6.5 in the highest range bin for which historical statistics are computed. However, within these regional domains, there is considerable variation among models in pinpointing exactly where the largest increases will occur.

A powerful approach for association analysis incorporating imprinting effects

PubMed Central

Xia, Fan; Zhou, Ji-Yuan; Fung, Wing Kam

2011-01-01

Motivation: For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants. Results: In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy–Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset. Contact: wingfung@hku.hk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21798962

A powerful approach for association analysis incorporating imprinting effects.

PubMed

Xia, Fan; Zhou, Ji-Yuan; Fung, Wing Kam

2011-09-15

For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants. In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy-Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset. wingfung@hku.hk Supplementary data are available at Bioinformatics online.

Which soft contact lens power is better for piggyback fitting in keratoconus?

PubMed

Romero-Jiménez, Miguel; Santodomingo-Rubido, Jacinto; Flores-Rodríguez, Patricia; González-Méijome, Jose Manuel

2013-02-01

To evaluate the impact of differente soft contact lens power in the anterior corneal curvature and regularity in subjects with keratoconus. Nineteen subjects (30 eyes) with keratoconus were included in the study. Six corneal topographies were taken with Pentacam Eye System over the naked eye and successively with soft lens (Senofilcon A) powers of -3.00, -1.50, 0.00, +1.50 and +3.00 D. Corneal measurements of mean central keratometry (MCK), maximum tangential curvature (TK), maximum front elevation (MFE) and eccentricity (Ecc) at 6 and 8 mm diameters as well as anterior corneal surface high order aberrations (i.e. total RMS, spherical- and coma-like and secondary astigmatism) were evaluated. Negative- and plano-powered soft lenses flattened (p<0.05 in all cases), whereas positive-powered lenses did not induce any significant changes (p>0.05 in all cases) in MCK in comparison to the naked eye. The TK power decreased with negative lenses (p<0.05 in both cases) and increased with +3.00 D lenses (p=0.03) in comparison to the naked eye. No statistically significant differences were found in MFE with any soft lens power in comparison to the naked eye (p>0.05 in all cases). Corneal eccentricity increased at 8 mm diameter for all lens powers (p<0.05 in all cases). No statistically differences were found in HOA RMS and spherical-like aberration (both p>0.05). Statistically differences were found in coma-like and secondary astigmatism (both p<0.05). Negative-powered soft contact lenses provide a flatter anterior surface in comparison to positive-powered lenses in subjects with keratoconus and thus they might be more suitable for piggyback contact lens fitting. Copyright © 2012 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

Mechanistic Considerations Used in the Development of the PROFIT PCI Failure Model

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

Pankaskie, P. J.

A fuel Pellet-Zircaloy Cladding (thermo-mechanical-chemical) Interactions (PC!) failure model for estimating the probability of failure in !ransient increases in power (PROFIT) was developed. PROFIT is based on 1) standard statistical methods applied to available PC! fuel failure data and 2) a mechanistic analysis of the environmental and strain-rate-dependent stress versus strain characteristics of Zircaloy cladding. The statistical analysis of fuel failures attributable to PCI suggested that parameters in addition to power, transient increase in power, and burnup are needed to define PCI fuel failures in terms of probability estimates with known confidence limits. The PROFIT model, therefore, introduces an environmentalmore » and strain-rate dependent strain energy absorption to failure (SEAF) concept to account for the stress versus strain anomalies attributable to interstitial-disloction interaction effects in the Zircaloy cladding. Assuming that the power ramping rate is the operating corollary of strain-rate in the Zircaloy cladding, then the variables of first order importance in the PCI fuel failure phenomenon are postulated to be: 1. pre-transient fuel rod power, P{sub I}, 2. transient increase in fuel rod power, {Delta}P, 3. fuel burnup, Bu, and 4. the constitutive material property of the Zircaloy cladding, SEAF.« less

The influence of control group reproduction on the statistical power of the Environmental Protection Agency's Medaka Extended One Generation Reproduction Test (MEOGRT).

PubMed

Flynn, Kevin; Swintek, Joe; Johnson, Rodney

2017-02-01

Because of various Congressional mandates to protect the environment from endocrine disrupting chemicals (EDCs), the United States Environmental Protection Agency (USEPA) initiated the Endocrine Disruptor Screening Program. In the context of this framework, the Office of Research and Development within the USEPA developed the Medaka Extended One Generation Reproduction Test (MEOGRT) to characterize the endocrine action of a suspected EDC. One important endpoint of the MEOGRT is fecundity of medaka breeding pairs. Power analyses were conducted to determine the number of replicates needed in proposed test designs and to determine the effects that varying reproductive parameters (e.g. mean fecundity, variance, and days with no egg production) would have on the statistical power of the test. The MEOGRT Reproduction Power Analysis Tool (MRPAT) is a software tool developed to expedite these power analyses by both calculating estimates of the needed reproductive parameters (e.g. population mean and variance) and performing the power analysis under user specified scenarios. Example scenarios are detailed that highlight the importance of the reproductive parameters on statistical power. When control fecundity is increased from 21 to 38 eggs per pair per day and the variance decreased from 49 to 20, the gain in power is equivalent to increasing replication by 2.5 times. On the other hand, if 10% of the breeding pairs, including controls, do not spawn, the power to detect a 40% decrease in fecundity drops to 0.54 from nearly 0.98 when all pairs have some level of egg production. Perhaps most importantly, MRPAT was used to inform the decision making process that lead to the final recommendation of the MEOGRT to have 24 control breeding pairs and 12 breeding pairs in each exposure group. Published by Elsevier Inc.

General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies

PubMed Central

Lee, Seunggeun; Teslovich, Tanya M.; Boehnke, Michael; Lin, Xihong

2013-01-01

We propose a general statistical framework for meta-analysis of gene- or region-based multimarker rare variant association tests in sequencing association studies. In genome-wide association studies, single-marker meta-analysis has been widely used to increase statistical power by combining results via regression coefficients and standard errors from different studies. In analysis of rare variants in sequencing studies, region-based multimarker tests are often used to increase power. We propose meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests. Because estimation of regression coefficients of individual rare variants is often unstable or not feasible, the proposed method avoids this difficulty by calculating score statistics instead that only require fitting the null model for each study and then aggregating these score statistics across studies. Our proposed meta-analysis rare variant association tests are conducted based on study-specific summary statistics, specifically score statistics for each variant and between-variant covariance-type (linkage disequilibrium) relationship statistics for each gene or region. The proposed methods are able to incorporate different levels of heterogeneity of genetic effects across studies and are applicable to meta-analysis of multiple ancestry groups. We show that the proposed methods are essentially as powerful as joint analysis by directly pooling individual level genotype data. We conduct extensive simulations to evaluate the performance of our methods by varying levels of heterogeneity across studies, and we apply the proposed methods to meta-analysis of rare variant effects in a multicohort study of the genetics of blood lipid levels. PMID:23768515

Incorporating Biological Knowledge into Evaluation of Casual Regulatory Hypothesis

NASA Technical Reports Server (NTRS)

Chrisman, Lonnie; Langley, Pat; Bay, Stephen; Pohorille, Andrew; DeVincenzi, D. (Technical Monitor)

2002-01-01

Biological data can be scarce and costly to obtain. The small number of samples available typically limits statistical power and makes reliable inference of causal relations extremely difficult. However, we argue that statistical power can be increased substantially by incorporating prior knowledge and data from diverse sources. We present a Bayesian framework that combines information from different sources and we show empirically that this lets one make correct causal inferences with small sample sizes that otherwise would be impossible.

A Statistical Analysis Plan to Support the Joint Forward Area Air Defense Test.

DTIC Science & Technology

1984-08-02

hy estahlishing a specific significance level prior to performing the statistical test (traditionally a levels are set at .01 or .05). What is often...undesirable increase in 8. For constant a levels , the power (I - 8) of a statistical test can he increased by Increasing the sample size of the test. fRef...ANOVA Iparison Test on MOP I=--ferences Exist AmongF "Upon MOP "A" Factor I "A" Factor I 1MOP " A " Levels ? I . I I I _ _ ________ IPerform k-Sample Com- I

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

PubMed Central

Wood, John

2017-01-01

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

Prevalence of diseases and statistical power of the Japan Nurses' Health Study.

PubMed

Fujita, Toshiharu; Hayashi, Kunihiko; Katanoda, Kota; Matsumura, Yasuhiro; Lee, Jung Su; Takagi, Hirofumi; Suzuki, Shosuke; Mizunuma, Hideki; Aso, Takeshi

2007-10-01

The Japan Nurses' Health Study (JNHS) is a long-term, large-scale cohort study investigating the effects of various lifestyle factors and healthcare habits on the health of Japanese women. Based on currently limited statistical data regarding the incidence of disease among Japanese women, our initial sample size was tentatively set at 50,000 during the design phase. The actual number of women who agreed to participate in follow-up surveys was approximately 18,000. Taking into account the actual sample size and new information on disease frequency obtained during the baseline component, we established the prevalence of past diagnoses of target diseases, predicted their incidence, and calculated the statistical power for JNHS follow-up surveys. For all diseases except ovarian cancer, the prevalence of a past diagnosis increased markedly with age, and incidence rates could be predicted based on the degree of increase in prevalence between two adjacent 5-yr age groups. The predicted incidence rate for uterine myoma, hypercholesterolemia, and hypertension was > or =3.0 (per 1,000 women, per year), while the rate of thyroid disease, hepatitis, gallstone disease, and benign breast tumor was predicted to be > or =1.0. For these diseases, the statistical power to detect risk factors with a relative risk of 1.5 or more within ten years, was 70% or higher.

The equal load-sharing model of cascade failures in power grids

NASA Astrophysics Data System (ADS)

Scala, Antonio; De Sanctis Lucentini, Pier Giorgio

2016-11-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing power demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into ;super-grids;.

The statistical overlap theory of chromatography using power law (fractal) statistics.

PubMed

Schure, Mark R; Davis, Joe M

2011-12-30

The chromatographic dimensionality was recently proposed as a measure of retention time spacing based on a power law (fractal) distribution. Using this model, a statistical overlap theory (SOT) for chromatographic peaks is developed that estimates the number of peak maxima as a function of the chromatographic dimension, saturation and scale. Power law models exhibit a threshold region whereby below a critical saturation value no loss of peak maxima due to peak fusion occurs as saturation increases. At moderate saturation, behavior is similar to the random (Poisson) peak model. At still higher saturation, the power law model shows loss of peaks nearly independent of the scale and dimension of the model. The physicochemical meaning of the power law scale parameter is discussed and shown to be equal to the Boltzmann-weighted free energy of transfer over the scale limits. The scale is discussed. Small scale range (small β) is shown to generate more uniform chromatograms. Large scale range chromatograms (large β) are shown to give occasional large excursions of retention times; this is a property of power laws where "wild" behavior is noted to occasionally occur. Both cases are shown to be useful depending on the chromatographic saturation. A scale-invariant model of the SOT shows very simple relationships between the fraction of peak maxima and the saturation, peak width and number of theoretical plates. These equations provide much insight into separations which follow power law statistics. Copyright © 2011 Elsevier B.V. All rights reserved.

The relation between statistical power and inference in fMRI

PubMed Central

Wager, Tor D.; Yarkoni, Tal

2017-01-01

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches. PMID:29155843

Evaluating and Reporting Statistical Power in Counseling Research

ERIC Educational Resources Information Center

Balkin, Richard S.; Sheperis, Carl J.

2011-01-01

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

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 importance of the exposure metric in air pollution epidemiology studies: When does it matter, and why?

EPA Science Inventory

Exposure error in ambient air pollution epidemiologic studies may introduce bias and/or attenuation of the health risk estimate, reduce statistical significance, and lower statistical power. Alternative exposure metrics are increasingly being used in place of central-site measure...

The Surprisingly Modest Relationship between SES and Educational Achievement

ERIC Educational Resources Information Center

Harwell, Michael; Maeda, Yukiko; Bishop, Kyoungwon; Xie, Aolin

2017-01-01

Measures of socioeconomic status (SES) are routinely used in analyses of achievement data to increase statistical power, statistically control for the effects of SES, and enhance causality arguments under the premise that the SES-achievement relationship is moderate to strong. Empirical evidence characterizing the strength of the SES-achievement…

Tests of Mediation: Paradoxical Decline in Statistical Power as a Function of Mediator Collinearity

ERIC Educational Resources Information Center

Beasley, T. Mark

2014-01-01

Increasing the correlation between the independent variable and the mediator ("a" coefficient) increases the effect size ("ab") for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation caused by…

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

PubMed

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

2017-08-23

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

The use of imputed sibling genotypes in sibship-based association analysis: on modeling alternatives, power and model misspecification.

PubMed

Minică, Camelia C; Dolan, Conor V; Hottenga, Jouke-Jan; Willemsen, Gonneke; Vink, Jacqueline M; Boomsma, Dorret I

2013-05-01

When phenotypic, but no genotypic data are available for relatives of participants in genetic association studies, previous research has shown that family-based imputed genotypes can boost the statistical power when included in such studies. Here, using simulations, we compared the performance of two statistical approaches suitable to model imputed genotype data: the mixture approach, which involves the full distribution of the imputed genotypes and the dosage approach, where the mean of the conditional distribution features as the imputed genotype. Simulations were run by varying sibship size, size of the phenotypic correlations among siblings, imputation accuracy and minor allele frequency of the causal SNP. Furthermore, as imputing sibling data and extending the model to include sibships of size two or greater requires modeling the familial covariance matrix, we inquired whether model misspecification affects power. Finally, the results obtained via simulations were empirically verified in two datasets with continuous phenotype data (height) and with a dichotomous phenotype (smoking initiation). Across the settings considered, the mixture and the dosage approach are equally powerful and both produce unbiased parameter estimates. In addition, the likelihood-ratio test in the linear mixed model appears to be robust to the considered misspecification in the background covariance structure, given low to moderate phenotypic correlations among siblings. Empirical results show that the inclusion in association analysis of imputed sibling genotypes does not always result in larger test statistic. The actual test statistic may drop in value due to small effect sizes. That is, if the power benefit is small, that the change in distribution of the test statistic under the alternative is relatively small, the probability is greater of obtaining a smaller test statistic. As the genetic effects are typically hypothesized to be small, in practice, the decision on whether family-based imputation could be used as a means to increase power should be informed by prior power calculations and by the consideration of the background correlation.

Statistical power comparisons at 3T and 7T with a GO / NOGO task.

PubMed

Torrisi, Salvatore; Chen, Gang; Glen, Daniel; Bandettini, Peter A; Baker, Chris I; Reynolds, Richard; Yen-Ting Liu, Jeffrey; Leshin, Joseph; Balderston, Nicholas; Grillon, Christian; Ernst, Monique

2018-07-15

The field of cognitive neuroscience is weighing evidence about whether to move from standard field strength to ultra-high field (UHF). The present study contributes to the evidence by comparing a cognitive neuroscience paradigm at 3 Tesla (3T) and 7 Tesla (7T). The goal was to test and demonstrate the practical effects of field strength on a standard GO/NOGO task using accessible preprocessing and analysis tools. Two independent matched healthy samples (N = 31 each) were analyzed at 3T and 7T. Results show gains at 7T in statistical strength, the detection of smaller effects and group-level power. With an increased availability of UHF scanners, these gains may be exploited by cognitive neuroscientists and other neuroimaging researchers to develop more efficient or comprehensive experimental designs and, given the same sample size, achieve greater statistical power at 7T. Published by Elsevier Inc.

Efficient Bayesian mixed model analysis increases association power in large cohorts

PubMed Central

Loh, Po-Ru; Tucker, George; Bulik-Sullivan, Brendan K; Vilhjálmsson, Bjarni J; Finucane, Hilary K; Salem, Rany M; Chasman, Daniel I; Ridker, Paul M; Neale, Benjamin M; Berger, Bonnie; Patterson, Nick; Price, Alkes L

2014-01-01

Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts, and may not optimize power. All existing methods require time cost O(MN2) (where N = #samples and M = #SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here, we present a far more efficient mixed model association method, BOLT-LMM, which requires only a small number of O(MN)-time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to nine quantitative traits in 23,294 samples from the Women’s Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for GWAS in large cohorts. PMID:25642633

Are the Nonparametric Person-Fit Statistics More Powerful than Their Parametric Counterparts? Revisiting the Simulations in Karabatsos (2003)

ERIC Educational Resources Information Center

Sinharay, Sandip

2017-01-01

Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

Power and Attraction to the Counternormative Aspects of Infidelity.

PubMed

Lammers, Joris; Maner, Jon

2016-01-01

Previous research shows that powerful people are more likely than those lacking power to engage in infidelity. One possible explanation holds (a) that power psychologically releases people from the inhibiting effects of social norms and thus increases their appetite for counternormative forms of sexuality. Two alternative explanations are (b) that power increases appetite for any form of sexuality, normative or counternormative, and (c) that power makes men (but not women) seem more attractive to others and thus increases their access to potential mating opportunities. The current research tested these explanations using correlational data from 610 Dutch men and women. Supporting the first explanation, power's relationship with infidelity was statistically mediated by increased attraction to the secrecy associated with infidelity. Inconsistent with the second explanation, power was linked with infidelity but not with casual sex among singles (a more normative form of sexuality). Inconsistent with the third explanation, the link between power and infidelity was observed just as strongly in women as in men. Findings suggest that power may be associated with infidelity because power draws people to the counternormative aspects of infidelity. Implications for theories of power, sexuality, and gender are discussed.

The Empirical Review of Meta-Analysis Published in Korea

ERIC Educational Resources Information Center

Park, Sunyoung; Hong, Sehee

2016-01-01

Meta-analysis is a statistical method that is increasingly utilized to combine and compare the results of previous primary studies. However, because of the lack of comprehensive guidelines for how to use meta-analysis, many meta-analysis studies have failed to consider important aspects, such as statistical programs, power analysis, publication…

The Power of 'Evidence': Reliable Science or a Set of Blunt Tools?

ERIC Educational Resources Information Center

Wrigley, Terry

2018-01-01

In response to the increasing emphasis on 'evidence-based teaching', this article examines the privileging of randomised controlled trials and their statistical synthesis (meta-analysis). It also pays particular attention to two third-level statistical syntheses: John Hattie's "Visible learning" project and the EEF's "Teaching and…

Abruptness of Cascade Failures in Power Grids

NASA Astrophysics Data System (ADS)

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into ``super-grids''.

Abruptness of cascade failures in power grids.

PubMed

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-15

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into "super-grids".

Abruptness of Cascade Failures in Power Grids

PubMed Central

Pahwa, Sakshi; Scoglio, Caterina; Scala, Antonio

2014-01-01

Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into “super-grids”. PMID:24424239

Update on work-related psychosocial factors and the development of ischemic heart disease: a systematic review.

PubMed

Pejtersen, Jan Hyld; Burr, Hermann; Hannerz, Harald; Fishta, Alba; Hurwitz Eller, Nanna

2015-01-01

The present review deals with the relationship between occupational psychosocial factors and the incidence of ischemic heart disease (IHD) with special regard to the statistical power of the findings. This review with 4 inclusion criteria is an update of a 2009 review of which the first 3 criteria were included in the original review: (1) STUDY: a prospective or case-control study if exposure was not self-reported (prognostic studies excluded); (2) OUTCOME: definite IHD determined externally; (3) EXPOSURE: psychosocial factors at work (excluding shift work, trauma, violence or accidents, and social capital); and (4) Statistical power: acceptable to detect a 20% increased risk in IHD. Eleven new papers met the inclusion criteria 1-3; a total of 44 papers were evaluated regarding inclusion criteria 4. Of 169 statistical analyses, only 10 analyses in 2 papers had acceptable statistical power. The results of the 2 papers pointed in the same direction, namely that only the control dimension of job strain explained the excess risk for myocardial infarction for job strain. The large number of underpowered studies and the focus on psychosocial models, such as the job strain models, make it difficult to determine to what extent psychosocial factors at work are risk factors of IHD. There is a need for considering statistical power when planning studies.

Statistical issues on the analysis of change in follow-up studies in dental research.

PubMed

Blance, Andrew; Tu, Yu-Kang; Baelum, Vibeke; Gilthorpe, Mark S

2007-12-01

To provide an overview to the problems in study design and associated analyses of follow-up studies in dental research, particularly addressing three issues: treatment-baselineinteractions; statistical power; and nonrandomization. Our previous work has shown that many studies purport an interacion between change (from baseline) and baseline values, which is often based on inappropriate statistical analyses. A priori power calculations are essential for randomized controlled trials (RCTs), but in the pre-test/post-test RCT design it is not well known to dental researchers that the choice of statistical method affects power, and that power is affected by treatment-baseline interactions. A common (good) practice in the analysis of RCT data is to adjust for baseline outcome values using ancova, thereby increasing statistical power. However, an important requirement for ancova is there to be no interaction between the groups and baseline outcome (i.e. effective randomization); the patient-selection process should not cause differences in mean baseline values across groups. This assumption is often violated for nonrandomized (observational) studies and the use of ancova is thus problematic, potentially giving biased estimates, invoking Lord's paradox and leading to difficulties in the interpretation of results. Baseline interaction issues can be overcome by use of statistical methods; not widely practiced in dental research: Oldham's method and multilevel modelling; the latter is preferred for its greater flexibility to deal with more than one follow-up occasion as well as additional covariates To illustrate these three key issues, hypothetical examples are considered from the fields of periodontology, orthodontics, and oral implantology. Caution needs to be exercised when considering the design and analysis of follow-up studies. ancova is generally inappropriate for nonrandomized studies and causal inferences from observational data should be avoided.

Discovering human germ cell mutagens with whole genome sequencing: Insights from power calculations reveal the importance of controlling for between-family variability.

PubMed

Webster, R J; Williams, A; Marchetti, F; Yauk, C L

2018-07-01

Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

[A comparison of convenience sampling and purposive sampling].

PubMed

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

2014-06-01

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

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

PubMed

Kim, Junghi; Bai, Yun; Pan, Wei

2015-12-01

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

More Powerful Tests of Simple Interaction Contrasts in the Two-Way Factorial Design

ERIC Educational Resources Information Center

Hancock, Gregory R.; McNeish, Daniel M.

2017-01-01

For the two-way factorial design in analysis of variance, the current article explicates and compares three methods for controlling the Type I error rate for all possible simple interaction contrasts following a statistically significant interaction, including a proposed modification to the Bonferroni procedure that increases the power of…

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

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

2016-12-01

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

Improved statistical power with a sparse shape model in detecting an aging effect in the hippocampus and amygdala

NASA Astrophysics Data System (ADS)

Chung, Moo K.; Kim, Seung-Goo; Schaefer, Stacey M.; van Reekum, Carien M.; Peschke-Schmitz, Lara; Sutterer, Matthew J.; Davidson, Richard J.

2014-03-01

The sparse regression framework has been widely used in medical image processing and analysis. However, it has been rarely used in anatomical studies. We present a sparse shape modeling framework using the Laplace- Beltrami (LB) eigenfunctions of the underlying shape and show its improvement of statistical power. Tradition- ally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes as a form of Fourier descriptors. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we present a LB-based method to filter out only the significant eigenfunctions by imposing a sparse penalty. For dense anatomical data such as deformation fields on a surface mesh, the sparse regression behaves like a smoothing process, which will reduce the error of incorrectly detecting false negatives. Hence the statistical power improves. The sparse shape model is then applied in investigating the influence of age on amygdala and hippocampus shapes in the normal population. The advantage of the LB sparse framework is demonstrated by showing the increased statistical power.

Statistical Power in Meta-Analysis

ERIC Educational Resources Information Center

Liu, Jin

2015-01-01

Statistical power is important in a meta-analysis study, although few studies have examined the performance of simulated power in meta-analysis. The purpose of this study is to inform researchers about statistical power estimation on two sample mean difference test under different situations: (1) the discrepancy between the analytical power and…

Determining the Statistical Power of the Kolmogorov-Smirnov and Anderson-Darling Goodness-of-Fit Tests via Monte Carlo Simulation

DTIC Science & Technology

2016-12-01

KS and AD Statistical Power via Monte Carlo Simulation Statistical power is the probability of correctly rejecting the null hypothesis when the...Select a caveat DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. Determining the Statistical Power...real-world data to test the accuracy of the simulation. Statistical comparison of these metrics can be necessary when making such a determination

The case for increasing the statistical power of eddy covariance ecosystem studies: why, where and how?

PubMed

Hill, Timothy; Chocholek, Melanie; Clement, Robert

2017-06-01

Eddy covariance (EC) continues to provide invaluable insights into the dynamics of Earth's surface processes. However, despite its many strengths, spatial replication of EC at the ecosystem scale is rare. High equipment costs are likely to be partially responsible. This contributes to the low sampling, and even lower replication, of ecoregions in Africa, Oceania (excluding Australia) and South America. The level of replication matters as it directly affects statistical power. While the ergodicity of turbulence and temporal replication allow an EC tower to provide statistically robust flux estimates for its footprint, these principles do not extend to larger ecosystem scales. Despite the challenge of spatially replicating EC, it is clearly of interest to be able to use EC to provide statistically robust flux estimates for larger areas. We ask: How much spatial replication of EC is required for statistical confidence in our flux estimates of an ecosystem? We provide the reader with tools to estimate the number of EC towers needed to achieve a given statistical power. We show that for a typical ecosystem, around four EC towers are needed to have 95% statistical confidence that the annual flux of an ecosystem is nonzero. Furthermore, if the true flux is small relative to instrument noise and spatial variability, the number of towers needed can rise dramatically. We discuss approaches for improving statistical power and describe one solution: an inexpensive EC system that could help by making spatial replication more affordable. However, we note that diverting limited resources from other key measurements in order to allow spatial replication may not be optimal, and a balance needs to be struck. While individual EC towers are well suited to providing fluxes from the flux footprint, we emphasize that spatial replication is essential for statistically robust fluxes if a wider ecosystem is being studied. © 2016 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

PubMed

Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

2010-07-15

With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions. Copyright 2010 Elsevier B.V. All rights reserved.

Explanation of Two Anomalous Results in Statistical Mediation Analysis.

PubMed

Fritz, Matthew S; Taylor, Aaron B; Mackinnon, David P

2012-01-01

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M , a , increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y , b , was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a . Implications of these findings are discussed.

A shift from significance test to hypothesis test through power analysis in medical research.

PubMed

Singh, G

2006-01-01

Medical research literature until recently, exhibited substantial dominance of the Fisher's significance test approach of statistical inference concentrating more on probability of type I error over Neyman-Pearson's hypothesis test considering both probability of type I and II error. Fisher's approach dichotomises results into significant or not significant results with a P value. The Neyman-Pearson's approach talks of acceptance or rejection of null hypothesis. Based on the same theory these two approaches deal with same objective and conclude in their own way. The advancement in computing techniques and availability of statistical software have resulted in increasing application of power calculations in medical research and thereby reporting the result of significance tests in the light of power of the test also. Significance test approach, when it incorporates power analysis contains the essence of hypothesis test approach. It may be safely argued that rising application of power analysis in medical research may have initiated a shift from Fisher's significance test to Neyman-Pearson's hypothesis test procedure.

Mixed-strain housing for female C57BL/6, DBA/2, and BALB/c mice: validating a split-plot design that promotes refinement and reduction.

PubMed

Walker, Michael; Fureix, Carole; Palme, Rupert; Newman, Jonathan A; Ahloy Dallaire, Jamie; Mason, Georgia

2016-01-27

Inefficient experimental designs are common in animal-based biomedical research, wasting resources and potentially leading to unreplicable results. Here we illustrate the intrinsic statistical power of split-plot designs, wherein three or more sub-units (e.g. individual subjects) differing in a variable of interest (e.g. genotype) share an experimental unit (e.g. a cage or litter) to which a treatment is applied (e.g. a drug, diet, or cage manipulation). We also empirically validate one example of such a design, mixing different mouse strains -- C57BL/6, DBA/2, and BALB/c -- within cages varying in degree of enrichment. As well as boosting statistical power, no other manipulations are needed for individual identification if co-housed strains are differentially pigmented, so also sparing mice from stressful marking procedures. The validation involved housing 240 females from weaning to 5 months of age in single- or mixed- strain trios, in cages allocated to enriched or standard treatments. Mice were screened for a range of 26 commonly-measured behavioural, physiological and haematological variables. Living in mixed-strain trios did not compromise mouse welfare (assessed via corticosterone metabolite output, stereotypic behaviour, signs of aggression, and other variables). It also did not alter the direction or magnitude of any strain- or enrichment-typical difference across the 26 measured variables, or increase variance in the data: indeed variance was significantly decreased by mixed- strain housing. Furthermore, using Monte Carlo simulations to quantify the statistical power benefits of this approach over a conventional design demonstrated that for our effect sizes, the split- plot design would require significantly fewer mice (under half in most cases) to achieve a power of 80%. Mixed-strain housing allows several strains to be tested at once, and potentially refines traditional marking practices for research mice. Furthermore, it dramatically illustrates the enhanced statistical power of split-plot designs, allowing many fewer animals to be used. More powerful designs can also increase the chances of replicable findings, and increase the ability of small-scale studies to yield significant results. Using mixed-strain housing for female C57BL/6, DBA/2 and BALB/c mice is therefore an effective, efficient way to promote both refinement and the reduction of animal-use in research.

Acute Respiratory Distress Syndrome Measurement Error. Potential Effect on Clinical Study Results

PubMed Central

Cooke, Colin R.; Iwashyna, Theodore J.; Hofer, Timothy P.

2016-01-01

Rationale: Identifying patients with acute respiratory distress syndrome (ARDS) is a recognized challenge. Experts often have only moderate agreement when applying the clinical definition of ARDS to patients. However, no study has fully examined the implications of low reliability measurement of ARDS on clinical studies. Objectives: To investigate how the degree of variability in ARDS measurement commonly reported in clinical studies affects study power, the accuracy of treatment effect estimates, and the measured strength of risk factor associations. Methods: We examined the effect of ARDS measurement error in randomized clinical trials (RCTs) of ARDS-specific treatments and cohort studies using simulations. We varied the reliability of ARDS diagnosis, quantified as the interobserver reliability (κ-statistic) between two reviewers. In RCT simulations, patients identified as having ARDS were enrolled, and when measurement error was present, patients without ARDS could be enrolled. In cohort studies, risk factors as potential predictors were analyzed using reviewer-identified ARDS as the outcome variable. Measurements and Main Results: Lower reliability measurement of ARDS during patient enrollment in RCTs seriously degraded study power. Holding effect size constant, the sample size necessary to attain adequate statistical power increased by more than 50% as reliability declined, although the result was sensitive to ARDS prevalence. In a 1,400-patient clinical trial, the sample size necessary to maintain similar statistical power increased to over 1,900 when reliability declined from perfect to substantial (κ = 0.72). Lower reliability measurement diminished the apparent effectiveness of an ARDS-specific treatment from a 15.2% (95% confidence interval, 9.4–20.9%) absolute risk reduction in mortality to 10.9% (95% confidence interval, 4.7–16.2%) when reliability declined to moderate (κ = 0.51). In cohort studies, the effect on risk factor associations was similar. Conclusions: ARDS measurement error can seriously degrade statistical power and effect size estimates of clinical studies. The reliability of ARDS measurement warrants careful attention in future ARDS clinical studies. PMID:27159648

Optimization of pulsed laser welding process parameters in order to attain minimum underfill and undercut defects in thin 316L stainless steel foils

NASA Astrophysics Data System (ADS)

Pakmanesh, M. R.; Shamanian, M.

2018-02-01

In this study, the optimization of pulsed Nd:YAG laser welding parameters was done on the lap-joint of a 316L stainless steel foil with the aim of reducing weld defects through response surface methodology. For this purpose, the effects of peak power, pulse-duration, and frequency were investigated. The most important weld defects seen in this method include underfill and undercut. By presenting a second-order polynomial, the above-mentioned statistical method was managed to be well employed to balance the welding parameters. The results showed that underfill increased with the increased power and reduced frequency, it first increased and then decreased with the increased pulse-duration; and the most important parameter affecting it was the power, whose effect was 65%. The undercut increased with the increased power, pulse-duration, and frequency; and the most important parameter affecting it was the power, whose effect was 64%. Finally, by superimposing different responses, improved conditions were presented to attain a weld with no defects.

Detection of changes of high-frequency activity by statistical time-frequency analysis in epileptic spikes

PubMed Central

Kobayashi, Katsuhiro; Jacobs, Julia; Gotman, Jean

2013-01-01

Objective A novel type of statistical time-frequency analysis was developed to elucidate changes of high-frequency EEG activity associated with epileptic spikes. Methods The method uses the Gabor Transform and detects changes of power in comparison to background activity using t-statistics that are controlled by the false discovery rate (FDR) to correct type I error of multiple testing. The analysis was applied to EEGs recorded at 2000 Hz from three patients with mesial temporal lobe epilepsy. Results Spike-related increase of high-frequency oscillations (HFOs) was clearly shown in the FDR-controlled t-spectra: it was most dramatic in spikes recorded from the hippocampus when the hippocampus was the seizure onset zone (SOZ). Depression of fast activity was observed immediately after the spikes, especially consistently in the discharges from the hippocampal SOZ. It corresponded to the slow wave part in case of spike-and-slow-wave complexes, but it was noted even in spikes without apparent slow waves. In one patient, a gradual increase of power above 200 Hz preceded spikes. Conclusions FDR-controlled t-spectra clearly detected the spike-related changes of HFOs that were unclear in standard power spectra. Significance We developed a promising tool to study the HFOs that may be closely linked to the pathophysiology of epileptogenesis. PMID:19394892

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

A mechanism producing power law etc. distributions

NASA Astrophysics Data System (ADS)

Li, Heling; Shen, Hongjun; Yang, Bin

2017-07-01

Power law distribution is playing an increasingly important role in the complex system study. Based on the insolvability of complex systems, the idea of incomplete statistics is utilized and expanded, three different exponential factors are introduced in equations about the normalization condition, statistical average and Shannon entropy, with probability distribution function deduced about exponential function, power function and the product form between power function and exponential function derived from Shannon entropy and maximal entropy principle. So it is shown that maximum entropy principle can totally replace equal probability hypothesis. Owing to the fact that power and probability distribution in the product form between power function and exponential function, which cannot be derived via equal probability hypothesis, can be derived by the aid of maximal entropy principle, it also can be concluded that maximal entropy principle is a basic principle which embodies concepts more extensively and reveals basic principles on motion laws of objects more fundamentally. At the same time, this principle also reveals the intrinsic link between Nature and different objects in human society and principles complied by all.

A Fundamental Study on Spectrum Center Estimation of Solar Spectral Irradiation by the Statistical Pattern Recognition

NASA Astrophysics Data System (ADS)

Iijima, Aya; Suzuki, Kazumi; Wakao, Shinji; Kawasaki, Norihiro; Usami, Akira

With a background of environmental problems and energy issues, it is expected that PV systems will be introduced rapidly and connected with power grids on a large scale in the future. For this reason, the concern to which PV power generation will affect supply and demand adjustment in electric power in the future arises and the technique of correctly grasping the PV power generation becomes increasingly important. The PV power generation depends on solar irradiance, temperature of a module and solar spectral irradiance. Solar spectral irradiance is distribution of the strength of the light for every wavelength. As the spectrum sensitivity of solar cell depends on kind of solar cell, it becomes important for exact grasp of PV power generation. Especially the preparation of solar spectral irradiance is, however, not easy because the observational instrument of solar spectral irradiance is expensive. With this background, in this paper, we propose a new method based on statistical pattern recognition for estimating the spectrum center which is representative index of solar spectral irradiance. Some numerical examples obtained by the proposed method are also presented.

Toward "Constructing" the Concept of Statistical Power: An Optical Analogy.

ERIC Educational Resources Information Center

Rogers, Bruce G.

This paper presents a visual analogy that may be used by instructors to teach the concept of statistical power in statistical courses. Statistical power is mathematically defined as the probability of rejecting a null hypothesis when that null is false, or, equivalently, the probability of detecting a relationship when it exists. The analogy…

Comparison of laser and power bleaching techniques in tooth color change.

PubMed

Fekrazad, Reza; Alimazandarani, Shervin; Kalhori, Katayoun Am; Assadian, Hadi; Mirmohammadi, Seyed-Mahdi

2017-04-01

Laser-assisted bleaching uses laser beam to accelerate release of free radicals within the bleaching gel to decrease time of whitening procedure. The aim of this study was to compare the efficacy of power bleaching using Opalescence Xtra Boost® and laser bleaching technique using LaserSmile gel and diode laser as an activator in their tooth whitening capacity. Student t test showed that the laser bleaching group significantly outperformed the power bleaching group in changing ∆E ( p =0.977). Similarly, while comparing the groups in changing ∆L, the laser bleaching group indicated significantly superior results ( p =0.953). Statistical data from student t test while comparing the groups in changing the parameter of yellowness indicated that samples in laser bleaching group underwent a more significant reduction than power-bleached samples ( p =0.85). Correspondingly, changes in whiteness were statistically tested through student t test, showing that laser bleaching technique increased whiteness of the samples significantly more than those treated by power bleaching ( p =0.965). The digital color evaluation data was in accordance with spectrophotometry and showed that laser bleaching outperformed power bleaching technique. Both techniques were able to increase whiteness and decrease yellowness ratio of the samples. ΔE decrease for laser bleaching and power bleaching groups were 3.05 and 1.67, respectively. Tooth color change in laser bleaching group was 1.88 times more than that of power bleaching group ( p <0.001). It could be concluded that under the conditions of this study, both laser-assisted and power bleaching techniques were capable of altering tooth color change, but laser bleaching was deemed a more efficient technique in this regard. Key words: Laser, power bleaching, tooth color introduction.

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-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.

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 provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic. PMID:20642827

Statistical modeling of an integrated boiler for coal fired thermal power plant.

PubMed

Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan

2017-06-01

The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.

The effects of age and gender on sleep EEG power spectral density in the middle years of life (ages 20-60 years old)

NASA Technical Reports Server (NTRS)

Carrier, J.; Land, S.; Buysse, D. J.; Kupfer, D. J.; Monk, T. H.

2001-01-01

The effects of age and gender on sleep EEG power spectral density were assessed in a group of 100 subjects aged 20 to 60 years. We propose a new statistical strategy (mixed-model using fixed-knot regression splines) to analyze quantitative EEG measures. The effect of gender varied according to frequency, but no interactions emerged between age and gender, suggesting that the aging process does not differentially influence men and women. Women had higher power density than men in delta, theta, low alpha, and high spindle frequency range. The effect of age varied according to frequency and across the night. The decrease in power with age was not restricted to slow-wave activity, but also included theta and sigma activity. With increasing age, the attenuation over the night in power density between 1.25 and 8.00 Hz diminished, and the rise in power between 12.25 and 14.00 Hz across the night decreased. Increasing age was associated with higher power in the beta range. These results suggest that increasing age may be related to an attenuation of homeostatic sleep pressure and to an increase in cortical activation during sleep.

A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data

PubMed Central

Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-01-01

Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics. PMID:29040274

From entropy-maximization to equality-maximization: Gauss, Laplace, Pareto, and Subbotin

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2014-12-01

The entropy-maximization paradigm of statistical physics is well known to generate the omnipresent Gauss law. In this paper we establish an analogous socioeconomic model which maximizes social equality, rather than physical disorder, in the context of the distributions of income and wealth in human societies. We show that-on a logarithmic scale-the Laplace law is the socioeconomic equality-maximizing counterpart of the physical entropy-maximizing Gauss law, and that this law manifests an optimized balance between two opposing forces: (i) the rich and powerful, striving to amass ever more wealth, and thus to increase social inequality; and (ii) the masses, struggling to form more egalitarian societies, and thus to increase social equality. Our results lead from log-Gauss statistics to log-Laplace statistics, yield Paretian power-law tails of income and wealth distributions, and show how the emergence of a middle-class depends on the underlying levels of socioeconomic inequality and variability. Also, in the context of asset-prices with Laplace-distributed returns, our results imply that financial markets generate an optimized balance between risk and predictability.

Power analysis on the time effect for the longitudinal Rasch model.

PubMed

Feddag, M L; Blanchin, M; Hardouin, J B; Sebille, V

2014-01-01

Statistics literature in the social, behavioral, and biomedical sciences typically stress the importance of power analysis. Patient Reported Outcomes (PRO) such as quality of life and other perceived health measures (pain, fatigue, stress,...) are increasingly used as important health outcomes in clinical trials or in epidemiological studies. They cannot be directly observed nor measured as other clinical or biological data and they are often collected through questionnaires with binary or polytomous items. The Rasch model is the well known model in the item response theory (IRT) for binary data. The article proposes an approach to evaluate the statistical power of the time effect for the longitudinal Rasch model with two time points. The performance of this method is compared to the one obtained by simulation study. Finally, the proposed approach is illustrated on one subscale of the SF-36 questionnaire.

Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size.

PubMed

Heidel, R Eric

2016-01-01

Statistical power is the ability to detect a significant effect, given that the effect actually exists in a population. Like most statistical concepts, statistical power tends to induce cognitive dissonance in hepatology researchers. However, planning for statistical power by an a priori sample size calculation is of paramount importance when designing a research study. There are five specific empirical components that make up an a priori sample size calculation: the scale of measurement of the outcome, the research design, the magnitude of the effect size, the variance of the effect size, and the sample size. A framework grounded in the phenomenon of isomorphism, or interdependencies amongst different constructs with similar forms, will be presented to understand the isomorphic effects of decisions made on each of the five aforementioned components of statistical power.

Prospective power calculations for the Four Lab study of a multigenerational reproductive/developmental toxicity rodent bioassay using a complex mixture of disinfection by-products in the low-response region.

PubMed

Dingus, Cheryl A; Teuschler, Linda K; Rice, Glenn E; Simmons, Jane Ellen; Narotsky, Michael G

2011-10-01

In complex mixture toxicology, there is growing emphasis on testing environmentally representative doses that improve the relevance of results for health risk assessment, but are typically much lower than those used in traditional toxicology studies. Traditional experimental designs with typical sample sizes may have insufficient statistical power to detect effects caused by environmentally relevant doses. Proper study design, with adequate statistical power, is critical to ensuring that experimental results are useful for environmental health risk assessment. Studies with environmentally realistic complex mixtures have practical constraints on sample concentration factor and sample volume as well as the number of animals that can be accommodated. This article describes methodology for calculation of statistical power for non-independent observations for a multigenerational rodent reproductive/developmental bioassay. The use of the methodology is illustrated using the U.S. EPA's Four Lab study in which rodents were exposed to chlorinated water concentrates containing complex mixtures of drinking water disinfection by-products. Possible experimental designs included two single-block designs and a two-block design. Considering the possible study designs and constraints, a design of two blocks of 100 females with a 40:60 ratio of control:treated animals and a significance level of 0.05 yielded maximum prospective power (~90%) to detect pup weight decreases, while providing the most power to detect increased prenatal loss.

Prospective Power Calculations for the Four Lab Study of A Multigenerational Reproductive/Developmental Toxicity Rodent Bioassay Using A Complex Mixture of Disinfection By-Products in the Low-Response Region

PubMed Central

Dingus, Cheryl A.; Teuschler, Linda K.; Rice, Glenn E.; Simmons, Jane Ellen; Narotsky, Michael G.

2011-01-01

In complex mixture toxicology, there is growing emphasis on testing environmentally representative doses that improve the relevance of results for health risk assessment, but are typically much lower than those used in traditional toxicology studies. Traditional experimental designs with typical sample sizes may have insufficient statistical power to detect effects caused by environmentally relevant doses. Proper study design, with adequate statistical power, is critical to ensuring that experimental results are useful for environmental health risk assessment. Studies with environmentally realistic complex mixtures have practical constraints on sample concentration factor and sample volume as well as the number of animals that can be accommodated. This article describes methodology for calculation of statistical power for non-independent observations for a multigenerational rodent reproductive/developmental bioassay. The use of the methodology is illustrated using the U.S. EPA’s Four Lab study in which rodents were exposed to chlorinated water concentrates containing complex mixtures of drinking water disinfection by-products. Possible experimental designs included two single-block designs and a two-block design. Considering the possible study designs and constraints, a design of two blocks of 100 females with a 40:60 ratio of control:treated animals and a significance level of 0.05 yielded maximum prospective power (~90%) to detect pup weight decreases, while providing the most power to detect increased prenatal loss. PMID:22073030

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…

Enhanced Higgs boson to τ(+)τ(-) search with deep learning.

PubMed

Baldi, P; Sadowski, P; Whiteson, D

2015-03-20

The Higgs boson is thought to provide the interaction that imparts mass to the fundamental fermions, but while measurements at the Large Hadron Collider (LHC) are consistent with this hypothesis, current analysis techniques lack the statistical power to cross the traditional 5σ significance barrier without more data. Deep learning techniques have the potential to increase the statistical power of this analysis by automatically learning complex, high-level data representations. In this work, deep neural networks are used to detect the decay of the Higgs boson to a pair of tau leptons. A Bayesian optimization algorithm is used to tune the network architecture and training algorithm hyperparameters, resulting in a deep network of eight nonlinear processing layers that improves upon the performance of shallow classifiers even without the use of features specifically engineered by physicists for this application. The improvement in discovery significance is equivalent to an increase in the accumulated data set of 25%.

Electroencephalographic dynamics of musical emotion perception revealed by independent spectral components.

PubMed

Lin, Yuan-Pin; Duann, Jeng-Ren; Chen, Jyh-Horng; Jung, Tzyy-Ping

2010-04-21

This study explores the electroencephalographic (EEG) correlates of emotional experience during music listening. Independent component analysis and analysis of variance were used to separate statistically independent spectral changes of the EEG in response to music-induced emotional processes. An independent brain process with equivalent dipole located in the fronto-central region exhibited distinct δ-band and θ-band power changes associated with self-reported emotional states. Specifically, the emotional valence was associated with δ-power decreases and θ-power increases in the frontal-central area, whereas the emotional arousal was accompanied by increases in both δ and θ powers. The resultant emotion-related component activations that were less interfered by the activities from other brain processes complement previous EEG studies of emotion perception to music.

Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability

ERIC Educational Resources Information Center

von Oertzen, Timo; Boker, Steven M.

2010-01-01

This paper investigates the precision of parameters estimated from local samples of time dependent functions. We find that "time delay embedding," i.e., structuring data prior to analysis by constructing a data matrix of overlapping samples, increases the precision of parameter estimates and in turn statistical power compared to standard…

The Inheritance of Metabolic Flux: Expressions for the within-Sibship Mean and Variance Given the Parental Genotypes

PubMed Central

Ward, P. J.

1990-01-01

Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux. PMID:2379825

A statistical physics view of pitch fluctuations in the classical music from Bach to Chopin: evidence for scaling.

PubMed

Liu, Lu; Wei, Jianrong; Zhang, Huishu; Xin, Jianhong; Huang, Jiping

2013-01-01

Because classical music has greatly affected our life and culture in its long history, it has attracted extensive attention from researchers to understand laws behind it. Based on statistical physics, here we use a different method to investigate classical music, namely, by analyzing cumulative distribution functions (CDFs) and autocorrelation functions of pitch fluctuations in compositions. We analyze 1,876 compositions of five representative classical music composers across 164 years from Bach, to Mozart, to Beethoven, to Mendelsohn, and to Chopin. We report that the biggest pitch fluctuations of a composer gradually increase as time evolves from Bach time to Mendelsohn/Chopin time. In particular, for the compositions of a composer, the positive and negative tails of a CDF of pitch fluctuations are distributed not only in power laws (with the scale-free property), but also in symmetry (namely, the probability of a treble following a bass and that of a bass following a treble are basically the same for each composer). The power-law exponent decreases as time elapses. Further, we also calculate the autocorrelation function of the pitch fluctuation. The autocorrelation function shows a power-law distribution for each composer. Especially, the power-law exponents vary with the composers, indicating their different levels of long-range correlation of notes. This work not only suggests a way to understand and develop music from a viewpoint of statistical physics, but also enriches the realm of traditional statistical physics by analyzing music.

Statistical testing and power analysis for brain-wide association study.

PubMed

Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

2018-04-05

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial correlation and irradiance statistics in a multiple-beam terrestrial free-space optical communication link.

PubMed

Anguita, Jaime A; Neifeld, Mark A; Vasic, Bane V

2007-09-10

By means of numerical simulations we analyze the statistical properties of the power fluctuations induced by the incoherent superposition of multiple transmitted laser beams in a terrestrial free-space optical communication link. The measured signals arising from different transmitted optical beams are found to be statistically correlated. This channel correlation increases with receiver aperture and propagation distance. We find a simple scaling rule for the spatial correlation coefficient in terms of the propagation distance and we are able to predict the scintillation reduction in previously reported experiments with good accuracy. We propose an approximation to the probability density function of the received power of a spatially correlated multiple-beam system in terms of the parameters of the single-channel gamma-gamma function. A bit-error-rate evaluation is also presented to demonstrate the improvement of a multibeam system over its single-beam counterpart.

System Study: Residual Heat Removal 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the residual heat removal (RHR) system in two modes of operation (low-pressure injection in response to a large loss-of-coolant accident and post-trip shutdown-cooling) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing trends were identified in themore » RHR results. A highly statistically significant decreasing trend was observed for the RHR injection mode start-only unreliability. Statistically significant decreasing trends were observed for RHR shutdown cooling mode start-only unreliability and RHR shutdown cooling model 24-hour unreliability.« less

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

Comparison of three longitudinal analysis models for the health-related quality of life in oncology: a simulation study.

PubMed

Anota, Amélie; Barbieri, Antoine; Savina, Marion; Pam, Alhousseiny; Gourgou-Bourgade, Sophie; Bonnetain, Franck; Bascoul-Mollevi, Caroline

2014-12-31

Health-Related Quality of Life (HRQoL) is an important endpoint in oncology clinical trials aiming to investigate the clinical benefit of new therapeutic strategies for the patient. However, the longitudinal analysis of HRQoL remains complex and unstandardized. There is clearly a need to propose accessible statistical methods and meaningful results for clinicians. The objective of this study was to compare three strategies for longitudinal analyses of HRQoL data in oncology clinical trials through a simulation study. The methods proposed were: the score and mixed model (SM); a survival analysis approach based on the time to HRQoL score deterioration (TTD); and the longitudinal partial credit model (LPCM). Simulations compared the methods in terms of type I error and statistical power of the test of an interaction effect between treatment arm and time. Several simulation scenarios were explored based on the EORTC HRQoL questionnaires and varying the number of patients (100, 200 or 300), items (1, 2 or 4) and response categories per item (4 or 7). Five or 10 measurement times were considered, with correlations ranging from low to high between each measure. The impact of informative missing data on these methods was also studied to reflect the reality of most clinical trials. With complete data, the type I error rate was close to the expected value (5%) for all methods, while the SM method was the most powerful method, followed by LPCM. The power of TTD is low for single-item dimensions, because only four possible values exist for the score. When the number of items increases, the power of the SM approach remained stable, those of the TTD method increases while the power of LPCM remained stable. With 10 measurement times, the LPCM was less efficient. With informative missing data, the statistical power of SM and TTD tended to decrease, while that of LPCM tended to increase. To conclude, the SM model was the most powerful model, irrespective of the scenario considered, and the presence or not of missing data. The TTD method should be avoided for single-item dimensions of the EORTC questionnaire. While the LPCM model was more adapted to this kind of data, it was less efficient than the SM model. These results warrant validation through comparisons on real data.

Explorations in Statistics: Power

ERIC Educational Resources Information Center

Curran-Everett, Douglas

2010-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fifth installment of "Explorations in Statistics" revisits power, a concept fundamental to the test of a null hypothesis. Power is the probability that we reject the null hypothesis when it is false. Four…

An Examination of Statistical Power in Multigroup Dynamic Structural Equation Models

ERIC Educational Resources Information Center

Prindle, John J.; McArdle, John J.

2012-01-01

This study used statistical simulation to calculate differential statistical power in dynamic structural equation models with groups (as in McArdle & Prindle, 2008). Patterns of between-group differences were simulated to provide insight into how model parameters influence power approximations. Chi-square and root mean square error of…

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Electric power annual 1992

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

Not Available

The Electric Power Annual presents a summary of electric utility statistics at national, regional and State levels. The objective of the publication is to provide industry decisionmakers, government policymakers, analysts and the general public with historical data that may be used in understanding US electricity markets. The Electric Power Annual is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels; Energy Information Administration (EIA); US Department of Energy. ``The US Electric Power Industry at a Glance`` section presents a profile of the electric power industry ownership and performance, and a review of key statistics formore » the year. Subsequent sections present data on generating capability, including proposed capability additions; net generation; fossil-fuel statistics; retail sales; revenue; financial statistics; environmental statistics; electric power transactions; demand-side management; and nonutility power producers. In addition, the appendices provide supplemental data on major disturbances and unusual occurrences in US electricity power systems. Each section contains related text and tables and refers the reader to the appropriate publication that contains more detailed data on the subject matter. Monetary values in this publication are expressed in nominal terms.« less

Confidence crisis of results in biomechanics research.

PubMed

Knudson, Duane

2017-11-01

Many biomechanics studies have small sample sizes and incorrect statistical analyses, so reporting of inaccurate inferences and inflated magnitude of effects are common in the field. This review examines these issues in biomechanics research and summarises potential solutions from research in other fields to increase the confidence in the experimental effects reported in biomechanics. Authors, reviewers and editors of biomechanics research reports are encouraged to improve sample sizes and the resulting statistical power, improve reporting transparency, improve the rigour of statistical analyses used, and increase the acceptance of replication studies to improve the validity of inferences from data in biomechanics research. The application of sports biomechanics research results would also improve if a larger percentage of unbiased effects and their uncertainty were reported in the literature.

Rank score and permutation testing alternatives for regression quantile estimates

USGS Publications Warehouse

Cade, B.S.; Richards, J.D.; Mielke, P.W.

2006-01-01

Performance of quantile rank score tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1) were evaluated by simulation for models with p = 2 and 6 predictors, moderate collinearity among predictors, homogeneous and hetero-geneous errors, small to moderate samples (n = 20–300), and central to upper quantiles (0.50–0.99). Test statistics evaluated were the conventional quantile rank score T statistic distributed as χ2 random variable with q degrees of freedom (where q parameters are constrained by H 0:) and an F statistic with its sampling distribution approximated by permutation. The permutation F-test maintained better Type I errors than the T-test for homogeneous error models with smaller n and more extreme quantiles τ. An F distributional approximation of the F statistic provided some improvements in Type I errors over the T-test for models with > 2 parameters, smaller n, and more extreme quantiles but not as much improvement as the permutation approximation. Both rank score tests required weighting to maintain correct Type I errors when heterogeneity under the alternative model increased to 5 standard deviations across the domain of X. A double permutation procedure was developed to provide valid Type I errors for the permutation F-test when null models were forced through the origin. Power was similar for conditions where both T- and F-tests maintained correct Type I errors but the F-test provided some power at smaller n and extreme quantiles when the T-test had no power because of excessively conservative Type I errors. When the double permutation scheme was required for the permutation F-test to maintain valid Type I errors, power was less than for the T-test with decreasing sample size and increasing quantiles. Confidence intervals on parameters and tolerance intervals for future predictions were constructed based on test inversion for an example application relating trout densities to stream channel width:depth.

The vertical pattern of microwave radiation around BTS (Base Transceiver Station) antennae in Hashtgerd township.

PubMed

Nasseri, Simin; Monazzam, Mohammadreza; Beheshti, Meisam; Zare, Sajad; Mahvi, Amirhosein

2013-12-20

New environmental pollutants interfere with the environment and human life along with technology development. One of these pollutants is electromagnetic field. This study determines the vertical microwave radiation pattern of different types of Base Transceiver Station (BTS) antennae in the Hashtgerd city as the capital of Savojbolagh County, Alborz Province of Iran. The basic data including the geographical location of the BTS antennae in the city, brand, operator type, installation and its height was collected from radio communication office, and then the measurements were carried out according to IEEE STD 95. 1 by the SPECTRAN 4060. The statistical analyses were carried out by SPSS16 using Kolmogorov Smirnov test and multiple regression method. Results indicated that in both operators of Irancell and Hamrah-e-Aval (First Operator), the power density rose with an increase in measurement height or decrease in the vertical distance of broadcaster antenna. With mix model test, a significant statistical relationship was observed between measurement height and the average power density in both types of the operators. With increasing measuring height, power density increased in both operators. The study showed installing antennae in a crowded area needs more care because of higher radiation emission. More rigid surfaces and mobile users are two important factors in crowded area that can increase wave density and hence raise public microwave exposure.

The vertical pattern of microwave radiation around BTS (Base Transceiver Station) antennae in Hashtgerd township

PubMed Central

2013-01-01

New environmental pollutants interfere with the environment and human life along with technology development. One of these pollutants is electromagnetic field. This study determines the vertical microwave radiation pattern of different types of Base Transceiver Station (BTS) antennae in the Hashtgerd city as the capital of Savojbolagh County, Alborz Province of Iran. The basic data including the geographical location of the BTS antennae in the city, brand, operator type, installation and its height was collected from radio communication office, and then the measurements were carried out according to IEEE STD 95. 1 by the SPECTRAN 4060. The statistical analyses were carried out by SPSS16 using Kolmogorov Smirnov test and multiple regression method. Results indicated that in both operators of Irancell and Hamrah-e-Aval (First Operator), the power density rose with an increase in measurement height or decrease in the vertical distance of broadcaster antenna. With mix model test, a significant statistical relationship was observed between measurement height and the average power density in both types of the operators. With increasing measuring height, power density increased in both operators. The study showed installing antennae in a crowded area needs more care because of higher radiation emission. More rigid surfaces and mobile users are two important factors in crowded area that can increase wave density and hence raise public microwave exposure. PMID:24359870

Load- and skill-related changes in segmental contributions to a weightlifting movement.

PubMed

Enoka, R M

1988-04-01

An exemplary short duration, high-power, weightlifting event was examined to determine whether the ability to lift heavier loads and whether variations in the level of skill were accompanied by quantitative changes in selected aspects of lower extremity joint power-time histories. Six experienced weightlifters, three skilled and three less skilled, performed the double-knee-bend execution of the pull in Olympic weightlifting, a movement which lasted almost 1 s. Analysis-of-variance statistics were performed on selected peak and average values of power generated by the three skilled subjects as they lifted three loads (69, 77, and 86% of their competition maximum). The results indicated that the skilled subjects lifted heavier loads by increasing the average power, but not the peak power, about the knee and ankle joints. In addition, the changes with load were more subtle than a mere quantitative scaling and also seemed to be associated with a skill element in the form of variation in the duration of the phases of power production and absorption. Similarly, statistical differences (independent t-test) due to skill did not involve changes in the magnitude of power but rather the temporal organization of the movement. Thus, the ability to successfully execute the double-knee-bend movement depends on an athlete's ability to both generate a sufficient magnitude of joint power and to organize the phases of power production and absorption into an appropriate temporal sequence.

MetaGenyo: a web tool for meta-analysis of genetic association studies.

PubMed

Martorell-Marugan, Jordi; Toro-Dominguez, Daniel; Alarcon-Riquelme, Marta E; Carmona-Saez, Pedro

2017-12-16

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise. We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results. MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

Global Active Stretching (SGA®) Practice for Judo Practitioners’ Physical Performance Enhancement

PubMed Central

ALMEIDA, HELENO; DE SOUZA, RAPHAEL F.; AIDAR, FELIPE J.; DA SILVA, ALISSON G.; REGI, RICARDO P.; BASTOS, AFRÂNIO A.

2018-01-01

In order to analyze the Global Active Stretching (SGA®) practice on the physical performance enhancement in judo-practitioner competitors, 12 male athletes from Judo Federation of Sergipe (Federação Sergipana de Judô), were divided into two groups: Experimental Group (EG) and Control Group (CG). For 10 weeks, the EG practiced SGA® self-postures and the CG practiced assorted calisthenic exercises. All of them were submitted to a variety of tests (before and after): handgrip strength, flexibility, upper limbs’ muscle power, isometric pull-up force, lower limbs’ muscle power (squat-jump – SJ and countermovement jump – CMJ) and Tokui Waza test. Due to the small number of people in the sample, the data were considered non-parametric and then we applied the Wilcoxon test using the software R version 3.3.2 (R Development Core Team, Austria). The effect size was calculated and considered statistically significant the values p ≤ 0.05. Concerning the results, the EG statistical differences were highlighted in flexibility, upper limbs’ muscle power and lower limbs’ muscle power (CMJ), with a gain of 3.00 ± (1.09) cm, 0,42 ± (0,51) m and 2.49 ± (0.63) cm, respectively. The CG only presented statistical difference in the lower limbs’ test (CMJ), with a gain of 0,55 ± 2,28 cm. Thus, the main results pointed out statistical differences before and after in the EG in the flexibility, upper limbs and lower limbs’ muscle power (CMJ), with a gain of 3.00 ± 1.09 cm, 0.42 ± 0.51 m 2.49 ± 0.63 cm, respectively. On the other hand, the CG presented a statistical difference only the lower limbs’ CMJ test, with a gain of 0.55 ± 2.28 cm. The regular 10-week practice of SGA® self-postures increased judoka practitioners’ posterior chain flexibility and vertical jumping (CMJ) performance. PMID:29795746

The Importance of Teaching Power in Statistical Hypothesis Testing

ERIC Educational Resources Information Center

Olinsky, Alan; Schumacher, Phyllis; Quinn, John

2012-01-01

In this paper, we discuss the importance of teaching power considerations in statistical hypothesis testing. Statistical power analysis determines the ability of a study to detect a meaningful effect size, where the effect size is the difference between the hypothesized value of the population parameter under the null hypothesis and the true value…

The wave-tide-river delta classification revisited: Introducing the effects of Humans on delta equilibriu

NASA Astrophysics Data System (ADS)

Besset, M.; Anthony, E.; Sabatier, F.

2016-12-01

The influence of physical processes on river deltas has long been identified, mainly on the basis of delta morphology. A cuspate delta is considered as wave-dominated, a delta with finger-like extensions is characterized as river-dominated, and a delta with estuarine re-entrants is considered tide-dominated (Galloway, 1975). The need for a more quantitative classification is increasingly recognized, and is achievable through quantified combinations, a good example being Syvitski and Saito (2007) wherein the joint influence of marine power - wave and tides - is compared to that of river influence. This need is further justified as deltas become more and more vulnerable. Going forward from the Syvitski and Saito (2007) approach, we confront, from a large database on 60 river deltas, the maximum potential power of waves and the tidal range (both representing marine power), and the specific stream power and river sediment supply reflecting an increasingly human-impacted river influence. The results show that 45 deltas (75%) have levels of marine power that are significantly higher than those of specific stream power. Five deltas have sufficient stream power to counterbalance marine power but a present sediment supply inadequate for them to be statistically considered as river-dominated. Six others have a sufficient sediment supply but a specific stream power that is not high enough for them to be statistically river-dominated. A major manifestation of the interplay of these parameters is accelerated delta erosion worldwide, shifting the balance towards marine power domination. Deltas currently eroding are mainly influenced by marine power (93%), and small deltas (< 300 km2 of deltaic protuberance) are the most vulnerable (82%). These high levels of erosion domination, compounded by accelerated subsidence, are related to human-induced sediment supply depletion and changes in water discharge in the face of the sediment-dispersive capacity of waves and currents.

New powerful statistics for alignment-free sequence comparison under a pattern transfer model.

PubMed

Liu, Xuemei; Wan, Lin; Li, Jing; Reinert, Gesine; Waterman, Michael S; Sun, Fengzhu

2011-09-07

Alignment-free sequence comparison is widely used for comparing gene regulatory regions and for identifying horizontally transferred genes. Recent studies on the power of a widely used alignment-free comparison statistic D2 and its variants D*2 and D(s)2 showed that their power approximates a limit smaller than 1 as the sequence length tends to infinity under a pattern transfer model. We develop new alignment-free statistics based on D2, D*2 and D(s)2 by comparing local sequence pairs and then summing over all the local sequence pairs of certain length. We show that the new statistics are much more powerful than the corresponding statistics and the power tends to 1 as the sequence length tends to infinity under the pattern transfer model. Copyright © 2011 Elsevier Ltd. All rights reserved.

New Powerful Statistics for Alignment-free Sequence Comparison Under a Pattern Transfer Model

PubMed Central

Liu, Xuemei; Wan, Lin; Li, Jing; Reinert, Gesine; Waterman, Michael S.; Sun, Fengzhu

2011-01-01

Alignment-free sequence comparison is widely used for comparing gene regulatory regions and for identifying horizontally transferred genes. Recent studies on the power of a widely used alignment-free comparison statistic D2 and its variants D2∗ and D2s showed that their power approximates a limit smaller than 1 as the sequence length tends to infinity under a pattern transfer model. We develop new alignment-free statistics based on D2, D2∗ and D2s by comparing local sequence pairs and then summing over all the local sequence pairs of certain length. We show that the new statistics are much more powerful than the corresponding statistics and the power tends to 1 as the sequence length tends to infinity under the pattern transfer model. PMID:21723298

Optimization of transversal phacoemulsification settings in peristaltic mode using a new transversal ultrasound machine.

PubMed

Wright, Dannen D; Wright, Alex J; Boulter, Tyler D; Bernhisel, Ashlie A; Stagg, Brian C; Zaugg, Brian; Pettey, Jeff H; Ha, Larry; Ta, Brian T; Olson, Randall J

2017-09-01

To determine the optimum bottle height, vacuum, aspiration rate, and power settings in the peristaltic mode of the Whitestar Signature Pro machine with Ellips FX tip action (transversal). John A. Moran Eye Center Laboratories, University of Utah, Salt Lake City, Utah, USA. Experimental study. Porcine lens nuclei were hardened with formalin and cut into 2.0 mm cubes. Lens cubes were emulsified using transversal and fragment removal time (efficiency), and fragment bounces off the tip (chatter) were measured to determine optimum aspiration rate, bottle height, vacuum, and power settings in the peristaltic mode. Efficiency increased in a linear fashion with increasing bottle height and vacuum. The most efficient aspiration rate was 50 mL/min, with 60 mL/min statistically similar. Increasing power increased efficiency up to 90% with increased chatter at 100%. The most efficient values for the settings tested were bottle height at 100 cm, vacuum at 600 mm Hg, aspiration rate of 50 or 60 mL/min, and power at 90%. Copyright © 2017 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

ACTN3 genotypes of Rugby Union players: distribution, power output and body composition.

PubMed

Bell, W; Colley, J P; Evans, W D; Darlington, S E; Cooper, S-M

2012-01-01

To identify the distribution and explore the relationship between ACTN3 genotypes and power and body composition phenotypes. Case control and association studies were employed using a homogeneous group of players (n = 102) and a control group (n = 110). Power-related phenotypes were measured using the counter movement jump (CMJ) and body composition phenotypes by dual-energy X-ray absorptiometry (DXA). Statistics used were Pearson's chi-square, ANCOVA, coefficients of correlation and independent t-tests. Genotyping was carried out using polymerase chain reaction followed by enzymatic Ddel digestion. Genotype proportions of players were compared with controls (p = 0.07). No significant genotype differences occurred between forwards or backs (p = 0.822) or within-forwards (p = 0.882) or within-backs (p = 0.07). Relative force and velocity were significantly larger in backs, power significantly greater in forwards; in body composition, all phenotypes were significantly greater in forwards than backs. Correlations between phenotypes were greater for the RX genotype (p = 0.05-0.01). Relationships between ACTN3 genotypes and power or body composition-related phenotypes were not significant. As fat increased, power-related phenotypes decreased. As body composition increased, power-related phenotypes increased.

Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

USGS Publications Warehouse

Dzul, Maria C.; Dixon, Philip M.; Quist, Michael C.; Dinsomore, Stephen J.; Bower, Michael R.; Wilson, Kevin P.; Gaines, D. Bailey

2013-01-01

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

The statistical big bang of 1911: ideology, technological innovation and the production of medical statistics.

PubMed

Higgs, W

1996-12-01

This paper examines the relationship between intellectual debate, technologies for analysing information, and the production of statistics in the General Register Office (GRO) in London in the early twentieth century. It argues that controversy between eugenicists and public health officials respecting the cause and effect of class-specific variations in fertility led to the introduction of questions in the 1911 census on marital fertility. The increasing complexity of the census necessitated a shift from manual to mechanised forms of data processing within the GRO. The subsequent increase in processing power allowed the GRO to make important changes to the medical and demographic statistics it published in the annual Reports of the Registrar General. These included substituting administrative sanitary districts for registration districts as units of analysis, consistently transferring deaths in institutions back to place of residence, and abstracting deaths according to the International List of Causes of Death.

Use of statistical and neural net approaches in predicting toxicity of chemicals.

PubMed

Basak, S C; Grunwald, G D; Gute, B D; Balasubramanian, K; Opitz, D

2000-01-01

Hierarchical quantitative structure-activity relationships (H-QSAR) have been developed as a new approach in constructing models for estimating physicochemical, biomedicinal, and toxicological properties of interest. This approach uses increasingly more complex molecular descriptors in a graduated approach to model building. In this study, statistical and neural network methods have been applied to the development of H-QSAR models for estimating the acute aquatic toxicity (LC50) of 69 benzene derivatives to Pimephales promelas (fathead minnow). Topostructural, topochemical, geometrical, and quantum chemical indices were used as the four levels of the hierarchical method. It is clear from both the statistical and neural network models that topostructural indices alone cannot adequately model this set of congeneric chemicals. Not surprisingly, topochemical indices greatly increase the predictive power of both statistical and neural network models. Quantum chemical indices also add significantly to the modeling of this set of acute aquatic toxicity data.

Approximate Bayesian Computation Using Markov Chain Monte Carlo Simulation: Theory, Concepts, and Applications

NASA Astrophysics Data System (ADS)

Sadegh, M.; Vrugt, J. A.

2013-12-01

The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex hydrologic models that simulate soil moisture flow, groundwater recharge, surface runoff, root water uptake, and river discharge at increasingly finer spatial and temporal scales. Reconciling these system models with field and remote sensing data is a difficult task, particularly because average measures of model/data similarity inherently lack the power to provide a meaningful comparative evaluation of the consistency in model form and function. The very construction of the likelihood function - as a summary variable of the (usually averaged) properties of the error residuals - dilutes and mixes the available information into an index having little remaining correspondence to specific behaviors of the system (Gupta et al., 2008). The quest for a more powerful method for model evaluation has inspired Vrugt and Sadegh [2013] to introduce "likelihood-free" inference as vehicle for diagnostic model evaluation. This class of methods is also referred to as Approximate Bayesian Computation (ABC) and relaxes the need for an explicit likelihood function in favor of one or multiple different summary statistics rooted in hydrologic theory that together have a much stronger and compelling diagnostic power than some aggregated measure of the size of the error residuals. Here, we will introduce an efficient ABC sampling method that is orders of magnitude faster in exploring the posterior parameter distribution than commonly used rejection and Population Monte Carlo (PMC) samplers. Our methodology uses Markov Chain Monte Carlo simulation with DREAM, and takes advantage of a simple computational trick to resolve discontinuity problems with the application of set-theoretic summary statistics. We will also demonstrate a set of summary statistics that are rather insensitive to errors in the forcing data. This enhances prospects of detecting model structural deficiencies.

Association analysis of multiple traits by an approach of combining P values.

PubMed

Chen, Lili; Wang, Yong; Zhou, Yajing

2018-03-01

Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…

Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis.

PubMed

Wong, Wing-Cheong; Ng, Hong-Kiat; Tantoso, Erwin; Soong, Richie; Eisenhaber, Frank

2018-02-12

Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip's law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically under the conditions of infinite observations, real world observations are finite where the finite-size effects will set in to force a power-law distribution into an exponential decay and consequently, manifests as a curvature (i.e., varying exponent values) in a log-log plot. If transcript abundance is truly power-law distributed, the varying exponent signifies changing mathematical moments (e.g., mean, variance) and creates heteroskedasticity which compromises statistical rigor in analysis. The impact of this deviation from the asymptotic power-law on sequencing count data has never truly been examined and quantified. The anecdotal description of transcript abundance being almost Zipf's law-like distributed can be conceptualized as the imperfect mathematical rendition of the Pareto power-law distribution when subjected to the finite-size effects in the real world; This is regardless of the advancement in sequencing technology since sampling is finite in practice. Our conceptualization agrees well with our empirical analysis of two modern day NGS (Next-generation sequencing) datasets: an in-house generated dilution miRNA study of two gastric cancer cell lines (NUGC3 and AGS) and a publicly available spike-in miRNA data; Firstly, the finite-size effects causes the deviations of sequencing count data from Zipf's law and issues of reproducibility in sequencing experiments. Secondly, it manifests as heteroskedasticity among experimental replicates to bring about statistical woes. Surprisingly, a straightforward power-law correction that restores the distribution distortion to a single exponent value can dramatically reduce data heteroskedasticity to invoke an instant increase in signal-to-noise ratio by 50% and the statistical/detection sensitivity by as high as 30% regardless of the downstream mapping and normalization methods. Most importantly, the power-law correction improves concordance in significant calls among different normalization methods of a data series averagely by 22%. When presented with a higher sequence depth (4 times difference), the improvement in concordance is asymmetrical (32% for the higher sequencing depth instance versus 13% for the lower instance) and demonstrates that the simple power-law correction can increase significant detection with higher sequencing depths. Finally, the correction dramatically enhances the statistical conclusions and eludes the metastasis potential of the NUGC3 cell line against AGS of our dilution analysis. The finite-size effects due to undersampling generally plagues transcript count data with reproducibility issues but can be minimized through a simple power-law correction of the count distribution. This distribution correction has direct implication on the biological interpretation of the study and the rigor of the scientific findings. This article was reviewed by Oliviero Carugo, Thomas Dandekar and Sandor Pongor.

A new u-statistic with superior design sensitivity in matched observational studies.

PubMed

Rosenbaum, Paul R

2011-09-01

In an observational or nonrandomized study of treatment effects, a sensitivity analysis indicates the magnitude of bias from unmeasured covariates that would need to be present to alter the conclusions of a naïve analysis that presumes adjustments for observed covariates suffice to remove all bias. The power of sensitivity analysis is the probability that it will reject a false hypothesis about treatment effects allowing for a departure from random assignment of a specified magnitude; in particular, if this specified magnitude is "no departure" then this is the same as the power of a randomization test in a randomized experiment. A new family of u-statistics is proposed that includes Wilcoxon's signed rank statistic but also includes other statistics with substantially higher power when a sensitivity analysis is performed in an observational study. Wilcoxon's statistic has high power to detect small effects in large randomized experiments-that is, it often has good Pitman efficiency-but small effects are invariably sensitive to small unobserved biases. Members of this family of u-statistics that emphasize medium to large effects can have substantially higher power in a sensitivity analysis. For example, in one situation with 250 pair differences that are Normal with expectation 1/2 and variance 1, the power of a sensitivity analysis that uses Wilcoxon's statistic is 0.08 while the power of another member of the family of u-statistics is 0.66. The topic is examined by performing a sensitivity analysis in three observational studies, using an asymptotic measure called the design sensitivity, and by simulating power in finite samples. The three examples are drawn from epidemiology, clinical medicine, and genetic toxicology. © 2010, The International Biometric Society.

Distribution of the Crystalline Lens Power In Vivo as a Function of Age.

PubMed

Jongenelen, Sien; Rozema, Jos J; Tassignon, Marie-José

2015-11-01

To observe the age-related changes in crystalline lens power in vivo in a noncataractous European population. Data were obtained though Project Gullstrand, a multicenter population study with data from healthy phakic subjects between 20 and 85 years old. One randomly selected eye per subject was used. Lens power was calculated using the modified Bennett-Rabbetts method, using biometry data from an autorefractometer, Oculus Pentacam, and Haag-Streit Lenstar. The study included 1069 Caucasian subjects (490 men, 579 women) with a mean age of 44.2 ± 14.2 years and mean lens power of 24.96 ± 2.18 diopters (D). The average lens power showed a statistically significant decrease as a function of age, with a steeper rate of decrease after the age of 55. The highest crystalline lens power was found in emmetropic eyes and eyes with a short axial length. The correlation of lens power with different refractive components was statistically significant for axial length (r = -0.523, P < 0.01) and anterior chamber depth (r = -0.161, P < 0.01), but not for spherical equivalent and corneal power (P > 0.05). This in vivo study showed a monotonous decrease in crystalline lens power with age, with a steeper decline after 55 years. While this finding fundamentally concurs with previous in vivo studies, it is at odds with studies performed on donor eyes that reported lens power increases after the age of 55.

Assessment and Implication of Prognostic Imbalance in Randomized Controlled Trials with a Binary Outcome – A Simulation Study

PubMed Central

Chu, Rong; Walter, Stephen D.; Guyatt, Gordon; Devereaux, P. J.; Walsh, Michael; Thorlund, Kristian; Thabane, Lehana

2012-01-01

Background Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives. Methods We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power. Results For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PF≥5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative risk = 5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RR = 2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance ≥5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF. Conclusions The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed. PMID:22629322

High-Density Signal Interface Electromagnetic Radiation Prediction for Electromagnetic Compatibility Evaluation.

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

Halligan, Matthew

Radiated power calculation approaches for practical scenarios of incomplete high- density interface characterization information and incomplete incident power information are presented. The suggested approaches build upon a method that characterizes power losses through the definition of power loss constant matrices. Potential radiated power estimates include using total power loss information, partial radiated power loss information, worst case analysis, and statistical bounding analysis. A method is also proposed to calculate radiated power when incident power information is not fully known for non-periodic signals at the interface. Incident data signals are modeled from a two-state Markov chain where bit state probabilities aremore » derived. The total spectrum for windowed signals is postulated as the superposition of spectra from individual pulses in a data sequence. Statistical bounding methods are proposed as a basis for the radiated power calculation due to the statistical calculation complexity to find a radiated power probability density function.« less

Soil carbon inventories under a bioenergy crop (switchgrass): Measurement limitations

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

Garten, C.T. Jr.; Wullschleger, S.D.

Approximately 5 yr after planting, coarse root carbon (C) and soil organic C (SOC) inventories were compared under different types of plant cover at four switchgrass (Panicum virgatum L.) production field trials in the southeastern USA. There was significantly more coarse root C under switchgrass (Alamo variety) and forest cover than tall fescue (Festuca arundinacea Schreb.), corn (Zea mays L.), or native pastures of mixed grasses. Inventories of SOC under switchgrass were not significantly greater than SOC inventories under other plant covers. At some locations the statistical power associated with ANOVA of SOC inventories was low, which raised questions aboutmore » whether differences in SOC could be detected statistically. A minimum detectable difference (MDD) for SOC inventories was calculated. The MDD is the smallest detectable difference between treatment means once the variation, significance level, statistical power, and sample size are specified. The analysis indicated that a difference of {approx}50 mg SOC/cm{sup 2} or 5 Mg SOC/ha, which is {approx}10 to 15% of existing SOC, could be detected with reasonable sample sizes and good statistical power. The smallest difference in SOC inventories that can be detected, and only with exceedingly large sample sizes, is {approx}2 to 3%. These measurement limitations have implications for monitoring and verification of proposals to ameliorate increasing global atmospheric CO{sub 2} concentrations by sequestering C in soils.« less

An analysis of quantum coherent solar photovoltaic cells

NASA Astrophysics Data System (ADS)

Kirk, A. P.

2012-02-01

A new hypothesis (Scully et al., Proc. Natl. Acad. Sci. USA 108 (2011) 15097) suggests that it is possible to break the statistical physics-based detailed balance-limiting power conversion efficiency and increase the power output of a solar photovoltaic cell by using “noise-induced quantum coherence” to increase the current. The fundamental errors of this hypothesis are explained here. As part of this analysis, we show that the maximum photogenerated current density for a practical solar cell is a function of the incident spectrum, sunlight concentration factor, and solar cell energy bandgap and thus the presence of quantum coherence is irrelevant as it is unable to lead to increased current output from a solar cell.

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

PubMed

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

2014-12-01

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

Increasing power-law range in avalanche amplitude and energy distributions

NASA Astrophysics Data System (ADS)

Navas-Portella, Víctor; Serra, Isabel; Corral, Álvaro; Vives, Eduard

2018-02-01

Power-law-type probability density functions spanning several orders of magnitude are found for different avalanche properties. We propose a methodology to overcome empirical constraints that limit the range of truncated power-law distributions. By considering catalogs of events that cover different observation windows, the maximum likelihood estimation of a global power-law exponent is computed. This methodology is applied to amplitude and energy distributions of acoustic emission avalanches in failure-under-compression experiments of a nanoporous silica glass, finding in some cases global exponents in an unprecedented broad range: 4.5 decades for amplitudes and 9.5 decades for energies. In the latter case, however, strict statistical analysis suggests experimental limitations might alter the power-law behavior.

Increasing power-law range in avalanche amplitude and energy distributions.

PubMed

Navas-Portella, Víctor; Serra, Isabel; Corral, Álvaro; Vives, Eduard

2018-02-01

Power-law-type probability density functions spanning several orders of magnitude are found for different avalanche properties. We propose a methodology to overcome empirical constraints that limit the range of truncated power-law distributions. By considering catalogs of events that cover different observation windows, the maximum likelihood estimation of a global power-law exponent is computed. This methodology is applied to amplitude and energy distributions of acoustic emission avalanches in failure-under-compression experiments of a nanoporous silica glass, finding in some cases global exponents in an unprecedented broad range: 4.5 decades for amplitudes and 9.5 decades for energies. In the latter case, however, strict statistical analysis suggests experimental limitations might alter the power-law behavior.

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

PubMed

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

2011-10-01

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

A Modified Kolmogorov-Smirnov, Anderson-Darling, and Cramer-Von Mises Test for the Cauchy Distribution with Unknown Location and Scale Parameters.

DTIC Science & Technology

1985-12-01

statistics, each of the a levels fall. The mirror image of this is to work with the percentiles, or the I - a levels . These then become the minimum...To be valid, the power would have to be close to the *-levels, and that Is the case. The powers are not exactly equal to the a - levels , but that is a...Information available increases with sample size. When a - levels are analyzed, for a = .0 1, the only reasonable power Is 33 L 4 against the

Relationship between relative net vertical impulse and jump height in jump squats performed to various squat depths and with various loads.

PubMed

McBride, Jeffrey M; Kirby, Tyler J; Haines, Tracie L; Skinner, Jared

2010-12-01

The purpose of the current investigation was to determine the relationship between relative net vertical impulse (net vertical impulse (VI)) and jump height in the jump squat (JS) going to different squat depths and utilizing various loads. Ten males with two years of jumping experience participated in this investigation (Age: 21.8 ± 1.9 y; Height: 176.9 ± 5.2 cm; Body Mass: 79.0 ± 7.1 kg, 1RM: 131.8 ± 29.5 kg, 1RM/BM: 1.66 ± 0.27). Subjects performed a series of static jumps (SJS) and countermovement jumps (CMJJS) with various loads (Body Mass, 20% of 1RM, 40% of 1RM) in a randomized fashion to a depth of 0.15, 0.30, 0.45, 0.60, and 0.75 m and a self-selected depth. During the concentric phase of each JS, peak force (PF), peak power (PP), jump height (JH) and relative VI were recorded and analyzed. Increasing squat depth corresponded to a decrease in PF and an increase in JH, relative VI for both SJS and CMJJS during all loads. Across all squat depths and loading conditions relative VI was statistically significantly correlated to JH in the SJS (r = .8956, P < .0001, power = 1.000) and CMJJS (r = .6007, P < .0001, power = 1.000). Across all squat depths and loading conditions PF was statistically nonsignificantly correlated to JH in the SJS (r = -0.1010, P = .2095, power = 0.2401) and CMJJS (r = -0.0594, P = .4527, power = 0.1131). Across all squat depths and loading conditions peak power (PP) was significantly correlated with JH during both the SJS (r = .6605, P < .0001, power = 1.000) and the CMJJS (r = .6631, P < .0001, power = 1.000). PP was statistically significantly higher at BM in comparison with 20% of 1RM and 40% of 1RM in the SJS and CMJJS across all squat depths. Results indicate that relative VI and PP can be used to predict JS performance, regardless of squat depth and loading condition. However, relative VI may be the best predictor of JS performance with PF being the worst predictor of JS performance.

Enhanced Single-Photon Emission from Carbon-Nanotube Dopant States Coupled to Silicon Microcavities.

PubMed

Ishii, Akihiro; He, Xiaowei; Hartmann, Nicolai F; Machiya, Hidenori; Htoon, Han; Doorn, Stephen K; Kato, Yuichiro K

2018-06-13

Single-walled carbon nanotubes are a promising material as quantum light sources at room temperature and as nanoscale light sources for integrated photonic circuits on silicon. Here, we show that the integration of dopant states in carbon nanotubes and silicon microcavities can provide bright and high-purity single-photon emitters on a silicon photonics platform at room temperature. We perform photoluminescence spectroscopy and observe the enhancement of emission from the dopant states by a factor of ∼50, and cavity-enhanced radiative decay is confirmed using time-resolved measurements, in which a ∼30% decrease of emission lifetime is observed. The statistics of photons emitted from the cavity-coupled dopant states are investigated by photon-correlation measurements, and high-purity single photon generation is observed. The excitation power dependence of photon emission statistics shows that the degree of photon antibunching can be kept high even when the excitation power increases, while the single-photon emission rate can be increased to ∼1.7 × 10 7 Hz.

Enhanced Single-Photon Emission from Carbon-Nanotube Dopant States Coupled to Silicon Microcavities

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

Ishii, Akihiro; He, Xiaowei; Hartmann, Nicolai F.

Single-walled carbon nanotubes are a promising material as quantum light sources at room temperature and as nanoscale light sources for integrated photonic circuits on silicon. Here, we show that the integration of dopant states in carbon nanotubes and silicon microcavities can provide bright and high-purity single-photon emitters on a silicon photonics platform at room temperature. We perform photoluminescence spectroscopy and observe the enhancement of emission from the dopant states by a factor of ~50, and cavity-enhanced radiative decay is confirmed using time-resolved measurements, in which a ~30% decrease of emission lifetime is observed. The statistics of photons emitted from themore » cavity-coupled dopant states are investigated by photon-correlation measurements, and high-purity single photon generation is observed. The excitation power dependence of photon emission statistics shows that the degree of photon antibunching can be kept high even when the excitation power increases, while the single-photon emission rate can be increased to ~1.7 × 10 7 Hz.« less

Enhanced Single-Photon Emission from Carbon-Nanotube Dopant States Coupled to Silicon Microcavities

DOE PAGES

Ishii, Akihiro; He, Xiaowei; Hartmann, Nicolai F.; ...

2018-05-21

Single-walled carbon nanotubes are a promising material as quantum light sources at room temperature and as nanoscale light sources for integrated photonic circuits on silicon. Here, we show that the integration of dopant states in carbon nanotubes and silicon microcavities can provide bright and high-purity single-photon emitters on a silicon photonics platform at room temperature. We perform photoluminescence spectroscopy and observe the enhancement of emission from the dopant states by a factor of ~50, and cavity-enhanced radiative decay is confirmed using time-resolved measurements, in which a ~30% decrease of emission lifetime is observed. The statistics of photons emitted from themore » cavity-coupled dopant states are investigated by photon-correlation measurements, and high-purity single photon generation is observed. The excitation power dependence of photon emission statistics shows that the degree of photon antibunching can be kept high even when the excitation power increases, while the single-photon emission rate can be increased to ~1.7 × 10 7 Hz.« less

Effects of Muslims praying (Salat) on EEG gamma activity.

PubMed

Doufesh, Hazem; Ibrahim, Fatimah; Safari, Mohammad

2016-08-01

This study investigates the difference of mean gamma EEG power between actual and mimic Salat practices in twenty healthy Muslim subjects. In the actual Salat practice, the participants were asked to recite and performing the physical steps in all four stages of Salat; whereas in the mimic Salat practice, they were instructed to perform only the physical steps without recitation. The gamma power during actual Salat was statistically higher than during mimic Salat in the frontal and parietal regions in all stages. In the actual Salat practice, the left hemisphere exhibited significantly higher mean gamma power in all cerebral regions and all stages, except the central-parietal region in the sitting position, and the frontal area in the bowing position. Increased gamma power during Salat, possibly related to an increase in cognitive and attentional processing, supports the concept of Salat as a focus attention meditation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulation-based power calculations for planning a two-stage individual participant data meta-analysis.

PubMed

Ensor, Joie; Burke, Danielle L; Snell, Kym I E; Hemming, Karla; Riley, Richard D

2018-05-18

Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions. The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has < 60% power to detect a reduction of 1 kg weight gain for a 10-unit increase in BMI. Additional IPD from ten other published trials (containing 1761 patients) would improve power to over 80%, but only if a fixed-effect meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials. Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely.

Ozone monitoring instrument observations of interannual increases in SO2 emissions from Indian coal-fired power plants during 2005-2012.

PubMed

Lu, Zifeng; Streets, David G; de Foy, Benjamin; Krotkov, Nickolay A

2013-12-17

Due to the rapid growth of electricity demand and the absence of regulations, sulfur dioxide (SO2) emissions from coal-fired power plants in India have increased notably in the past decade. In this study, we present the first interannual comparison of SO2 emissions and the satellite SO2 observations from the Ozone Monitoring Instrument (OMI) for Indian coal-fired power plants during the OMI era of 2005-2012. A detailed unit-based inventory is developed for the Indian coal-fired power sector, and results show that its SO2 emissions increased dramatically by 71% during 2005-2012. Using the oversampling technique, yearly high-resolution OMI maps for the whole domain of India are created, and they reveal a continuous increase in SO2 columns over India. Power plant regions with annual SO2 emissions greater than 50 Gg year(-1) produce statistically significant OMI signals, and a high correlation (R = 0.93) is found between SO2 emissions and OMI-observed SO2 burdens. Contrary to the decreasing trend of national mean SO2 concentrations reported by the Indian Government, both the total OMI-observed SO2 and annual average SO2 concentrations in coal-fired power plant regions increased by >60% during 2005-2012, implying the air quality monitoring network needs to be optimized to reflect the true SO2 situation in India.

Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

PubMed

Westfall, Jacob; Kenny, David A; Judd, Charles M

2014-10-01

Researchers designing experiments in which a sample of participants responds to a sample of stimuli are faced with difficult questions about optimal study design. The conventional procedures of statistical power analysis fail to provide appropriate answers to these questions because they are based on statistical models in which stimuli are not assumed to be a source of random variation in the data, models that are inappropriate for experiments involving crossed random factors of participants and stimuli. In this article, we present new methods of power analysis for designs with crossed random factors, and we give detailed, practical guidance to psychology researchers planning experiments in which a sample of participants responds to a sample of stimuli. We extensively examine 5 commonly used experimental designs, describe how to estimate statistical power in each, and provide power analysis results based on a reasonable set of default parameter values. We then develop general conclusions and formulate rules of thumb concerning the optimal design of experiments in which a sample of participants responds to a sample of stimuli. We show that in crossed designs, statistical power typically does not approach unity as the number of participants goes to infinity but instead approaches a maximum attainable power value that is possibly small, depending on the stimulus sample. We also consider the statistical merits of designs involving multiple stimulus blocks. Finally, we provide a simple and flexible Web-based power application to aid researchers in planning studies with samples of stimuli.

Monte Carlo based statistical power analysis for mediation models: methods and software.

PubMed

Zhang, Zhiyong

2014-12-01

The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

Population morbidity in the Zaporizhzhia Nuclear Power Plant observation zone as an integral part of public health.

PubMed

Khomenko, I M; Zakladna, N V; Orlova, N M

2017-12-01

To evaluate the health status of adult population living in the Ukrainian nuclear power industry obser vation zone on the example of Zaporizhzhia Nuclear Power Plant. System review, analytic, sociological survey and statistical methods. There was established an increase in the incidence of digestive diseases among adult population in Nikopol of Dnipropetrovsk region, which is included in the Zaporizhzhia NPP observation zone. The highest increase was observed in the incidence of peptic ulcer, gastritis and duodenitis, cholecystitis and cholangitis by 340 %, 305 % and 83 %, respectively. In connection with the residence in industrially developed region and NPP life extension in Ukraine, the possible influence of harmful factors on health status of the population of observation zones, an increase in the incidence of digestive diseases among adult population, there is required continuous monitoring and detailed study of public health. I. M. Khomenko, N. V. Zakladna, N. M. Orlova.

The predictive power of Japanese candlestick charting in Chinese stock market

NASA Astrophysics Data System (ADS)

Chen, Shi; Bao, Si; Zhou, Yu

2016-09-01

This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

Quantum fluctuation theorems and power measurements

NASA Astrophysics Data System (ADS)

Prasanna Venkatesh, B.; Watanabe, Gentaro; Talkner, Peter

2015-07-01

Work in the paradigm of the quantum fluctuation theorems of Crooks and Jarzynski is determined by projective measurements of energy at the beginning and end of the force protocol. In analogy to classical systems, we consider an alternative definition of work given by the integral of the supplied power determined by integrating up the results of repeated measurements of the instantaneous power during the force protocol. We observe that such a definition of work, in spite of taking account of the process dependence, has different possible values and statistics from the work determined by the conventional two energy measurement approach (TEMA). In the limit of many projective measurements of power, the system’s dynamics is frozen in the power measurement basis due to the quantum Zeno effect leading to statistics only trivially dependent on the force protocol. In general the Jarzynski relation is not satisfied except for the case when the instantaneous power operator commutes with the total Hamiltonian at all times. We also consider properties of the joint statistics of power-based definition of work and TEMA work in protocols where both values are determined. This allows us to quantify their correlations. Relaxing the projective measurement condition, weak continuous measurements of power are considered within the stochastic master equation formalism. Even in this scenario the power-based work statistics is in general not able to reproduce qualitative features of the TEMA work statistics.

Statistical Power of Psychological Research: What Have We Gained in 20 Years?

ERIC Educational Resources Information Center

Rossi, Joseph S.

1990-01-01

Calculated power for 6,155 statistical tests in 221 journal articles published in 1982 volumes of "Journal of Abnormal Psychology,""Journal of Consulting and Clinical Psychology," and "Journal of Personality and Social Psychology." Power to detect small, medium, and large effects was .17, .57, and .83, respectively. Concluded that power of…

Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization.

PubMed

Dobson, Ian; Carreras, Benjamin A; Lynch, Vickie E; Newman, David E

2007-06-01

We give an overview of a complex systems approach to large blackouts of electric power transmission systems caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics and dynamics of series of blackouts with approximate global models. Blackout data from several countries suggest that the frequency of large blackouts is governed by a power law. The power law makes the risk of large blackouts consequential and is consistent with the power system being a complex system designed and operated near a critical point. Power system overall loading or stress relative to operating limits is a key factor affecting the risk of cascading failure. Power system blackout models and abstract models of cascading failure show critical points with power law behavior as load is increased. To explain why the power system is operated near these critical points and inspired by concepts from self-organized criticality, we suggest that power system operating margins evolve slowly to near a critical point and confirm this idea using a power system model. The slow evolution of the power system is driven by a steady increase in electric loading, economic pressures to maximize the use of the grid, and the engineering responses to blackouts that upgrade the system. Mitigation of blackout risk should account for dynamical effects in complex self-organized critical systems. For example, some methods of suppressing small blackouts could ultimately increase the risk of large blackouts.

Statistical analysis of plasmatrough exohiss waves on Van Allen Probes

NASA Astrophysics Data System (ADS)

Zhu, H.; Chen, L.

2017-12-01

Plasmatrough exohiss waves have attracted much attention due to their potential important role in dynamics of radiation belt. We investigated three-year Van Allen Probe data and built up an event list of exohiss. The statistical analysis shows exohiss preferentially occurred in dayside at quite time and most wave power focuses on afternoon side of low L region. Consistent with plasmaspheric hiss, the peak frequency is around 200 Hz and wave amplitude decreases with L increasing. Furthermore, the ratios of equatorward Poynting fluxes to poleward Poynting fluxes significantly increase up to 10 times as magnetic latitude increasing up to 20 deg. Those results strong support that the formation of exohiss wave results from hiss leakage, particularly at quite time.

Optimized design and analysis of preclinical intervention studies in vivo

PubMed Central

Laajala, Teemu D.; Jumppanen, Mikael; Huhtaniemi, Riikka; Fey, Vidal; Kaur, Amanpreet; Knuuttila, Matias; Aho, Eija; Oksala, Riikka; Westermarck, Jukka; Mäkelä, Sari; Poutanen, Matti; Aittokallio, Tero

2016-01-01

Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions. PMID:27480578

Optimized design and analysis of preclinical intervention studies in vivo.

PubMed

Laajala, Teemu D; Jumppanen, Mikael; Huhtaniemi, Riikka; Fey, Vidal; Kaur, Amanpreet; Knuuttila, Matias; Aho, Eija; Oksala, Riikka; Westermarck, Jukka; Mäkelä, Sari; Poutanen, Matti; Aittokallio, Tero

2016-08-02

Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions.

Evolutionary dynamics of selfish DNA explains the abundance distribution of genomic subsequences

PubMed Central

Sheinman, Michael; Ramisch, Anna; Massip, Florian; Arndt, Peter F.

2016-01-01

Since the sequencing of large genomes, many statistical features of their sequences have been found. One intriguing feature is that certain subsequences are much more abundant than others. In fact, abundances of subsequences of a given length are distributed with a scale-free power-law tail, resembling properties of human texts, such as Zipf’s law. Despite recent efforts, the understanding of this phenomenon is still lacking. Here we find that selfish DNA elements, such as those belonging to the Alu family of repeats, dominate the power-law tail. Interestingly, for the Alu elements the power-law exponent increases with the length of the considered subsequences. Motivated by these observations, we develop a model of selfish DNA expansion. The predictions of this model qualitatively and quantitatively agree with the empirical observations. This allows us to estimate parameters for the process of selfish DNA spreading in a genome during its evolution. The obtained results shed light on how evolution of selfish DNA elements shapes non-trivial statistical properties of genomes. PMID:27488939

Wind power error estimation in resource assessments.

PubMed

Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel

2015-01-01

Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

Wind Power Error Estimation in Resource Assessments

PubMed Central

Rodríguez, Osvaldo; del Río, Jesús A.; Jaramillo, Oscar A.; Martínez, Manuel

2015-01-01

Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies. PMID:26000444

Investigation of the delay time distribution of high power microwave surface flashover

NASA Astrophysics Data System (ADS)

Foster, J.; Krompholz, H.; Neuber, A.

2011-01-01

Characterizing and modeling the statistics associated with the initiation of gas breakdown has proven to be difficult due to a variety of rather unexplored phenomena involved. Experimental conditions for high power microwave window breakdown for pressures on the order of 100 to several 100 torr are complex: there are little to no naturally occurring free electrons in the breakdown region. The initial electron generation rate, from an external source, for example, is time dependent and so is the charge carrier amplification in the increasing radio frequency (RF) field amplitude with a rise time of 50 ns, which can be on the same order as the breakdown delay time. The probability of reaching a critical electron density within a given time period is composed of the statistical waiting time for the appearance of initiating electrons in the high-field region and the build-up of an avalanche with an inherent statistical distribution of the electron number. High power microwave breakdown and its delay time is of critical importance, since it limits the transmission through necessary windows, especially for high power, high altitude, low pressure applications. The delay time distribution of pulsed high power microwave surface flashover has been examined for nitrogen and argon as test gases for pressures ranging from 60 to 400 torr, with and without external UV illumination. A model has been developed for predicting the discharge delay time for these conditions. The results provide indications that field induced electron generation, other than standard field emission, plays a dominant role, which might be valid for other gas discharge types as well.

Detecting trends in raptor counts: power and type I error rates of various statistical tests

USGS Publications Warehouse

Hatfield, J.S.; Gould, W.R.; Hoover, B.A.; Fuller, M.R.; Lindquist, E.L.

1996-01-01

We conducted simulations that estimated power and type I error rates of statistical tests for detecting trends in raptor population count data collected from a single monitoring site. Results of the simulations were used to help analyze count data of bald eagles (Haliaeetus leucocephalus) from 7 national forests in Michigan, Minnesota, and Wisconsin during 1980-1989. Seven statistical tests were evaluated, including simple linear regression on the log scale and linear regression with a permutation test. Using 1,000 replications each, we simulated n = 10 and n = 50 years of count data and trends ranging from -5 to 5% change/year. We evaluated the tests at 3 critical levels (alpha = 0.01, 0.05, and 0.10) for both upper- and lower-tailed tests. Exponential count data were simulated by adding sampling error with a coefficient of variation of 40% from either a log-normal or autocorrelated log-normal distribution. Not surprisingly, tests performed with 50 years of data were much more powerful than tests with 10 years of data. Positive autocorrelation inflated alpha-levels upward from their nominal levels, making the tests less conservative and more likely to reject the null hypothesis of no trend. Of the tests studied, Cox and Stuart's test and Pollard's test clearly had lower power than the others. Surprisingly, the linear regression t-test, Collins' linear regression permutation test, and the nonparametric Lehmann's and Mann's tests all had similar power in our simulations. Analyses of the count data suggested that bald eagles had increasing trends on at least 2 of the 7 national forests during 1980-1989.

Statistical power analysis of cardiovascular safety pharmacology studies in conscious rats.

PubMed

Bhatt, Siddhartha; Li, Dingzhou; Flynn, Declan; Wisialowski, Todd; Hemkens, Michelle; Steidl-Nichols, Jill

2016-01-01

Cardiovascular (CV) toxicity and related attrition are a major challenge for novel therapeutic entities and identifying CV liability early is critical for effective derisking. CV safety pharmacology studies in rats are a valuable tool for early investigation of CV risk. Thorough understanding of data analysis techniques and statistical power of these studies is currently lacking and is imperative for enabling sound decision-making. Data from 24 crossover and 12 parallel design CV telemetry rat studies were used for statistical power calculations. Average values of telemetry parameters (heart rate, blood pressure, body temperature, and activity) were logged every 60s (from 1h predose to 24h post-dose) and reduced to 15min mean values. These data were subsequently binned into super intervals for statistical analysis. A repeated measure analysis of variance was used for statistical analysis of crossover studies and a repeated measure analysis of covariance was used for parallel studies. Statistical power analysis was performed to generate power curves and establish relationships between detectable CV (blood pressure and heart rate) changes and statistical power. Additionally, data from a crossover CV study with phentolamine at 4, 20 and 100mg/kg are reported as a representative example of data analysis methods. Phentolamine produced a CV profile characteristic of alpha adrenergic receptor antagonism, evidenced by a dose-dependent decrease in blood pressure and reflex tachycardia. Detectable blood pressure changes at 80% statistical power for crossover studies (n=8) were 4-5mmHg. For parallel studies (n=8), detectable changes at 80% power were 6-7mmHg. Detectable heart rate changes for both study designs were 20-22bpm. Based on our results, the conscious rat CV model is a sensitive tool to detect and mitigate CV risk in early safety studies. Furthermore, these results will enable informed selection of appropriate models and study design for early stage CV studies. Copyright © 2016 Elsevier Inc. All rights reserved.

System Study: Auxiliary Feedwater 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the auxiliary feedwater (AFW) system at 69 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the AFW results.

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

PubMed

Golder, W

1999-09-01

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

How Many Studies Do You Need? A Primer on Statistical Power for Meta-Analysis

ERIC Educational Resources Information Center

Valentine, Jeffrey C.; Pigott, Therese D.; Rothstein, Hannah R.

2010-01-01

In this article, the authors outline methods for using fixed and random effects power analysis in the context of meta-analysis. Like statistical power analysis for primary studies, power analysis for meta-analysis can be done either prospectively or retrospectively and requires assumptions about parameters that are unknown. The authors provide…

Global health business: the production and performativity of statistics in Sierra Leone and Germany.

PubMed

Erikson, Susan L

2012-01-01

The global push for health statistics and electronic digital health information systems is about more than tracking health incidence and prevalence. It is also experienced on the ground as means to develop and maintain particular norms of health business, knowledge, and decision- and profit-making that are not innocent. Statistics make possible audit and accountability logics that undergird the management of health at a distance and that are increasingly necessary to the business of health. Health statistics are inextricable from their social milieus, yet as business artifacts they operate as if they are freely formed, objectively originated, and accurate. This article explicates health statistics as cultural forms and shows how they have been produced and performed in two very different countries: Sierra Leone and Germany. In both familiar and surprising ways, this article shows how statistics and their pursuit organize and discipline human behavior, constitute subject positions, and reify existing relations of power.

The 1993 Mississippi river flood: A one hundred or a one thousand year event?

USGS Publications Warehouse

Malamud, B.D.; Turcotte, D.L.; Barton, C.C.

1996-01-01

Power-law (fractal) extreme-value statistics are applicable to many natural phenomena under a wide variety of circumstances. Data from a hydrologic station in Keokuk, Iowa, shows the great flood of the Mississippi River in 1993 has a recurrence interval on the order of 100 years using power-law statistics applied to partial-duration flood series and on the order of 1,000 years using a log-Pearson type 3 (LP3) distribution applied to annual series. The LP3 analysis is the federally adopted probability distribution for flood-frequency estimation of extreme events. We suggest that power-law statistics are preferable to LP3 analysis. As a further test of the power-law approach we consider paleoflood data from the Colorado River. We compare power-law and LP3 extrapolations of historical data with these paleo-floods. The results are remarkably similar to those obtained for the Mississippi River: Recurrence intervals from power-law statistics applied to Lees Ferry discharge data are generally consistent with inferred 100- and 1,000-year paleofloods, whereas LP3 analysis gives recurrence intervals that are orders of magnitude longer. For both the Keokuk and Lees Ferry gauges, the use of an annual series introduces an artificial curvature in log-log space that leads to an underestimate of severe floods. Power-law statistics are predicting much shorter recurrence intervals than the federally adopted LP3 statistics. We suggest that if power-law behavior is applicable, then the likelihood of severe floods is much higher. More conservative dam designs and land-use restrictions Nay be required.

On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis.

PubMed

Martinez-Murcia, Francisco Jesús; Lai, Meng-Chuan; Górriz, Juan Manuel; Ramírez, Javier; Young, Adam M H; Deoni, Sean C L; Ecker, Christine; Lombardo, Michael V; Baron-Cohen, Simon; Murphy, Declan G M; Bullmore, Edward T; Suckling, John

2017-03-01

Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208-1223, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

Intraclass Correlation Values for Planning Group-Randomized Trials in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.

2007-01-01

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate…

Estimating Statistical Power When Making Adjustments for Multiple Tests

ERIC Educational Resources Information Center

Porter, Kristin E.

2016-01-01

In recent years, there has been increasing focus on the issue of multiple hypotheses testing in education evaluation studies. In these studies, researchers are typically interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time or across multiple treatment groups. When…

A Statistical Method for Synthesizing Mediation Analyses Using the Product of Coefficient Approach Across Multiple Trials

PubMed Central

Huang, Shi; MacKinnon, David P.; Perrino, Tatiana; Gallo, Carlos; Cruden, Gracelyn; Brown, C Hendricks

2016-01-01

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: 1) marginal means for mediation path a, the relation of the independent variable to the mediator; 2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and 3) the between-trial level variance-covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings. PMID:28239330

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

PubMed

Cairns, David A

2011-03-01

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

Bangladesh.

PubMed

Ahmed, K S

1979-01-01

In Bangladesh the Population Control and Family Planning Division of the Ministry of Health and Population Control has decided to delegate increased financial and administrative powers to the officers of the family planning program at the district level and below. Currently, about 20,000 family planning workers and officials are at work in rural areas. The government believes that the success of the entire family planning program depends on the performance of workers in rural areas, because that is where about 90% of the population lives. Awareness of the need to improve statistical data in Bangladesh has been increasing, particularly in regard to the development of rural areas. An accurate statistical profile of rural Bangladesh is crucial to the formation, implementation and evaluation of rural development programs. A Seminar on Statistics for Rural Development will be held from June 18-20, 1980. The primary objectives of the Seminar are to make an exhaustive analysis of the current availability of statistics required for rural development programs and to consider methodological and operational improvements toward building up an adequate data base.

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

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

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

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

efficient association study design via power-optimized tag SNP selection

PubMed Central

HAN, BUHM; KANG, HYUN MIN; SEO, MYEONG SEONG; ZAITLEN, NOAH; ESKIN, ELEAZAR

2008-01-01

Discovering statistical correlation between causal genetic variation and clinical traits through association studies is an important method for identifying the genetic basis of human diseases. Since fully resequencing a cohort is prohibitively costly, genetic association studies take advantage of local correlation structure (or linkage disequilibrium) between single nucleotide polymorphisms (SNPs) by selecting a subset of SNPs to be genotyped (tag SNPs). While many current association studies are performed using commercially available high-throughput genotyping products that define a set of tag SNPs, choosing tag SNPs remains an important problem for both custom follow-up studies as well as designing the high-throughput genotyping products themselves. The most widely used tag SNP selection method optimizes over the correlation between SNPs (r2). However, tag SNPs chosen based on an r2 criterion do not necessarily maximize the statistical power of an association study. We propose a study design framework that chooses SNPs to maximize power and efficiently measures the power through empirical simulation. Empirical results based on the HapMap data show that our method gains considerable power over a widely used r2-based method, or equivalently reduces the number of tag SNPs required to attain the desired power of a study. Our power-optimized 100k whole genome tag set provides equivalent power to the Affymetrix 500k chip for the CEU population. For the design of custom follow-up studies, our method provides up to twice the power increase using the same number of tag SNPs as r2-based methods. Our method is publicly available via web server at http://design.cs.ucla.edu. PMID:18702637

Cerebral oscillatory activity during simulated driving using MEG.

PubMed

Sakihara, Kotoe; Hirata, Masayuki; Ebe, Kazutoshi; Kimura, Kenji; Yi Ryu, Seong; Kono, Yoshiyuki; Muto, Nozomi; Yoshioka, Masako; Yoshimine, Toshiki; Yorifuji, Shiro

2014-01-01

We aimed to examine cerebral oscillatory differences associated with psychological processes during simulated car driving. We recorded neuromagnetic signals in 14 healthy volunteers using magnetoencephalography (MEG) during simulated driving. MEG data were analyzed using synthetic aperture magnetometry to detect the spatial distribution of cerebral oscillations. Group effects between subjects were analyzed statistically using a non-parametric permutation test. Oscillatory differences were calculated by comparison between "passive viewing" and "active driving." "Passive viewing" was the baseline, and oscillatory differences during "active driving" showed an increase or decrease in comparison with a baseline. Power increase in the theta band was detected in the superior frontal gyrus (SFG) during active driving. Power decreases in the alpha, beta, and low gamma bands were detected in the right inferior parietal lobe (IPL), left postcentral gyrus (PoCG), middle temporal gyrus (MTG), and posterior cingulate gyrus (PCiG) during active driving. Power increase in the theta band in the SFG may play a role in attention. Power decrease in the right IPL may reflect selectively divided attention and visuospatial processing, whereas that in the left PoCG reflects sensorimotor activation related to driving manipulation. Power decreases in the MTG and PCiG may be associated with object recognition.

Correcting Too Much or Too Little? The Performance of Three Chi-Square Corrections.

PubMed

Foldnes, Njål; Olsson, Ulf Henning

2015-01-01

This simulation study investigates the performance of three test statistics, T1, T2, and T3, used to evaluate structural equation model fit under non normal data conditions. T1 is the well-known mean-adjusted statistic of Satorra and Bentler. T2 is the mean-and-variance adjusted statistic of Sattertwaithe type where the degrees of freedom is manipulated. T3 is a recently proposed version of T2 that does not manipulate degrees of freedom. Discrepancies between these statistics and their nominal chi-square distribution in terms of errors of Type I and Type II are investigated. All statistics are shown to be sensitive to increasing kurtosis in the data, with Type I error rates often far off the nominal level. Under excess kurtosis true models are generally over-rejected by T1 and under-rejected by T2 and T3, which have similar performance in all conditions. Under misspecification there is a loss of power with increasing kurtosis, especially for T2 and T3. The coefficient of variation of the nonzero eigenvalues of a certain matrix is shown to be a reliable indicator for the adequacy of these statistics.

Prenatal yoga in late pregnancy and optimism, power, and well-being.

PubMed

Reis, Pamela J; Alligood, Martha R

2014-01-01

The study reported here explored changes in optimism, power, and well-being over time in women who participated in a six-week prenatal yoga program during their second and third trimesters of pregnancy. The study was conceptualized from the perspective of Rogers' science of unitary human beings. A correlational, one-group, pre-post-assessment survey design with a convenience sample was conducted. Increases in mean scores for optimism, power, and well-being were statistically significant from baseline to completion of the prenatal yoga program. Findings from this study suggested that yoga as a self-care practice that nurses might recommend to promote well-being in pregnant women.

Robust inference for group sequential trials.

PubMed

Ganju, Jitendra; Lin, Yunzhi; Zhou, Kefei

2017-03-01

For ethical reasons, group sequential trials were introduced to allow trials to stop early in the event of extreme results. Endpoints in such trials are usually mortality or irreversible morbidity. For a given endpoint, the norm is to use a single test statistic and to use that same statistic for each analysis. This approach is risky because the test statistic has to be specified before the study is unblinded, and there is loss in power if the assumptions that ensure optimality for each analysis are not met. To minimize the risk of moderate to substantial loss in power due to a suboptimal choice of a statistic, a robust method was developed for nonsequential trials. The concept is analogous to diversification of financial investments to minimize risk. The method is based on combining P values from multiple test statistics for formal inference while controlling the type I error rate at its designated value.This article evaluates the performance of 2 P value combining methods for group sequential trials. The emphasis is on time to event trials although results from less complex trials are also included. The gain or loss in power with the combination method relative to a single statistic is asymmetric in its favor. Depending on the power of each individual test, the combination method can give more power than any single test or give power that is closer to the test with the most power. The versatility of the method is that it can combine P values from different test statistics for analysis at different times. The robustness of results suggests that inference from group sequential trials can be strengthened with the use of combined tests. Copyright © 2017 John Wiley & Sons, Ltd.

Exploiting excess sharing: a more powerful test of linkage for affected sib pairs than the transmission/disequilibrium test.

PubMed Central

Wicks, J

2000-01-01

The transmission/disequilibrium test (TDT) is a popular, simple, and powerful test of linkage, which can be used to analyze data consisting of transmissions to the affected members of families with any kind pedigree structure, including affected sib pairs (ASPs). Although it is based on the preferential transmission of a particular marker allele across families, it is not a valid test of association for ASPs. Martin et al. devised a similar statistic for ASPs, Tsp, which is also based on preferential transmission of a marker allele but which is a valid test of both linkage and association for ASPs. It is, however, less powerful than the TDT as a test of linkage for ASPs. What I show is that the differences between the TDT and Tsp are due to the fact that, although both statistics are based on preferential transmission of a marker allele, the TDT also exploits excess sharing in identity-by-descent transmissions to ASPs. Furthermore, I show that both of these statistics are members of a family of "TDT-like" statistics for ASPs. The statistics in this family are based on preferential transmission but also, to varying extents, exploit excess sharing. From this family of statistics, we see that, although the TDT exploits excess sharing to some extent, it is possible to do so to a greater extent-and thus produce a more powerful test of linkage, for ASPs, than is provided by the TDT. Power simulations conducted under a number of disease models are used to verify that the most powerful member of this family of TDT-like statistics is more powerful than the TDT for ASPs. PMID:10788332

Exploiting excess sharing: a more powerful test of linkage for affected sib pairs than the transmission/disequilibrium test.

PubMed

Wicks, J

2000-06-01

The transmission/disequilibrium test (TDT) is a popular, simple, and powerful test of linkage, which can be used to analyze data consisting of transmissions to the affected members of families with any kind pedigree structure, including affected sib pairs (ASPs). Although it is based on the preferential transmission of a particular marker allele across families, it is not a valid test of association for ASPs. Martin et al. devised a similar statistic for ASPs, Tsp, which is also based on preferential transmission of a marker allele but which is a valid test of both linkage and association for ASPs. It is, however, less powerful than the TDT as a test of linkage for ASPs. What I show is that the differences between the TDT and Tsp are due to the fact that, although both statistics are based on preferential transmission of a marker allele, the TDT also exploits excess sharing in identity-by-descent transmissions to ASPs. Furthermore, I show that both of these statistics are members of a family of "TDT-like" statistics for ASPs. The statistics in this family are based on preferential transmission but also, to varying extents, exploit excess sharing. From this family of statistics, we see that, although the TDT exploits excess sharing to some extent, it is possible to do so to a greater extent-and thus produce a more powerful test of linkage, for ASPs, than is provided by the TDT. Power simulations conducted under a number of disease models are used to verify that the most powerful member of this family of TDT-like statistics is more powerful than the TDT for ASPs.

A maximally selected test of symmetry about zero.

PubMed

Laska, Eugene; Meisner, Morris; Wanderling, Joseph

2012-11-20

The problem of testing symmetry about zero has a long and rich history in the statistical literature. We introduce a new test that sequentially discards observations whose absolute value is below increasing thresholds defined by the data. McNemar's statistic is obtained at each threshold and the largest is used as the test statistic. We obtain the exact distribution of this maximally selected McNemar and provide tables of critical values and a program for computing p-values. Power is compared with the t-test, the Wilcoxon Signed Rank Test and the Sign Test. The new test, MM, is slightly less powerful than the t-test and Wilcoxon Signed Rank Test for symmetric normal distributions with nonzero medians and substantially more powerful than all three tests for asymmetric mixtures of normal random variables with or without zero medians. The motivation for this test derives from the need to appraise the safety profile of new medications. If pre and post safety measures are obtained, then under the null hypothesis, the variables are exchangeable and the distribution of their difference is symmetric about a zero median. Large pre-post differences are the major concern of a safety assessment. The discarded small observations are not particularly relevant to safety and can reduce power to detect important asymmetry. The new test was utilized on data from an on-road driving study performed to determine if a hypnotic, a drug used to promote sleep, has next day residual effects. Copyright © 2012 John Wiley & Sons, Ltd.

An overview of meta-analysis for clinicians.

PubMed

Lee, Young Ho

2018-03-01

The number of medical studies being published is increasing exponentially, and clinicians must routinely process large amounts of new information. Moreover, the results of individual studies are often insufficient to provide confident answers, as their results are not consistently reproducible. A meta-analysis is a statistical method for combining the results of different studies on the same topic and it may resolve conflicts among studies. Meta-analysis is being used increasingly and plays an important role in medical research. This review introduces the basic concepts, steps, advantages, and caveats of meta-analysis, to help clinicians understand it in clinical practice and research. A major advantage of a meta-analysis is that it produces a precise estimate of the effect size, with considerably increased statistical power, which is important when the power of the primary study is limited because of a small sample size. A meta-analysis may yield conclusive results when individual studies are inconclusive. Furthermore, meta-analyses investigate the source of variation and different effects among subgroups. In summary, a meta-analysis is an objective, quantitative method that provides less biased estimates on a specific topic. Understanding how to conduct a meta-analysis aids clinicians in the process of making clinical decisions.

Modulation of electroencephalograph activity by manual acupuncture stimulation in healthy subjects: An autoregressive spectral analysis

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Han, Chun-Xiao

2013-02-01

To investigate whether and how manual acupuncture (MA) modulates brain activities, we design an experiment where acupuncture at acupoint ST36 of the right leg is used to obtain electroencephalograph (EEG) signals in healthy subjects. We adopt the autoregressive (AR) Burg method to estimate the power spectrum of EEG signals and analyze the relative powers in delta (0 Hz-4 Hz), theta (4 Hz-8 Hz), alpha (8 Hz-13 Hz), and beta (13 Hz-30 Hz) bands. Our results show that MA at ST36 can significantly increase the EEG slow wave relative power (delta band) and reduce the fast wave relative powers (alpha and beta bands), while there are no statistical differences in theta band relative power between different acupuncture states. In order to quantify the ratio of slow to fast wave EEG activity, we compute the power ratio index. It is found that the MA can significantly increase the power ratio index, especially in frontal and central lobes. All the results highlight the modulation of brain activities with MA and may provide potential help for the clinical use of acupuncture. The proposed quantitative method of acupuncture signals may be further used to make MA more standardized.

The effect of the polymer relaxation time on the nonlinear energy cas- cade and dissipation of statistically steady and decaying homogeneous isotropic turbulence

NASA Astrophysics Data System (ADS)

Valente, Pedro C.; da Silva, Carlos B.; Pinho, Fernando T.

2013-11-01

We report a numerical study of statistically steady and decaying turbulence of FENE-P fluids for varying polymer relaxation times ranging from the Kolmogorov dissipation time-scale to the eddy turnover time. The total turbulent kinetic energy dissipation is shown to increase with the polymer relaxation time in both steady and decaying turbulence, implying a ``drag increase.'' If the total power input in the statistically steady case is kept equal in the Newtonian and the viscoelastic simulations the increase in the turbulence-polymer energy transfer naturally lead to the previously reported depletion of the Newtonian, but not the overall, kinetic energy dissipation. The modifications to the nonlinear energy cascade with varying Deborah/Weissenberg numbers are quantified and their origins investigated. The authors acknowledge the financial support from Fundação para a Ciência e a Tecnologia under grant PTDC/EME-MFE/113589/2009.

Ozone Monitoring Instrument Observations of Interannual Increases in SO2 Emissions from Indian Coal-fired Power Plants During 2005-2012

NASA Technical Reports Server (NTRS)

Lu, Zifeng; Streets, David D.; de Foy, Benjamin; Krotkov, Nickolay A.

2014-01-01

Due to the rapid growth of electricity demand and the absence of regulations, sulfur dioxide (SO2) emissions from coal-fired power plants in India have increased notably in the past decade. In this study, we present the first interannual comparison of SO2 emissions and the satellite SO2 observations from the Ozone Monitoring Instrument (OMI) for Indian coal-fired power plants during the OMI era of 2005-2012. A detailed unit-based inventory is developed for the Indian coal-fired power sector, and results show that its SO2 emissions increased dramatically by 71 percent during 2005-2012. Using the oversampling technique, yearly high-resolution OMI maps for the whole domain of India are created, and they reveal a continuous increase in SO2 columns over India. Power plant regions with annual SO2 emissions greater than 50 Gg year-1 produce statistically significant OMI signals, and a high correlation (R equals 0.93) is found between SO2 emissions and OMI-observed SO2 burdens. Contrary to the decreasing trend of national mean SO2 concentrations reported by the Indian Government, both the total OMI-observed SO2 and average SO2 concentrations in coal-fired power plant regions increased by greater than 60 percent during 2005-2012, implying the air quality monitoring network needs to be optimized to reflect the true SO2 situation in India.

“Forward Genetics” as a Method to Maximize Power and Cost-Efficiency in Studies of Human Complex Traits

PubMed Central

Derks, E. M.; Dolan, C. V.; Kahn, R. S.; Ophoff, R. A.

2010-01-01

There is increasing interest in methods to disentangle the relationship between genotype and (endo)phenotypes in human complex traits. We present a population-based method of increasing the power and cost-efficiency of studies by selecting random individuals with a particular genotype and then assessing the accompanying quantitative phenotypes. Using statistical derivations, power- and cost graphs we show that such a “forward genetics” approach can lead to a marked reduction in sample size and costs. This approach is particularly apt for implementing in epidemiological studies for which DNA is already available but the phenotyping costs are high. Electronic supplementary material The online version of this article (doi:10.1007/s10519-010-9348-y) contains supplementary material, which is available to authorized users. PMID:20232132

The Power of Neuroimaging Biomarkers for Screening Frontotemporal Dementia

PubMed Central

McMillan, Corey T.; Avants, Brian B.; Cook, Philip; Ungar, Lyle; Trojanowski, John Q.; Grossman, Murray

2014-01-01

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer’s disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N=93) with cerebrospinal fluid, gray matter (GM) MRI, and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes (mSS) required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% SENSITIVE; 89% SPECIFIC) and required a lower minimum sample size (N=26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach employing Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials. PMID:24687814

Spurious correlations and inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Reliable interpretation of landscape genetic analyses depends on statistical methods that have high power to identify the correct process driving gene flow while rejecting incorrect alternative hypotheses. Little is known about statistical power and inference in individual-based landscape genetics. Our objective was to evaluate the power of causalmodelling with partial...

Adaptive smoothing based on Gaussian processes regression increases the sensitivity and specificity of fMRI data.

PubMed

Strappini, Francesca; Gilboa, Elad; Pitzalis, Sabrina; Kay, Kendrick; McAvoy, Mark; Nehorai, Arye; Snyder, Abraham Z

2017-03-01

Temporal and spatial filtering of fMRI data is often used to improve statistical power. However, conventional methods, such as smoothing with fixed-width Gaussian filters, remove fine-scale structure in the data, necessitating a tradeoff between sensitivity and specificity. Specifically, smoothing may increase sensitivity (reduce noise and increase statistical power) but at the cost loss of specificity in that fine-scale structure in neural activity patterns is lost. Here, we propose an alternative smoothing method based on Gaussian processes (GP) regression for single subjects fMRI experiments. This method adapts the level of smoothing on a voxel by voxel basis according to the characteristics of the local neural activity patterns. GP-based fMRI analysis has been heretofore impractical owing to computational demands. Here, we demonstrate a new implementation of GP that makes it possible to handle the massive data dimensionality of the typical fMRI experiment. We demonstrate how GP can be used as a drop-in replacement to conventional preprocessing steps for temporal and spatial smoothing in a standard fMRI pipeline. We present simulated and experimental results that show the increased sensitivity and specificity compared to conventional smoothing strategies. Hum Brain Mapp 38:1438-1459, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Generalizing Terwilliger's likelihood approach: a new score statistic to test for genetic association.

PubMed

el Galta, Rachid; Uitte de Willige, Shirley; de Visser, Marieke C H; Helmer, Quinta; Hsu, Li; Houwing-Duistermaat, Jeanine J

2007-09-24

In this paper, we propose a one degree of freedom test for association between a candidate gene and a binary trait. This method is a generalization of Terwilliger's likelihood ratio statistic and is especially powerful for the situation of one associated haplotype. As an alternative to the likelihood ratio statistic, we derive a score statistic, which has a tractable expression. For haplotype analysis, we assume that phase is known. By means of a simulation study, we compare the performance of the score statistic to Pearson's chi-square statistic and the likelihood ratio statistic proposed by Terwilliger. We illustrate the method on three candidate genes studied in the Leiden Thrombophilia Study. We conclude that the statistic follows a chi square distribution under the null hypothesis and that the score statistic is more powerful than Terwilliger's likelihood ratio statistic when the associated haplotype has frequency between 0.1 and 0.4 and has a small impact on the studied disorder. With regard to Pearson's chi-square statistic, the score statistic has more power when the associated haplotype has frequency above 0.2 and the number of variants is above five.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

Modifications of EEG power spectra in mesial temporal lobe during n-back tasks of increasing difficulty. A sLORETA study.

PubMed

Imperatori, Claudio; Farina, Benedetto; Brunetti, Riccardo; Gnoni, Valentina; Testani, Elisa; Quintiliani, Maria I; Del Gatto, Claudia; Indraccolo, Allegra; Contardi, Anna; Speranza, Anna M; Della Marca, Giacomo

2013-01-01

The n-back task is widely used to investigate the neural basis of Working Memory (WM) processes. The principal aim of this study was to explore and compare the EEG power spectra during two n-back tests with different levels of difficulty (1-back vs. 3-back). Fourteen healthy subjects were enrolled (seven men and seven women, mean age 31.21 ± 7.05 years, range: 23-48). EEG was recorded while performing the N-back test, by means of 19 surface electrodes referred to joint mastoids. EEG analysis were conducted by means of the standardized Low Resolution brain Electric Tomography (sLORETA) software. The statistical comparison between EEG power spectra in the two conditions was performed using paired t-statistics on the coherence values after Fisher's z transformation available in the LORETA program package. The frequency bands considered were: delta (0.5-4 Hz); theta (4.5-7.5 Hz); alpha (8-12.5 Hz); beta (13-30 Hz); gamma (30.5-100 Hz). Significant changes occurred in the delta band: in the 3-back condition an increased delta power was localized in a brain region corresponding to the Brodmann Area (BA) 28 in the left posterior entorhinal cortex (T = 3.112; p < 0.05) and in the BA 35 in the left perirhinal cortex in the parahippocampal gyrus (T = 2.876; p < 0.05). No significant differences were observed in the right hemisphere and in the alpha, theta, beta, and gamma frequency bands. Our results indicate that the most prominent modification induced by the increased complexity of the task occur in the mesial left temporal lobe structures.

Universal partitioning of the hierarchical fold network of 50-residue segments in proteins

PubMed Central

Ito, Jun-ichi; Sonobe, Yuki; Ikeda, Kazuyoshi; Tomii, Kentaro; Higo, Junichi

2009-01-01

Background Several studies have demonstrated that protein fold space is structured hierarchically and that power-law statistics are satisfied in relation between the numbers of protein families and protein folds (or superfamilies). We examined the internal structure and statistics in the fold space of 50 amino-acid residue segments taken from various protein folds. We used inter-residue contact patterns to measure the tertiary structural similarity among segments. Using this similarity measure, the segments were classified into a number (Kc) of clusters. We examined various Kc values for the clustering. The special resolution to differentiate the segment tertiary structures increases with increasing Kc. Furthermore, we constructed networks by linking structurally similar clusters. Results The network was partitioned persistently into four regions for Kc ≥ 1000. This main partitioning is consistent with results of earlier studies, where similar partitioning was reported in classifying protein domain structures. Furthermore, the network was partitioned naturally into several dozens of sub-networks (i.e., communities). Therefore, intra-sub-network clusters were mutually connected with numerous links, although inter-sub-network ones were rarely done with few links. For Kc ≥ 1000, the major sub-networks were about 40; the contents of the major sub-networks were conserved. This sub-partitioning is a novel finding, suggesting that the network is structured hierarchically: Segments construct a cluster, clusters form a sub-network, and sub-networks constitute a region. Additionally, the network was characterized by non-power-law statistics, which is also a novel finding. Conclusion Main findings are: (1) The universe of 50 residue segments found here was characterized by non-power-law statistics. Therefore, the universe differs from those ever reported for the protein domains. (2) The 50-residue segments were partitioned persistently and universally into some dozens (ca. 40) of major sub-networks, irrespective of the number of clusters. (3) These major sub-networks encompassed 90% of all segments. Consequently, the protein tertiary structure is constructed using the dozens of elements (sub-networks). PMID:19454039

ASSESSMENT OF OXIDATIVE STRESS IN EARLY AND LATE ONSET PRE-ECLAMPSIA AMONG GHANAIAN WOMEN.

PubMed

Tetteh, P W; Adu-Bonsaffoh, K; Antwi-Boasiako, C; Antwi, D A; Gyan, B; Obed, S A

2015-01-01

Pre-eclampsia is a multisystem pregnancy-related disorder with multiple theories regarding its aetiology resulting in lack of reliable screening tests and well-established measures for primary prevention. However, oxidative stress is increasingly being implicated in the pathogenesi of pre-eclampsia although conflicting findings have been reported. To determine and compare the levels of oxidative stress in early and late onset pre-eclampsia by measuring urinary excretion of isoprostane and total antioxidant power (TAP) in a cohort of pre-eclamptic women at Korle Bu Teaching Hospital. This was a cross-sectional study conducted at Korle-Bu Teaching Hospital, Accra, Ghana involving pre-eclamptic women between the ages 18 and 45 years who gave written informed consent. Urinary isoprostane levels were determined using an enzyme-linked immunosorbent assay (ELISA) kit whereas the Total Anti-oxidant Power in urine samples was determined using Total Antioxidant Power Colorimetric Microplate Assay kit. The data obtained were analyzed using MEGASTAT statistical software package. We included 102 pre-eclamptic women comprising 68 (66.7%) and 34 (33.3%) with early-onset and late-onset pre-eclampsia respectively. There were no statistically significant differences between the mean maternal age, haematological indices, serum ALT, AST, ALT, albumin, urea, creatinine uric acid and total protein at the time of diagnosis. The mean gestational age at diagnosis of early and late onset pre-eclampsia were 31.65 ± 0.41 and 38.03 ± 0.21 respectively (p ˂ 0.001). Also, there were statistically significant differences between the diastolic blood pressure (BP), systolic BP and mean arterial pressure (MAP) at diagnosis of pre-eclampsia in the two categories. The mean urinary Isoprostane excretion was significantly higher in the early onset pre-eclamptic group (3.04 ± 0.34 ng/mg Cr) compared to that of the late onset pre-eclamptic group (2.36 ± 0.45 ng/mg Cr), (p=0.019). Urinary total antioxidant power (TAP) in early onset PE (1.64 ± 0.06) was lower but not significantly different from that of late onset PE (1.74 ± 0.09) with p = 0.369. Significantly increased urinary isoprostane excretion was detected in early onset pre-eclampsia compared to late onset pre-eclampsia, suggestive of increased oxidative stress in the former. However, there was no significant difference in total anti-oxidant power between the two categories of pre-eclampsia women although there was a tendency of reduced total antioxidant power in the women with early onset pre-ecalmpsia.

Multiplicative point process as a model of trading activity

NASA Astrophysics Data System (ADS)

Gontis, V.; Kaulakys, B.

2004-11-01

Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

The cost of large numbers of hypothesis tests on power, effect size and sample size.

PubMed

Lazzeroni, L C; Ray, A

2012-01-01

Advances in high-throughput biology and computer science are driving an exponential increase in the number of hypothesis tests in genomics and other scientific disciplines. Studies using current genotyping platforms frequently include a million or more tests. In addition to the monetary cost, this increase imposes a statistical cost owing to the multiple testing corrections needed to avoid large numbers of false-positive results. To safeguard against the resulting loss of power, some have suggested sample sizes on the order of tens of thousands that can be impractical for many diseases or may lower the quality of phenotypic measurements. This study examines the relationship between the number of tests on the one hand and power, detectable effect size or required sample size on the other. We show that once the number of tests is large, power can be maintained at a constant level, with comparatively small increases in the effect size or sample size. For example at the 0.05 significance level, a 13% increase in sample size is needed to maintain 80% power for ten million tests compared with one million tests, whereas a 70% increase in sample size is needed for 10 tests compared with a single test. Relative costs are less when measured by increases in the detectable effect size. We provide an interactive Excel calculator to compute power, effect size or sample size when comparing study designs or genome platforms involving different numbers of hypothesis tests. The results are reassuring in an era of extreme multiple testing.

Powerlaw: a Python package for analysis of heavy-tailed distributions.

PubMed

Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

2014-01-01

Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible.

Non-Gaussian power grid frequency fluctuations characterized by Lévy-stable laws and superstatistics

NASA Astrophysics Data System (ADS)

Schäfer, Benjamin; Beck, Christian; Aihara, Kazuyuki; Witthaut, Dirk; Timme, Marc

2018-02-01

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading and an increasing share of renewable power feed-in. Here we analyse principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a strong deviation from Gaussianity best described as Lévy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions, as well as a superstatistical approach that systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today's frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids.

Sample Size in Clinical Cardioprotection Trials Using Myocardial Salvage Index, Infarct Size, or Biochemical Markers as Endpoint.

PubMed

Engblom, Henrik; Heiberg, Einar; Erlinge, David; Jensen, Svend Eggert; Nordrehaug, Jan Erik; Dubois-Randé, Jean-Luc; Halvorsen, Sigrun; Hoffmann, Pavel; Koul, Sasha; Carlsson, Marcus; Atar, Dan; Arheden, Håkan

2016-03-09

Cardiac magnetic resonance (CMR) can quantify myocardial infarct (MI) size and myocardium at risk (MaR), enabling assessment of myocardial salvage index (MSI). We assessed how MSI impacts the number of patients needed to reach statistical power in relation to MI size alone and levels of biochemical markers in clinical cardioprotection trials and how scan day affect sample size. Controls (n=90) from the recent CHILL-MI and MITOCARE trials were included. MI size, MaR, and MSI were assessed from CMR. High-sensitivity troponin T (hsTnT) and creatine kinase isoenzyme MB (CKMB) levels were assessed in CHILL-MI patients (n=50). Utilizing distribution of these variables, 100 000 clinical trials were simulated for calculation of sample size required to reach sufficient power. For a treatment effect of 25% decrease in outcome variables, 50 patients were required in each arm using MSI compared to 93, 98, 120, 141, and 143 for MI size alone, hsTnT (area under the curve [AUC] and peak), and CKMB (AUC and peak) in order to reach a power of 90%. If average CMR scan day between treatment and control arms differed by 1 day, sample size needs to be increased by 54% (77 vs 50) to avoid scan day bias masking a treatment effect of 25%. Sample size in cardioprotection trials can be reduced 46% to 65% without compromising statistical power when using MSI by CMR as an outcome variable instead of MI size alone or biochemical markers. It is essential to ensure lack of bias in scan day between treatment and control arms to avoid compromising statistical power. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

GPA in Research Studies: An Invaluable but Neglected Opportunity

ERIC Educational Resources Information Center

Bacon, Donald R.; Bean, Beth

2006-01-01

Grade point average (GPA) often correlates highly with variables of interest to educational researchers and thus offers the potential to greatly increase the statistical power of their research studies. Yet this variable is often underused in marketing education research studies. The reliability and validity of the GPA are closely examined here in…

Intraclass Correlations and Covariate Outcome Correlations for Planning Two-and Three-Level Cluster-Randomized Experiments in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.

2013-01-01

Background: Cluster-randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…

Intraclass Correlations and Covariate Outcome Correlations for Planning 2 and 3 Level Cluster Randomized Experiments in Education

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, Eric C.

2013-01-01

Background: Cluster randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…

The power and robustness of maximum LOD score statistics.

PubMed

Yoo, Y J; Mendell, N R

2008-07-01

The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.

Power Enhancement in High Dimensional Cross-Sectional Tests

PubMed Central

Fan, Jianqing; Liao, Yuan; Yao, Jiawei

2016-01-01

We propose a novel technique to boost the power of testing a high-dimensional vector H : θ = 0 against sparse alternatives where the null hypothesis is violated only by a couple of components. Existing tests based on quadratic forms such as the Wald statistic often suffer from low powers due to the accumulation of errors in estimating high-dimensional parameters. More powerful tests for sparse alternatives such as thresholding and extreme-value tests, on the other hand, require either stringent conditions or bootstrap to derive the null distribution and often suffer from size distortions due to the slow convergence. Based on a screening technique, we introduce a “power enhancement component”, which is zero under the null hypothesis with high probability, but diverges quickly under sparse alternatives. The proposed test statistic combines the power enhancement component with an asymptotically pivotal statistic, and strengthens the power under sparse alternatives. The null distribution does not require stringent regularity conditions, and is completely determined by that of the pivotal statistic. As specific applications, the proposed methods are applied to testing the factor pricing models and validating the cross-sectional independence in panel data models. PMID:26778846

Age-Associated Changes in the Spectral and Statistical Parameters of Surface Electromyogram of Tibialis Anterior.

PubMed

Siddiqi, Ariba; Arjunan, Sridhar Poosapadi; Kumar, Dinesh Kant

2016-01-01

Age-related neuromuscular change of Tibialis Anterior (TA) is a leading cause of muscle strength decline among the elderly. This study has established the baseline for age-associated changes in sEMG of TA at different levels of voluntary contraction. We have investigated the use of Gaussianity and maximal power of the power spectral density (PSD) as suitable features to identify age-associated changes in the surface electromyogram (sEMG). Eighteen younger (20-30 years) and 18 older (60-85 years) cohorts completed two trials of isometric dorsiflexion at four different force levels between 10% and 50% of the maximal voluntary contraction. Gaussianity and maximal power of the PSD of sEMG were determined. Results show a significant increase in sEMG's maximal power of the PSD and Gaussianity with increase in force for both cohorts. It was also observed that older cohorts had higher maximal power of the PSD and lower Gaussianity. These age-related differences observed in the PSD and Gaussianity could be due to motor unit remodelling. This can be useful for noninvasive tracking of age-associated neuromuscular changes.

Relationship Power, Sexual Decision Making, and HIV Risk Among Midlife and Older Women.

PubMed

Altschuler, Joanne; Rhee, Siyon

2015-01-01

The number of midlife and older women with HIV/AIDS is high and increasing, especially among women of color. This article addresses these demographic realities by reporting on findings about self-esteem, relationship power, and HIV risk from a pilot study of midlife and older women. A purposive sample (N = 110) of ethnically, economically, and educationally diverse women 40 years and older from the Greater Los Angeles Area was surveyed to determine their levels of self-esteem, general relationship power, sexual decision-making power, safer sex behaviors, and HIV knowledge. Women with higher levels of self-esteem exercised greater power in their relationships with their partner. Women with higher levels of general relationship power and self-esteem tend to exercise greater power in sexual decision making, such as having sex and choosing sexual acts. Income and sexual decision-making power were statistically significant in predicting the use of condoms. Implications and recommendations for future HIV/AIDS research and intervention targeting midlife and older women are presented.

Anthropogenic Sulphur Dioxide Load over China as Observed from Different Satellite Sensors

NASA Technical Reports Server (NTRS)

Koukouli, M. E.; Balis, D. S.; Johannes Van Der A, Ronald; Theys, N.; Hedelt, P.; Richter, A.; Krotkov, N.; Li, Can; Taylor, M.

2016-01-01

China, with its rapid economic growth and immense exporting power, has been the focus of many studies during this previous decade quantifying its increasing emissions contribution to the Earth's atmosphere. With a population slowly shifting towards enlarged power and purchasing needs, the ceaseless inauguration of new power plants, smelters, refineries and industrial parks leads infallibly to increases in sulphur dioxide, SO2, emissions. The recent capability of next generation algorithms as well as new space-borne instruments to detect anthropogenic SO2 loads has enabled a fast advancement in this field. In the following work, algorithms providing total SO2 columns over China based on SCIAMACHY/Envisat, OMI/Aura and GOME2/MetopA observations are presented. The need for post-processing and gridding of the SO2 fields is further revealed in this work, following the path of previous publications. Further, it is demonstrated that the usage of appropriate statistical tools permits studying parts of the datasets typically excluded, such as the winter months loads. Focusing on actual point sources, such as megacities and known power plant locations, instead of entire provinces, monthly mean time series have been examined in detail. The sharp decline in SO2 emissions in more than 90% - 95% of the locations studied confirms the recent implementation of government desulphurisation legislation; however, locations with increases, even for the previous five years, are also identified. These belong to provinces with emerging economies which are in haste to install power plants and are possibly viewed leniently by the authorities, in favour of growth. The SO2 load seasonality has also been examined in detail with a novel mathematical tool, with 70% of the point sources having a statistically significant annual cycle with highs in winter and lows in summer, following the heating requirements of the Chinese population.

Anthropogenic sulphur dioxide load over China as observed from different satellite sensors

NASA Astrophysics Data System (ADS)

Koukouli, M. E.; Balis, D. S.; van der A, Ronald Johannes; Theys, N.; Hedelt, P.; Richter, A.; Krotkov, N.; Li, C.; Taylor, M.

2016-11-01

China, with its rapid economic growth and immense exporting power, has been the focus of many studies during this previous decade quantifying its increasing emissions contribution to the Earth's atmosphere. With a population slowly shifting towards enlarged power and purchasing needs, the ceaseless inauguration of new power plants, smelters, refineries and industrial parks leads infallibly to increases in sulphur dioxide, SO2, emissions. The recent capability of next generation algorithms as well as new space-borne instruments to detect anthropogenic SO2 loads has enabled a fast advancement in this field. In the following work, algorithms providing total SO2 columns over China based on SCIAMACHY/Envisat, OMI/Aura and GOME2/MetopA observations are presented. The need for post-processing and gridding of the SO2 fields is further revealed in this work, following the path of previous publications. Further, it is demonstrated that the usage of appropriate statistical tools permits studying parts of the datasets typically excluded, such as the winter months loads. Focusing on actual point sources, such as megacities and known power plant locations, instead of entire provinces, monthly mean time series have been examined in detail. The sharp decline in SO2 emissions in more than 90%-95% of the locations studied confirms the recent implementation of government desulphurisation legislation; however, locations with increases, even for the previous five years, are also identified. These belong to provinces with emerging economies which are in haste to install power plants and are possibly viewed leniently by the authorities, in favour of growth. The SO2 load seasonality has also been examined in detail with a novel mathematical tool, with 70% of the point sources having a statistically significant annual cycle with highs in winter and lows in summer, following the heating requirements of the Chinese population.

Interpreting the gamma statistic in phylogenetic diversification rate studies: a rate decrease does not necessarily indicate an early burst.

PubMed

Fordyce, James A

2010-07-23

Phylogenetic hypotheses are increasingly being used to elucidate historical patterns of diversification rate-variation. Hypothesis testing is often conducted by comparing the observed vector of branching times to a null, pure-birth expectation. A popular method for inferring a decrease in speciation rate, which might suggest an early burst of diversification followed by a decrease in diversification rate is the gamma statistic. Using simulations under varying conditions, I examine the sensitivity of gamma to the distribution of the most recent branching times. Using an exploratory data analysis tool for lineages through time plots, tree deviation, I identified trees with a significant gamma statistic that do not appear to have the characteristic early accumulation of lineages consistent with an early, rapid rate of cladogenesis. I further investigated the sensitivity of the gamma statistic to recent diversification by examining the consequences of failing to simulate the full time interval following the most recent cladogenic event. The power of gamma to detect rate decrease at varying times was assessed for simulated trees with an initial high rate of diversification followed by a relatively low rate. The gamma statistic is extraordinarily sensitive to recent diversification rates, and does not necessarily detect early bursts of diversification. This was true for trees of various sizes and completeness of taxon sampling. The gamma statistic had greater power to detect recent diversification rate decreases compared to early bursts of diversification. Caution should be exercised when interpreting the gamma statistic as an indication of early, rapid diversification.

Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives

USGS Publications Warehouse

Wagner, Tyler; Irwin, Brian J.; James R. Bence,; Daniel B. Hayes,

2016-01-01

Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.

Statistical Analysis of Large-Scale Structure of Universe

NASA Astrophysics Data System (ADS)

Tugay, A. V.

While galaxy cluster catalogs were compiled many decades ago, other structural elements of cosmic web are detected at definite level only in the newest works. For example, extragalactic filaments were described by velocity field and SDSS galaxy distribution during the last years. Large-scale structure of the Universe could be also mapped in the future using ATHENA observations in X-rays and SKA in radio band. Until detailed observations are not available for the most volume of Universe, some integral statistical parameters can be used for its description. Such methods as galaxy correlation function, power spectrum, statistical moments and peak statistics are commonly used with this aim. The parameters of power spectrum and other statistics are important for constraining the models of dark matter, dark energy, inflation and brane cosmology. In the present work we describe the growth of large-scale density fluctuations in one- and three-dimensional case with Fourier harmonics of hydrodynamical parameters. In result we get power-law relation for the matter power spectrum.

System Study: High-Pressure Safety Injection 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 69 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPSI results.

Statistical power of intervention analyses: simulation and empirical application to treated lumber prices

Treesearch

Jeffrey P. Prestemon

2009-01-01

Timber product markets are subject to large shocks deriving from natural disturbances and policy shifts. Statistical modeling of shocks is often done to assess their economic importance. In this article, I simulate the statistical power of univariate and bivariate methods of shock detection using time series intervention models. Simulations show that bivariate methods...

Improving qPCR telomere length assays: Controlling for well position effects increases statistical power.

PubMed

Eisenberg, Dan T A; Kuzawa, Christopher W; Hayes, M Geoffrey

2015-01-01

Telomere length (TL) is commonly measured using quantitative PCR (qPCR). Although, easier than the southern blot of terminal restriction fragments (TRF) TL measurement method, one drawback of qPCR is that it introduces greater measurement error and thus reduces the statistical power of analyses. To address a potential source of measurement error, we consider the effect of well position on qPCR TL measurements. qPCR TL data from 3,638 people run on a Bio-Rad iCycler iQ are reanalyzed here. To evaluate measurement validity, correspondence with TRF, age, and between mother and offspring are examined. First, we present evidence for systematic variation in qPCR TL measurements in relation to thermocycler well position. Controlling for these well-position effects consistently improves measurement validity and yields estimated improvements in statistical power equivalent to increasing sample sizes by 16%. We additionally evaluated the linearity of the relationships between telomere and single copy gene control amplicons and between qPCR and TRF measures. We find that, unlike some previous reports, our data exhibit linear relationships. We introduce the standard error in percent, a superior method for quantifying measurement error as compared to the commonly used coefficient of variation. Using this measure, we find that excluding samples with high measurement error does not improve measurement validity in our study. Future studies using block-based thermocyclers should consider well position effects. Since additional information can be gleaned from well position corrections, rerunning analyses of previous results with well position correction could serve as an independent test of the validity of these results. © 2015 Wiley Periodicals, Inc.

New Insights into Handling Missing Values in Environmental Epidemiological Studies

PubMed Central

Roda, Célina; Nicolis, Ioannis; Momas, Isabelle; Guihenneuc, Chantal

2014-01-01

Missing data are unavoidable in environmental epidemiologic surveys. The aim of this study was to compare methods for handling large amounts of missing values: omission of missing values, single and multiple imputations (through linear regression or partial least squares regression), and a fully Bayesian approach. These methods were applied to the PARIS birth cohort, where indoor domestic pollutant measurements were performed in a random sample of babies' dwellings. A simulation study was conducted to assess performances of different approaches with a high proportion of missing values (from 50% to 95%). Different simulation scenarios were carried out, controlling the true value of the association (odds ratio of 1.0, 1.2, and 1.4), and varying the health outcome prevalence. When a large amount of data is missing, omitting these missing data reduced statistical power and inflated standard errors, which affected the significance of the association. Single imputation underestimated the variability, and considerably increased risk of type I error. All approaches were conservative, except the Bayesian joint model. In the case of a common health outcome, the fully Bayesian approach is the most efficient approach (low root mean square error, reasonable type I error, and high statistical power). Nevertheless for a less prevalent event, the type I error is increased and the statistical power is reduced. The estimated posterior distribution of the OR is useful to refine the conclusion. Among the methods handling missing values, no approach is absolutely the best but when usual approaches (e.g. single imputation) are not sufficient, joint modelling approach of missing process and health association is more efficient when large amounts of data are missing. PMID:25226278

Properties of different selection signature statistics and a new strategy for combining them.

PubMed

Ma, Y; Ding, X; Qanbari, S; Weigend, S; Zhang, Q; Simianer, H

2015-11-01

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

On base station cooperation using statistical CSI in jointly correlated MIMO downlink channels

NASA Astrophysics Data System (ADS)

Zhang, Jun; Jiang, Bin; Jin, Shi; Gao, Xiqi; Wong, Kai-Kit

2012-12-01

This article studies the transmission of a single cell-edge user's signal using statistical channel state information at cooperative base stations (BSs) with a general jointly correlated multiple-input multiple-output (MIMO) channel model. We first present an optimal scheme to maximize the ergodic sum capacity with per-BS power constraints, revealing that the transmitted signals of all BSs are mutually independent and the optimum transmit directions for each BS align with the eigenvectors of the BS's own transmit correlation matrix of the channel. Then, we employ matrix permanents to derive a closed-form tight upper bound for the ergodic sum capacity. Based on these results, we develop a low-complexity power allocation solution using convex optimization techniques and a simple iterative water-filling algorithm (IWFA) for power allocation. Finally, we derive a necessary and sufficient condition for which a beamforming approach achieves capacity for all BSs. Simulation results demonstrate that the upper bound of ergodic sum capacity is tight and the proposed cooperative transmission scheme increases the downlink system sum capacity considerably.

An entropy-based statistic for genomewide association studies.

PubMed

Zhao, Jinying; Boerwinkle, Eric; Xiong, Momiao

2005-07-01

Efficient genotyping methods and the availability of a large collection of single-nucleotide polymorphisms provide valuable tools for genetic studies of human disease. The standard chi2 statistic for case-control studies, which uses a linear function of allele frequencies, has limited power when the number of marker loci is large. We introduce a novel test statistic for genetic association studies that uses Shannon entropy and a nonlinear function of allele frequencies to amplify the differences in allele and haplotype frequencies to maintain statistical power with large numbers of marker loci. We investigate the relationship between the entropy-based test statistic and the standard chi2 statistic and show that, in most cases, the power of the entropy-based statistic is greater than that of the standard chi2 statistic. The distribution of the entropy-based statistic and the type I error rates are validated using simulation studies. Finally, we apply the new entropy-based test statistic to two real data sets, one for the COMT gene and schizophrenia and one for the MMP-2 gene and esophageal carcinoma, to evaluate the performance of the new method for genetic association studies. The results show that the entropy-based statistic obtained smaller P values than did the standard chi2 statistic.

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

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation betweenmore » ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars.« less

Error, Power, and Blind Sentinels: The Statistics of Seagrass Monitoring

PubMed Central

Schultz, Stewart T.; Kruschel, Claudia; Bakran-Petricioli, Tatjana; Petricioli, Donat

2015-01-01

We derive statistical properties of standard methods for monitoring of habitat cover worldwide, and criticize them in the context of mandated seagrass monitoring programs, as exemplified by Posidonia oceanica in the Mediterranean Sea. We report the novel result that cartographic methods with non-trivial classification errors are generally incapable of reliably detecting habitat cover losses less than about 30 to 50%, and the field labor required to increase their precision can be orders of magnitude higher than that required to estimate habitat loss directly in a field campaign. We derive a universal utility threshold of classification error in habitat maps that represents the minimum habitat map accuracy above which direct methods are superior. Widespread government reliance on blind-sentinel methods for monitoring seafloor can obscure the gradual and currently ongoing losses of benthic resources until the time has long passed for meaningful management intervention. We find two classes of methods with very high statistical power for detecting small habitat cover losses: 1) fixed-plot direct methods, which are over 100 times as efficient as direct random-plot methods in a variable habitat mosaic; and 2) remote methods with very low classification error such as geospatial underwater videography, which is an emerging, low-cost, non-destructive method for documenting small changes at millimeter visual resolution. General adoption of these methods and their further development will require a fundamental cultural change in conservation and management bodies towards the recognition and promotion of requirements of minimal statistical power and precision in the development of international goals for monitoring these valuable resources and the ecological services they provide. PMID:26367863

1/f noise and plastic deformation

NASA Astrophysics Data System (ADS)

Laurson, Lasse

2006-11-01

There is increasing evidence from experiments that plastic deformation in the micro- and meso- scopic scales is an intermittent and heterogeneous process, consisting of avalanches of dislocation activity with a power law distribution of sizes. This has been also discovered in many simulation studies of simplified models. In addition to direct studies of the avalanche statistics, interesting information about the dynamics of the system can be obtained by studying the spectral proper- ties of some associated time series, such as the acoustic emission amplitude in an experiment. We discuss the generic aspects concerning the power spectra of such signals, e.g. the possibility of relating the exponent of the power spectrum to the avalanche exponents of the (dislocation) system.

The Statistical Power of the Cluster Randomized Block Design with Matched Pairs--A Simulation Study

ERIC Educational Resources Information Center

Dong, Nianbo; Lipsey, Mark

2010-01-01

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…

Asking Sensitive Questions: A Statistical Power Analysis of Randomized Response Models

ERIC Educational Resources Information Center

Ulrich, Rolf; Schroter, Hannes; Striegel, Heiko; Simon, Perikles

2012-01-01

This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warner's model, crosswise model, unrelated…

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

NASA Astrophysics Data System (ADS)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.

Implications of clinical trial design on sample size requirements.

PubMed

Leon, Andrew C

2008-07-01

The primary goal in designing a randomized controlled clinical trial (RCT) is to minimize bias in the estimate of treatment effect. Randomized group assignment, double-blinded assessments, and control or comparison groups reduce the risk of bias. The design must also provide sufficient statistical power to detect a clinically meaningful treatment effect and maintain a nominal level of type I error. An attempt to integrate neurocognitive science into an RCT poses additional challenges. Two particularly relevant aspects of such a design often receive insufficient attention in an RCT. Multiple outcomes inflate type I error, and an unreliable assessment process introduces bias and reduces statistical power. Here we describe how both unreliability and multiple outcomes can increase the study costs and duration and reduce the feasibility of the study. The objective of this article is to consider strategies that overcome the problems of unreliability and multiplicity.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, M. H.; Giebel, G.; Nielsen, T. S.; Hahmann, A.; Sørensen, P.; Madsen, H.

2012-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting (WRF) model. Furthermore, the integrated simulation tool will be improved so it can handle simultaneously 10-50 times more turbines than the present ~ 300, as well as additional atmospheric parameters will be included in the model. The WRF data will also be input for a statistical short term prediction model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated prediction tool constitute scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator, and the need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2020, from the current 20%.

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.

Low-dose ionizing radiation increases the mortality risk of solid cancers in nuclear industry workers: A meta-analysis.

PubMed

Qu, Shu-Gen; Gao, Jin; Tang, Bo; Yu, Bo; Shen, Yue-Ping; Tu, Yu

2018-05-01

Low-dose ionizing radiation (LDIR) may increase the mortality of solid cancers in nuclear industry workers, but only few individual cohort studies exist, and the available reports have low statistical power. The aim of the present study was to focus on solid cancer mortality risk from LDIR in the nuclear industry using standard mortality ratios (SMRs) and 95% confidence intervals. A systematic literature search through the PubMed and Embase databases identified 27 studies relevant to this meta-analysis. There was statistical significance for total, solid and lung cancers, with meta-SMR values of 0.88, 0.80, and 0.89, respectively. There was evidence of stochastic effects by IR, but more definitive conclusions require additional analyses using standardized protocols to determine whether LDIR increases the risk of solid cancer-related mortality.

Selection of nontarget arthropod taxa for field research on transgenic insecticidal crops: using empirical data and statistical power.

PubMed

Prasifka, J R; Hellmich, R L; Dively, G P; Higgins, L S; Dixon, P M; Duan, J J

2008-02-01

One of the possible adverse effects of transgenic insecticidal crops is the unintended decline in the abundance of nontarget arthropods. Field trials designed to evaluate potential nontarget effects can be more complex than expected because decisions to conduct field trials and the selection of taxa to include are not always guided by the results of laboratory tests. Also, recent studies emphasize the potential for indirect effects (adverse impacts to nontarget arthropods without feeding directly on plant tissues), which are difficult to predict because of interactions among nontarget arthropods, target pests, and transgenic crops. As a consequence, field studies may attempt to monitor expansive lists of arthropod taxa, making the design of such broad studies more difficult and reducing the likelihood of detecting any negative effects that might be present. To improve the taxonomic focus and statistical rigor of future studies, existing field data and corresponding power analysis may provide useful guidance. Analysis of control data from several nontarget field trials using repeated-measures designs suggests that while detection of small effects may require considerable increases in replication, there are taxa from different ecological roles that are sampled effectively using standard methods. The use of statistical power to guide selection of taxa for nontarget trials reflects scientists' inability to predict the complex interactions among arthropod taxa, particularly when laboratory trials fail to provide guidance on which groups are more likely to be affected. However, scientists still may exercise judgment, including taxa that are not included in or supported by power analyses.

The In vitro Evaluation of the effect of xyliwhite, probiotic, and the conventional toothpastes on the enamel roughness and microhardness.

PubMed

Maden, E Arat; Altun, C; Polat, G Guven; Basak, F

2018-03-01

The aim of this study was to evaluate the effect of fluoride, Xylitol, Probiotic, and Whitening toothpastes on the permanent teeth enamel roughness and microhardness. One hundred and twenty teeth were randomly divided into 2 groups, each group having 60 samples. G1: The group in which enamel roughness was examined (n = 60). G2: The group in which enamel microhardness was examined (n = 60). Then, these groups were randomly divided into 4 groups among themselves (n = 15). Each group was brushed using four different toothpastes for 1 week with a battery-powered toothbrush in the morning and evening for 2 min. Vicker's hardness tester was used to measure the changes in microhardness, and the profilometer was used to measure the changes in surface roughness. No statistically significant differences were found on surface roughness and microhardness values measured after tooth brushing process in group brushed with Colgate MaxFresh toothpaste (P > 0.01). Statistically significant decrease was observed on Vicker's hardness values measured after tooth brushing process in groups brushed with Ipana White Power Carbonate toothpaste, Xyliwhite Toothpaste Gel, and Periobiotic Probiotic Toothpaste (P < 0.01). Statistically significant increase was observed on surface roughness values in groups brushed with Ipana White Power Carbonate toothpaste, Xyliwhite Toothpaste Gel, Periobiotic Probiotic Toothpaste (P < 0.01). As a result, Colgate MaxFresh abrasive-free toothpaste with fluoride has no effect on permanent tooth enamel surface roughness and microhardness. Xyliwhite, Periobiotic, and Ipana White Power Carbonate-containing abrasive toothpastes led to changes negatively on permanent tooth enamel surface roughness and microhardness.

Extreme prices in electricity balancing markets from an approach of statistical physics

NASA Astrophysics Data System (ADS)

Mureddu, Mario; Meyer-Ortmanns, Hildegard

2018-01-01

An increase in energy production from renewable energy sources is viewed as a crucial achievement in most industrialized countries. The higher variability of power production via renewables leads to a rise in ancillary service costs over the power system, in particular costs within the electricity balancing markets, mainly due to an increased number of extreme price spikes. This study analyzes the impact of an increased share of renewable energy sources on the behavior of price and volumes of the Italian balancing market. Starting from configurations of load and power production, which guarantee a stable performance, we implement fluctuations in the load and in renewables; in particular we artificially increase the contribution of renewables as compared to conventional power sources to cover the total load. We then determine the amount of requested energy in the balancing market and its fluctuations, which are induced by production and consumption. Within an approach of agent-based modeling we estimate the resulting energy prices and costs. While their average values turn out to be only slightly affected by an increased contribution from renewables, the probability for extreme price events is shown to increase along with undesired peaks in the costs. Our methodology provides a tool for estimating outliers in prices obtained in the energy balancing market, once data of consumption, production and their typical fluctuations are provided.

A powerful test for Balaam's design.

PubMed

Mori, Joji; Kano, Yutaka

2015-01-01

The crossover trial design (AB/BA design) is often used to compare the effects of two treatments in medical science because it performs within-subject comparisons, which increase the precision of a treatment effect (i.e., a between-treatment difference). However, the AB/BA design cannot be applied in the presence of carryover effects and/or treatments-by-period interaction. In such cases, Balaam's design is a more suitable choice. Unlike the AB/BA design, Balaam's design inflates the variance of an estimate of the treatment effect, thereby reducing the statistical power of tests. This is a serious drawback of the design. Although the variance of parameter estimators in Balaam's design has been extensively studied, the estimators of the treatment effect to improve the inference have received little attention. If the estimate of the treatment effect is obtained by solving the mixed model equations, the AA and BB sequences are excluded from the estimation process. In this study, we develop a new estimator of the treatment effect and a new test statistic using the estimator. The aim is to improve the statistical inference in Balaam's design. Simulation studies indicate that the type I error of the proposed test is well controlled, and that the test is more powerful and has more suitable characteristics than other existing tests when interactions are substantial. The proposed test is also applied to analyze a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Does raising type 1 error rate improve power to detect interactions in linear regression models? A simulation study.

PubMed

Durand, Casey P

2013-01-01

Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

Comparison of isokinetic muscle strength and muscle power by types of warm-up.

PubMed

Sim, Young-Je; Byun, Yong-Hyun; Yoo, Jaehyun

2015-05-01

[Purpose] The purpose of this study was to clarify the influence of static stretching at warm-up on the isokinetic muscle torque (at 60°/sec) and muscle power (at 180°/sec) of the flexor muscle and extensor muscle of the knee joint. [Subjects and Methods] The subjects of this study were 10 healthy students with no medically specific findings. The warm-up group and warm-up with stretching group performed their respective warm-up prior to the isokinetic muscle torque evaluation of the knee joint. One-way ANOVA was performed by randomized block design for each variable. [Results] The results were as follows: First, the flexor peak torque and extensor peak torque of the knee joint tended to decrease at 60°/sec in the warm-up with stretching group compared with the control group and warm-up group, but without statistical significance. Second, extensor power at 180°/sec was also not statistically significant. However, it was found that flexor power increased significantly in the warm-up with stretching group at 180°/sec compared with the control group and warm-up group in which stretching was not performed. [Conclusion] Therefore, it is considered that in healthy adults, warm-up including two sets of stretching for 20 seconds per muscle group does not decrease muscle strength and muscle power.

A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data.

PubMed

Nishiyama, Takeshi; Takahashi, Kunihiko; Tango, Toshiro; Pinto, Dalila; Scherer, Stephen W; Takami, Satoshi; Kishino, Hirohisa

2011-05-26

Several statistical tests have been developed for analyzing genome-wide association data by incorporating gene pathway information in terms of gene sets. Using these methods, hundreds of gene sets are typically tested, and the tested gene sets often overlap. This overlapping greatly increases the probability of generating false positives, and the results obtained are difficult to interpret, particularly when many gene sets show statistical significance. We propose a flexible statistical framework to circumvent these problems. Inspired by spatial scan statistics for detecting clustering of disease occurrence in the field of epidemiology, we developed a scan statistic to extract disease-associated gene clusters from a whole gene pathway. Extracting one or a few significant gene clusters from a global pathway limits the overall false positive probability, which results in increased statistical power, and facilitates the interpretation of test results. In the present study, we applied our method to genome-wide association data for rare copy-number variations, which have been strongly implicated in common diseases. Application of our method to a simulated dataset demonstrated the high accuracy of this method in detecting disease-associated gene clusters in a whole gene pathway. The scan statistic approach proposed here shows a high level of accuracy in detecting gene clusters in a whole gene pathway. This study has provided a sound statistical framework for analyzing genome-wide rare CNV data by incorporating topological information on the gene pathway.

On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

PubMed

Koyama, Shinsuke

2015-07-01

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

Joint probability of statistical success of multiple phase III trials.

PubMed

Zhang, Jianliang; Zhang, Jenny J

2013-01-01

In drug development, after completion of phase II proof-of-concept trials, the sponsor needs to make a go/no-go decision to start expensive phase III trials. The probability of statistical success (PoSS) of the phase III trials based on data from earlier studies is an important factor in that decision-making process. Instead of statistical power, the predictive power of a phase III trial, which takes into account the uncertainty in the estimation of treatment effect from earlier studies, has been proposed to evaluate the PoSS of a single trial. However, regulatory authorities generally require statistical significance in two (or more) trials for marketing licensure. We show that the predictive statistics of two future trials are statistically correlated through use of the common observed data from earlier studies. Thus, the joint predictive power should not be evaluated as a simplistic product of the predictive powers of the individual trials. We develop the relevant formulae for the appropriate evaluation of the joint predictive power and provide numerical examples. Our methodology is further extended to the more complex phase III development scenario comprising more than two (K > 2) trials, that is, the evaluation of the PoSS of at least k₀ (k₀≤ K) trials from a program of K total trials. Copyright © 2013 John Wiley & Sons, Ltd.

Cerebral oscillatory activity during simulated driving using MEG

PubMed Central

Sakihara, Kotoe; Hirata, Masayuki; Ebe, Kazutoshi; Kimura, Kenji; Yi Ryu, Seong; Kono, Yoshiyuki; Muto, Nozomi; Yoshioka, Masako; Yoshimine, Toshiki; Yorifuji, Shiro

2014-01-01

We aimed to examine cerebral oscillatory differences associated with psychological processes during simulated car driving. We recorded neuromagnetic signals in 14 healthy volunteers using magnetoencephalography (MEG) during simulated driving. MEG data were analyzed using synthetic aperture magnetometry to detect the spatial distribution of cerebral oscillations. Group effects between subjects were analyzed statistically using a non-parametric permutation test. Oscillatory differences were calculated by comparison between “passive viewing” and “active driving.” “Passive viewing” was the baseline, and oscillatory differences during “active driving” showed an increase or decrease in comparison with a baseline. Power increase in the theta band was detected in the superior frontal gyrus (SFG) during active driving. Power decreases in the alpha, beta, and low gamma bands were detected in the right inferior parietal lobe (IPL), left postcentral gyrus (PoCG), middle temporal gyrus (MTG), and posterior cingulate gyrus (PCiG) during active driving. Power increase in the theta band in the SFG may play a role in attention. Power decrease in the right IPL may reflect selectively divided attention and visuospatial processing, whereas that in the left PoCG reflects sensorimotor activation related to driving manipulation. Power decreases in the MTG and PCiG may be associated with object recognition. PMID:25566017

Power of tests for comparing trend curves with application to national immunization survey (NIS).

PubMed

Zhao, Zhen

2011-02-28

To develop statistical tests for comparing trend curves of study outcomes between two socio-demographic strata across consecutive time points, and compare statistical power of the proposed tests under different trend curves data, three statistical tests were proposed. For large sample size with independent normal assumption among strata and across consecutive time points, the Z and Chi-square test statistics were developed, which are functions of outcome estimates and the standard errors at each of the study time points for the two strata. For small sample size with independent normal assumption, the F-test statistic was generated, which is a function of sample size of the two strata and estimated parameters across study period. If two trend curves are approximately parallel, the power of Z-test is consistently higher than that of both Chi-square and F-test. If two trend curves cross at low interaction, the power of Z-test is higher than or equal to the power of both Chi-square and F-test; however, at high interaction, the powers of Chi-square and F-test are higher than that of Z-test. The measurement of interaction of two trend curves was defined. These tests were applied to the comparison of trend curves of vaccination coverage estimates of standard vaccine series with National Immunization Survey (NIS) 2000-2007 data. Copyright © 2011 John Wiley & Sons, Ltd.

Increasing point-count duration increases standard error

USGS Publications Warehouse

Smith, W.P.; Twedt, D.J.; Hamel, P.B.; Ford, R.P.; Wiedenfeld, D.A.; Cooper, R.J.

1998-01-01

We examined data from point counts of varying duration in bottomland forests of west Tennessee and the Mississippi Alluvial Valley to determine if counting interval influenced sampling efficiency. Estimates of standard error increased as point count duration increased both for cumulative number of individuals and species in both locations. Although point counts appear to yield data with standard errors proportional to means, a square root transformation of the data may stabilize the variance. Using long (>10 min) point counts may reduce sample size and increase sampling error, both of which diminish statistical power and thereby the ability to detect meaningful changes in avian populations.

Predictor sort sampling and one-sided confidence bounds on quantiles

Treesearch

Steve Verrill; Victoria L. Herian; David W. Green

2002-01-01

Predictor sort experiments attempt to make use of the correlation between a predictor that can be measured prior to the start of an experiment and the response variable that we are investigating. Properly designed and analyzed, they can reduce necessary sample sizes, increase statistical power, and reduce the lengths of confidence intervals. However, if the non- random...

Statistical Power in Experimental Audit Studies: Cautions and Calculations for Matched Tests With Nominal Outcomes

ERIC Educational Resources Information Center

Vuolo, Mike; Uggen, Christopher; Lageson, Sarah

2016-01-01

Given their capacity to identify causal relationships, experimental audit studies have grown increasingly popular in the social sciences. Typically, investigators send fictitious auditors who differ by a key factor (e.g., race) to particular experimental units (e.g., employers) and then compare treatment and control groups on a dichotomous outcome…

Turning the Potential Liability of Large Enrollment Laboratory Science Courses into an Asset

ERIC Educational Resources Information Center

Johnson, Dan; Levy, Foster; Karsai, Istvan; Stroud, Kimberly

2006-01-01

Data sharing among multiple lab sections increases statistical power of data analyses and informs student-generated hypotheses. We describe how to collect, organize, and manage data to support replicate and rolling inquiry models, with three illustrative examples of activities from a population-level biology course for science majors. (Contains 1…

Optimal Sample Size Determinations for the Heteroscedastic Two One-Sided Tests of Mean Equivalence: Design Schemes and Software Implementations

ERIC Educational Resources Information Center

Jan, Show-Li; Shieh, Gwowen

2017-01-01

Equivalence assessment is becoming an increasingly important topic in many application areas including behavioral and social sciences research. Although there exist more powerful tests, the two one-sided tests (TOST) procedure is a technically transparent and widely accepted method for establishing statistical equivalence. Alternatively, a direct…

Hybrid two-dimensional navigator correction: a new technique to suppress respiratory-induced physiological noise in multi-shot echo-planar functional MRI

PubMed Central

Barry, Robert L.; Klassen, L. Martyn; Williams, Joy M.; Menon, Ravi S.

2008-01-01

A troublesome source of physiological noise in functional magnetic resonance imaging (fMRI) is due to the spatio-temporal modulation of the magnetic field in the brain caused by normal subject respiration. fMRI data acquired using echo-planar imaging is very sensitive to these respiratory-induced frequency offsets, which cause significant geometric distortions in images. Because these effects increase with main magnetic field, they can nullify the gains in statistical power expected by the use of higher magnetic fields. As a study of existing navigator correction techniques for echo-planar fMRI has shown that further improvements can be made in the suppression of respiratory-induced physiological noise, a new hybrid two-dimensional (2D) navigator is proposed. Using a priori knowledge of the slow spatial variations of these induced frequency offsets, 2D field maps are constructed for each shot using spatial frequencies between ±0.5 cm−1 in k-space. For multi-shot fMRI experiments, we estimate that the improvement of hybrid 2D navigator correction over the best performance of one-dimensional navigator echo correction translates into a 15% increase in the volume of activation, 6% and 10% increases in the maximum and average t-statistics, respectively, for regions with high t-statistics, and 71% and 56% increases in the maximum and average t-statistics, respectively, in regions with low t-statistics due to contamination by residual physiological noise. PMID:18024159

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

PubMed Central

Gray, Alastair

2017-01-01

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

Critical Fluctuations in Cortical Models Near Instability

PubMed Central

Aburn, Matthew J.; Holmes, C. A.; Roberts, James A.; Boonstra, Tjeerd W.; Breakspear, Michael

2012-01-01

Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human electroencephalography (EEG), however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where non-linearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power law scaling, and bistable switching have been suggested as generic indicators of the approach to bifurcation in non-linear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen–Rit model) of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations. PMID:22952464

Magnetic Field Fluctuations in Saturn's Magnetosphere

NASA Astrophysics Data System (ADS)

von Papen, Michael; Saur, Joachim; Alexandrova, Olga

2013-04-01

In the framework of turbulence, we analyze the statistical properties of magnetic field fluctuations measured by the Cassini spacecraft inside Saturn's plasma sheet. In the spacecraft-frame power spectra of the fluctuations we identify two power-law spectral ranges seperated by a spectral break around ion gyro-frequencies of O+ and H+. The spectral indices of the low frequency power-law are found to be between 5-3 (for fully developed cascades) and 1 (during energy input on the corresponding scales). Above the spectral break there is a constant power-law with mean spectral index ~2.5 indicating a permament turbulent cascade in the kinetic range. An increasing non-gaussian probability density with frequency indicates the build-up of intermittency. Correlations of plasma parameters with the spectral indices are examined and it is found that the power-law slope depends on background magnetic field strength and plasma beta.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

A General Framework for Power Analysis to Detect the Moderator Effects in Two- and Three-Level Cluster Randomized Trials

ERIC Educational Resources Information Center

Dong, Nianbo; Spybrook, Jessaca; Kelcey, Ben

2016-01-01

The purpose of this study is to propose a general framework for power analyses to detect the moderator effects in two- and three-level cluster randomized trials (CRTs). The study specifically aims to: (1) develop the statistical formulations for calculating statistical power, minimum detectable effect size (MDES) and its confidence interval to…

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

PubMed

Rüeger, Sina; McDaid, Aaron; Kutalik, Zoltán

2018-05-01

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

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

PubMed Central

2018-01-01

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

Invited Article: Visualisation of extreme value events in optical communications

NASA Astrophysics Data System (ADS)

Derevyanko, Stanislav; Redyuk, Alexey; Vergeles, Sergey; Turitsyn, Sergei

2018-06-01

Fluctuations of a temporal signal propagating along long-haul transoceanic scale fiber links can be visualised in the spatio-temporal domain drawing visual analogy with ocean waves. Substantial overlapping of information symbols or use of multi-frequency signals leads to strong statistical deviations of local peak power from an average signal power level. We consider long-haul optical communication systems from this unusual angle, treating them as physical systems with a huge number of random statistical events, including extreme value fluctuations that potentially might affect the quality of data transmission. We apply the well-established concepts of adaptive wavefront shaping used in imaging through turbid medium to detect the detrimental phase modulated sequences in optical communications that can cause extreme power outages (rare optical waves of ultra-high amplitude) during propagation down the ultra-long fiber line. We illustrate the concept by a theoretical analysis of rare events of high-intensity fluctuations—optical freak waves, taking as an example an increasingly popular optical frequency division multiplexing data format where the problem of high peak to average power ratio is the most acute. We also show how such short living extreme value spikes in the optical data streams are affected by nonlinearity and demonstrate the negative impact of such events on the system performance.

Simulation and evaluation of phase noise for optical amplification using semiconductor optical amplifiers in DPSK applications

NASA Astrophysics Data System (ADS)

Hong, Wei; Huang, Dexiu; Zhang, Xinliang; Zhu, Guangxi

2008-01-01

A thorough simulation and evaluation of phase noise for optical amplification using semiconductor optical amplifier (SOA) is very important for predicting its performance in differential phase-shift keyed (DPSK) applications. In this paper, standard deviation and probability distribution of differential phase noise at the SOA output are obtained from the statistics of simulated differential phase noise. By using a full-wave model of SOA, the noise performance in the entire operation range can be investigated. It is shown that nonlinear phase noise substantially contributes to the total phase noise in case of a noisy signal amplified by a saturated SOA and the nonlinear contribution is larger with shorter SOA carrier lifetime. It is also shown that Gaussian distribution can be useful as a good approximation of the total differential phase noise statistics in the whole operation range. Power penalty due to differential phase noise is evaluated using a semi-analytical probability density function (PDF) of receiver noise. Obvious increase of power penalty at high signal input powers can be found for low input OSNR, which is due to both the large nonlinear differential phase noise and the dependence of BER vs. receiving power curvature on differential phase noise standard deviation.

STATISTICAL COMPARISON BETWEEN PORES AND SUNSPOTS BY USING SDO/HMI

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

Cho, I.-H.; Cho, K.-S.; Bong, S.-C.

2015-09-20

We carried out an extensive statistical study of the properties of pores and sunspots, and investigated the relationship among their physical parameters such as size, intensity, magnetic field, and the line-of-sight (LOS) velocity in the umbrae. For this, we classified 9881 samples into three groups of pores, transitional sunspots, and mature sunspots. As a result, (1) we find that the total magnetic flux inside the umbra of pores, transitional sunspots, and mature sunspots increases proportionally to the powers of the area and the power indices in the three groups significantly differ from each other. (2) The umbral area distribution ofmore » each group shows a Gaussian distribution and they are clearly separated, displaying three distinct peak values. All of the quantities significantly overlap among the three groups. (3) The umbral intensity shows a rapid decrease with increasing area, and their magnetic field strength shows a rapid increase with decreasing intensity. (4) The LOS velocity in pores is predominantly redshifted and its magnitude decreases with increasing magnetic field strength. The decreasing trend becomes nearly constant with marginal blueshift in the case of mature sunspots. The dispersion of LOS velocities in mature sunspots is significantly suppressed compared to pores. From our results, we conclude that the three groups have different characteristics in their area, intensity, magnetic field, and LOS velocity as well in their relationships.« less

Acute nonlymphocytic leukemia and residential exposure to power frequency magnetic fields

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

Severson, R.K.

1986-01-01

A population-based case-control study of adult acute nonlymphocytic leukemia (ANLL) and residential exposure to power frequency magnetic fields was conducted in King, Pierce and Snohomish Counties in Washington state. Of 164 cases who were diagnosed from January 1, 1981 through December 31, 1984, 114 were interviewed. Controls were selected from the study area on the basis of random digit dialing and frequency matched to the cases by age and sex. Analyses were undertaken to evaluate whether exposure to high levels of power frequency magnetic fields in the residence were associated with an increased risk of ANLL. Neither the directly measuredmore » magnetic fields nor the surrogate values based on the wiring configurations were associated with ANLL. Additional analyses suggested that persons with prior allergies were at decreased risk of acute myelocytic leukemia (AML). Also, persons with prior autoimmune diseases were at increased risk of AML. The increase in AML risk in rheumatoid arthritics was of borderline statistical significance. Finally, cigarette smoking was associated with an increased risk of AML. The risk of AML increased significantly with the number of years of cigarette smoking.« less

Histologic and photonic evaluation of a pulsed Nd:YAG laser for ablation of subcutaneous adipose tissue.

PubMed

Ichikawa, Kota; Tanino, Ryuzaburo; Wakaki, Moriaki

2006-12-20

Although various lasers are available, few of them are applicable in liposculpture. Laser interaction with fat tissue has not also been well documented. The aim of our study was to gather basic data on laser absorption in fat tissue and to analyze the relationship between laser energy and lipolysis for development of a more effective laser system. The transmittance rate in human fat specimens was measured by a spectrophotometer to determine the optimum wavelength. The absorption coefficient was used to evaluate laser absorption at a wavelength of 1064 nm. Areas of heat degeneration and evaporation were measured by scanning electron microscopy. The relation between laser energy and the areas was analyzed statistically among low-power and high-power groups and controls. Energy dispersion at the fiber tip was investigated and analyzed statistically using the far field pattern. A graph of the absorption rate at wavelengths from 400 to 2400 nm showed a peak near 1700 nm and increases at wavelengths over 2000 nm. The formula gave as an absorption coefficient of 0.4 cm(-1), and involvement of the photo-acoustic effect and non-linear effect with short-pulse and high-peak energy was suggested. Findings of tissue evaporation, destruction, heat coagulation, and rupture of cell membrane were more frequently seen in irradiated specimens than in controls in scanning electron microscopy. The destroyed area in the low-power irradiated groups was significantly larger than that of controls in the statistical analysis. The affected area in the high-power irradiated groups was significantly larger than that of low-power specimens. Energy was concentrated at the tip with laser coherency. Energy at the oblique-cut tip was statistically lower than that at the normal tip, revealing that durability and maintenance of the fiber tip is essential to maintain energy levels in clinical practice. This study is the first to demonstrate the histologic and photonic relationship of energy absorption and lipolysis using a pulsed Nd:YAG laser. The results will be useful for research and development of a more effective laser system for liposculpture.

Detecting Genomic Clustering of Risk Variants from Sequence Data: Cases vs. Controls

PubMed Central

Schaid, Daniel J.; Sinnwell, Jason P.; McDonnell, Shannon K.; Thibodeau, Stephen N.

2013-01-01

As the ability to measure dense genetic markers approaches the limit of the DNA sequence itself, taking advantage of possible clustering of genetic variants in, and around, a gene would benefit genetic association analyses, and likely provide biological insights. The greatest benefit might be realized when multiple rare variants cluster in a functional region. Several statistical tests have been developed, one of which is based on the popular Kulldorff scan statistic for spatial clustering of disease. We extended another popular spatial clustering method – Tango’s statistic – to genomic sequence data. An advantage of Tango’s method is that it is rapid to compute, and when single test statistic is computed, its distribution is well approximated by a scaled chi-square distribution, making computation of p-values very rapid. We compared the Type-I error rates and power of several clustering statistics, as well as the omnibus sequence kernel association test (SKAT). Although our version of Tango’s statistic, which we call “Kernel Distance” statistic, took approximately half the time to compute than the Kulldorff scan statistic, it had slightly less power than the scan statistic. Our results showed that the Ionita-Laza version of Kulldorff’s scan statistic had the greatest power over a range of clustering scenarios. PMID:23842950

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.

PubMed

Egbewale, Bolaji E; Lewis, Martyn; Sim, Julius

2014-04-09

Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126,000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

PubMed Central

2014-01-01

Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

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

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed tomore » estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.« less

On the structure and phase transitions of power-law Poissonian ensembles

NASA Astrophysics Data System (ADS)

Eliazar, Iddo; Oshanin, Gleb

2012-10-01

Power-law Poissonian ensembles are Poisson processes that are defined on the positive half-line, and that are governed by power-law intensities. Power-law Poissonian ensembles are stochastic objects of fundamental significance; they uniquely display an array of fractal features and they uniquely generate a span of important applications. In this paper we apply three different methods—oligarchic analysis, Lorenzian analysis and heterogeneity analysis—to explore power-law Poissonian ensembles. The amalgamation of these analyses, combined with the topology of power-law Poissonian ensembles, establishes a detailed and multi-faceted picture of the statistical structure and the statistical phase transitions of these elemental ensembles.

Power spectra as a diagnostic tool in probing statistical/nonstatistical behavior in unimolecular reactions

NASA Astrophysics Data System (ADS)

Chang, Xiaoyen Y.; Sewell, Thomas D.; Raff, Lionel M.; Thompson, Donald L.

1992-11-01

The possibility of utilizing different types of power spectra obtained from classical trajectories as a diagnostic tool to identify the presence of nonstatistical dynamics is explored by using the unimolecular bond-fission reactions of 1,2-difluoroethane and the 2-chloroethyl radical as test cases. In previous studies, the reaction rates for these systems were calculated by using a variational transition-state theory and classical trajectory methods. A comparison of the results showed that 1,2-difluoroethane is a nonstatistical system, while the 2-chloroethyl radical behaves statistically. Power spectra for these two systems have been generated under various conditions. The characteristics of these spectra are as follows: (1) The spectra for the 2-chloroethyl radical are always broader and more coupled to other modes than is the case for 1,2-difluoroethane. This is true even at very low levels of excitation. (2) When an internal energy near or above the dissociation threshold is initially partitioned into a local C-H stretching mode, the power spectra for 1,2-difluoroethane broaden somewhat, but discrete and somewhat isolated bands are still clearly evident. In contrast, the analogous power spectra for the 2-chloroethyl radical exhibit a near complete absence of isolated bands. The general appearance of the spectrum suggests a very high level of mode-to-mode coupling, large intramolecular vibrational energy redistribution (IVR) rates, and global statistical behavior. (3) The appearance of the power spectrum for the 2-chloroethyl radical is unaltered regardless of whether the initial C-H excitation is in the CH2 or the CH2Cl group. This result also suggests statistical behavior. These results are interpreted to mean that power spectra may be used as a diagnostic tool to assess the statistical character of a system. The presence of a diffuse spectrum exhibiting a nearly complete loss of isolated structures indicates that the dissociation dynamics of the molecule will be well described by statistical theories. If, however, the power spectrum maintains its discrete, isolated character, as is the case for 1,2-difluoroethane, the opposite conclusion is suggested. Since power spectra are very easily computed, this diagnostic method may prove to be useful.

Mysid (Mysidopsis bahia) life-cycle test: Design comparisons and assessment

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

Lussier, S.M.; Champlin, D.; Kuhn, A.

1996-12-31

This study examines ASTM Standard E1191-90, ``Standard Guide for Conducting Life-cycle Toxicity Tests with Saltwater Mysids,`` 1990, using Mysidopsis bahia, by comparing several test designs to assess growth, reproduction, and survival. The primary objective was to determine the most labor efficient and statistically powerful test design for the measurement of statistically detectable effects on biologically sensitive endpoints. Five different test designs were evaluated varying compartment size, number of organisms per compartment and sex ratio. Results showed that while paired organisms in the ASTM design had the highest rate of reproduction among designs tested, no individual design had greater statistical powermore » to detect differences in reproductive effects. Reproduction was not statistically different between organisms paired in the ASTM design and those with randomized sex ratios using larger test compartments. These treatments had numerically higher reproductive success and lower within tank replicate variance than treatments using smaller compartments where organisms were randomized, or had a specific sex ratio. In this study, survival and growth were not statistically different among designs tested. Within tank replicate variability can be reduced by using many exposure compartments with pairs, or few compartments with many organisms in each. While this improves variance within replicate chambers, it does not strengthen the power of detection among treatments in the test. An increase in the number of true replicates (exposure chambers) to eight will have the effect of reducing the percent detectable difference by a factor of two.« less

MODELING THE TIME VARIABILITY OF SDSS STRIPE 82 QUASARS AS A DAMPED RANDOM WALK

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

MacLeod, C. L.; Ivezic, Z.; Bullock, E.

2010-10-01

We model the time variability of {approx}9000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk (DRW). Using 2.7 million photometric measurements collected over 10 yr, we confirm the results of Kelly et al. and Kozlowski et al. that this model can explain quasar light curves at an impressive fidelity level (0.01-0.02 mag). The DRW model provides a simple, fast (O(N) for N data points), and powerful statistical description of quasar light curves by a characteristic timescale ({tau}) and an asymptotic rms variability on long timescales (SF{sub {infinity}}). We searched for correlations between these two variability parametersmore » and physical parameters such as luminosity and black hole mass, and rest-frame wavelength. Our analysis shows SF{sub {infinity}} to increase with decreasing luminosity and rest-frame wavelength as observed previously, and without a correlation with redshift. We find a correlation between SF{sub {infinity}} and black hole mass with a power-law index of 0.18 {+-} 0.03, independent of the anti-correlation with luminosity. We find that {tau} increases with increasing wavelength with a power-law index of 0.17, remains nearly constant with redshift and luminosity, and increases with increasing black hole mass with a power-law index of 0.21 {+-} 0.07. The amplitude of variability is anti-correlated with the Eddington ratio, which suggests a scenario where optical fluctuations are tied to variations in the accretion rate. However, we find an additional dependence on luminosity and/or black hole mass that cannot be explained by the trend with Eddington ratio. The radio-loudest quasars have systematically larger variability amplitudes by about 30%, when corrected for the other observed trends, while the distribution of their characteristic timescale is indistinguishable from that of the full sample. We do not detect any statistically robust differences in the characteristic timescale and variability amplitude between the full sample and the small subsample of quasars detected by ROSAT. Our results provide a simple quantitative framework for generating mock quasar light curves, such as currently used in LSST image simulations.« less

ICRH system performance during ITER-Like Wall operations at JET and the outlook for DT campaign

NASA Astrophysics Data System (ADS)

Monakhov, Igor; Blackman, Trevor; Dumortier, Pierre; Durodié, Frederic; Jacquet, Philippe; Lerche, Ernesto; Noble, Craig

2017-10-01

Performance of JET ICRH system since installation of the metal ITER-Like Wall (ILW) has been assessed statistically. The data demonstrate steady increase of the RF power coupled to plasmas over recent years with the maximum pulse-average and peak values exceeding respectively 6MW and 8MW in 2016. Analysis and extrapolation of power capabilities of conventional JET ICRH antennas is provided and key performance-limiting factors are discussed. The RF plant operational frequency options are presented highlighting the issues of efficient ICRH application within a foreseeable range of DT plasma scenarios.

Age-Associated Changes in the Spectral and Statistical Parameters of Surface Electromyogram of Tibialis Anterior

PubMed Central

2016-01-01

Age-related neuromuscular change of Tibialis Anterior (TA) is a leading cause of muscle strength decline among the elderly. This study has established the baseline for age-associated changes in sEMG of TA at different levels of voluntary contraction. We have investigated the use of Gaussianity and maximal power of the power spectral density (PSD) as suitable features to identify age-associated changes in the surface electromyogram (sEMG). Eighteen younger (20–30 years) and 18 older (60–85 years) cohorts completed two trials of isometric dorsiflexion at four different force levels between 10% and 50% of the maximal voluntary contraction. Gaussianity and maximal power of the PSD of sEMG were determined. Results show a significant increase in sEMG's maximal power of the PSD and Gaussianity with increase in force for both cohorts. It was also observed that older cohorts had higher maximal power of the PSD and lower Gaussianity. These age-related differences observed in the PSD and Gaussianity could be due to motor unit remodelling. This can be useful for noninvasive tracking of age-associated neuromuscular changes. PMID:27610379

Low-dose ionizing radiation increases the mortality risk of solid cancers in nuclear industry workers: A meta-analysis

PubMed Central

Qu, Shu-Gen; Gao, Jin; Tang, Bo; Yu, Bo; Shen, Yue-Ping; Tu, Yu

2018-01-01

Low-dose ionizing radiation (LDIR) may increase the mortality of solid cancers in nuclear industry workers, but only few individual cohort studies exist, and the available reports have low statistical power. The aim of the present study was to focus on solid cancer mortality risk from LDIR in the nuclear industry using standard mortality ratios (SMRs) and 95% confidence intervals. A systematic literature search through the PubMed and Embase databases identified 27 studies relevant to this meta-analysis. There was statistical significance for total, solid and lung cancers, with meta-SMR values of 0.88, 0.80, and 0.89, respectively. There was evidence of stochastic effects by IR, but more definitive conclusions require additional analyses using standardized protocols to determine whether LDIR increases the risk of solid cancer-related mortality. PMID:29725540

Powerful Statistical Inference for Nested Data Using Sufficient Summary Statistics

PubMed Central

Dowding, Irene; Haufe, Stefan

2018-01-01

Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests against group-level null hypotheses. A common approach is to summarize subject-level data by a single quantity per subject, which is often the mean or the difference between class means, and treat these as samples in a group-level t-test. This “naive” approach is, however, suboptimal in terms of statistical power, as it ignores information about the intra-subject variance. To address this issue, we review several approaches to deal with nested data, with a focus on methods that are easy to implement. With what we call the sufficient-summary-statistic approach, we highlight a computationally efficient technique that can improve statistical power by taking into account within-subject variances, and we provide step-by-step instructions on how to apply this approach to a number of frequently-used measures of effect size. The properties of the reviewed approaches and the potential benefits over a group-level t-test are quantitatively assessed on simulated data and demonstrated on EEG data from a simulated-driving experiment. PMID:29615885

Temperature rise induced by some light emitting diode and quartz-tungsten-halogen curing units.

PubMed

Asmussen, Erik; Peutzfeldt, Anne

2005-02-01

Because of the risk of thermal damage to the pulp, the temperature rise induced by light-curing units should not be too high. LED (light emitting diode) curing units have the main part of their irradiation in the blue range and have been reported to generate less heat than QTH (quartz-tungsten-halogen) curing units. This study had two aims: first, to measure the temperature rise induced by ten LED and three QTH curing units; and, second, to relate the measured temperature rise to the power density of the curing units. The light-induced temperature rise was measured by means of a thermocouple embedded in a small cylinder of resin composite. The power density was measured by using a dental radiometer. For LED units, the temperature rise increased with increasing power density, in a statistically significant manner. Two of the three QTH curing units investigated resulted in a higher temperature rise than LED curing units of the same power density. Previous findings, that LED curing units induce less temperature rise than QTH units, does not hold true in general.

Exercise reduces depressive symptoms in adults with arthritis: Evidential value.

PubMed

Kelley, George A; Kelley, Kristi S

2016-07-12

To determine whether evidential value exists that exercise reduces depression in adults with arthritis and other rheumatic conditions. Utilizing data derived from a prior meta-analysis of 29 randomized controlled trials comprising 2449 participants (1470 exercise, 979 control) with fibromyalgia, osteoarthritis, rheumatoid arthritis or systemic lupus erythematosus, a new method, P -curve, was utilized to assess for evidentiary worth as well as dismiss the possibility of discriminating reporting of statistically significant results regarding exercise and depression in adults with arthritis and other rheumatic conditions. Using the method of Stouffer, Z -scores were calculated to examine selective-reporting bias. An alpha ( P ) value < 0.05 was deemed statistically significant. In addition, average power of the tests included in P -curve, adjusted for publication bias, was calculated. Fifteen of 29 studies (51.7%) with exercise and depression results were statistically significant ( P < 0.05) while none of the results were statistically significant with respect to exercise increasing depression in adults with arthritis and other rheumatic conditions. Right-skew to dismiss selective reporting was identified ( Z = -5.28, P < 0.0001). In addition, the included studies did not lack evidential value ( Z = 2.39, P = 0.99), nor did they lack evidential value and were P -hacked ( Z = 5.28, P > 0.99). The relative frequencies of P -values were 66.7% at 0.01, 6.7% each at 0.02 and 0.03, 13.3% at 0.04 and 6.7% at 0.05. The average power of the tests included in P -curve, corrected for publication bias, was 69%. Diagnostic plot results revealed that the observed power estimate was a better fit than the alternatives. Evidential value results provide additional support that exercise reduces depression in adults with arthritis and other rheumatic conditions.

Exercise reduces depressive symptoms in adults with arthritis: Evidential value

PubMed Central

Kelley, George A; Kelley, Kristi S

2016-01-01

AIM To determine whether evidential value exists that exercise reduces depression in adults with arthritis and other rheumatic conditions. METHODS Utilizing data derived from a prior meta-analysis of 29 randomized controlled trials comprising 2449 participants (1470 exercise, 979 control) with fibromyalgia, osteoarthritis, rheumatoid arthritis or systemic lupus erythematosus, a new method, P-curve, was utilized to assess for evidentiary worth as well as dismiss the possibility of discriminating reporting of statistically significant results regarding exercise and depression in adults with arthritis and other rheumatic conditions. Using the method of Stouffer, Z-scores were calculated to examine selective-reporting bias. An alpha (P) value < 0.05 was deemed statistically significant. In addition, average power of the tests included in P-curve, adjusted for publication bias, was calculated. RESULTS Fifteen of 29 studies (51.7%) with exercise and depression results were statistically significant (P < 0.05) while none of the results were statistically significant with respect to exercise increasing depression in adults with arthritis and other rheumatic conditions. Right-skew to dismiss selective reporting was identified (Z = −5.28, P < 0.0001). In addition, the included studies did not lack evidential value (Z = 2.39, P = 0.99), nor did they lack evidential value and were P-hacked (Z = 5.28, P > 0.99). The relative frequencies of P-values were 66.7% at 0.01, 6.7% each at 0.02 and 0.03, 13.3% at 0.04 and 6.7% at 0.05. The average power of the tests included in P-curve, corrected for publication bias, was 69%. Diagnostic plot results revealed that the observed power estimate was a better fit than the alternatives. CONCLUSION Evidential value results provide additional support that exercise reduces depression in adults with arthritis and other rheumatic conditions. PMID:27489782

Statistical performance and information content of time lag analysis and redundancy analysis in time series modeling.

PubMed

Angeler, David G; Viedma, Olga; Moreno, José M

2009-11-01

Time lag analysis (TLA) is a distance-based approach used to study temporal dynamics of ecological communities by measuring community dissimilarity over increasing time lags. Despite its increased use in recent years, its performance in comparison with other more direct methods (i.e., canonical ordination) has not been evaluated. This study fills this gap using extensive simulations and real data sets from experimental temporary ponds (true zooplankton communities) and landscape studies (landscape categories as pseudo-communities) that differ in community structure and anthropogenic stress history. Modeling time with a principal coordinate of neighborhood matrices (PCNM) approach, the canonical ordination technique (redundancy analysis; RDA) consistently outperformed the other statistical tests (i.e., TLAs, Mantel test, and RDA based on linear time trends) using all real data. In addition, the RDA-PCNM revealed different patterns of temporal change, and the strength of each individual time pattern, in terms of adjusted variance explained, could be evaluated, It also identified species contributions to these patterns of temporal change. This additional information is not provided by distance-based methods. The simulation study revealed better Type I error properties of the canonical ordination techniques compared with the distance-based approaches when no deterministic component of change was imposed on the communities. The simulation also revealed that strong emphasis on uniform deterministic change and low variability at other temporal scales is needed to result in decreased statistical power of the RDA-PCNM approach relative to the other methods. Based on the statistical performance of and information content provided by RDA-PCNM models, this technique serves ecologists as a powerful tool for modeling temporal change of ecological (pseudo-) communities.

Consequences of Base Time for Redundant Signals Experiments

PubMed Central

Townsend, James T.; Honey, Christopher

2007-01-01

We report analytical and computational investigations into the effects of base time on the diagnosticity of two popular theoretical tools in the redundant signals literature: (1) the race model inequality and (2) the capacity coefficient. We show analytically and without distributional assumptions that the presence of base time decreases the sensitivity of both of these measures to model violations. We further use simulations to investigate the statistical power model selection tools based on the race model inequality, both with and without base time. Base time decreases statistical power, and biases the race model test toward conservatism. The magnitude of this biasing effect increases as we increase the proportion of total reaction time variance contributed by base time. We marshal empirical evidence to suggest that the proportion of reaction time variance contributed by base time is relatively small, and that the effects of base time on the diagnosticity of our model-selection tools are therefore likely to be minor. However, uncertainty remains concerning the magnitude and even the definition of base time. Experimentalists should continue to be alert to situations in which base time may contribute a large proportion of the total reaction time variance. PMID:18670591

Spatial Pattern Classification for More Accurate Forecasting of Variable Energy Resources

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Hayes, C.; Collier, C.

2014-12-01

The accuracy of solar and wind forecasts is becoming increasingly essential as grid operators continue to integrate additional renewable generation onto the electric grid. Forecast errors affect rate payers, grid operators, wind and solar plant maintenance crews and energy traders through increases in prices, project down time or lost revenue. While extensive and beneficial efforts were undertaken in recent years to improve physical weather models for a broad spectrum of applications these improvements have generally not been sufficient to meet the accuracy demands of system planners. For renewables, these models are often used in conjunction with additional statistical models utilizing both meteorological observations and the power generation data. Forecast accuracy can be dependent on specific weather regimes for a given location. To account for these dependencies it is important that parameterizations used in statistical models change as the regime changes. An automated tool, based on an artificial neural network model, has been developed to identify different weather regimes as they impact power output forecast accuracy at wind or solar farms. In this study, improvements in forecast accuracy were analyzed for varying time horizons for wind farms and utility-scale PV plants located in different geographical regions.

915MHz microwave ablation with high output power in in vivo porcine spleens.

PubMed

Gao, Yongyan; Wang, Yang; Duan, Yaqi; Li, Chunling; Sun, Yuanyuan; Zhang, Dakun; Lu, Tong; Liang, Ping

2010-07-01

The purpose of this study was to evaluate the efficacy of 915 MHz microwave (MW) ablation with high output power in in vivo porcine spleens. MW ablations were performed in 9 porcine spleens with an internally cooled 915 MHz antenna. Thermocouples were placed at 5, 10, 15, 20 mm away from the antenna to measure temperatures in real-time during MW emission. The energy was applied for 10 min at high output power of 60 W, 70 W or 80 W. Gross specimens were sectioned and measured to determine ablation size. Representative areas were examined by light microscopy and electron microscopy. Coagulation sizes and temperatures were compared among the three power groups. Hematoxylin-eosin staining showed irreversible necrosis in the splenic coagulation area after MW ablation. As the power was increased, long-axis diameter enlarged significantly (p<.05). Short-axis diameter also tended to increase, but there were no statistical difference (p>.05). The coagulation size of long-axis and short-axis diameter with 80 W in vivo spleen ablation was 6.43+/-0.52 and 4.95+/-0.30 cm, respectively. With the increase of output power, maximum temperatures at 5, 10, 15, 20 mm from the antenna were increased accordingly (p<.05). The maximum temperature with 80 W at 5 and 20 mm from the antenna reached 146.17+/-6.65 and 72.38+/-4.23 degrees C respectively. With internally cooled antenna and high output power, 915 MHz MW ablation in the spleen could produce irreversible tissue necrosis of clinical significance. MW ablation may be used as a promising minimally invasive method for the treatment of splenic diseases. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Affected sib pair tests in inbred populations.

PubMed

Liu, W; Weir, B S

2004-11-01

The affected-sib-pair (ASP) method for detecting linkage between a disease locus and marker loci was first established 50 years ago, and since then numerous modifications have been made. We modify two identity-by-state (IBS) test statistics of Lange (Lange, 1986a, 1986b) to allow for inbreeding in the population. We evaluate the power and false positive rates of the modified tests under three disease models, using simulated data. Before estimating false positive rates, we demonstrate that IBS tests are tests of both linkage and linkage disequilibrium between marker and disease loci. Therefore, the null hypothesis of IBS tests should be no linkage and no LD. When the population inbreeding coefficient is large, the false positive rates of Lange's tests become much larger than the nominal value, while those of our modified tests remain close to the nominal value. To estimate power with a controlled false positive rate, we choose the cutoff values based on simulated datasets under the null hypothesis, so that both Lange's tests and the modified tests generate same false positive rate. The powers of Lange's z-test and our modified z-test are very close and do not change much with increasing inbreeding. The power of the modified chi-square test also stays stable when the inbreeding coefficient increases. However, the power of Lange's chi-square test increases with increasing inbreeding, and is larger than that of our modified chi-square test for large inbreeding coefficients. The power is high under a recessive disease model for both Lange's tests and the modified tests, though the power is low for additive and dominant disease models. Allowing for inbreeding is therefore appropriate, at least for diseases known to be recessive.

Task Context Influences Brain Activation during Music Listening

PubMed Central

Markovic, Andjela; Kühnis, Jürg; Jäncke, Lutz

2017-01-01

In this paper, we examined brain activation in subjects during two music listening conditions: listening while simultaneously rating the musical piece being played [Listening and Rating (LR)] and listening to the musical pieces unconstrained [Listening (L)]. Using these two conditions, we tested whether the sequence in which the two conditions were fulfilled influenced the brain activation observable during the L condition (LR → L or L → LR). We recorded high-density EEG during the playing of four well-known positively experienced soundtracks in two subject groups. One group started with the L condition and continued with the LR condition (L → LR); the second group performed this experiment in reversed order (LR → L). We computed from the recorded EEG the power for different frequency bands (theta, lower alpha, upper alpha, lower beta, and upper beta). Statistical analysis revealed that the power in all examined frequency bands increased during the L condition but only when the subjects had not had previous experience with the LR condition (i.e., L → LR). For the subjects who began with the LR condition, there were no power increases during the L condition. Thus, the previous experience with the LR condition prevented subjects from developing the particular mental state associated with the typical power increase in all frequency bands. The subjects without previous experience of the LR condition listened to the musical pieces in an unconstrained and undisturbed manner and showed a general power increase in all frequency bands. We interpret the fact that unconstrained music listening was associated with increased power in all examined frequency bands as a neural indicator of a mental state that can best be described as a mind-wandering state during which the subjects are “drawn into” the music. PMID:28706480

Small sample mediation testing: misplaced confidence in bootstrapped confidence intervals.

PubMed

Koopman, Joel; Howe, Michael; Hollenbeck, John R; Sin, Hock-Peng

2015-01-01

Bootstrapping is an analytical tool commonly used in psychology to test the statistical significance of the indirect effect in mediation models. Bootstrapping proponents have particularly advocated for its use for samples of 20-80 cases. This advocacy has been heeded, especially in the Journal of Applied Psychology, as researchers are increasingly utilizing bootstrapping to test mediation with samples in this range. We discuss reasons to be concerned with this escalation, and in a simulation study focused specifically on this range of sample sizes, we demonstrate not only that bootstrapping has insufficient statistical power to provide a rigorous hypothesis test in most conditions but also that bootstrapping has a tendency to exhibit an inflated Type I error rate. We then extend our simulations to investigate an alternative empirical resampling method as well as a Bayesian approach and demonstrate that they exhibit comparable statistical power to bootstrapping in small samples without the associated inflated Type I error. Implications for researchers testing mediation hypotheses in small samples are presented. For researchers wishing to use these methods in their own research, we have provided R syntax in the online supplemental materials. (c) 2015 APA, all rights reserved.

[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].

PubMed

Suzukawa, Yumi; Toyoda, Hideki

2012-04-01

This study analyzed the statistical power of research studies published in the "Japanese Journal of Psychology" in 2008 and 2009. Sample effect sizes and sample statistical powers were calculated for each statistical test and analyzed with respect to the analytical methods and the fields of the studies. The results show that in the fields like perception, cognition or learning, the effect sizes were relatively large, although the sample sizes were small. At the same time, because of the small sample sizes, some meaningful effects could not be detected. In the other fields, because of the large sample sizes, meaningless effects could be detected. This implies that researchers who could not get large enough effect sizes would use larger samples to obtain significant results.

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

PubMed

Ng'andu, N H

1997-03-30

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

Sparse approximation of currents for statistics on curves and surfaces.

PubMed

Durrleman, Stanley; Pennec, Xavier; Trouvé, Alain; Ayache, Nicholas

2008-01-01

Computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. Modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. This framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. However, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. Statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. We propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. Besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. Experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.

Advances in Statistical Methods for Substance Abuse Prevention Research

PubMed Central

MacKinnon, David P.; Lockwood, Chondra M.

2010-01-01

The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods. PMID:12940467

The Problem of Auto-Correlation in Parasitology

PubMed Central

Pollitt, Laura C.; Reece, Sarah E.; Mideo, Nicole; Nussey, Daniel H.; Colegrave, Nick

2012-01-01

Explaining the contribution of host and pathogen factors in driving infection dynamics is a major ambition in parasitology. There is increasing recognition that analyses based on single summary measures of an infection (e.g., peak parasitaemia) do not adequately capture infection dynamics and so, the appropriate use of statistical techniques to analyse dynamics is necessary to understand infections and, ultimately, control parasites. However, the complexities of within-host environments mean that tracking and analysing pathogen dynamics within infections and among hosts poses considerable statistical challenges. Simple statistical models make assumptions that will rarely be satisfied in data collected on host and parasite parameters. In particular, model residuals (unexplained variance in the data) should not be correlated in time or space. Here we demonstrate how failure to account for such correlations can result in incorrect biological inference from statistical analysis. We then show how mixed effects models can be used as a powerful tool to analyse such repeated measures data in the hope that this will encourage better statistical practices in parasitology. PMID:22511865

Advancing solar energy forecasting through the underlying physics

NASA Astrophysics Data System (ADS)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Determination of Type I Error Rates and Power of Answer Copying Indices under Various Conditions

ERIC Educational Resources Information Center

Yormaz, Seha; Sünbül, Önder

2017-01-01

This study aims to determine the Type I error rates and power of S[subscript 1] , S[subscript 2] indices and kappa statistic at detecting copying on multiple-choice tests under various conditions. It also aims to determine how copying groups are created in order to calculate how kappa statistics affect Type I error rates and power. In this study,…

Statistical Power Analysis with Microsoft Excel: Normal Tests for One or Two Means as a Prelude to Using Non-Central Distributions to Calculate Power

ERIC Educational Resources Information Center

Texeira, Antonio; Rosa, Alvaro; Calapez, Teresa

2009-01-01

This article presents statistical power analysis (SPA) based on the normal distribution using Excel, adopting textbook and SPA approaches. The objective is to present the latter in a comparative way within a framework that is familiar to textbook level readers, as a first step to understand SPA with other distributions. The analysis focuses on the…

On the analysis of very small samples of Gaussian repeated measurements: an alternative approach.

PubMed

Westgate, Philip M; Burchett, Woodrow W

2017-03-15

The analysis of very small samples of Gaussian repeated measurements can be challenging. First, due to a very small number of independent subjects contributing outcomes over time, statistical power can be quite small. Second, nuisance covariance parameters must be appropriately accounted for in the analysis in order to maintain the nominal test size. However, available statistical strategies that ensure valid statistical inference may lack power, whereas more powerful methods may have the potential for inflated test sizes. Therefore, we explore an alternative approach to the analysis of very small samples of Gaussian repeated measurements, with the goal of maintaining valid inference while also improving statistical power relative to other valid methods. This approach uses generalized estimating equations with a bias-corrected empirical covariance matrix that accounts for all small-sample aspects of nuisance correlation parameter estimation in order to maintain valid inference. Furthermore, the approach utilizes correlation selection strategies with the goal of choosing the working structure that will result in the greatest power. In our study, we show that when accurate modeling of the nuisance correlation structure impacts the efficiency of regression parameter estimation, this method can improve power relative to existing methods that yield valid inference. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Précis of statistical significance: rationale, validity, and utility.

PubMed

Chow, S L

1998-04-01

The null-hypothesis significance-test procedure (NHSTP) is defended in the context of the theory-corroboration experiment, as well as the following contrasts: (a) substantive hypotheses versus statistical hypotheses, (b) theory corroboration versus statistical hypothesis testing, (c) theoretical inference versus statistical decision, (d) experiments versus nonexperimental studies, and (e) theory corroboration versus treatment assessment. The null hypothesis can be true because it is the hypothesis that errors are randomly distributed in data. Moreover, the null hypothesis is never used as a categorical proposition. Statistical significance means only that chance influences can be excluded as an explanation of data; it does not identify the nonchance factor responsible. The experimental conclusion is drawn with the inductive principle underlying the experimental design. A chain of deductive arguments gives rise to the theoretical conclusion via the experimental conclusion. The anomalous relationship between statistical significance and the effect size often used to criticize NHSTP is more apparent than real. The absolute size of the effect is not an index of evidential support for the substantive hypothesis. Nor is the effect size, by itself, informative as to the practical importance of the research result. Being a conditional probability, statistical power cannot be the a priori probability of statistical significance. The validity of statistical power is debatable because statistical significance is determined with a single sampling distribution of the test statistic based on H0, whereas it takes two distributions to represent statistical power or effect size. Sample size should not be determined in the mechanical manner envisaged in power analysis. It is inappropriate to criticize NHSTP for nonstatistical reasons. At the same time, neither effect size, nor confidence interval estimate, nor posterior probability can be used to exclude chance as an explanation of data. Neither can any of them fulfill the nonstatistical functions expected of them by critics.

Fourier power spectrum characteristics of face photographs: attractiveness perception depends on low-level image properties.

PubMed

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks - but not veridical face photographs - affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess - compared to face images - a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope - in contrast to the other tested image properties - did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis.

Fourier Power Spectrum Characteristics of Face Photographs: Attractiveness Perception Depends on Low-Level Image Properties

PubMed Central

Langner, Oliver; Wiese, Holger; Redies, Christoph

2015-01-01

We investigated whether low-level processed image properties that are shared by natural scenes and artworks – but not veridical face photographs – affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess – compared to face images – a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope – in contrast to the other tested image properties – did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis. PMID:25835539

Empirical support for global integrated assessment modeling: Productivity trends and technological change in developing countries' agriculture and electric power sectors

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

Sathaye, Jayant A.

2000-04-01

Integrated assessment (IA) modeling of climate policy is increasingly global in nature, with models incorporating regional disaggregation. The existing empirical basis for IA modeling, however, largely arises from research on industrialized economies. Given the growing importance of developing countries in determining long-term global energy and carbon emissions trends, filling this gap with improved statistical information on developing countries' energy and carbon-emissions characteristics is an important priority for enhancing IA modeling. Earlier research at LBNL on this topic has focused on assembling and analyzing statistical data on productivity trends and technological change in the energy-intensive manufacturing sectors of five developing countries,more » India, Brazil, Mexico, Indonesia, and South Korea. The proposed work will extend this analysis to the agriculture and electric power sectors in India, South Korea, and two other developing countries. They will also examine the impact of alternative model specifications on estimates of productivity growth and technological change for each of the three sectors, and estimate the contribution of various capital inputs--imported vs. indigenous, rigid vs. malleable-- in contributing to productivity growth and technological change. The project has already produced a data resource on the manufacturing sector which is being shared with IA modelers. This will be extended to the agriculture and electric power sectors, which would also be made accessible to IA modeling groups seeking to enhance the empirical descriptions of developing country characteristics. The project will entail basic statistical and econometric analysis of productivity and energy trends in these developing country sectors, with parameter estimates also made available to modeling groups. The parameter estimates will be developed using alternative model specifications that could be directly utilized by the existing IAMs for the manufacturing, agriculture, and electric power sectors.« less

Characteristic correlation study of UV disinfection performance for ballast water treatment

NASA Astrophysics Data System (ADS)

Ba, Te; Li, Hongying; Osman, Hafiiz; Kang, Chang-Wei

2016-11-01

Characteristic correlation between ultraviolet disinfection performance and operating parameters, including ultraviolet transmittance (UVT), lamp power and water flow rate, was studied by numerical and experimental methods. A three-stage model was developed to simulate the fluid flow, UV radiation and the trajectories of microorganisms. Navier-Stokes equation with k-epsilon turbulence was solved to model the fluid flow, while discrete ordinates (DO) radiation model and discrete phase model (DPM) were used to introduce UV radiation and microorganisms trajectories into the model, respectively. The UV dose statistical distribution for the microorganisms was found to move to higher value with the increase of UVT and lamp power, but moves to lower value when the water flow rate increases. Further investigation shows that the fluence rate increases exponentially with UVT but linearly with the lamp power. The average and minimum resident time decreases linearly with the water flow rate while the maximum resident time decrease rapidly in a certain range. The current study can be used as a digital design and performance evaluation tool of the UV reactor for ballast water treatment.

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

New heterogeneous test statistics for the unbalanced fixed-effect nested design.

PubMed

Guo, Jiin-Huarng; Billard, L; Luh, Wei-Ming

2011-05-01

When the underlying variances are unknown or/and unequal, using the conventional F test is problematic in the two-factor hierarchical data structure. Prompted by the approximate test statistics (Welch and Alexander-Govern methods), the authors develop four new heterogeneous test statistics to test factor A and factor B nested within A for the unbalanced fixed-effect two-stage nested design under variance heterogeneity. The actual significance levels and statistical power of the test statistics were compared in a simulation study. The results show that the proposed procedures maintain better Type I error rate control and have greater statistical power than those obtained by the conventional F test in various conditions. Therefore, the proposed test statistics are recommended in terms of robustness and easy implementation. ©2010 The British Psychological Society.

Correlation techniques and measurements of wave-height statistics

NASA Technical Reports Server (NTRS)

Guthart, H.; Taylor, W. C.; Graf, K. A.; Douglas, D. G.

1972-01-01

Statistical measurements of wave height fluctuations have been made in a wind wave tank. The power spectral density function of temporal wave height fluctuations evidenced second-harmonic components and an f to the minus 5th power law decay beyond the second harmonic. The observations of second harmonic effects agreed very well with a theoretical prediction. From the wave statistics, surface drift currents were inferred and compared to experimental measurements with satisfactory agreement. Measurements were made of the two dimensional correlation coefficient at 15 deg increments in angle with respect to the wind vector. An estimate of the two-dimensional spatial power spectral density function was also made.

Performance map of a cluster detection test using extended power

PubMed Central

2013-01-01

Background Conventional power studies possess limited ability to assess the performance of cluster detection tests. In particular, they cannot evaluate the accuracy of the cluster location, which is essential in such assessments. Furthermore, they usually estimate power for one or a few particular alternative hypotheses and thus cannot assess performance over an entire region. Takahashi and Tango developed the concept of extended power that indicates both the rate of null hypothesis rejection and the accuracy of the cluster location. We propose a systematic assessment method, using here extended power, to produce a map showing the performance of cluster detection tests over an entire region. Methods To explore the behavior of a cluster detection test on identical cluster types at any possible location, we successively applied four different spatial and epidemiological parameters. These parameters determined four cluster collections, each covering the entire study region. We simulated 1,000 datasets for each cluster and analyzed them with Kulldorff’s spatial scan statistic. From the area under the extended power curve, we constructed a map for each parameter set showing the performance of the test across the entire region. Results Consistent with previous studies, the performance of the spatial scan statistic increased with the baseline incidence of disease, the size of the at-risk population and the strength of the cluster (i.e., the relative risk). Performance was heterogeneous, however, even for very similar clusters (i.e., similar with respect to the aforementioned factors), suggesting the influence of other factors. Conclusions The area under the extended power curve is a single measure of performance and, although needing further exploration, it is suitable to conduct a systematic spatial evaluation of performance. The performance map we propose enables epidemiologists to assess cluster detection tests across an entire study region. PMID:24156765

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Statistical characteristics of dynamics for population migration driven by the economic interests

NASA Astrophysics Data System (ADS)

Huo, Jie; Wang, Xu-Ming; Zhao, Ning; Hao, Rui

2016-06-01

Population migration typically occurs under some constraints, which can deeply affect the structure of a society and some other related aspects. Therefore, it is critical to investigate the characteristics of population migration. Data from the China Statistical Yearbook indicate that the regional gross domestic product per capita relates to the population size via a linear or power-law relation. In addition, the distribution of population migration sizes or relative migration strength introduced here is dominated by a shifted power-law relation. To reveal the mechanism that creates the aforementioned distributions, a dynamic model is proposed based on the population migration rule that migration is facilitated by higher financial gains and abated by fewer employment opportunities at the destination, considering the migration cost as a function of the migration distance. The calculated results indicate that the distribution of the relative migration strength is governed by a shifted power-law relation, and that the distribution of migration distances is dominated by a truncated power-law relation. These results suggest the use of a power-law to fit a distribution may be not always suitable. Additionally, from the modeling framework, one can infer that it is the randomness and determinacy that jointly create the scaling characteristics of the distributions. The calculation also demonstrates that the network formed by active nodes, representing the immigration and emigration regions, usually evolves from an ordered state with a non-uniform structure to a disordered state with a uniform structure, which is evidenced by the increasing structural entropy.

Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials

PubMed Central

Hobbs, Brian P.; Carlin, Bradley P.; Mandrekar, Sumithra J.; Sargent, Daniel J.

2011-01-01

Summary Bayesian clinical trial designs offer the possibility of a substantially reduced sample size, increased statistical power, and reductions in cost and ethical hazard. However when prior and current information conflict, Bayesian methods can lead to higher than expected Type I error, as well as the possibility of a costlier and lengthier trial. This motivates an investigation of the feasibility of hierarchical Bayesian methods for incorporating historical data that are adaptively robust to prior information that reveals itself to be inconsistent with the accumulating experimental data. In this paper, we present several models that allow for the commensurability of the information in the historical and current data to determine how much historical information is used. A primary tool is elaborating the traditional power prior approach based upon a measure of commensurability for Gaussian data. We compare the frequentist performance of several methods using simulations, and close with an example of a colon cancer trial that illustrates a linear models extension of our adaptive borrowing approach. Our proposed methods produce more precise estimates of the model parameters, in particular conferring statistical significance to the observed reduction in tumor size for the experimental regimen as compared to the control regimen. PMID:21361892

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

PubMed

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

2012-08-01

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

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

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

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

Ecological statistics of Gestalt laws for the perceptual organization of contours.

PubMed

Elder, James H; Goldberg, Richard M

2002-01-01

Although numerous studies have measured the strength of visual grouping cues for controlled psychophysical stimuli, little is known about the statistical utility of these various cues for natural images. In this study, we conducted experiments in which human participants trace perceived contours in natural images. These contours are automatically mapped to sequences of discrete tangent elements detected in the image. By examining relational properties between pairs of successive tangents on these traced curves, and between randomly selected pairs of tangents, we are able to estimate the likelihood distributions required to construct an optimal Bayesian model for contour grouping. We employed this novel methodology to investigate the inferential power of three classical Gestalt cues for contour grouping: proximity, good continuation, and luminance similarity. The study yielded a number of important results: (1) these cues, when appropriately defined, are approximately uncorrelated, suggesting a simple factorial model for statistical inference; (2) moderate image-to-image variation of the statistics indicates the utility of general probabilistic models for perceptual organization; (3) these cues differ greatly in their inferential power, proximity being by far the most powerful; and (4) statistical modeling of the proximity cue indicates a scale-invariant power law in close agreement with prior psychophysics.

A clinicomicrobiological study to evaluate the efficacy of manual and powered toothbrushes among autistic patients

PubMed Central

Vajawat, Mayuri; Deepika, P. C.; Kumar, Vijay; Rajeshwari, P.

2015-01-01

Aim: To compare the efficacy of powered toothbrushes in improving gingival health and reducing salivary red complex counts as compared to manual toothbrushes, among autistic individuals. Materials and Methods: Forty autistics was selected. Test group received powered toothbrushes, and control group received manual toothbrushes. Plaque index and gingival index were recorded. Unstimulated saliva was collected for analysis of red complex organisms using polymerase chain reaction. Results: A statistically significant reduction in the plaque scores was seen over a period of 12 weeks in both the groups (P < 0.001 for tests and P = 0.002 for controls). This reduction was statistically more significant in the test group (P = 0.024). A statistically significant reduction in the gingival scores was seen over a period of 12 weeks in both the groups (P < 0.001 for tests and P = 0.001 for controls). This reduction was statistically more significant in the test group (P = 0.042). No statistically significant reduction in the detection rate of red complex organisms were seen at 4 weeks in both the groups. Conclusion: Powered toothbrushes result in a significant overall improvement in gingival health when constant reinforcement of oral hygiene instructions is given. PMID:26681855

Possible Improvements of the ACE Diversity Interchange Methodology

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

Etingov, Pavel V.; Zhou, Ning; Makarov, Yuri V.

2010-07-26

North American Electric Reliability Corporation (NERC) grid is operated by about 131 balancing authorities (BA). Within each BA, operators are responsible for managing the unbalance (caused by both load and wind). As wind penetration levels increase, the challenges of managing power variation increases. Working independently, balancing area with limited regulating/load following generation and high wind power penetration faces significant challenges. The benefits of BA cooperation and consolidation increase when there is a significant wind energy penetration. To explore the benefits of BA cooperation, this paper investigates ACE sharing approach. A technology called ACE diversity interchange (ADI) is already in usemore » in the western interconnection. A new methodology extending ADI is proposed in the paper. The proposed advanced ADI overcoming some limitations existing in conventional ADI. Simulations using real statistical data of CAISO and BPA have shown high performance of the proposed advanced ADI methodology.« less

Statistical properties of radiation power levels from a high-gain free-electron laser at and beyond saturation

NASA Astrophysics Data System (ADS)

Schroeder, C. B.; Fawley, W. M.; Esarey, E.

2003-07-01

We investigate the statistical properties (e.g., shot-to-shot power fluctuations) of the radiation from a high-gain free-electron laser (FEL) operating in the nonlinear regime. We consider the case of an FEL amplifier reaching saturation whose shot-to-shot fluctuations in input radiation power follow a gamma distribution. We analyze the corresponding output power fluctuations at and beyond saturation, including beam energy spread effects, and find that there are well-characterized values of undulator length for which the fluctuations reach a minimum.

Sampling benthic macroinvertebrates in a large flood-plain river: Considerations of study design, sample size, and cost

USGS Publications Warehouse

Bartsch, L.A.; Richardson, W.B.; Naimo, T.J.

1998-01-01

Estimation of benthic macroinvertebrate populations over large spatial scales is difficult due to the high variability in abundance and the cost of sample processing and taxonomic analysis. To determine a cost-effective, statistically powerful sample design, we conducted an exploratory study of the spatial variation of benthic macroinvertebrates in a 37 km reach of the Upper Mississippi River. We sampled benthos at 36 sites within each of two strata, contiguous backwater and channel border. Three standard ponar (525 cm(2)) grab samples were obtained at each site ('Original Design'). Analysis of variance and sampling cost of strata-wide estimates for abundance of Oligochaeta, Chironomidae, and total invertebrates showed that only one ponar sample per site ('Reduced Design') yielded essentially the same abundance estimates as the Original Design, while reducing the overall cost by 63%. A posteriori statistical power analysis (alpha = 0.05, beta = 0.20) on the Reduced Design estimated that at least 18 sites per stratum were needed to detect differences in mean abundance between contiguous backwater and channel border areas for Oligochaeta, Chironomidae, and total invertebrates. Statistical power was nearly identical for the three taxonomic groups. The abundances of several taxa of concern (e.g., Hexagenia mayflies and Musculium fingernail clams) were too spatially variable to estimate power with our method. Resampling simulations indicated that to achieve adequate sampling precision for Oligochaeta, at least 36 sample sites per stratum would be required, whereas a sampling precision of 0.2 would not be attained with any sample size for Hexagenia in channel border areas, or Chironomidae and Musculium in both strata given the variance structure of the original samples. Community-wide diversity indices (Brillouin and 1-Simpsons) increased as sample area per site increased. The backwater area had higher diversity than the channel border area. The number of sampling sites required to sample benthic macroinvertebrates during our sampling period depended on the study objective and ranged from 18 to more than 40 sites per stratum. No single sampling regime would efficiently and adequately sample all components of the macroinvertebrate community.

EEG and Eye Tracking Demonstrate Vigilance Enhancement with Challenge Integration

PubMed Central

Bodala, Indu P.; Li, Junhua; Thakor, Nitish V.; Al-Nashash, Hasan

2016-01-01

Maintaining vigilance is possibly the first requirement for surveillance tasks where personnel are faced with monotonous yet intensive monitoring tasks. Decrement in vigilance in such situations could result in dangerous consequences such as accidents, loss of life and system failure. In this paper, we investigate the possibility to enhance vigilance or sustained attention using “challenge integration,” a strategy that integrates a primary task with challenging stimuli. A primary surveillance task (identifying an intruder in a simulated factory environment) and a challenge stimulus (periods of rain obscuring the surveillance scene) were employed to test the changes in vigilance levels. The effect of integrating challenging events (resulting from artificially simulated rain) into the task were compared to the initial monotonous phase. EEG and eye tracking data is collected and analyzed for n = 12 subjects. Frontal midline theta power and frontal theta to parietal alpha power ratio which are used as measures of engagement and attention allocation show an increase due to challenge integration (p < 0.05 in each case). Relative delta band power of EEG also shows statistically significant suppression on the frontoparietal and occipital cortices due to challenge integration (p < 0.05). Saccade amplitude, saccade velocity and blink rate obtained from eye tracking data exhibit statistically significant changes during the challenge phase of the experiment (p < 0.05 in each case). From the correlation analysis between the statistically significant measures of eye tracking and EEG, we infer that saccade amplitude and saccade velocity decrease with vigilance decrement along with frontal midline theta and frontal theta to parietal alpha ratio. Conversely, blink rate and relative delta power increase with vigilance decrement. However, these measures exhibit a reverse trend when challenge stimulus appears in the task suggesting vigilance enhancement. Moreover, the mean reaction time is lower for the challenge integrated phase (RTmean = 3.65 ± 1.4s) compared to initial monotonous phase without challenge (RTmean = 4.6 ± 2.7s). Our work shows that vigilance level, as assessed by response of these vital signs, is enhanced by challenge integration. PMID:27375464

Single-Item Measurement of Suicidal Behaviors: Validity and Consequences of Misclassification

PubMed Central

Millner, Alexander J.; Lee, Michael D.; Nock, Matthew K.

2015-01-01

Suicide is a leading cause of death worldwide. Although research has made strides in better defining suicidal behaviors, there has been less focus on accurate measurement. Currently, the widespread use of self-report, single-item questions to assess suicide ideation, plans and attempts may contribute to measurement problems and misclassification. We examined the validity of single-item measurement and the potential for statistical errors. Over 1,500 participants completed an online survey containing single-item questions regarding a history of suicidal behaviors, followed by questions with more precise language, multiple response options and narrative responses to examine the validity of single-item questions. We also conducted simulations to test whether common statistical tests are robust against the degree of misclassification produced by the use of single-items. We found that 11.3% of participants that endorsed a single-item suicide attempt measure engaged in behavior that would not meet the standard definition of a suicide attempt. Similarly, 8.8% of those who endorsed a single-item measure of suicide ideation endorsed thoughts that would not meet standard definitions of suicide ideation. Statistical simulations revealed that this level of misclassification substantially decreases statistical power and increases the likelihood of false conclusions from statistical tests. Providing a wider range of response options for each item reduced the misclassification rate by approximately half. Overall, the use of single-item, self-report questions to assess the presence of suicidal behaviors leads to misclassification, increasing the likelihood of statistical decision errors. Improving the measurement of suicidal behaviors is critical to increase understanding and prevention of suicide. PMID:26496707

EEG low-resolution brain electromagnetic tomography (LORETA) in Huntington's disease.

PubMed

Painold, Annamaria; Anderer, Peter; Holl, Anna K; Letmaier, Martin; Saletu-Zyhlarz, Gerda M; Saletu, Bernd; Bonelli, Raphael M

2011-05-01

Previous studies have shown abnormal electroencephalography (EEG) in Huntington's disease (HD). The aim of the present investigation was to compare quantitatively analyzed EEGs of HD patients and controls by means of low-resolution brain electromagnetic tomography (LORETA). Further aims were to delineate the sensitivity and utility of EEG LORETA in the progression of HD, and to correlate parameters of cognitive and motor impairment with neurophysiological variables. In 55 HD patients and 55 controls a 3-min vigilance-controlled EEG (V-EEG) was recorded during midmorning hours. Power spectra and intracortical tomography were computed by LORETA in seven frequency bands and compared between groups. Spearman rank correlations were based on V-EEG and psychometric data. Statistical overall analysis by means of the omnibus significance test demonstrated significant (p < 0.01) differences between HD patients and controls. LORETA theta, alpha and beta power were decreased from early to late stages of the disease. Only advanced disease stages showed a significant increase in delta power, mainly in the right orbitofrontal cortex. Correlation analyses revealed that a decrease of alpha and theta power correlated significantly with increasing cognitive and motor decline. LORETA proved to be a sensitive instrument for detecting progressive electrophysiological changes in HD. Reduced alpha power seems to be a trait marker of HD, whereas increased prefrontal delta power seems to reflect worsening of the disease. Motor function and cognitive function deteriorate together with a decrease in alpha and theta power. This data set, so far the largest in HD research, helps to elucidate remaining uncertainties about electrophysiological abnormalities in HD.

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE PAGES

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

2016-09-01

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

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

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Novel Atmospheric and Sea State Modeling in Ocean Energy Applications

NASA Astrophysics Data System (ADS)

Kallos, George; Galanis, George; Kalogeri, Christina; Larsen, Xiaoli Guo

2013-04-01

The rapidly increasing use of renewable energy sources poses new challenges for the research and technological community today. The integration of the, usually, highly variable wind and wave energy amounts into the general grid, the optimization of energy transition and the forecast of extreme values that could lead to instabilities and failures of the system can be listed among them. In the present work, novel methodologies based on state of the art numerical wind/wave simulation systems and advanced statistical techniques addressing such type of problems are discussed. In particular, extremely high resolution modeling systems simulating the atmospheric and sea state conditions with spatial resolution of 100 meters or less and temporal discretization of a few seconds are utilized in order to simulate in the most detailed way the combined wind-wave energy potential at offshore sites. In addition, a statistical analysis based on a variety of mean and variation measures as well as univariate and bivariate probability distributions is used for the estimation of the variability of the power potential revealing the advantages of the use of combined forms of energy by offshore platforms able to produce wind and wave power simultaneously. The estimation and prediction of extreme wind/wave conditions - a critical issue both for site assessment and infrastructure maintenance - is also studied by means of the 50-year return period over areas with increased power potential. This work has been carried out within the framework of the FP7 project MARINA Platform (http://www.marina-platform.info/index.aspx).

A comparison of interocular differences in patients with pigment dispersion syndrome.

PubMed

Yip, Leonard W; Sothornwit, Nisa; Berkowitz, Jonathan; Mikelberg, Frederick S

2009-01-01

Pigment dispersion syndrome (PDS) and pigmentary glaucoma (PG) are characterized by loss of iris pigment because of reverse pupillary block. The loss of iris pigment is manifested as transillumination defects. Differences in ocular anatomy have been found between subjects with PDS and controls. Our study aims to see if differences in interocular anatomic features are also related to differences in the quantity of transillumination defects between eyes. This is an observational case series of 30 eyes of 15 subjects with PDS/PG in at least 1 eye. Patients underwent refraction, exophthalmometry, corneal and anterior chamber analysis by Pentacam, biometry, A-scan, ultrasound biomicroscopy, and anterior segment digital photography. The Pentacam mean central radii of the posterior corneal surface (cornea back Rm), vertical central radius of curvature of the posterior corneal surface (cornea back Rv), and keratometric power deviation (influence of the posterior surface of the cornea on refractive power) were statistically different between eyes with greater pigment loss and eyes with lesser pigment loss. Eyes with greater pigment loss had a larger back radius of corneal curvature and a correspondingly numerically smaller keratometric power deviation. Other measurements of ocular anatomy were not statistically significant. A flatter curvature of the posterior corneal surface of the eye is associated with increased pigment loss in PDS and PG. The authors postulate that this could result in a difference in the biomechanical properties of the cornea, increased deformation with blinking, and a pumping action resulting in the reverse pupil block of PDS.

A geometrical optics approach for modeling aperture averaging in free space optical communication applications

NASA Astrophysics Data System (ADS)

Yuksel, Heba; Davis, Christopher C.

2006-09-01

Intensity fluctuations at the receiver in free space optical (FSO) communication links lead to a received power variance that depends on the size of the receiver aperture. Increasing the size of the receiver aperture reduces the power variance. This effect of the receiver size on power variance is called aperture averaging. If there were no aperture size limitation at the receiver, then there would be no turbulence-induced scintillation. In practice, there is always a tradeoff between aperture size, transceiver weight, and potential transceiver agility for pointing, acquisition and tracking (PAT) of FSO communication links. We have developed a geometrical simulation model to predict the aperture averaging factor. This model is used to simulate the aperture averaging effect at given range by using a large number of rays, Gaussian as well as uniformly distributed, propagating through simulated turbulence into a circular receiver of varying aperture size. Turbulence is simulated by filling the propagation path with spherical bubbles of varying sizes and refractive index discontinuities statistically distributed according to various models. For each statistical representation of the atmosphere, the three-dimensional trajectory of each ray is analyzed using geometrical optics. These Monte Carlo techniques have proved capable of assessing the aperture averaging effect, in particular, the quantitative expected reduction in intensity fluctuations with increasing aperture diameter. In addition, beam wander results have demonstrated the range-cubed dependence of mean-squared beam wander. An effective turbulence parameter can also be determined by correlating beam wander behavior with the path length.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Power increases the socially toxic component of narcissism among individuals with high baseline testosterone.

PubMed

Mead, Nicole L; Baumeister, Roy F; Stuppy, Anika; Vohs, Kathleen D

2018-04-01

The corrosive effects of power have been noted for centuries, but the self-related changes responsible for those effects have remained somewhat elusive. Narcissists tend to rise to-and abuse-positions of power, so we considered the possibility that positions of power may corrupt because they inflate narcissism. Two pathways were considered: Powerholders abuse their power because having power over others makes them feel superior (grandiosity pathway) or deserving of special treatment (entitlement pathway). Supporting the entitlement pathway, assigning participants to a position of power (vs. equal control) over a group task increased scores on the Exploitative/Entitlement component of narcissism among those with high baseline testosterone. What is more, heightened Exploitative/Entitlement scores among high-testosterone participants endowed with power (vs. equal control) statistically explained amplified self-reported willingness to misuse their power (e.g., taking fringe benefits as extra compensation). The grandiosity pathway was not well supported. The Superiority/Arrogance, Self-Absorption/Self-Admiration, and Leadership/Authority facets of narcissism did not change as a function of the power manipulation and testosterone levels. Taken together, these results suggest that people with high (but not low) testosterone may be inclined to misuse their power because having power over others makes them feel entitled to special treatment. This work identifies testosterone as a characteristic that contributes to the development of the socially toxic component of narcissism (Exploitative/Entitlement). It points to the possibility that structural positions of power and individual differences in narcissism may be mutually reinforcing, suggesting a vicious cycle with personal, relational, and societal implications. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Metacontrast Inferred from Reaction Time and Verbal Report: Replication and Comments on the Feher-Biederman Experiment

ERIC Educational Resources Information Center

Amundson, Vickie E.; Bernstein, Ira H.

1973-01-01

Authors note that Fehrer and Biederman's two statistical tests were not of equal power and that their conclusion could be a statistical artifact of both the lesser power of the verbal report comparison and the insensitivity of their particular verbal report indicator. (Editor)

Individuals on alert: digital epidemiology and the individualization of surveillance.

PubMed

Samerski, Silja

2018-06-14

This article examines how digital epidemiology and eHealth coalesce into a powerful health surveillance system that fundamentally changes present notions of body and health. In the age of Big Data and Quantified Self, the conceptual and practical distinctions between individual and population body, personal and public health, surveillance and health care are diminishing. Expanding on Armstrong's concept of "surveillance medicine" to "quantified self medicine" and drawing on my own research on the symbolic power of statistical constructs in medical encounters, this article explores the impact of digital health surveillance on people's perceptions, actions and subjectivities. It discusses the epistemic confusions and paradoxes produced by a health care system that increasingly treats patients as risk profiles and prompts them to do the same, namely to perceive and manage themselves as a bundle of health and security risks. Since these risks are necessarily constructed in reference to epidemiological data that postulate a statistical gaze, they also construct or make-up disembodied "individuals on alert".

Fully moderated T-statistic for small sample size gene expression arrays.

PubMed

Yu, Lianbo; Gulati, Parul; Fernandez, Soledad; Pennell, Michael; Kirschner, Lawrence; Jarjoura, David

2011-09-15

Gene expression microarray experiments with few replications lead to great variability in estimates of gene variances. Several Bayesian methods have been developed to reduce this variability and to increase power. Thus far, moderated t methods assumed a constant coefficient of variation (CV) for the gene variances. We provide evidence against this assumption, and extend the method by allowing the CV to vary with gene expression. Our CV varying method, which we refer to as the fully moderated t-statistic, was compared to three other methods (ordinary t, and two moderated t predecessors). A simulation study and a familiar spike-in data set were used to assess the performance of the testing methods. The results showed that our CV varying method had higher power than the other three methods, identified a greater number of true positives in spike-in data, fit simulated data under varying assumptions very well, and in a real data set better identified higher expressing genes that were consistent with functional pathways associated with the experiments.

Got power? A systematic review of sample size adequacy in health professions education research.

PubMed

Cook, David A; Hatala, Rose

2015-03-01

Many education research studies employ small samples, which in turn lowers statistical power. We re-analyzed the results of a meta-analysis of simulation-based education to determine study power across a range of effect sizes, and the smallest effect that could be plausibly excluded. We systematically searched multiple databases through May 2011, and included all studies evaluating simulation-based education for health professionals in comparison with no intervention or another simulation intervention. Reviewers working in duplicate abstracted information to calculate standardized mean differences (SMD's). We included 897 original research studies. Among the 627 no-intervention-comparison studies the median sample size was 25. Only two studies (0.3%) had ≥80% power to detect a small difference (SMD > 0.2 standard deviations) and 136 (22%) had power to detect a large difference (SMD > 0.8). 110 no-intervention-comparison studies failed to find a statistically significant difference, but none excluded a small difference and only 47 (43%) excluded a large difference. Among 297 studies comparing alternate simulation approaches the median sample size was 30. Only one study (0.3%) had ≥80% power to detect a small difference and 79 (27%) had power to detect a large difference. Of the 128 studies that did not detect a statistically significant effect, 4 (3%) excluded a small difference and 91 (71%) excluded a large difference. In conclusion, most education research studies are powered only to detect effects of large magnitude. For most studies that do not reach statistical significance, the possibility of large and important differences still exists.

Joint-level energetics differentiate isoinertial from speed-power resistance training-a Bayesian analysis.

PubMed

Liew, Bernard X W; Drovandi, Christopher C; Clifford, Samuel; Keogh, Justin W L; Morris, Susan; Netto, Kevin

2018-01-01

There is convincing evidence for the benefits of resistance training on vertical jump improvements, but little evidence to guide optimal training prescription. The inability to detect small between modality effects may partially reflect the use of ANOVA statistics. This study represents the results of a sub-study from a larger project investigating the effects of two resistance training methods on load carriage running energetics. Bayesian statistics were used to compare the effectiveness of isoinertial resistance against speed-power training to change countermovement jump (CMJ) and squat jump (SJ) height, and joint energetics. Active adults were randomly allocated to either a six-week isoinertial ( n  = 16; calf raises, leg press, and lunge), or a speed-power training program ( n  = 14; countermovement jumps, hopping, with hip flexor training to target pre-swing running energetics). Primary outcome variables included jump height and joint power. Bayesian mixed modelling and Functional Data Analysis were used, where significance was determined by a non-zero crossing of the 95% Bayesian Credible Interval (CrI). The gain in CMJ height after isoinertial training was 1.95 cm (95% CrI [0.85-3.04] cm) greater than the gain after speed-power training, but the gain in SJ height was similar between groups. In the CMJ, isoinertial training produced a larger increase in power absorption at the hip by a mean 0.018% (equivalent to 35 W) (95% CrI [0.007-0.03]), knee by 0.014% (equivalent to 27 W) (95% CrI [0.006-0.02]) and foot by 0.011% (equivalent to 21 W) (95% CrI [0.005-0.02]) compared to speed-power training. Short-term isoinertial training improved CMJ height more than speed-power training. The principle adaptive difference between training modalities was at the level of hip, knee and foot power absorption.

Addressing the "Elephant in the Room". The Role of the Primary School Practitioner in Supporting Children's Mental Well-Being

ERIC Educational Resources Information Center

Danby, Gillian; Hamilton, Paula

2016-01-01

The enthusiasm regarding the school as a place for mental health promotion is powered by a large body of research demonstrating the links between mental health and well-being, academic success and future life opportunities. Despite on-going commitment to mental well-being in the U.K., statistics suggest mental health issues are increasing among…

JPRS Report, China.

DTIC Science & Technology

1988-12-19

Statistics [CEI Database 4 Nov] 17 Construction Bank Checks on Investment Loans [XINHUA] 17 Gold Output Rising 10 Percent Annually [CHINA DAILY 8...Industrial Output for September [CEI Database 11 Nov] 23 Energy Industry Grows Steadily in 1988 [CEI Database 11 Nov] 23 Government Plans To Boost...Plastics Industry [XINHUA] 24 Chongqing’s Industrial Output Increases [XINHUA] 24 Haikou Boosts Power Industry [CEI Database 27 Oct] 24 Jilin

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

The Effects of a Maximal Power Training Cycle on the Strength, Maximum Power, Vertical Jump Height and Acceleration of High-Level 400-Meter Hurdlers

PubMed Central

Balsalobre-Fernández, Carlos; Tejero-González, Carlos Mª; del Campo-Vecino, Juan; Alonso-Curiel, Dionisio

2013-01-01

The aim of this study was to determine the effects of a power training cycle on maximum strength, maximum power, vertical jump height and acceleration in seven high-level 400-meter hurdlers subjected to a specific training program twice a week for 10 weeks. Each training session consisted of five sets of eight jump-squats with the load at which each athlete produced his maximum power. The repetition maximum in the half squat position (RM), maximum power in the jump-squat (W), a squat jump (SJ), countermovement jump (CSJ), and a 30-meter sprint from a standing position were measured before and after the training program using an accelerometer, an infra-red platform and photo-cells. The results indicated the following statistically significant improvements: a 7.9% increase in RM (Z=−2.03, p=0.021, δc=0.39), a 2.3% improvement in SJ (Z=−1.69, p=0.045, δc=0.29), a 1.43% decrease in the 30-meter sprint (Z=−1.70, p=0.044, δc=0.12), and, where maximum power was produced, a change in the RM percentage from 56 to 62% (Z=−1.75, p=0.039, δc=0.54). As such, it can be concluded that strength training with a maximum power load is an effective means of increasing strength and acceleration in high-level hurdlers. PMID:23717361

The effects of a maximal power training cycle on the strength, maximum power, vertical jump height and acceleration of high-level 400-meter hurdlers.

PubMed

Balsalobre-Fernández, Carlos; Tejero-González, Carlos M; Del Campo-Vecino, Juan; Alonso-Curiel, Dionisio

2013-03-01

The aim of this study was to determine the effects of a power training cycle on maximum strength, maximum power, vertical jump height and acceleration in seven high-level 400-meter hurdlers subjected to a specific training program twice a week for 10 weeks. Each training session consisted of five sets of eight jump-squats with the load at which each athlete produced his maximum power. The repetition maximum in the half squat position (RM), maximum power in the jump-squat (W), a squat jump (SJ), countermovement jump (CSJ), and a 30-meter sprint from a standing position were measured before and after the training program using an accelerometer, an infra-red platform and photo-cells. The results indicated the following statistically significant improvements: a 7.9% increase in RM (Z=-2.03, p=0.021, δc=0.39), a 2.3% improvement in SJ (Z=-1.69, p=0.045, δc=0.29), a 1.43% decrease in the 30-meter sprint (Z=-1.70, p=0.044, δc=0.12), and, where maximum power was produced, a change in the RM percentage from 56 to 62% (Z=-1.75, p=0.039, δc=0.54). As such, it can be concluded that strength training with a maximum power load is an effective means of increasing strength and acceleration in high-level hurdlers.

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.

The power and limits of a rule-based morpho-semantic parser.

PubMed Central

Baud, R. H.; Rassinoux, A. M.; Ruch, P.; Lovis, C.; Scherrer, J. R.

1999-01-01

The venue of Electronic Patient Record (EPR) implies an increasing amount of medical texts readily available for processing, as soon as convenient tools are made available. The chief application is text analysis, from which one can drive other disciplines like indexing for retrieval, knowledge representation, translation and inferencing for medical intelligent systems. Prerequisites for a convenient analyzer of medical texts are: building the lexicon, developing semantic representation of the domain, having a large corpus of texts available for statistical analysis, and finally mastering robust and powerful parsing techniques in order to satisfy the constraints of the medical domain. This article aims at presenting an easy-to-use parser ready to be adapted in different settings. It describes its power together with its practical limitations as experienced by the authors. PMID:10566313

The power and limits of a rule-based morpho-semantic parser.

PubMed

Baud, R H; Rassinoux, A M; Ruch, P; Lovis, C; Scherrer, J R

1999-01-01

The venue of Electronic Patient Record (EPR) implies an increasing amount of medical texts readily available for processing, as soon as convenient tools are made available. The chief application is text analysis, from which one can drive other disciplines like indexing for retrieval, knowledge representation, translation and inferencing for medical intelligent systems. Prerequisites for a convenient analyzer of medical texts are: building the lexicon, developing semantic representation of the domain, having a large corpus of texts available for statistical analysis, and finally mastering robust and powerful parsing techniques in order to satisfy the constraints of the medical domain. This article aims at presenting an easy-to-use parser ready to be adapted in different settings. It describes its power together with its practical limitations as experienced by the authors.

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

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

St. Martin, Clara M.; Lundquist, Julie K.; Clifton, Andrew

Using detailed upwind and nacelle-based measurements from a General Electric (GE) 1.5sle model with a 77 m rotor diameter, we calculate power curves and annual energy production (AEP) and explore their sensitivity to different atmospheric parameters to provide guidelines for the use of stability and turbulence filters in segregating power curves. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower as well as profiles from a lidar. We calculate power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) as well as atmospheric stability parameters such as the bulk Richardson number ( Rmore » B). We also calculate AEP with and without these atmospheric filters and highlight differences between the results of these calculations. The power curves for different TI regimes reveal that increased TI undermines power production at wind speeds near rated, but TI increases power production at lower wind speeds at this site, the US Department of Energy (DOE) National Wind Technology Center (NWTC). Similarly, power curves for different R B regimes reveal that periods of stable conditions produce more power at wind speeds near rated and periods of unstable conditions produce more power at lower wind speeds. AEP results suggest that calculations without filtering for these atmospheric regimes may overestimate the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to incorporate effects of atmospheric stability and turbulence across the rotor disk.« less

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

DOE PAGES

St. Martin, Clara M.; Lundquist, Julie K.; Clifton, Andrew; ...

2016-11-01

Using detailed upwind and nacelle-based measurements from a General Electric (GE) 1.5sle model with a 77 m rotor diameter, we calculate power curves and annual energy production (AEP) and explore their sensitivity to different atmospheric parameters to provide guidelines for the use of stability and turbulence filters in segregating power curves. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower as well as profiles from a lidar. We calculate power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) as well as atmospheric stability parameters such as the bulk Richardson number ( Rmore » B). We also calculate AEP with and without these atmospheric filters and highlight differences between the results of these calculations. The power curves for different TI regimes reveal that increased TI undermines power production at wind speeds near rated, but TI increases power production at lower wind speeds at this site, the US Department of Energy (DOE) National Wind Technology Center (NWTC). Similarly, power curves for different R B regimes reveal that periods of stable conditions produce more power at wind speeds near rated and periods of unstable conditions produce more power at lower wind speeds. AEP results suggest that calculations without filtering for these atmospheric regimes may overestimate the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to incorporate effects of atmospheric stability and turbulence across the rotor disk.« less

A Novel Approach of Battery Energy Storage for Improving Value of Wind Power in Deregulated Markets

NASA Astrophysics Data System (ADS)

Nguyen, Y. Minh; Yoon, Yong Tae

2013-06-01

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

Detecting higher spin fields through statistical anisotropy in the CMB and galaxy power spectra

NASA Astrophysics Data System (ADS)

Bartolo, Nicola; Kehagias, Alex; Liguori, Michele; Riotto, Antonio; Shiraishi, Maresuke; Tansella, Vittorio

2018-01-01

Primordial inflation may represent the most powerful collider to test high-energy physics models. In this paper we study the impact on the inflationary power spectrum of the comoving curvature perturbation in the specific model where massive higher spin fields are rendered effectively massless during a de Sitter epoch through suitable couplings to the inflaton field. In particular, we show that such fields with spin s induce a distinctive statistical anisotropic signal on the power spectrum, in such a way that not only the usual g2 M-statistical anisotropy coefficients, but also higher-order ones (i.e., g4 M,g6 M,…,g(2 s -2 )M and g(2 s )M) are nonvanishing. We examine their imprints in the cosmic microwave background and galaxy power spectra. Our Fisher matrix forecasts indicate that the detectability of gL M depends very weakly on L : all coefficients could be detected in near future if their magnitudes are bigger than about 10-3.

Maximizing ecological and evolutionary insight in bisulfite sequencing data sets

PubMed Central

Lea, Amanda J.; Vilgalys, Tauras P.; Durst, Paul A.P.; Tung, Jenny

2017-01-01

Preface Genome-scale bisulfite sequencing approaches have opened the door to ecological and evolutionary studies of DNA methylation in many organisms. These approaches can be powerful. However, they introduce new methodological and statistical considerations, some of which are particularly relevant to non-model systems. Here, we highlight how these considerations influence a study’s power to link methylation variation with a predictor variable of interest. Relative to current practice, we argue that sample sizes will need to increase to provide robust insights. We also provide recommendations for overcoming common challenges and an R Shiny app to aid in study design. PMID:29046582

Impact of resistance exercise program on functional capacity and muscular strength of knee extensor in pre-frail community-dwelling older women: a randomized crossover trial.

PubMed

Lustosa, Lygia P; Silva, Juscélio P; Coelho, Fernanda M; Pereira, Daniele S; Parentoni, Adriana N; Pereira, Leani S M

2011-01-01

Frailty syndrome in elderly people is characterized by a reduction of energy reserves and also by a decreased of resistance to stressors, resulting in an increase of vulnerability. The aim of this study was to verify the effect of a muscle-strengthening program with load in pre-frail elder women with regards to the functional capacity, knee extensor muscle strength and their correlation. Thrity-two pre-frail community-dwelling women participated in this study. Potential participants with cognitive impairment (MEEM), lower extremities orthopedic surgery, fractures, inability to walk unaided, neurological diseases, acute inflammatory disease, tumor growth, regular physical activity and current use of immunomodulators were excluded. All partcipants were evaluated by a blinded assessor using: Timed up and go (TUG), 10-Meter Walk Test (10MWT) and knee extensor muscle strength (Byodex System 3 Pro® isokinetic dynamometer at angular speeds of 60 and 180(0)/s). The intervention consisted of strengthening exercises of the lower extremities at 70% of 1RM, three times/ week for ten weeks. The statistical analysis was performed using the ANOVA and Spearman tests After the intervention, it was observed statistical significance on the work at 180(0)/s (F=12.71, p=0.02), on the power at 180(0)/s (F=15.40, p=0.02) and on the functional capacity (TUG, F=9.54, p=0.01; TC10, F=3.80, p=0.01). There was a good negative and statistically significant correlation between the TUG and work at 60(0)/s, such as the TUG and work at 180(0)/s (r=-0.65, p=0.01; r=-0.72, p=0.01). The intervention improved the muscular power and the functional capacity. The increase of the power correlated with function, which is an important variable of the quality of life in the pre-frail elders. Article registered in the ISRCT register under number ISRCTN62824599.

Are dragon-king neuronal avalanches dungeons for self-organized brain activity?

NASA Astrophysics Data System (ADS)

de Arcangelis, L.

2012-05-01

Recent experiments have detected a novel form of spontaneous neuronal activity both in vitro and in vivo: neuronal avalanches. The statistical properties of this activity are typical of critical phenomena, with power laws characterizing the distributions of avalanche size and duration. A critical behaviour for the spontaneous brain activity has important consequences on stimulated activity and learning. Very interestingly, these statistical properties can be altered in significant ways in epilepsy and by pharmacological manipulations. In particular, there can be an increase in the number of large events anticipated by the power law, referred to herein as dragon-king avalanches. This behaviour, as verified by numerical models, can originate from a number of different mechanisms. For instance, it is observed experimentally that the emergence of a critical behaviour depends on the subtle balance between excitatory and inhibitory mechanisms acting in the system. Perturbing this balance, by increasing either synaptic excitation or the incidence of depolarized neuronal up-states causes frequent dragon-king avalanches. Conversely, an unbalanced GABAergic inhibition or long periods of low activity in the network give rise to sub-critical behaviour. Moreover, the existence of power laws, common to other stochastic processes, like earthquakes or solar flares, suggests that correlations are relevant in these phenomena. The dragon-king avalanches may then also be the expression of pathological correlations leading to frequent avalanches encompassing all neurons. We will review the statistics of neuronal avalanches in experimental systems. We then present numerical simulations of a neuronal network model introducing within the self-organized criticality framework ingredients from the physiology of real neurons, as the refractory period, synaptic plasticity and inhibitory synapses. The avalanche critical behaviour and the role of dragon-king avalanches will be discussed in relation to different drives, neuronal states and microscopic mechanisms of charge storage and release in neuronal networks.

On the Relationship between Energy Density and Net Power (Intensity) in Coupled One-Dimensional Dynamic Systems

DTIC Science & Technology

1990-03-01

equation of the statistical energy analysis (SEA) using the procedure indicated in equation (13) [8, 9]. Similarly, one may state the quantities (. (X-)) and...CONGRESS ON ACOUSTICS, July 24-31 1986, Toronto, Canada, Paper D6-1. 5. CUSCHIERI, J.M., Power flow as a compliment to statistical energy analysis and...34Random response of identical one-dimensional subsystems", Journal of Sound and Vibration, 1980, Vol. 70, p. 343-353. 8. LYON, R.H., Statistical Energy Analysis of

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

NASA Technical Reports Server (NTRS)

Zimmerman, G. A.; Olsen, E. T.

1992-01-01

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Random-matrix approach to the statistical compound nuclear reaction at low energies using the Monte-Carlo technique [PowerPoint

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

Kawano, Toshihiko

2015-11-10

This theoretical treatment of low-energy compound nucleus reactions begins with the Bohr hypothesis, with corrections, and various statistical theories. The author investigates the statistical properties of the scattering matrix containing a Gaussian Orthogonal Ensemble (GOE) Hamiltonian in the propagator. The following conclusions are reached: For all parameter values studied, the numerical average of MC-generated cross sections coincides with the result of the Verbaarschot, Weidenmueller, Zirnbauer triple-integral formula. Energy average and ensemble average agree reasonably well when the width I is one or two orders of magnitude larger than the average resonance spacing d. In the strong-absorption limit, the channel degree-of-freedommore » ν a is 2. The direct reaction increases the inelastic cross sections while the elastic cross section is reduced.« less

Experimental design and statistical methods for improved hit detection in high-throughput screening.

PubMed

Malo, Nathalie; Hanley, James A; Carlile, Graeme; Liu, Jing; Pelletier, Jerry; Thomas, David; Nadon, Robert

2010-09-01

Identification of active compounds in high-throughput screening (HTS) contexts can be substantially improved by applying classical experimental design and statistical inference principles to all phases of HTS studies. The authors present both experimental and simulated data to illustrate how true-positive rates can be maximized without increasing false-positive rates by the following analytical process. First, the use of robust data preprocessing methods reduces unwanted variation by removing row, column, and plate biases. Second, replicate measurements allow estimation of the magnitude of the remaining random error and the use of formal statistical models to benchmark putative hits relative to what is expected by chance. Receiver Operating Characteristic (ROC) analyses revealed superior power for data preprocessed by a trimmed-mean polish method combined with the RVM t-test, particularly for small- to moderate-sized biological hits.

How often should we expect to be wrong? Statistical power, P values, and the expected prevalence of false discoveries.

PubMed

Marino, Michael J

2018-05-01

There is a clear perception in the literature that there is a crisis in reproducibility in the biomedical sciences. Many underlying factors contributing to the prevalence of irreproducible results have been highlighted with a focus on poor design and execution of experiments along with the misuse of statistics. While these factors certainly contribute to irreproducibility, relatively little attention outside of the specialized statistical literature has focused on the expected prevalence of false discoveries under idealized circumstances. In other words, when everything is done correctly, how often should we expect to be wrong? Using a simple simulation of an idealized experiment, it is possible to show the central role of sample size and the related quantity of statistical power in determining the false discovery rate, and in accurate estimation of effect size. According to our calculations, based on current practice many subfields of biomedical science may expect their discoveries to be false at least 25% of the time, and the only viable course to correct this is to require the reporting of statistical power and a minimum of 80% power (1 - β = 0.80) for all studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Do stages of menopause affect the outcomes of pelvic floor muscle training?

PubMed

Tosun, Özge Çeliker; Mutlu, Ebru Kaya; Tosun, Gökhan; Ergenoğlu, Ahmet Mete; Yeniel, Ahmet Özgur; Malkoç, Mehtap; Aşkar, Niyazi; İtil, İsmail Mete

2015-02-01

The purpose of our study is to determine whether there is a difference in pelvic floor muscle strength attributable to pelvic floor muscle training conducted during different stages of menopause. One hundred twenty-two women with stress urinary incontinence and mixed urinary incontinence were included in this prospective controlled study. The participants included in this study were separated into three groups according to the Stages of Reproductive Aging Workshop staging system as follows: group 1 (n = 41): stages -3 and -2; group 2 (n = 32): stages +1 and -1; and group 3 (n = 30): stage +2. All three groups were provided an individual home exercise program throughout the 12-week study. Pelvic floor muscle strength before and after the 12-week treatment was measured in all participants (using the PERFECT [power, endurance, number of repetitions, and number of fast (1-s) contractions; every contraction is timed] scheme, perineometry, transabdominal ultrasound, Brink scale, pad test, and stop test). Data were analyzed using analysis of variance. There were no statistically significant differences in pre-exercise training pelvic floor muscle strength parameters among the three groups. After 12 weeks, there were statistically significant increases in PERFECT scheme, Brink scale, perineometry, and ultrasound values. In contrast, there were significant decreases in stop test and 1-hour pad test values observed in the three groups (P = 0.001, dependent t test). In comparison with the other groups, group 1 demonstrated statistically significant improvements in the following postexercise training parameters: power, repetition, speed, Brink vertical displacement, and stop test. The lowest increase was observed in group 2 (P < 0.05). Strength increase can be achieved at all stages of menopause with pelvic floor muscle training, but the rates of increase vary according to the menopausal stage of the participants. Women in the late menopausal transition and early menopause are least responsive to pelvic floor muscle strength training. Further studies in this field are needed.

Power-law ansatz in complex systems: Excessive loss of information.

PubMed

Tsai, Sun-Ting; Chang, Chin-De; Chang, Ching-Hao; Tsai, Meng-Xue; Hsu, Nan-Jung; Hong, Tzay-Ming

2015-12-01

The ubiquity of power-law relations in empirical data displays physicists' love of simple laws and uncovering common causes among seemingly unrelated phenomena. However, many reported power laws lack statistical support and mechanistic backings, not to mention discrepancies with real data are often explained away as corrections due to finite size or other variables. We propose a simple experiment and rigorous statistical procedures to look into these issues. Making use of the fact that the occurrence rate and pulse intensity of crumple sound obey a power law with an exponent that varies with material, we simulate a complex system with two driving mechanisms by crumpling two different sheets together. The probability function of the crumple sound is found to transit from two power-law terms to a bona fide power law as compaction increases. In addition to showing the vicinity of these two distributions in the phase space, this observation nicely demonstrates the effect of interactions to bring about a subtle change in macroscopic behavior and more information may be retrieved if the data are subject to sorting. Our analyses are based on the Akaike information criterion that is a direct measurement of information loss and emphasizes the need to strike a balance between model simplicity and goodness of fit. As a show of force, the Akaike information criterion also found the Gutenberg-Richter law for earthquakes and the scale-free model for a brain functional network, a two-dimensional sandpile, and solar flare intensity to suffer an excessive loss of information. They resemble more the crumpled-together ball at low compactions in that there appear to be two driving mechanisms that take turns occurring.

A neuromechanics-based powered ankle exoskeleton to assist walking post-stroke: a feasibility study.

PubMed

Takahashi, Kota Z; Lewek, Michael D; Sawicki, Gregory S

2015-02-25

In persons post-stroke, diminished ankle joint function can contribute to inadequate gait propulsion. To target paretic ankle impairments, we developed a neuromechanics-based powered ankle exoskeleton. Specifically, this exoskeleton supplies plantarflexion assistance that is proportional to the user's paretic soleus electromyography (EMG) amplitude only during a phase of gait when the stance limb is subjected to an anteriorly directed ground reaction force (GRF). The purpose of this feasibility study was to examine the short-term effects of the powered ankle exoskeleton on the mechanics and energetics of gait. Five subjects with stroke walked with a powered ankle exoskeleton on the paretic limb for three 5 minute sessions. We analyzed the peak paretic ankle plantarflexion moment, paretic ankle positive work, symmetry of GRF propulsion impulse, and net metabolic power. The exoskeleton increased the paretic plantarflexion moment by 16% during the powered walking trials relative to unassisted walking condition (p < .05). Despite this enhanced paretic ankle moment, there was no significant increase in paretic ankle positive work, or changes in any other mechanical variables with the powered assistance. The exoskeleton assistance appeared to reduce the net metabolic power gradually with each 5 minute repetition, though no statistical significance was found. In three of the subjects, the paretic soleus activation during the propulsion phase of stance was reduced during the powered assistance compared to unassisted walking (35% reduction in the integrated EMG amplitude during the third powered session). This feasibility study demonstrated that the exoskeleton can enhance paretic ankle moment. Future studies with greater sample size and prolonged sessions are warranted to evaluate the effects of the powered ankle exoskeleton on overall gait outcomes in persons post-stroke.

Robust Statistical Detection of Power-Law Cross-Correlation.

PubMed

Blythe, Duncan A J; Nikulin, Vadim V; Müller, Klaus-Robert

2016-06-02

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.

Robust Statistical Detection of Power-Law Cross-Correlation

PubMed Central

Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

2016-01-01

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630

Fractal analysis of the short time series in a visibility graph method

NASA Astrophysics Data System (ADS)

Li, Ruixue; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Chen, Yingyuan

2016-05-01

The aim of this study is to evaluate the performance of the visibility graph (VG) method on short fractal time series. In this paper, the time series of Fractional Brownian motions (fBm), characterized by different Hurst exponent H, are simulated and then mapped into a scale-free visibility graph, of which the degree distributions show the power-law form. The maximum likelihood estimation (MLE) is applied to estimate power-law indexes of degree distribution, and in this progress, the Kolmogorov-Smirnov (KS) statistic is used to test the performance of estimation of power-law index, aiming to avoid the influence of droop head and heavy tail in degree distribution. As a result, we find that the MLE gives an optimal estimation of power-law index when KS statistic reaches its first local minimum. Based on the results from KS statistic, the relationship between the power-law index and the Hurst exponent is reexamined and then amended to meet short time series. Thus, a method combining VG, MLE and KS statistics is proposed to estimate Hurst exponents from short time series. Lastly, this paper also offers an exemplification to verify the effectiveness of the combined method. In addition, the corresponding results show that the VG can provide a reliable estimation of Hurst exponents.

Controlling the joint local false discovery rate is more powerful than meta-analysis methods in joint analysis of summary statistics from multiple genome-wide association studies.

PubMed

Jiang, Wei; Yu, Weichuan

2017-02-15

In genome-wide association studies (GWASs) of common diseases/traits, we often analyze multiple GWASs with the same phenotype together to discover associated genetic variants with higher power. Since it is difficult to access data with detailed individual measurements, summary-statistics-based meta-analysis methods have become popular to jointly analyze datasets from multiple GWASs. In this paper, we propose a novel summary-statistics-based joint analysis method based on controlling the joint local false discovery rate (Jlfdr). We prove that our method is the most powerful summary-statistics-based joint analysis method when controlling the false discovery rate at a certain level. In particular, the Jlfdr-based method achieves higher power than commonly used meta-analysis methods when analyzing heterogeneous datasets from multiple GWASs. Simulation experiments demonstrate the superior power of our method over meta-analysis methods. Also, our method discovers more associations than meta-analysis methods from empirical datasets of four phenotypes. The R-package is available at: http://bioinformatics.ust.hk/Jlfdr.html . eeyu@ust.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Power availability at terrestrial receptor sites for laser-power transmission from the satellite power system

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1982-01-01

A statistical model was developed for relating the temporal transmission parameters of a laser beam from a solar power satellite to observable meteorological data to determine the influence of weather on power reception at the earth-based receiver. Sites within 100 miles of existing high voltage transmission lines were examined and the model was developed for clear-sky and clouded conditions. The cases of total transmission through clouds at certain wavelengths, no transmission, and partial transmission were calculated for the cloud portion of the model. The study covered cirriform, stratiform, cumiliform, and mixed type clouds and the possibility of boring holes through the clouds with the beam. Utilization of weapons-quality beams for hole boring, was found to yield power availability increases of 9-33%, although no beneficial effects could be predicted in regions of persistent cloud cover. An efficiency of 80% was determined as possible if several receptor sites were available within 200-300 miles of each other, thereby allowing changes of reception point in cases of unacceptable meteorological conditions.

Neuroplasticity and Clinical Practice: Building Brain Power for Health.

PubMed

Shaffer, Joyce

2016-01-01

The focus of this review is on driving neuroplasticity in a positive direction using evidence-based interventions that also have the potential to improve general health. One goal is to provide an overview of the many ways new neuroscience can inform treatment protocols to empower and motivate clients to make the lifestyle choices that could help build brain power and could increase adherence to healthy lifestyle changes that have also been associated with simultaneously enhancing vigorous longevity, health, happiness, and wellness. Another goal is to explore the use of a focus in clinical practice on helping clients appreciate this new evidence and use evolving neuroscience in establishing individualized goals, designing strategies for achieving them and increasing treatment compliance. The timing is urgent for such interventions with goals of enhancing brain health across the lifespan and improving statistics on dementia worldwide.

Neuroplasticity and Clinical Practice: Building Brain Power for Health

PubMed Central

Shaffer, Joyce

2016-01-01

The focus of this review is on driving neuroplasticity in a positive direction using evidence-based interventions that also have the potential to improve general health. One goal is to provide an overview of the many ways new neuroscience can inform treatment protocols to empower and motivate clients to make the lifestyle choices that could help build brain power and could increase adherence to healthy lifestyle changes that have also been associated with simultaneously enhancing vigorous longevity, health, happiness, and wellness. Another goal is to explore the use of a focus in clinical practice on helping clients appreciate this new evidence and use evolving neuroscience in establishing individualized goals, designing strategies for achieving them and increasing treatment compliance. The timing is urgent for such interventions with goals of enhancing brain health across the lifespan and improving statistics on dementia worldwide. PMID:27507957

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

NASA Astrophysics Data System (ADS)

Chen, Lin; Abbey, Craig K.; Boone, John M.

2013-03-01

Previous research has demonstrated that a parameter extracted from a power function fit to the anatomical noise power spectrum, β, may be predictive of breast mass lesion detectability in x-ray based medical images of the breast. In this investigation, the value of β was compared with a number of other more widely used parameters, in order to determine the relationship between β and these other parameters. This study made use of breast CT data sets, acquired on two breast CT systems developed in our laboratory. A total of 185 breast data sets in 183 women were used, and only the unaffected breast was used (where no lesion was suspected). The anatomical noise power spectrum computed from two-dimensional region of interests (ROIs), was fit to a power function (NPS(f) = α f-β), and the exponent parameter (β) was determined using log/log linear regression. Breast density for each of the volume data sets was characterized in previous work. The breast CT data sets analyzed in this study were part of a previous study which evaluated the receiver operating characteristic (ROC) curve performance using simulated spherical lesions and a pre-whitened matched filter computer observer. This ROC information was used to compute the detectability index as well as the sensitivity at 95% specificity. The fractal dimension was computed from the same ROIs which were used for the assessment of β. The value of β was compared to breast density, detectability index, sensitivity, and fractal dimension, and the slope of these relationships was investigated to assess statistical significance from zero slope. A statistically significant non-zero slope was considered to be a positive association in this investigation. All comparisons between β and breast density, detectability index, sensitivity at 95% specificity, and fractal dimension demonstrated statistically significant association with p < 0.001 in all cases. The value of β was also found to be associated with patient age and breast diameter, parameters both related to breast density. In all associations between other parameters, lower values of β were associated with increased breast cancer detection performance. Specifically, lower values of β were associated with lower breast density, higher detectability index, higher sensitivity, and lower fractal dimension values. While causality was not and probably cannot be demonstrated, the strong, statistically significant association between the β metric and the other more widely used parameters suggest that β may be considered as a surrogate measure for breast cancer detection performance. These findings are specific to breast parenchymal patterns and mass lesions only.

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the principles are long known, historically, sample size determination has been difficult, because of relatively complex mathematical considerations and numerous different formulas. However, of late, there has been remarkable improvement in the availability, capability, and user-friendliness of power and sample size determination software. Many can execute routines for determination of sample size and power for a wide variety of research designs and statistical tests. With the drudgery of mathematical calculation gone, researchers must now concentrate on determining appropriate sample size and achieving these targets, so that study conclusions can be accepted as meaningful. PMID:27688437

Efficacy of plaque removal and learning effect of a powered and a manual toothbrush.

PubMed

Lazarescu, D; Boccaneala, S; Illiescu, A; De Boever, J A

2003-08-01

Subjects with high plaque and gingivitis scores can profit most from the introduction of new manual or powered tooth brushes. To improve their hygiene, not only the technical characteristics of new brushes but also the learning effect in efficient handling are of importance. : The present study compared the efficacy in plaque removal of an electric and a manual toothbrush in a general population and analysed the learning effect in efficient handling. Eighty healthy subjects, unfamiliar with electric brushes, were divided into two groups: group 1 used the Philips/Jordan HP 735 powered brush and group 2 used a manual brush, Oral-B40+. Plaque index (PI) and gingival bleeding index (GBI) were assessed at baseline and at weeks 3, 6, 12 and 18. After each evaluation, patients abstained from oral hygiene for 24 h. The next day a 3-min supervised brushing was performed. Before and after this brushing, PI was assessed for the estimation of the individual learning effect. The study was single blinded. Over the 18-week period, PI reduced gradually and statistically significantly (p<0.001) in group 1 from 2.9 (+/-0.38) to 1.5 (+/-0.24) and in group 2 from 2.9 (+/-0.34) to 2.2 (+/-0.23). From week 3 onwards, the difference between groups was statistically significant (p<0.001). The bleeding index decreased in group 1 from 28% (+/-17%) to 7% (+/-5%) (p<0.001) and in group 2 from 30% (+/-12%) to 12% (+/-6%) (p<0.001). The difference between groups was statistically significant (p<0.001) from week 6 onwards. The learning effect, expressed as the percentage of plaque reduction after 3 min of supervised brushing, was 33% for group 1 and 26% for group 2 at week 0. This percentage increased at week 18 to 64% in group 1 and 44% in group 2 (difference between groups statistically significant: p<0.001). The powered brush was significantly more efficient in removing plaque and improving gingival health than the manual brush in the group of subjects unfamiliar with electric brushes. There was also a significant learning effect that was more pronounced with the electric toothbrush.

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

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

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

DOE PAGES

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

2017-10-31

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI.

PubMed

Caroli, Anna; Prestia, Annapaola; Wade, Sara; Chen, Kewei; Ayutyanont, Napatkamon; Landau, Susan M; Madison, Cindee M; Haense, Cathleen; Herholz, Karl; Reiman, Eric M; Jagust, William J; Frisoni, Giovanni B

2015-01-01

The aim of this study was to compare the performance and power of the best-established diagnostic biological markers as outcome measures for clinical trials in patients with mild cognitive impairment (MCI). Magnetic resonance imaging, F-18 fluorodeoxyglucose positron emission tomography markers, and Alzheimer's Disease Assessment Scale-cognitive subscale were compared in terms of effect size and statistical power over different follow-up periods in 2 MCI groups, selected from Alzheimer's Disease Neuroimaging Initiative data set based on cerebrospinal fluid (abnormal cerebrospinal fluid Aβ1-42 concentration-ABETA+) or magnetic resonance imaging evidence of Alzheimer disease (positivity to hippocampal atrophy-HIPPO+). Biomarkers progression was modeled through mixed effect models. Scaled slope was chosen as measure of effect size. Biomarkers power was estimated using simulation algorithms. Seventy-four ABETA+ and 51 HIPPO+ MCI patients were included in the study. Imaging biomarkers of neurodegeneration, especially MR measurements, showed highest performance. For all biomarkers and both MCI groups, power increased with increasing follow-up time, irrespective of biomarker assessment frequency. These findings provide information about biomarker enrichment and outcome measurements that could be employed to reduce MCI patient samples and treatment duration in future clinical trials.

The Acute Effect of Upper-Body Complex Training on Power Output of Martial Art Athletes as Measured by the Bench Press Throw Exercise

PubMed Central

Liossis, Loudovikos Dimitrios; Forsyth, Jacky; Liossis, Ceorge; Tsolakis, Charilaos

2013-01-01

The purpose of this study was to examine the acute effect of upper body complex training on power output, as well as to determine the requisite preload intensity and intra-complex recovery interval needed to induce power output increases. Nine amateur-level combat/martial art athletes completed four distinct experimental protocols, which consisted of 5 bench press repetitions at either: 65% of one-repetition maximum (1RM) with a 4 min rest interval; 65% of 1RM with an 8 min rest; 85% of 1RM with a 4 min rest; or 85% of 1RM with an 8 min rest interval, performed on different days. Before (pre-conditioning) and after (post-conditioning) each experimental protocol, three bench press throws at 30% of 1RM were performed. Significant differences in power output pre-post conditioning were observed across all experimental protocols (F=26.489, partial eta2=0.768, p=0.001). Mean power output significantly increased when the preload stimulus of 65% 1RM was matched with 4 min of rest (p=0.001), and when the 85% 1RM preload stimulus was matched with 8 min of rest (p=0.001). Moreover, a statistically significant difference in power output was observed between the four conditioning protocols (F= 21.101, partial eta2=0.913, p=0.001). It was concluded that, in complex training, matching a heavy preload stimulus with a longer rest interval, and a lighter preload stimulus with a shorter rest interval is important for athletes wishing to increase their power production before training or competition. PMID:24511352

The association between major depression prevalence and sex becomes weaker with age.

PubMed

Patten, Scott B; Williams, Jeanne V A; Lavorato, Dina H; Wang, Jian Li; Bulloch, Andrew G M; Sajobi, Tolulope

2016-02-01

Women have a higher prevalence of major depressive episodes (MDE) than men, and the annual prevalence of MDE declines with age. Age by sex interactions may occur (a weakening of the sex effect with age), but are easily overlooked since individual studies lack statistical power to detect interactions. The objective of this study was to evaluate age by sex interactions in MDE prevalence. In Canada, a series of 10 national surveys conducted between 1996 and 2013 assessed MDE prevalence in respondents over the age of 14. Treating age as a continuous variable, binomial and linear regression was used to model age by sex interactions in each survey. To increase power, the survey-specific interaction coefficients were then pooled using meta-analytic methods. The estimated interaction terms were homogeneous. In the binomial regression model I (2) was 31.2 % and was not statistically significant (Q statistic = 13.1, df = 9, p = 0.159). The pooled estimate (-0.004) was significant (z = 3.13, p = 0.002), indicating that the effect of sex became weaker with increasing age. This resulted in near disappearance of the sex difference in the 75+ age group. This finding was also supported by an examination of age- and sex-specific estimates pooled across the surveys. The association of MDE prevalence with sex becomes weaker with age. The interaction may reflect biological effect modification. Investigators should test for, and consider inclusion of age by sex interactions in epidemiological analyses of MDE prevalence.

Gambling Risk Groups are Not All the Same: Risk Factors Amongst Sports Bettors.

PubMed

Russell, Alex M T; Hing, Nerilee; Li, En; Vitartas, Peter

2018-03-20

Sports betting is increasing worldwide, with an associated increase in sports betting-related problems. Previous studies have examined risk factors for problem gambling amongst sports bettors and have identified demographic, behavioural, marketing, normative and impulsiveness factors. These studies have generally compared those in problem gambling, or a combination of moderate risk and problem gambling, groups to non-problem gamblers, often due to statistical power issues. However, recent evidence suggests that, at a population level, the bulk of gambling-related harm stems from low risk and moderate risk gamblers, rather than problem gamblers. Thus it is essential to understand the risk factors for each level of gambling-related problems (low risk, moderate risk, problem) separately. The present study used a large sample (N = 1813) to compare each gambling risk group to non-problem gamblers, first using bivariate and then multivariate statistical techniques. A range of demographic, behavioural, marketing, normative and impulsiveness variables were included as possible risk factors. The results indicated that some variables, such as gambling expenditure, number of accounts with different operators, number of different types of promotions used and impulsiveness were significantly higher for all risk groups, while others such as some normative factors, age, gender and particular sports betting variables only applied to those with the highest level of gambling-related problems. The results generally supported findings from previous literature for problem gamblers, and extended these findings to low risk and moderate risk groups. In the future, where statistical power allows, risk factors should be assessed separately for all levels of gambling problems.

Statistical mechanics and scaling of fault populations with increasing strain in the Corinth Rift

NASA Astrophysics Data System (ADS)

Michas, Georgios; Vallianatos, Filippos; Sammonds, Peter

2015-12-01

Scaling properties of fracture/fault systems are studied in order to characterize the mechanical properties of rocks and to provide insight into the mechanisms that govern fault growth. A comprehensive image of the fault network in the Corinth Rift, Greece, obtained through numerous field studies and marine geophysical surveys, allows for the first time such a study over the entire area of the Rift. We compile a detailed fault map of the area and analyze the scaling properties of fault trace-lengths by using a statistical mechanics model, derived in the framework of generalized statistical mechanics and associated maximum entropy principle. By using this framework, a range of asymptotic power-law to exponential-like distributions are derived that can well describe the observed scaling patterns of fault trace-lengths in the Rift. Systematic variations and in particular a transition from asymptotic power-law to exponential-like scaling are observed to be a function of increasing strain in distinct strain regimes in the Rift, providing quantitative evidence for such crustal processes in a single tectonic setting. These results indicate the organization of the fault system as a function of brittle strain in the Earth's crust and suggest there are different mechanisms for fault growth in the distinct parts of the Rift. In addition, other factors such as fault interactions and the thickness of the brittle layer affect how the fault system evolves in time. The results suggest that regional strain, fault interactions and the boundary condition of the brittle layer may control fault growth and the fault network evolution in the Corinth Rift.

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

A statistical spatial power spectrum of the Earth's lithospheric magnetic field

NASA Astrophysics Data System (ADS)

Thébault, E.; Vervelidou, F.

2015-05-01

The magnetic field of the Earth's lithosphere arises from rock magnetization contrasts that were shaped over geological times. The field can be described mathematically in spherical harmonics or with distributions of magnetization. We exploit this dual representation and assume that the lithospheric field is induced by spatially varying susceptibility values within a shell of constant thickness. By introducing a statistical assumption about the power spectrum of the susceptibility, we then derive a statistical expression for the spatial power spectrum of the crustal magnetic field for the spatial scales ranging from 60 to 2500 km. This expression depends on the mean induced magnetization, the thickness of the shell, and a power law exponent for the power spectrum of the susceptibility. We test the relevance of this form with a misfit analysis to the observational NGDC-720 lithospheric magnetic field model power spectrum. This allows us to estimate a mean global apparent induced magnetization value between 0.3 and 0.6 A m-1, a mean magnetic crustal thickness value between 23 and 30 km, and a root mean square for the field value between 190 and 205 nT at 95 per cent. These estimates are in good agreement with independent models of the crustal magnetization and of the seismic crustal thickness. We carry out the same analysis in the continental and oceanic domains separately. We complement the misfit analyses with a Kolmogorov-Smirnov goodness-of-fit test and we conclude that the observed power spectrum can be each time a sample of the statistical one.

Statistical power and effect sizes of depression research in Japan.

PubMed

Okumura, Yasuyuki; Sakamoto, Shinji

2011-06-01

Few studies have been conducted on the rationales for using interpretive guidelines for effect size, and most of the previous statistical power surveys have covered broad research domains. The present study aimed to estimate the statistical power and to obtain realistic target effect sizes of depression research in Japan. We systematically reviewed 18 leading journals of psychiatry and psychology in Japan and identified 974 depression studies that were mentioned in 935 articles published between 1990 and 2006. In 392 studies, logistic regression analyses revealed that using clinical populations was independently associated with being a statistical power of <0.80 (odds ratio 5.9, 95% confidence interval 2.9-12.0) and of <0.50 (odds ratio 4.9, 95% confidence interval 2.3-10.5). Of the studies using clinical populations, 80% did not achieve a power of 0.80 or more, and 44% did not achieve a power of 0.50 or more to detect the medium population effect sizes. A predictive model for the proportion of variance explained was developed using a linear mixed-effects model. The model was then used to obtain realistic target effect sizes in defined study characteristics. In the face of a real difference or correlation in population, many depression researchers are less likely to give a valid result than simply tossing a coin. It is important to educate depression researchers in order to enable them to conduct an a priori power analysis. © 2011 The Authors. Psychiatry and Clinical Neurosciences © 2011 Japanese Society of Psychiatry and Neurology.

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

PubMed Central

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-01-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0. PMID:27892471

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies.

PubMed

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-28

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

NASA Astrophysics Data System (ADS)

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies.

PubMed

Grimm, Dominik G; Roqueiro, Damian; Salomé, Patrice A; Kleeberger, Stefan; Greshake, Bastian; Zhu, Wangsheng; Liu, Chang; Lippert, Christoph; Stegle, Oliver; Schölkopf, Bernhard; Weigel, Detlef; Borgwardt, Karsten M

2017-01-01

The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana , using flowering and growth-related traits. © 2016 American Society of Plant Biologists. All rights reserved.

Accounting for undetected compounds in statistical analyses of mass spectrometry 'omic studies.

PubMed

Taylor, Sandra L; Leiserowitz, Gary S; Kim, Kyoungmi

2013-12-01

Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a compound is absent from a sample or is present but at a concentration below the detection limit. Several strategies are available for statistically analyzing data with missing values. The accelerated failure time (AFT) model assumes all missing values result from censoring below a detection limit. Under a mixture model, missing values can result from a combination of censoring and the absence of a compound. We compare power and estimation of a mixture model to an AFT model. Based on simulated data, we found the AFT model to have greater power to detect differences in means and point mass proportions between groups. However, the AFT model yielded biased estimates with the bias increasing as the proportion of observations in the point mass increased while estimates were unbiased with the mixture model except if all missing observations came from censoring. These findings suggest using the AFT model for hypothesis testing and mixture model for estimation. We demonstrated this approach through application to glycomics data of serum samples from women with ovarian cancer and matched controls.

Locus of emotion: the effect of task order and age on emotion perceived and emotion felt in response to music.

PubMed

Schubert, Emery

2007-01-01

The relationship between emotions perceived to be expressed (external locus EL) versus emotions felt (internal locus--IL) in response to music was examined using 5 contrasting pieces of Romantic, Western art music. The main hypothesis tested was that emotion expressed along the dimensions of emotional-strength, valence, and arousal were lower in magnitude for IL than EL. IL and EL judgments made together after one listening (Experiment 2, n = 18) produced less differentiated responses than when each task was performed after separate listenings (Experiment 1, n = 28). This merging of responses in the locus-task-together condition started to disappear as statistical power was increased. Statistical power was increased by recruiting an additional subject pool of elderly individuals (Experiment 3, n = 19, mean age 75 years). Their valence responses were more positive, and their emotional-strength ratings were generally lower, compared to their younger counterparts. Overall data analysis revealed that IL responses fluctuated slightly more than EL emotions, meaning that the latter are more stable. An additional dimension of dominance-submissiveness was also examined, and was useful in differentiating between pieces, but did not return a difference between IL and EL. Some therapy applications of these findings are discussed.

Targeted On-Demand Team Performance App Development

DTIC Science & Technology

2016-10-01

from three sites; 6) Preliminary analysis indicates larger than estimate effect size and study is sufficiently powered for generalizable outcomes...statistical analyses, and examine any resulting qualitative data for trends or connections to statistical outcomes. On Schedule 21 Predictive...Preliminary analysis indicates larger than estimate effect size and study is sufficiently powered for generalizable outcomes.  What opportunities for

Testing for qualitative heterogeneity: An application to composite endpoints in survival analysis.

PubMed

Oulhaj, Abderrahim; El Ghouch, Anouar; Holman, Rury R

2017-01-01

Composite endpoints are frequently used in clinical outcome trials to provide more endpoints, thereby increasing statistical power. A key requirement for a composite endpoint to be meaningful is the absence of the so-called qualitative heterogeneity to ensure a valid overall interpretation of any treatment effect identified. Qualitative heterogeneity occurs when individual components of a composite endpoint exhibit differences in the direction of a treatment effect. In this paper, we develop a general statistical method to test for qualitative heterogeneity, that is to test whether a given set of parameters share the same sign. This method is based on the intersection-union principle and, provided that the sample size is large, is valid whatever the model used for parameters estimation. We propose two versions of our testing procedure, one based on a random sampling from a Gaussian distribution and another version based on bootstrapping. Our work covers both the case of completely observed data and the case where some observations are censored which is an important issue in many clinical trials. We evaluated the size and power of our proposed tests by carrying out some extensive Monte Carlo simulations in the case of multivariate time to event data. The simulations were designed under a variety of conditions on dimensionality, censoring rate, sample size and correlation structure. Our testing procedure showed very good performances in terms of statistical power and type I error. The proposed test was applied to a data set from a single-center, randomized, double-blind controlled trial in the area of Alzheimer's disease.

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.

Equivalent circuit model parameters of a high-power Li-ion battery: Thermal and state of charge effects

NASA Astrophysics Data System (ADS)

Gomez, Jamie; Nelson, Ruben; Kalu, Egwu E.; Weatherspoon, Mark H.; Zheng, Jim P.

2011-05-01

Equivalent circuit model (EMC) of a high-power Li-ion battery that accounts for both temperature and state of charge (SOC) effects known to influence battery performance is presented. Electrochemical impedance measurements of a commercial high power Li-ion battery obtained in the temperature range 20 to 50 °C at various SOC values was used to develop a simple EMC which was used in combination with a non-linear least squares fitting procedure that used thirteen parameters for the analysis of the Li-ion cell. The experimental results show that the solution and charge transfer resistances decreased with increase in cell operating temperature and decreasing SOC. On the other hand, the Warburg admittance increased with increasing temperature and decreasing SOC. The developed model correlations that are capable of being used in process control algorithms are presented for the observed impedance behavior with respect to temperature and SOC effects. The predicted model parameters for the impedance elements Rs, Rct and Y013 show low variance of 5% when compared to the experimental data and therefore indicates a good statistical agreement of correlation model to the actual experimental values.

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

PubMed

Adams, Dean C

2014-09-01

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

Regression assumptions in clinical psychology research practice-a systematic review of common misconceptions.

PubMed

Ernst, Anja F; Albers, Casper J

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.

System Study: Isolation Condenser 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the isolation condenser (ISO) system at four U.S. boiling water reactors. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing trends were identified. A statistically significant decreasing trend was identified for ISO unreliability. The magnitude of the trend indicated a 1.5 percent decrease inmore » system unreliability over the last 10 years.« less

Regression assumptions in clinical psychology research practice—a systematic review of common misconceptions

PubMed Central

Ernst, Anja F.

2017-01-01

Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking. PMID:28533971

Phase transitions in the first-passage time of scale-invariant correlated processes

PubMed Central

Carretero-Campos, Concepción; Bernaola-Galván, Pedro; Ch. Ivanov, Plamen

2012-01-01

A key quantity describing the dynamics of complex systems is the first-passage time (FPT). The statistical properties of FPT depend on the specifics of the underlying system dynamics. We present a unified approach to account for the diversity of statistical behaviors of FPT observed in real-world systems. We find three distinct regimes, separated by two transition points, with fundamentally different behavior for FPT as a function of increasing strength of the correlations in the system dynamics: stretched exponential, power-law, and saturation regimes. In the saturation regime, the average length of FPT diverges proportionally to the system size, with important implications for understanding electronic delocalization in one-dimensional correlated-disordered systems. PMID:22400544

BIG DATA AND STATISTICS

PubMed Central

Rossell, David

2016-01-01

Big Data brings unprecedented power to address scientific, economic and societal issues, but also amplifies the possibility of certain pitfalls. These include using purely data-driven approaches that disregard understanding the phenomenon under study, aiming at a dynamically moving target, ignoring critical data collection issues, summarizing or preprocessing the data inadequately and mistaking noise for signal. We review some success stories and illustrate how statistical principles can help obtain more reliable information from data. We also touch upon current challenges that require active methodological research, such as strategies for efficient computation, integration of heterogeneous data, extending the underlying theory to increasingly complex questions and, perhaps most importantly, training a new generation of scientists to develop and deploy these strategies. PMID:27722040

Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

PubMed Central

Bacchetti, Peter; Deeks, Steven G.; McCune, Joseph M.

2011-01-01

Innovative clinical and translational research is often delayed or prevented by reviewers’ expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an N of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation. PMID:21677197

A global goodness-of-fit statistic for Cox regression models.

PubMed

Parzen, M; Lipsitz, S R

1999-06-01

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.

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

Mendes, J.; Bessa, R.J.; Keko, H.

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highlymore » dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.« less

Pathway analysis with next-generation sequencing data.

PubMed

Zhao, Jinying; Zhu, Yun; Boerwinkle, Eric; Xiong, Momiao

2015-04-01

Although pathway analysis methods have been developed and successfully applied to association studies of common variants, the statistical methods for pathway-based association analysis of rare variants have not been well developed. Many investigators observed highly inflated false-positive rates and low power in pathway-based tests of association of rare variants. The inflated false-positive rates and low true-positive rates of the current methods are mainly due to their lack of ability to account for gametic phase disequilibrium. To overcome these serious limitations, we develop a novel statistic that is based on the smoothed functional principal component analysis (SFPCA) for pathway association tests with next-generation sequencing data. The developed statistic has the ability to capture position-level variant information and account for gametic phase disequilibrium. By intensive simulations, we demonstrate that the SFPCA-based statistic for testing pathway association with either rare or common or both rare and common variants has the correct type 1 error rates. Also the power of the SFPCA-based statistic and 22 additional existing statistics are evaluated. We found that the SFPCA-based statistic has a much higher power than other existing statistics in all the scenarios considered. To further evaluate its performance, the SFPCA-based statistic is applied to pathway analysis of exome sequencing data in the early-onset myocardial infarction (EOMI) project. We identify three pathways significantly associated with EOMI after the Bonferroni correction. In addition, our preliminary results show that the SFPCA-based statistic has much smaller P-values to identify pathway association than other existing methods.

Investigating human skeletal muscle physiology with unilateral exercise models: when one limb is more powerful than two.

PubMed

MacInnis, Martin J; McGlory, Chris; Gibala, Martin J; Phillips, Stuart M

2017-06-01

Direct sampling of human skeletal muscle using the needle biopsy technique can facilitate insight into the biochemical and histological responses resulting from changes in exercise or feeding. However, the muscle biopsy procedure is invasive, and analyses are often expensive, which places pragmatic restraints on sample sizes. The unilateral exercise model can serve to increase statistical power and reduce the time and cost of a study. With this approach, 2 limbs of a participant are randomized to 1 of 2 treatments that can be applied almost concurrently or sequentially depending on the nature of the intervention. Similar to a typical repeated measures design, comparisons are made within participants, which increases statistical power by reducing the amount of between-person variability. A washout period is often unnecessary, reducing the time needed to complete the experiment and the influence of potential confounding variables such as habitual diet, activity, and sleep. Variations of the unilateral exercise model have been employed to investigate the influence of exercise, diet, and the interaction between the 2, on a wide range of variables including mitochondrial content, capillary density, and skeletal muscle hypertrophy. Like any model, unilateral exercise has some limitations: it cannot be used to study variables that potentially transfer across limbs, and it is generally limited to exercises that can be performed in pairs of treatments. Where appropriate, however, the unilateral exercise model can yield robust, well-controlled investigations of skeletal muscle responses to a wide range of interventions and conditions including exercise, dietary manipulation, and disuse or immobilization.

Cycling on rollers: influence of tyre pressure and cross section on power requirements.

PubMed

Reiser, Raoul; Watt, Jon; Peterson, Michael

2003-07-01

The resistance against a cyclist while riding on rollers is due mainly to rolling resistance produced by the deformation of the tyre as it rolls against small diameter drums. Resistance is then combined with wheel speed to set power output. The effect of tyre pressure and cross-section on power was investigated by systematically altering the pressure (552 kPa, 690 kPa, and 827 KPa) in a 20c, 23c, 25c, and 28c tyre of the same design while riding at a wheel speed of 45 kph. Average power over 1 minute was measured with a Power Tap Hub (Tune Corporation, Cambridge, Massachusetts, USA) on five occasions. Statistical significance was evaluated at p < 0.05. Power requirements increased significantly with each reduction in tyre pressure for all tyres and pressures except the 25c between 690 and 827 kPa. The 20c tyre required significantly more power from the cyclist at each tested tyre pressure when compared to the other tyres (which were not different from each other). The differences in resistance from tyre size were not observed when ridden on the road. Additionally, a slightly different tyre design from the same manufacturer responded similarly in the 20c, but was significantly different in the 23c size. It was also observed that power requirements increased significantly when both the wheels were ridden on the rollers as compared to just the rear wheel. These results indicate that the power requirements may be significantly altered by the cyclist by adjusting tyre pressure, tyre cross-section size, tyre type, and with the number of wheels contacting the rollers. However, the magnitude of these power requirements may not be suitable for intense workouts of trained cyclists.

PCA as a practical indicator of OPLS-DA model reliability.

PubMed

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

Detecting the response of fish assemblages to stream restoration: Effects of different sampling designsf

USGS Publications Warehouse

Baldigo, Barry P.; Warren, D.R.

2008-01-01

Increased trout production within limited stream reaches is a popular goal for restoration projects, yet investigators seldom monitor, assess, or publish the associated effects on fish assemblages. Fish community data from a total of 40 surveys at restored and reference reaches in three streams of the Catskill Mountains, New York, were analyzed a posteriori to determine how the ability to detect significant changes in biomass of brown trout Salmo trutta, all salmonids, or the entire fish community differs with effect size, number of streams assessed, process used to quantify the index response, and number of replicates collected before and after restoration. Analyses of statistical power (probability of detecting a meaningful difference or effect) and integrated power (average power over all possible ??-values) were combined with before-after, control-impact analyses to assess the effectiveness of alternate sampling and analysis designs. In general, the more robust analyses indicated that biomass of brown trout and salmonid populations increased significantly in restored reaches but that the net increases (relative to the reference reach) were significant only at two of four restored reaches. Restoration alone could not account for the net increases in total biomass of fish communities. Power analyses generally showed that integrated power was greater than 0.95 when (1) biomass increases were larger than 5.0 g/m2, (2) the total number of replicates ranged from 4 to 8, and (3) coefficients of variation (CVs) for responses were less than 40%. Integrated power was often greater than 0.95 for responses as low as 1.0 g/m2 if the response CVs were less than 30%. Considering that brown trout, salmonid, and community biomass increased by 2.99 g/m2 on average (SD= 1.17 g/m2) in the four restored reaches, use of two to three replicates both before and after restoration would have an integrated power of about 0.95 and would help detect significant changes in fish biomass under similar situations. ?? Copyright by the American Fisheries Society 2008.

Threshold-dependent sample sizes for selenium assessment with stream fish tissue

USGS Publications Warehouse

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

Nonlinear GARCH model and 1 / f noise

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Ruseckas, J.

2015-06-01

Auto-regressive conditionally heteroskedastic (ARCH) family models are still used, by practitioners in business and economic policy making, as a conditional volatility forecasting models. Furthermore ARCH models still are attracting an interest of the researchers. In this contribution we consider the well known GARCH(1,1) process and its nonlinear modifications, reminiscent of NGARCH model. We investigate the possibility to reproduce power law statistics, probability density function and power spectral density, using ARCH family models. For this purpose we derive stochastic differential equations from the GARCH processes in consideration. We find the obtained equations to be similar to a general class of stochastic differential equations known to reproduce power law statistics. We show that linear GARCH(1,1) process has power law distribution, but its power spectral density is Brownian noise-like. However, the nonlinear modifications exhibit both power law distribution and power spectral density of the 1 /fβ form, including 1 / f noise.

The MAX Statistic is Less Powerful for Genome Wide Association Studies Under Most Alternative Hypotheses.

PubMed

Shifflett, Benjamin; Huang, Rong; Edland, Steven D

2017-01-01

Genotypic association studies are prone to inflated type I error rates if multiple hypothesis testing is performed, e.g., sequentially testing for recessive, multiplicative, and dominant risk. Alternatives to multiple hypothesis testing include the model independent genotypic χ 2 test, the efficiency robust MAX statistic, which corrects for multiple comparisons but with some loss of power, or a single Armitage test for multiplicative trend, which has optimal power when the multiplicative model holds but with some loss of power when dominant or recessive models underlie the genetic association. We used Monte Carlo simulations to describe the relative performance of these three approaches under a range of scenarios. All three approaches maintained their nominal type I error rates. The genotypic χ 2 and MAX statistics were more powerful when testing a strictly recessive genetic effect or when testing a dominant effect when the allele frequency was high. The Armitage test for multiplicative trend was most powerful for the broad range of scenarios where heterozygote risk is intermediate between recessive and dominant risk. Moreover, all tests had limited power to detect recessive genetic risk unless the sample size was large, and conversely all tests were relatively well powered to detect dominant risk. Taken together, these results suggest the general utility of the multiplicative trend test when the underlying genetic model is unknown.

Statistical research into low-power solar flares. Main phase duration

NASA Astrophysics Data System (ADS)

Borovik, Aleksandr; Zhdanov, Anton

2017-12-01

This paper is a sequel to earlier papers on time parameters of solar flares in the Hα line. Using data from the International Flare Patrol, an electronic database of solar flares for the period 1972-2010 has been created. The statistical analysis of the duration of the main phase has shown that it increases with increasing flare class and brightness. It has been found that the duration of the main phase depends on the type and features of development of solar flares. Flares with one brilliant point have the shortest main phase; flares with several intensity maxima and two-ribbon flares, the longest one. We have identified more than 3000 cases with an ultra-long duration of the main phase (more than 60 minutes). For 90% of such flares the duration of the main phase is 2-3 hrs, but sometimes it reaches 12 hrs.

Modeling of a Robust Confidence Band for the Power Curve of a Wind Turbine.

PubMed

Hernandez, Wilmar; Méndez, Alfredo; Maldonado-Correa, Jorge L; Balleteros, Francisco

2016-12-07

Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques. However, the observations that are used for carrying out the statistical analysis are obtained by using the binning method, and in each bin, the outliers are eliminated by using a censorship process based on robust statistical techniques. Then, the observations that are not outliers are divided into observation sets. Finally, both the power curve of the wind turbine and the two curves that define the robust confidence band are estimated using each of the previously mentioned observation sets.

Modeling of a Robust Confidence Band for the Power Curve of a Wind Turbine

PubMed Central

Hernandez, Wilmar; Méndez, Alfredo; Maldonado-Correa, Jorge L.; Balleteros, Francisco

2016-01-01

Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques. However, the observations that are used for carrying out the statistical analysis are obtained by using the binning method, and in each bin, the outliers are eliminated by using a censorship process based on robust statistical techniques. Then, the observations that are not outliers are divided into observation sets. Finally, both the power curve of the wind turbine and the two curves that define the robust confidence band are estimated using each of the previously mentioned observation sets. PMID:27941604

Water Polo Game-Related Statistics in Women’s International Championships: Differences and Discriminatory Power

PubMed Central

Escalante, Yolanda; Saavedra, Jose M.; Tella, Victor; Mansilla, Mirella; García-Hermoso, Antonio; Dominguez, Ana M.

2012-01-01

The aims of this study were (i) to compare women’s water polo game-related statistics by match outcome (winning and losing teams) and phase (preliminary, classificatory, and semi-final/bronze medal/gold medal), and (ii) identify characteristics that discriminate performances for each phase. The game-related statistics of the 124 women’s matches played in five International Championships (World and European Championships) were analyzed. Differences between winning and losing teams in each phase were determined using the chi-squared. A discriminant analysis was then performed according to context in each of the three phases. It was found that the game-related statistics differentiate the winning from the losing teams in each phase of an international championship. The differentiating variables were both offensive (centre goals, power-play goals, counterattack goal, assists, offensive fouls, steals, blocked shots, and won sprints) and defensive (goalkeeper-blocked shots, goalkeeper-blocked inferiority shots, and goalkeeper-blocked 5-m shots). The discriminant analysis showed the game-related statistics to discriminate performance in all phases: preliminary, classificatory, and final phases (92%, 90%, and 83%, respectively). Two variables were discriminatory by match outcome (winning or losing teams) in all three phases: goals and goalkeeper-blocked shots. Key pointsThe preliminary phase that more than one variable was involved in this differentiation, including both offensive and defensive aspects of the game.The game-related statistics were found to have a high discriminatory power in predicting the result of matches with shots and goalkeeper-blocked shots being discriminatory variables in all three phases.Knowledge of the characteristics of women’s water polo game-related statistics of the winning teams and their power to predict match outcomes will allow coaches to take these characteristics into account when planning training and match preparation. PMID:24149356

Jump Shrug Height and Landing Forces Across Various Loads.

PubMed

Suchomel, Timothy J; Taber, Christopher B; Wright, Glenn A

2016-01-01

The purpose of this study was to examine the effect that load has on the mechanics of the jump shrug. Fifteen track and field and club/intramural athletes (age 21.7 ± 1.3 y, height 180.9 ± 6.6 cm, body mass 84.7 ± 13.2 kg, 1-repetition-maximum (1RM) hang power clean 109.1 ± 17.2 kg) performed repetitions of the jump shrug at 30%, 45%, 65%, and 80% of their 1RM hang power clean. Jump height, peak landing force, and potential energy of the system at jump-shrug apex were compared between loads using a series of 1-way repeated-measures ANOVAs. Statistical differences in jump height (P < .001), peak landing force (P = .012), and potential energy of the system (P < .001) existed; however, there were no statistically significant pairwise comparisons in peak landing force between loads (P > .05). The greatest magnitudes of jump height, peak landing force, and potential energy of the system at the apex of the jump shrug occurred at 30% 1RM hang power clean and decreased as the external load increased from 45% to 80% 1RM hang power clean. Relationships between peak landing force and potential energy of the system at jump-shrug apex indicate that the landing forces produced during the jump shrug may be due to the landing strategy used by the athletes, especially at lighter loads. Practitioners may prescribe heavier loads during the jump-shrug exercise without viewing landing force as a potential limitation.

Kidney function endpoints in kidney transplant trials: a struggle for power.

PubMed

Ibrahim, A; Garg, A X; Knoll, G A; Akbari, A; White, C A

2013-03-01

Kidney function endpoints are commonly used in randomized controlled trials (RCTs) in kidney transplantation (KTx). We conducted this study to estimate the proportion of ongoing RCTs with kidney function endpoints in KTx where the proposed sample size is large enough to detect meaningful differences in glomerular filtration rate (GFR) with adequate statistical power. RCTs were retrieved using the key word "kidney transplantation" from the National Institute of Health online clinical trial registry. Included trials had at least one measure of kidney function tracked for at least 1 month after transplant. We determined the proportion of two-arm parallel trials that had sufficient sample sizes to detect a minimum 5, 7.5 and 10 mL/min difference in GFR between arms. Fifty RCTs met inclusion criteria. Only 7% of the trials were above a sample size of 562, the number needed to detect a minimum 5 mL/min difference between the groups should one exist (assumptions: α = 0.05; power = 80%, 10% loss to follow-up, common standard deviation of 20 mL/min). The result increased modestly to 36% of trials when a minimum 10 mL/min difference was considered. Only a minority of ongoing trials have adequate statistical power to detect between-group differences in kidney function using conventional sample size estimating parameters. For this reason, some potentially effective interventions which ultimately could benefit patients may be abandoned from future assessment. © Copyright 2013 The American Society of Transplantation and the American Society of Transplant Surgeons.

On damage detection in wind turbine gearboxes using outlier analysis

NASA Astrophysics Data System (ADS)

Antoniadou, Ifigeneia; Manson, Graeme; Dervilis, Nikolaos; Staszewski, Wieslaw J.; Worden, Keith

2012-04-01

The proportion of worldwide installed wind power in power systems increases over the years as a result of the steadily growing interest in renewable energy sources. Still, the advantages offered by the use of wind power are overshadowed by the high operational and maintenance costs, resulting in the low competitiveness of wind power in the energy market. In order to reduce the costs of corrective maintenance, the application of condition monitoring to gearboxes becomes highly important, since gearboxes are among the wind turbine components with the most frequent failure observations. While condition monitoring of gearboxes in general is common practice, with various methods having been developed over the last few decades, wind turbine gearbox condition monitoring faces a major challenge: the detection of faults under the time-varying load conditions prevailing in wind turbine systems. Classical time and frequency domain methods fail to detect faults under variable load conditions, due to the temporary effect that these faults have on vibration signals. This paper uses the statistical discipline of outlier analysis for the damage detection of gearbox tooth faults. A simplified two-degree-of-freedom gearbox model considering nonlinear backlash, time-periodic mesh stiffness and static transmission error, simulates the vibration signals to be analysed. Local stiffness reduction is used for the simulation of tooth faults and statistical processes determine the existence of intermittencies. The lowest level of fault detection, the threshold value, is considered and the Mahalanobis squared-distance is calculated for the novelty detection problem.

A global estimate of the Earth's magnetic crustal thickness

NASA Astrophysics Data System (ADS)

Vervelidou, Foteini; Thébault, Erwan

2014-05-01

The Earth's lithosphere is considered to be magnetic only down to the Curie isotherm. Therefore the Curie isotherm can, in principle, be estimated by analysis of magnetic data. Here, we propose such an analysis in the spectral domain by means of a newly introduced regional spatial power spectrum. This spectrum is based on the Revised Spherical Cap Harmonic Analysis (R-SCHA) formalism (Thébault et al., 2006). We briefly discuss its properties and its relationship with the Spherical Harmonic spatial power spectrum. This relationship allows us to adapt any theoretical expression of the lithospheric field power spectrum expressed in Spherical Harmonic degrees to the regional formulation. We compared previously published statistical expressions (Jackson, 1994 ; Voorhies et al., 2002) to the recent lithospheric field models derived from the CHAMP and airborne measurements and we finally developed a new statistical form for the power spectrum of the Earth's magnetic lithosphere that we think provides more consistent results. This expression depends on the mean magnetization, the mean crustal thickness and a power law value that describes the amount of spatial correlation of the sources. In this study, we make a combine use of the R-SCHA surface power spectrum and this statistical form. We conduct a series of regional spectral analyses for the entire Earth. For each region, we estimate the R-SCHA surface power spectrum of the NGDC-720 Spherical Harmonic model (Maus, 2010). We then fit each of these observational spectra to the statistical expression of the power spectrum of the Earth's lithosphere. By doing so, we estimate the large wavelengths of the magnetic crustal thickness on a global scale that are not accessible directly from the magnetic measurements due to the masking core field. We then discuss these results and compare them to the results we obtained by conducting a similar spectral analysis, but this time in the cartesian coordinates, by means of a published statistical expression (Maus et al., 1997). We also compare our results to crustal thickness global maps derived by means of additional geophysical data (Purucker et al., 2002).

An adaptive design for updating the threshold value of a continuous biomarker.

PubMed

Spencer, Amy V; Harbron, Chris; Mander, Adrian; Wason, James; Peers, Ian

2016-11-30

Potential predictive biomarkers are often measured on a continuous scale, but in practice, a threshold value to divide the patient population into biomarker 'positive' and 'negative' is desirable. Early phase clinical trials are increasingly using biomarkers for patient selection, but at this stage, it is likely that little will be known about the relationship between the biomarker and the treatment outcome. We describe a single-arm trial design with adaptive enrichment, which can increase power to demonstrate efficacy within a patient subpopulation, the parameters of which are also estimated. Our design enables us to learn about the biomarker and optimally adjust the threshold during the study, using a combination of generalised linear modelling and Bayesian prediction. At the final analysis, a binomial exact test is carried out, allowing the hypothesis that 'no population subset exists in which the novel treatment has a desirable response rate' to be tested. Through extensive simulations, we are able to show increased power over fixed threshold methods in many situations without increasing the type-I error rate. We also show that estimates of the threshold, which defines the population subset, are unbiased and often more precise than those from fixed threshold studies. We provide an example of the method applied (retrospectively) to publically available data from a study of the use of tamoxifen after mastectomy by the German Breast Study Group, where progesterone receptor is the biomarker of interest. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

State Electricity Profiles

EIA Publications

2017-01-01

The annual report presents data tables describing the electricity industry in each State. Data include: summary statistics; the 10 largest plants by generating capacity; the top five entities ranked by sector; electric power industry generating capacity by primary energy source; electric power industry generation by primary energy source; utility delivered fuel prices for coal, petroleum, and natural gas; electric power industry emissions estimates; retail sales, revenue, and average retail price by sector; retail electricity sales statistics; and supply and disposition of electricity; net metering counts and capacity by technology and customer type; and advanced metering counts by customer type.

Statistical patterns of visual search for hidden objects

PubMed Central

Credidio, Heitor F.; Teixeira, Elisângela N.; Reis, Saulo D. S.; Moreira, André A.; Andrade Jr, José S.

2012-01-01

The movement of the eyes has been the subject of intensive research as a way to elucidate inner mechanisms of cognitive processes. A cognitive task that is rather frequent in our daily life is the visual search for hidden objects. Here we investigate through eye-tracking experiments the statistical properties associated with the search of target images embedded in a landscape of distractors. Specifically, our results show that the twofold process of eye movement, composed of sequences of fixations (small steps) intercalated by saccades (longer jumps), displays characteristic statistical signatures. While the saccadic jumps follow a log-normal distribution of distances, which is typical of multiplicative processes, the lengths of the smaller steps in the fixation trajectories are consistent with a power-law distribution. Moreover, the present analysis reveals a clear transition between a directional serial search to an isotropic random movement as the difficulty level of the searching task is increased. PMID:23226829

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

PubMed

Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

2004-11-01

Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.

Use of higher order signal moments and high speed digital sampling technique for neutron flux measurement

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

Baers, L.B.; Gutierrez, T.R.; Mendoza, R.A.

1993-08-01

The second (conventional variance or Campbell signal) , , , the third , and the modified fourth order [minus] 3*[sup 2] etc. central signal moments associated with the amplified (K) and filtered currents [i[sub 1], i[sub 2], x = K * (i[sub 2]-),] from two electrodes of an ex-core neutron sensitive fission detector have been measured versus the reactor power of the 1 MW TRIGA reactor in Mexico City. Two channels of a high speed (400 kHz) multiplexing data sampler and A/D converter with 12 bit resolution and one megawords buffer memory were used. The data were further retrieved intomore » a PC and estimates for auto- and cross-correlation moments up to the fifth order, coherence (/[radical]), skewness (/([radical]/)[sup 3]), excess (/[sup 2] - 3) etc. quantities were calculated off-line. A five mode operation of the detector was achieved including the conventional counting rates and currents in agreement with the theory and the authors previous results with analogue techniques. The signals were proportional to the neutron flux and reactor power in some flux ranges. The suppression of background noise is improved and the lower limit of the measurement range is extended as the order of moment is increased, in agreement with the theory. On the other hand the statistical uncertainty is increased. At increasing flux levels it was statistically more difficult to obtain flux estimates based on the higher order ([>=]3) moments.« less

Gravitational dynamos and the low-frequency geomagnetic secular variation.

PubMed

Olson, P

2007-12-18

Self-sustaining numerical dynamos are used to infer the sources of low-frequency secular variation of the geomagnetic field. Gravitational dynamo models powered by compositional convection in an electrically conducting, rotating fluid shell exhibit several regimes of magnetic field behavior with an increasing Rayleigh number of the convection, including nearly steady dipoles, chaotic nonreversing dipoles, and chaotic reversing dipoles. The time average dipole strength and dipolarity of the magnetic field decrease, whereas the dipole variability, average dipole tilt angle, and frequency of polarity reversals increase with Rayleigh number. Chaotic gravitational dynamos have large-amplitude dipole secular variation with maximum power at frequencies corresponding to a few cycles per million years on Earth. Their external magnetic field structure, dipole statistics, low-frequency power spectra, and polarity reversal frequency are comparable to the geomagnetic field. The magnetic variability is driven by the Lorentz force and is characterized by an inverse correlation between dynamo magnetic and kinetic energy fluctuations. A constant energy dissipation theory accounts for this inverse energy correlation, which is shown to produce conditions favorable for dipole drift, polarity reversals, and excursions.

Gravitational dynamos and the low-frequency geomagnetic secular variation

PubMed Central

Olson, P.

2007-01-01

Self-sustaining numerical dynamos are used to infer the sources of low-frequency secular variation of the geomagnetic field. Gravitational dynamo models powered by compositional convection in an electrically conducting, rotating fluid shell exhibit several regimes of magnetic field behavior with an increasing Rayleigh number of the convection, including nearly steady dipoles, chaotic nonreversing dipoles, and chaotic reversing dipoles. The time average dipole strength and dipolarity of the magnetic field decrease, whereas the dipole variability, average dipole tilt angle, and frequency of polarity reversals increase with Rayleigh number. Chaotic gravitational dynamos have large-amplitude dipole secular variation with maximum power at frequencies corresponding to a few cycles per million years on Earth. Their external magnetic field structure, dipole statistics, low-frequency power spectra, and polarity reversal frequency are comparable to the geomagnetic field. The magnetic variability is driven by the Lorentz force and is characterized by an inverse correlation between dynamo magnetic and kinetic energy fluctuations. A constant energy dissipation theory accounts for this inverse energy correlation, which is shown to produce conditions favorable for dipole drift, polarity reversals, and excursions. PMID:18048345

Weighted Lin-Wang Tests for Crossing Hazards

PubMed Central

Koziol, James A.; Jia, Zhenyu

2014-01-01

Lin and Wang have introduced a quadratic version of the logrank test, appropriate for situations in which the underlying survival distributions may cross. In this note, we generalize the Lin-Wang procedure to incorporate weights and investigate the performance of Lin and Wang's test and weighted versions in various scenarios. We find that weighting does increase statistical power in certain situations; however, none of the procedures was dominant under every scenario. PMID:24795776

Can power-law scaling and neuronal avalanches arise from stochastic dynamics?

PubMed

Touboul, Jonathan; Destexhe, Alain

2010-02-11

The presence of self-organized criticality in biology is often evidenced by a power-law scaling of event size distributions, which can be measured by linear regression on logarithmic axes. We show here that such a procedure does not necessarily mean that the system exhibits self-organized criticality. We first provide an analysis of multisite local field potential (LFP) recordings of brain activity and show that event size distributions defined as negative LFP peaks can be close to power-law distributions. However, this result is not robust to change in detection threshold, or when tested using more rigorous statistical analyses such as the Kolmogorov-Smirnov test. Similar power-law scaling is observed for surrogate signals, suggesting that power-law scaling may be a generic property of thresholded stochastic processes. We next investigate this problem analytically, and show that, indeed, stochastic processes can produce spurious power-law scaling without the presence of underlying self-organized criticality. However, this power-law is only apparent in logarithmic representations, and does not survive more rigorous analysis such as the Kolmogorov-Smirnov test. The same analysis was also performed on an artificial network known to display self-organized criticality. In this case, both the graphical representations and the rigorous statistical analysis reveal with no ambiguity that the avalanche size is distributed as a power-law. We conclude that logarithmic representations can lead to spurious power-law scaling induced by the stochastic nature of the phenomenon. This apparent power-law scaling does not constitute a proof of self-organized criticality, which should be demonstrated by more stringent statistical tests.

High Resolution Topography of Age-Related Changes in Non-Rapid Eye Movement Sleep Electroencephalography

PubMed Central

Sprecher, Kate E.; Riedner, Brady A.; Smith, Richard F.; Tononi, Giulio; Davidson, Richard J.; Benca, Ruth M.

2016-01-01

Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel) electroencephalography (EEG) during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18–65 years old using full polysomnography and high density EEG. After artifact removal, spectral power density was calculated for standard frequency bands for all channels, averaged across the NREM periods of the first 3 sleep cycles. To quantify topographic changes with age, maps were generated of the Pearson’s coefficient of the correlation between power and age at each electrode. Significant correlations were determined by statistical non-parametric mapping. Absolute slow wave power declined significantly with increasing age across the entire scalp, whereas declines in theta and sigma power were significant only in frontal regions. Power in fast spindle frequencies declined significantly with increasing age frontally, whereas absolute power of slow spindle frequencies showed no significant change with age. When EEG power was normalized across the scalp, a left centro-parietal region showed significantly less age-related decline in power than the rest of the scalp. This partial preservation was particularly significant in the slow wave and sigma bands. The effect of age on sleep EEG varies substantially by region and frequency band. This non-uniformity should inform the design of future investigations of aging and sleep. This study provides normative data on the effect of age on sleep EEG topography, and provides a basis from which to explore the mechanisms of normal aging as well as neurodegenerative disorders for which age is a risk factor. PMID:26901503

Exploration of time-course combinations of outcome scales for use in a global test of stroke recovery.

PubMed

Goldie, Fraser C; Fulton, Rachael L; Dawson, Jesse; Bluhmki, Erich; Lees, Kennedy R

2014-08-01

Clinical trials for acute ischemic stroke treatment require large numbers of participants and are expensive to conduct. Methods that enhance statistical power are therefore desirable. We explored whether this can be achieved by a measure incorporating both early and late measures of outcome (e.g. seven-day NIH Stroke Scale combined with 90-day modified Rankin scale). We analyzed sensitivity to treatment effect, using proportional odds logistic regression for ordinal scales and generalized estimating equation method for global outcomes, with all analyses adjusted for baseline severity and age. We ran simulations to assess relations between sample size and power for ordinal scales and corresponding global outcomes. We used R version 2·12·1 (R Development Core Team. R Foundation for Statistical Computing, Vienna, Austria) for simulations and SAS 9·2 (SAS Institute Inc., Cary, NC, USA) for all other analyses. Each scale considered for combination was sensitive to treatment effect in isolation. The mRS90 and NIHSS90 had adjusted odds ratio of 1·56 and 1·62, respectively. Adjusted odds ratio for global outcomes of the combination of mRS90 with NIHSS7 and NIHSS90 with NIHSS7 were 1·69 and 1·73, respectively. The smallest sample sizes required to generate statistical power ≥80% for mRS90, NIHSS7, and global outcomes of mRS90 and NIHSS7 combined and NIHSS90 and NIHSS7 combined were 500, 490, 400, and 380, respectively. When data concerning both early and late outcomes are combined into a global measure, there is increased sensitivity to treatment effect compared with solitary ordinal scales. This delivers a 20% reduction in required sample size at 80% power. Combining early with late outcomes merits further consideration. © 2013 The Authors. International Journal of Stroke © 2013 World Stroke Organization.

Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation

PubMed Central

van Belzen, Jim; van de Koppel, Johan; Kirwan, Matthew L.; van der Wal, Daphne; Herman, Peter M. J.; Dakos, Vasilis; Kéfi, Sonia; Scheffer, Marten; Guntenspergen, Glenn R.; Bouma, Tjeerd J.

2017-01-01

A declining rate of recovery following disturbance has been proposed as an important early warning for impending tipping points in complex systems. Despite extensive theoretical and laboratory studies, this ‘critical slowing down' remains largely untested in the complex settings of real-world ecosystems. Here, we provide both observational and experimental support of critical slowing down along natural stress gradients in tidal marsh ecosystems. Time series of aerial images of European marsh development reveal a consistent lengthening of recovery time as inundation stress increases. We corroborate this finding with transplantation experiments in European and North American tidal marshes. In particular, our results emphasize the power of direct observational or experimental measures of recovery over indirect statistical signatures, such as spatial variance or autocorrelation. Our results indicate that the phenomenon of critical slowing down can provide a powerful tool to probe the resilience of natural ecosystems. PMID:28598430

Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation

NASA Astrophysics Data System (ADS)

van Belzen, Jim; van de Koppel, Johan; Kirwan, Matthew L.; van der Wal, Daphne; Herman, Peter M. J.; Dakos, Vasilis; Kéfi, Sonia; Scheffer, Marten; Guntenspergen, Glenn R.; Bouma, Tjeerd J.

2017-06-01

A declining rate of recovery following disturbance has been proposed as an important early warning for impending tipping points in complex systems. Despite extensive theoretical and laboratory studies, this `critical slowing down' remains largely untested in the complex settings of real-world ecosystems. Here, we provide both observational and experimental support of critical slowing down along natural stress gradients in tidal marsh ecosystems. Time series of aerial images of European marsh development reveal a consistent lengthening of recovery time as inundation stress increases. We corroborate this finding with transplantation experiments in European and North American tidal marshes. In particular, our results emphasize the power of direct observational or experimental measures of recovery over indirect statistical signatures, such as spatial variance or autocorrelation. Our results indicate that the phenomenon of critical slowing down can provide a powerful tool to probe the resilience of natural ecosystems.

Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation.

PubMed

van Belzen, Jim; van de Koppel, Johan; Kirwan, Matthew L; van der Wal, Daphne; Herman, Peter M J; Dakos, Vasilis; Kéfi, Sonia; Scheffer, Marten; Guntenspergen, Glenn R; Bouma, Tjeerd J

2017-06-09

A declining rate of recovery following disturbance has been proposed as an important early warning for impending tipping points in complex systems. Despite extensive theoretical and laboratory studies, this 'critical slowing down' remains largely untested in the complex settings of real-world ecosystems. Here, we provide both observational and experimental support of critical slowing down along natural stress gradients in tidal marsh ecosystems. Time series of aerial images of European marsh development reveal a consistent lengthening of recovery time as inundation stress increases. We corroborate this finding with transplantation experiments in European and North American tidal marshes. In particular, our results emphasize the power of direct observational or experimental measures of recovery over indirect statistical signatures, such as spatial variance or autocorrelation. Our results indicate that the phenomenon of critical slowing down can provide a powerful tool to probe the resilience of natural ecosystems.

Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach

NASA Astrophysics Data System (ADS)

Lo, Min-Tzu; Lee, Wen-Chung

2014-05-01

Many risk factors/interventions in epidemiologic/biomedical studies are of minuscule effects. To detect such weak associations, one needs a study with a very large sample size (the number of subjects, n). The n of a study can be increased but unfortunately only to an extent. Here, we propose a novel method which hinges on increasing sample size in a different direction-the total number of variables (p). We construct a p-based `multiple perturbation test', and conduct power calculations and computer simulations to show that it can achieve a very high power to detect weak associations when p can be made very large. As a demonstration, we apply the method to analyze a genome-wide association study on age-related macular degeneration and identify two novel genetic variants that are significantly associated with the disease. The p-based method may set a stage for a new paradigm of statistical tests.

Sound texture perception via statistics of the auditory periphery: Evidence from sound synthesis

PubMed Central

McDermott, Josh H.; Simoncelli, Eero P.

2014-01-01

Rainstorms, insect swarms, and galloping horses produce “sound textures” – the collective result of many similar acoustic events. Sound textures are distinguished by temporal homogeneity, suggesting they could be recognized with time-averaged statistics. To test this hypothesis, we processed real-world textures with an auditory model containing filters tuned for sound frequencies and their modulations, and measured statistics of the resulting decomposition. We then assessed the realism and recognizability of novel sounds synthesized to have matching statistics. Statistics of individual frequency channels, capturing spectral power and sparsity, generally failed to produce compelling synthetic textures. However, combining them with correlations between channels produced identifiable and natural-sounding textures. Synthesis quality declined if statistics were computed from biologically implausible auditory models. The results suggest that sound texture perception is mediated by relatively simple statistics of early auditory representations, presumably computed by downstream neural populations. The synthesis methodology offers a powerful tool for their further investigation. PMID:21903084

High temporal resolution aberrometry in a 50-eye population and implications for adaptive optics error budget.

PubMed

Jarosz, Jessica; Mecê, Pedro; Conan, Jean-Marc; Petit, Cyril; Paques, Michel; Meimon, Serge

2017-04-01

We formed a database gathering the wavefront aberrations of 50 healthy eyes measured with an original custom-built Shack-Hartmann aberrometer at a temporal frequency of 236 Hz, with 22 lenslets across a 7-mm diameter pupil, for a duration of 20 s. With this database, we draw statistics on the spatial and temporal behavior of the dynamic aberrations of the eye. Dynamic aberrations were studied on a 5-mm diameter pupil and on a 3.4 s sequence between blinks. We noted that, on average, temporal wavefront variance exhibits a n -2 power-law with radial order n and temporal spectra follow a f -1.5 power-law with temporal frequency f . From these statistics, we then extract guidelines for designing an adaptive optics system. For instance, we show the residual wavefront error evolution as a function of the number of corrected modes and of the adaptive optics loop frame rate. In particular, we infer that adaptive optics performance rapidly increases with the loop frequency up to 50 Hz, with gain being more limited at higher rates.

Enhanced Component Performance Study: Turbine-Driven Pumps 1998–2014

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

Schroeder, John Alton

2015-11-01

This report presents an enhanced performance evaluation of turbine-driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from fiscal year 1998 through 2014 for the component reliability as reported in the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The TDP failure modes considered are failure to start (FTS), failure to run less than or equal to one hour (FTR=1H), failure to run more than one hour (FTR>1H), and normally running systems FTS and failure to run (FTR). The component reliability estimates and themore » reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire active period. Statistically significant increasing trends were identified for TDP unavailability, for frequency of start demands for standby TDPs, and for run hours in the first hour after start. Statistically significant decreasing trends were identified for start demands for normally running TDPs, and for run hours per reactor critical year for normally running TDPs.« less

High temporal resolution aberrometry in a 50-eye population and implications for adaptive optics error budget

PubMed Central

Jarosz, Jessica; Mecê, Pedro; Conan, Jean-Marc; Petit, Cyril; Paques, Michel; Meimon, Serge

2017-01-01

We formed a database gathering the wavefront aberrations of 50 healthy eyes measured with an original custom-built Shack-Hartmann aberrometer at a temporal frequency of 236 Hz, with 22 lenslets across a 7-mm diameter pupil, for a duration of 20 s. With this database, we draw statistics on the spatial and temporal behavior of the dynamic aberrations of the eye. Dynamic aberrations were studied on a 5-mm diameter pupil and on a 3.4 s sequence between blinks. We noted that, on average, temporal wavefront variance exhibits a n−2 power-law with radial order n and temporal spectra follow a f−1.5 power-law with temporal frequency f. From these statistics, we then extract guidelines for designing an adaptive optics system. For instance, we show the residual wavefront error evolution as a function of the number of corrected modes and of the adaptive optics loop frame rate. In particular, we infer that adaptive optics performance rapidly increases with the loop frequency up to 50 Hz, with gain being more limited at higher rates. PMID:28736657

Low power radiofrequency electromagnetic radiation for the treatment of pain due to osteoarthritis of the knee.

PubMed

Alcidi, L; Beneforti, E; Maresca, M; Santosuosso, U; Zoppi, M

2007-01-01

To investigate the analgesic effect of low power radiofrequency electromagnetic radiation (RF) in osteoarthritis (OA) of the knee. In a randomized study on 40 patients the analgesic effect of RF was compared with the effect of transcutaneous electrical nerve stimulation (TENS). RF and TENS applications were repeated every day for a period of 5 days. The therapeutic effect was evaluated by a visual analogue scale (VAS) and by Lequesne's index: tests were performed before, immediately after and 30 days after therapy. RF therapy induced a statistically significant and long lasting decrease of VAS and of Lequesne's index; TENS induced a decrease of VAS and of Lequesne's index which was not statistically significant. A therapeutic effect of RF was therefore demonstrated on pain and disability due to knee OA. This effect was better than the effect of TENS, which is a largely used analgesic technique. Such a difference of the therapeutic effect may be due to the fact that TENS acts only on superficial tissues and nerve terminals, while RF acts increasing superficial and deep tissue temperature.

Hurricane destructive power predictions based on historical storm and sea surface temperature data.

PubMed

Bogen, Kenneth T; Jones, Edwin D; Fischer, Larry E

2007-12-01

Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm-specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this "SST hypothesis" and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best-track data on NAO hurricanes during 1880-2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane-specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R(2)= 0.55) or with combined mean location and a approximately 90-year periodic trend (R(2)= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST-independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST-dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An additional model was developed that predicts PDI statistics conditional on APDI. These PDI and APDI models can be used to estimate upper bounds on indices of hurricane power likely to be realized over the next century, under divergent assumptions regarding SST influence.

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

PubMed Central

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

2014-01-01

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

Numerical investigation of differential phase noise and its power penalty for optical amplification using semiconductor optical amplifiers in DPSK applications

NASA Astrophysics Data System (ADS)

Hong, Wei; Huang, Dexiu; Zhang, Xinliang; Zhu, Guangxi

2007-11-01

A thorough simulation and evaluation of phase noise for optical amplification using semiconductor optical amplifier (SOA) is very important for predicting its performance in differential phase shift keyed (DPSK) applications. In this paper, standard deviation and probability distribution of differential phase noise are obtained from the statistics of simulated differential phase noise. By using a full-wave model of SOA, the noise performance in the entire operation range can be investigated. It is shown that nonlinear phase noise substantially contributes to the total phase noise in case of a noisy signal amplified by a saturated SOA and the nonlinear contribution is larger with shorter SOA carrier lifetime. Power penalty due to differential phase noise is evaluated using a semi-analytical probability density function (PDF) of receiver noise. Obvious increase of power penalty at high signal input powers can be found for low input OSNR, which is due to both the large nonlinear differential phase noise and the dependence of BER vs. receiving power curvature on differential phase noise standard deviation.

Effects of Plymetrics Training and Weight Training on selected Motor Ability Components among University Male Students

NASA Astrophysics Data System (ADS)

Shaikh, Alauddin; Mallick, Nazrul Islam

2012-11-01

Introduction: The aim of this study was to find out the effects of plyometrics training and weight training among university male students.Procedure: 60 male students from the different colleges of the Burdwan University were randomly selected as subjects and their age were 19-25 years served as Weight training Group (WTG), second group served as Plyometric Training Group (PTG) and the third group served as Control Group (CT). Eight weeks weight training and six weeks plyometric training were given for experiment accordingly. The control group was not given any training except of their routine. The selected subjects were measured of their motor ability components, speed, endurance, explosive power and agility. ANCOVA was calculation for statistical treatment.Finding: Plyometric training and weight training groups significantly increase speed, endurance, explosive power and agility.Conclusion: The plyometric training has significantly improved speed, explosive power, muscular endurance and agility. The weight training programme has significantly improved agility, muscular endurance, and explosive power. The plometric training is superior to weight training in improving explosive power, agility and muscular endurance.

Increased statistical power with combined independent randomization tests used with multiple-baseline design.

PubMed

Tyrrell, Pascal N; Corey, Paul N; Feldman, Brian M; Silverman, Earl D

2013-06-01

Physicians often assess the effectiveness of treatments on a small number of patients. Multiple-baseline designs (MBDs), based on the Wampold-Worsham (WW) method of randomization and applied to four subjects, have relatively low power. Our objective was to propose another approach with greater power that does not suffer from the time requirements of the WW method applied to a greater number of subjects. The power of a design that involves the combination of two four-subject MBDs was estimated using computer simulation and compared with the four- and eight-subject designs. The effect of a delayed linear response to treatment on the power of the test was also investigated. Power was found to be adequate (>80%) for a standardized mean difference (SMD) greater than 0.8. The effect size associated with 80% power from combined tests was smaller than that of the single four-subject MBD (SMD=1.3) and comparable with the eight-subject MBD (SMD=0.6). A delayed linear response to the treatment resulted in important reductions in power (20-35%). By combining two four-subject MBD tests, an investigator can detect better effect sizes (SMD=0.8) and be able to complete a comparatively timelier and feasible study. Copyright © 2013 Elsevier Inc. All rights reserved.

Relationship Power and Sexual Violence Among HIV-Positive Women in Rural Uganda

PubMed Central

Tsai, Alexander C.; Clark, Gina M.; Boum, Yap; Hatcher, Abigail M.; Kawuma, Annet; Hunt, Peter W.; Martin, Jeffrey N.; Bangsberg, David R.; Weiser, Sheri D.

2016-01-01

Gender-based power imbalances place women at significant risk for sexual violence, however, little research has examined this association among women living with HIV/AIDS. We performed a cross-sectional analysis of relationship power and sexual violence among HIV-positive women on anti-retroviral therapy in rural Uganda. Relationship power was measured using the Sexual Relationship Power Scale (SRPS), a validated measure consisting of two subscales: relationship control (RC) and decision-making dominance. We used multivariable logistic regression to test for associations between the SRPS and two dependent variables: recent forced sex and transactional sex. Higher relationship power (full SRPS) was associated with reduced odds of forced sex (AOR = 0.24; 95 % CI 0.07–0.80; p = 0.020). The association between higher relationship power and transactional sex was strong and in the expected direction, but not statistically significant (AOR = 0.47; 95 % CI 0.18–1.22; p = 0.119). Higher RC was associated with reduced odds of both forced sex (AOR = 0.18; 95 % CI 0.06–0.59; p < 0.01) and transactional sex (AOR = 0.38; 95 % CI 0.15–0.99; p = 0.048). Violence prevention interventions with HIV-positive women should consider approaches that increase women’s power in their relationships. PMID:27052844

Effects of cold plasma treatment on alfalfa seed growth under simulated drought stress

NASA Astrophysics Data System (ADS)

Jinkui, FENG; Decheng, WANG; Changyong, SHAO; Lili, ZHANG; Xin, TANG

2018-03-01

The effect of different cold plasma treatments on the germination and seedling growth of alfalfa (Medicago sativa L.) seeds under simulated drought stress conditions was investigated. Polyethyleneglycol-6000 (PEG 6000)with the mass fraction of 0% (purified water), 5%, 10%, and 15% were applied to simulate the drought environment. The alfalfa seeds were treated with 15 different power levels ranged between 0-280 W for 15 s. The germination potential, germination rate, germination index, seedling root length, seedling height, and vigor index were investigated. Results indicated significant differences between treated with proper power and untreated alfalfa seeds. With the increase of treatment power, these indexes mentioned above almost presented bimodal curves. Under the different mass fractions of PEG 6000, results showed that the lower power led to increased germination, and the seedlings presented good adaptability to different drought conditions. Meanwhile, higher power levels resulted in a decreased germination rate. Seeds treated with 40 W resulted in higher germination potential, germination rate, seedling height, root length, and vigor index. Vigor indexes of the treated seeds under different PEG 6000 stresses increased by 38.68%, 43.91%, 74.34%, and 39.20% respectively compared to CK0-0, CK5-0, CK10-0, and CK15-0 (the control sample under 0%, 5%, 10%, and 15% PEG 6000). Therefore, 40 W was regarded as the best treatment in this research. Although the trend indexes of alfalfa seeds treated with the same power were statistically the same under different PEG 6000 stresses, the cold plasma treatment had a significant effect on the adaptability of alfalfa seeds in different drought environments. Thus, this kind of treatment is worth implementing to promote seed growth under drought situations.

Peripheral Defocus of the Monkey Crystalline Lens With Accommodation in a Lens Stretcher

PubMed Central

Maceo Heilman, Bianca; Manns, Fabrice; Ruggeri, Marco; Ho, Arthur; Gonzalez, Alex; Rowaan, Cor; Bernal, Andres; Arrieta, Esdras; Parel, Jean-Marie

2018-01-01

Purpose To characterize the peripheral defocus of the monkey crystalline lens and its changes with accommodation. Methods Experiments were performed on 15 lenses from 11 cynomolgus monkey eyes (age: 3.8–12.4 years, postmortem time: 33.5 ± 15.3 hours). The tissue was mounted in a motorized lens stretcher to allow for measurements of the lens in the accommodated (unstretched) and unaccommodated (stretched) states. A custom-built combined laser ray tracing and optical coherence tomography system was used to measure the paraxial on-axis and off-axis lens power for delivery angles ranging from −20° to +20° (in air). For each delivery angle, peripheral defocus was quantified as the difference between paraxial off-axis and on-axis power. The peripheral defocus of the lens was compared in the unstretched and stretched states. Results On average, the paraxial on-axis lens power was 52.0 ± 3.4 D in the unstretched state and 32.5 ± 5.1 D in the stretched state. In both states, the lens power increased with increasing delivery angle. From 0° to +20°, the relative peripheral lens power increased by 10.7 ± 1.4 D in the unstretched state and 7.5 ± 1.6 D in the stretched state. The change in field curvature with accommodation was statistically significant (P < 0.001), indicating that the unstretched (accommodated) lens has greater curvature or relative peripheral power. Conclusions The cynomolgus monkey lens has significant accommodation-dependent curvature of field, which suggests that the lens asserts a significant contribution to the peripheral optical performance of the eye that also varies with the state of accommodation.

Joint power and kinematics coordination in load carriage running: Implications for performance and injury.

PubMed

Liew, Bernard X W; Morris, Susan; Netto, Kevin

2016-06-01

Investigating the impact of incremental load magnitude on running joint power and kinematics is important for understanding the energy cost burden and potential injury-causative mechanisms associated with load carriage. It was hypothesized that incremental load magnitude would result in phase-specific, joint power and kinematic changes within the stance phase of running, and that these relationships would vary at different running velocities. Thirty-one participants performed running while carrying three load magnitudes (0%, 10%, 20% body weight), at three velocities (3, 4, 5m/s). Lower limb trajectories and ground reaction forces were captured, and global optimization was used to derive the variables. The relationships between load magnitude and joint power and angle vectors, at each running velocity, were analyzed using Statistical Parametric Mapping Canonical Correlation Analysis. Incremental load magnitude was positively correlated to joint power in the second half of stance. Increasing load magnitude was also positively correlated with alterations in three dimensional ankle angles during mid-stance (4.0 and 5.0m/s), knee angles at mid-stance (at 5.0m/s), and hip angles during toe-off (at all velocities). Post hoc analyses indicated that at faster running velocities (4.0 and 5.0m/s), increasing load magnitude appeared to alter power contribution in a distal-to-proximal (ankle→hip) joint sequence from mid-stance to toe-off. In addition, kinematic changes due to increasing load influenced both sagittal and non-sagittal plane lower limb joint angles. This study provides a list of plausible factors that may influence running energy cost and injury risk during load carriage running. Copyright © 2016 Elsevier B.V. All rights reserved.

A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring.

PubMed

Takahashi, Kunihiko; Kulldorff, Martin; Tango, Toshiro; Yih, Katherine

2008-04-11

Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. Based on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic. The flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.

Inferring Demographic History Using Two-Locus Statistics.

PubMed

Ragsdale, Aaron P; Gutenkunst, Ryan N

2017-06-01

Population demographic history may be learned from contemporary genetic variation data. Methods based on aggregating the statistics of many single loci into an allele frequency spectrum (AFS) have proven powerful, but such methods ignore potentially informative patterns of linkage disequilibrium (LD) between neighboring loci. To leverage such patterns, we developed a composite-likelihood framework for inferring demographic history from aggregated statistics of pairs of loci. Using this framework, we show that two-locus statistics are more sensitive to demographic history than single-locus statistics such as the AFS. In particular, two-locus statistics escape the notorious confounding of depth and duration of a bottleneck, and they provide a means to estimate effective population size based on the recombination rather than mutation rate. We applied our approach to a Zambian population of Drosophila melanogaster Notably, using both single- and two-locus statistics, we inferred a substantially lower ancestral effective population size than previous works and did not infer a bottleneck history. Together, our results demonstrate the broad potential for two-locus statistics to enable powerful population genetic inference. Copyright © 2017 by the Genetics Society of America.

The influence of control group reproduction on the statistical ...

EPA Pesticide Factsheets

Because of various Congressional mandates to protect the environment from endocrine disrupting chemicals (EDCs), the United States Environmental Protection Agency (USEPA) initiated the Endocrine Disruptor Screening Program. In the context of this framework, the Office of Research and Development within the USEPA developed the Medaka Extended One Generation Reproduction Test (MEOGRT) to characterize the endocrine action of a suspected EDC. One important endpoint of the MEOGRT is fecundity of breeding pairs of medaka. Power analyses were conducted to determine the number of replicates needed in proposed test designs and to determine the effects that varying reproductive parameters (e.g. mean fecundity, variance, and days with no egg production) will have on the statistical power of the test. A software tool, the MEOGRT Reproduction Power Analysis Tool, was developed to expedite these power analyses by both calculating estimates of the needed reproductive parameters (e.g. population mean and variance) and performing the power analysis under user specified scenarios. The manuscript illustrates how the reproductive performance of the control medaka that are used in a MEOGRT influence statistical power, and therefore the successful implementation of the protocol. Example scenarios, based upon medaka reproduction data collected at MED, are discussed that bolster the recommendation that facilities planning to implement the MEOGRT should have a culture of medaka with hi

Comparing methods to combine functional loss and mortality in clinical trials for amyotrophic lateral sclerosis

PubMed Central

van Eijk, Ruben PA; Eijkemans, Marinus JC; Rizopoulos, Dimitris

2018-01-01

Objective Amyotrophic lateral sclerosis (ALS) clinical trials based on single end points only partially capture the full treatment effect when both function and mortality are affected, and may falsely dismiss efficacious drugs as futile. We aimed to investigate the statistical properties of several strategies for the simultaneous analysis of function and mortality in ALS clinical trials. Methods Based on the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we simulated longitudinal patterns of functional decline, defined by the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R) and conditional survival time. Different treatment scenarios with varying effect sizes were simulated with follow-up ranging from 12 to 18 months. We considered the following analytical strategies: 1) Cox model; 2) linear mixed effects (LME) model; 3) omnibus test based on Cox and LME models; 4) composite time-to-6-point decrease or death; 5) combined assessment of function and survival (CAFS); and 6) test based on joint modeling framework. For each analytical strategy, we calculated the empirical power and sample size. Results Both Cox and LME models have increased false-negative rates when treatment exclusively affects either function or survival. The joint model has superior power compared to other strategies. The composite end point increases false-negative rates among all treatment scenarios. To detect a 15% reduction in ALSFRS-R decline and 34% decline in hazard with 80% power after 18 months, the Cox model requires 524 patients, the LME model 794 patients, the omnibus test 526 patients, the composite end point 1,274 patients, the CAFS 576 patients and the joint model 464 patients. Conclusion Joint models have superior statistical power to analyze simultaneous effects on survival and function and may circumvent pitfalls encountered by other end points. Optimizing trial end points is essential, as selecting suboptimal outcomes may disguise important treatment clues. PMID:29593436

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

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

Partial Least Squares Regression Can Aid in Detecting Differential Abundance of Multiple Features in Sets of Metagenomic Samples

PubMed Central

Libiger, Ondrej; Schork, Nicholas J.

2015-01-01

It is now feasible to examine the composition and diversity of microbial communities (i.e., “microbiomes”) that populate different human organs and orifices using DNA sequencing and related technologies. To explore the potential links between changes in microbial communities and various diseases in the human body, it is essential to test associations involving different species within and across microbiomes, environmental settings and disease states. Although a number of statistical techniques exist for carrying out relevant analyses, it is unclear which of these techniques exhibit the greatest statistical power to detect associations given the complexity of most microbiome datasets. We compared the statistical power of principal component regression, partial least squares regression, regularized regression, distance-based regression, Hill's diversity measures, and a modified test implemented in the popular and widely used microbiome analysis methodology “Metastats” across a wide range of simulated scenarios involving changes in feature abundance between two sets of metagenomic samples. For this purpose, simulation studies were used to change the abundance of microbial species in a real dataset from a published study examining human hands. Each technique was applied to the same data, and its ability to detect the simulated change in abundance was assessed. We hypothesized that a small subset of methods would outperform the rest in terms of the statistical power. Indeed, we found that the Metastats technique modified to accommodate multivariate analysis and partial least squares regression yielded high power under the models and data sets we studied. The statistical power of diversity measure-based tests, distance-based regression and regularized regression was significantly lower. Our results provide insight into powerful analysis strategies that utilize information on species counts from large microbiome data sets exhibiting skewed frequency distributions obtained on a small to moderate number of samples. PMID:26734061

Statistical modeling to support power system planning

NASA Astrophysics Data System (ADS)

Staid, Andrea

This dissertation focuses on data-analytic approaches that improve our understanding of power system applications to promote better decision-making. It tackles issues of risk analysis, uncertainty management, resource estimation, and the impacts of climate change. Tools of data mining and statistical modeling are used to bring new insight to a variety of complex problems facing today's power system. The overarching goal of this research is to improve the understanding of the power system risk environment for improved operation, investment, and planning decisions. The first chapter introduces some challenges faced in planning for a sustainable power system. Chapter 2 analyzes the driving factors behind the disparity in wind energy investments among states with a goal of determining the impact that state-level policies have on incentivizing wind energy. Findings show that policy differences do not explain the disparities; physical and geographical factors are more important. Chapter 3 extends conventional wind forecasting to a risk-based focus of predicting maximum wind speeds, which are dangerous for offshore operations. Statistical models are presented that issue probabilistic predictions for the highest wind speed expected in a three-hour interval. These models achieve a high degree of accuracy and their use can improve safety and reliability in practice. Chapter 4 examines the challenges of wind power estimation for onshore wind farms. Several methods for wind power resource assessment are compared, and the weaknesses of the Jensen model are demonstrated. For two onshore farms, statistical models outperform other methods, even when very little information is known about the wind farm. Lastly, chapter 5 focuses on the power system more broadly in the context of the risks expected from tropical cyclones in a changing climate. Risks to U.S. power system infrastructure are simulated under different scenarios of tropical cyclone behavior that may result from climate change. The scenario-based approach allows me to address the deep uncertainty present by quantifying the range of impacts, identifying the most critical parameters, and assessing the sensitivity of local areas to a changing risk. Overall, this body of work quantifies the uncertainties present in several operational and planning decisions for power system applications.

Statistical inference methods for two crossing survival curves: a comparison of methods.

PubMed

Li, Huimin; Han, Dong; Hou, Yawen; Chen, Huilin; Chen, Zheng

2015-01-01

A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman's smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér-von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman's smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.

Statistical Inference Methods for Two Crossing Survival Curves: A Comparison of Methods

PubMed Central

Li, Huimin; Han, Dong; Hou, Yawen; Chen, Huilin; Chen, Zheng

2015-01-01

A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman’s smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér—von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman’s smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests. PMID:25615624

Categorization of the trophic status of a hydroelectric power plant reservoir in the Brazilian Amazon by statistical analyses and fuzzy approaches.

PubMed

da Costa Lobato, Tarcísio; Hauser-Davis, Rachel Ann; de Oliveira, Terezinha Ferreira; Maciel, Marinalva Cardoso; Tavares, Maria Regina Madruga; da Silveira, Antônio Morais; Saraiva, Augusto Cesar Fonseca

2015-02-15

The Amazon area has been increasingly suffering from anthropogenic impacts, especially due to the construction of hydroelectric power plant reservoirs. The analysis and categorization of the trophic status of these reservoirs are of interest to indicate man-made changes in the environment. In this context, the present study aimed to categorize the trophic status of a hydroelectric power plant reservoir located in the Brazilian Amazon by constructing a novel Water Quality Index (WQI) and Trophic State Index (TSI) for the reservoir using major ion concentrations and physico-chemical water parameters determined in the area and taking into account the sampling locations and the local hydrological regimes. After applying statistical analyses (factor analysis and cluster analysis) and establishing a rule base of a fuzzy system to these indicators, the results obtained by the proposed method were then compared to the generally applied Carlson and a modified Lamparelli trophic state index (TSI), specific for trophic regions. The categorization of the trophic status by the proposed fuzzy method was shown to be more reliable, since it takes into account the specificities of the study area, while the Carlson and Lamparelli TSI do not, and, thus, tend to over or underestimate the trophic status of these ecosystems. The statistical techniques proposed and applied in the present study, are, therefore, relevant in cases of environmental management and policy decision-making processes, aiding in the identification of the ecological status of water bodies. With this, it is possible to identify which factors should be further investigated and/or adjusted in order to attempt the recovery of degraded water bodies. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

PubMed Central

Han, Buhm; Kang, Hyun Min; Eskin, Eleazar

2009-01-01

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

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 ion-signature prior to the Kobe earthquake and for financial markets.

Effects of dynamic-demand-control appliances on the power grid frequency.

PubMed

Tchuisseu, E B Tchawou; Gomila, D; Brunner, D; Colet, P

2017-08-01

Power grid frequency control is a demanding task requiring expensive idle power plants to adapt the supply to the fluctuating demand. An alternative approach is controlling the demand side in such a way that certain appliances modify their operation to adapt to the power availability. This is especially important to achieve a high penetration of renewable energy sources. A number of methods to manage the demand side have been proposed. In this work we focus on dynamic demand control (DDC), where smart appliances can delay their switchings depending on the frequency of the system. We introduce a simple model to study the effects of DDC on the frequency of the power grid. The model includes the power plant equations, a stochastic model for the demand that reproduces, adjusting a single parameter, the statistical properties of frequency fluctuations measured experimentally, and a generic DDC protocol. We find that DDC can reduce small and medium-size fluctuations but it can also increase the probability of observing large frequency peaks due to the necessity of recovering pending task. We also conclude that a deployment of DDC around 30-40% already allows a significant reduction of the fluctuations while keeping the number of pending tasks low.

Effects of dynamic-demand-control appliances on the power grid frequency

NASA Astrophysics Data System (ADS)

Tchuisseu, E. B. Tchawou; Gomila, D.; Brunner, D.; Colet, P.

2017-08-01

Power grid frequency control is a demanding task requiring expensive idle power plants to adapt the supply to the fluctuating demand. An alternative approach is controlling the demand side in such a way that certain appliances modify their operation to adapt to the power availability. This is especially important to achieve a high penetration of renewable energy sources. A number of methods to manage the demand side have been proposed. In this work we focus on dynamic demand control (DDC), where smart appliances can delay their switchings depending on the frequency of the system. We introduce a simple model to study the effects of DDC on the frequency of the power grid. The model includes the power plant equations, a stochastic model for the demand that reproduces, adjusting a single parameter, the statistical properties of frequency fluctuations measured experimentally, and a generic DDC protocol. We find that DDC can reduce small and medium-size fluctuations but it can also increase the probability of observing large frequency peaks due to the necessity of recovering pending task. We also conclude that a deployment of DDC around 30-40% already allows a significant reduction of the fluctuations while keeping the number of pending tasks low.

The effects of electric power industry restructuring on the safety of nuclear power plants in the United States

NASA Astrophysics Data System (ADS)

Butler, Thomas S.

Throughout the United States the electric utility industry is restructuring in response to federal legislation mandating deregulation. The electric utility industry has embarked upon an extraordinary experiment by restructuring in response to deregulation that has been advocated on the premise of improving economic efficiency by encouraging competition in as many sectors of the industry as possible. However, unlike the telephone, trucking, and airline industries, the potential effects of electric deregulation reach far beyond simple energy economics. This dissertation presents the potential safety risks involved with the deregulation of the electric power industry in the United States and abroad. The pressures of a competitive environment on utilities with nuclear power plants in their portfolio to lower operation and maintenance costs could squeeze them to resort to some risky cost-cutting measures. These include deferring maintenance, reducing training, downsizing staff, excessive reductions in refueling down time, and increasing the use of on-line maintenance. The results of this study indicate statistically significant differences at the .01 level between the safety of pressurized water reactor nuclear power plants and boiling water reactor nuclear power plants. Boiling water reactors exhibited significantly more problems than did pressurized water reactors.

Utilising family-based designs for detecting rare variant disease associations.

PubMed

Preston, Mark D; Dudbridge, Frank

2014-03-01

Rare genetic variants are thought to be important components in the causality of many diseases but discovering these associations is challenging. We demonstrate how best to use family-based designs to improve the power to detect rare variant disease associations. We show that using genetic data from enriched families (those pedigrees with greater than one affected member) increases the power and sensitivity of existing case-control rare variant tests. However, we show that transmission- (or within-family-) based tests do not benefit from this enrichment. This means that, in studies where a limited amount of genotyping is available, choosing a single case from each of many pedigrees has greater power than selecting multiple cases from fewer pedigrees. Finally, we show how a pseudo-case-control design allows a greater range of statistical tests to be applied to family data. © 2014 The Authors. Annals of Human Genetics published by John Wiley & Sons Ltd/University College London.

Simultaneous Microwave Extraction and Separation of Volatile and Non-Volatile Organic Compounds of Boldo Leaves. From Lab to Industrial Scale

PubMed Central

Petigny, Loïc; Périno, Sandrine; Minuti, Matteo; Visinoni, Francesco; Wajsman, Joël; Chemat, Farid

2014-01-01

Microwave extraction and separation has been used to increase the concentration of the extract compared to the conventional method with the same solid/liquid ratio, reducing extraction time and separate at the same time Volatile Organic Compounds (VOC) from non-Volatile Organic Compounds (NVOC) of boldo leaves. As preliminary study, a response surface method has been used to optimize the extraction of soluble material and the separation of VOC from the plant in laboratory scale. The results from the statistical analysis revealed that the optimized conditions were: microwave power 200 W, extraction time 56 min and solid liquid ratio of 7.5% of plants in water. Lab scale optimized microwave method is compared to conventional distillation, and requires a power/mass ratio of 0.4 W/g of water engaged. This power/mass ratio is kept in order to upscale from lab to pilot plant. PMID:24776762

Mining protein-protein interaction networks: denoising effects

NASA Astrophysics Data System (ADS)

Marras, Elisabetta; Capobianco, Enrico

2009-01-01

A typical instrument to pursue analysis in complex network studies is the analysis of the statistical distributions. They are usually computed for measures which characterize network topology, and are aimed at capturing both structural and dynamics aspects. Protein-protein interaction networks (PPIN) have also been studied through several measures. It is in general observed that a power law is expected to characterize scale-free networks. However, mixing the original noise cover with outlying information and other system-dependent fluctuations makes the empirical detection of the power law a difficult task. As a result the uncertainty level increases when looking at the observed sample; in particular, one may wonder whether the computed features may be sufficient to explain the interactome. We then address noise problems by implementing both decomposition and denoising techniques that reduce the impact of factors known to affect the accuracy of power law detection.

Similarity principles for the biology of pelagic animals

PubMed Central

Barenblatt, G. I.; Monin, A. S.

1983-01-01

A similarity principle is formulated according to which the statistical pattern of the pelagic population is identical in all scales sufficiently large in comparison with the molecular one. From this principle, a power law is obtained analytically for the pelagic animal biomass distribution over the animal sizes. A hypothesis is presented according to which, under fixed external conditions, the oxygen exchange intensity of an animal is governed only by its mass and density and by the specific absorbing capacity of the animal's respiratory organ. From this hypothesis a power law is obtained by the method of dimensional analysis for the exchange intensity mass dependence. The known empirical values of the exponent of this power law are interpreted as an indication that the oxygen-absorbing organs of the animals can be represented as so-called fractal surfaces. In conclusion the biological principle of the decrease in specific exchange intensity with increase in animal mass is discussed. PMID:16593327

Construction of cosmic string induced temperature anisotropy maps with CMBFAST and statistical analysis

NASA Astrophysics Data System (ADS)

Simatos, N.; Perivolaropoulos, L.

2001-01-01

We use the publicly available code CMBFAST, as modified by Pogosian and Vachaspati, to simulate the effects of wiggly cosmic strings on the cosmic microwave background (CMB). Using the modified CMBFAST code, which takes into account vector modes and models wiggly cosmic strings by the one-scale model, we go beyond the angular power spectrum to construct CMB temperature maps with a resolution of a few degrees. The statistics of these maps are then studied using conventional and recently proposed statistical tests optimized for the detection of hidden temperature discontinuities induced by the Gott-Kaiser-Stebbins effect. We show, however, that these realistic maps cannot be distinguished in a statistically significant way from purely Gaussian maps with an identical power spectrum.

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

PubMed

Li, Zitong; Sillanpää, Mikko J

2015-12-01

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

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2010-01-01

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS-derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant end toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; Riggs, George A.; DiGirolano, Nocolo E.

2010-01-01

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station a are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS- derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant trend toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management.

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

PubMed

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

The power to detect trends in Missouri River fish populations within the Pallid Sturgeon Population Assessment Program

USGS Publications Warehouse

Bryan, Janice L.; Wildhaber, Mark L.; Gladish, Dan; Holan, Scott; Ellerseick, Mark

2010-01-01

As with all large rivers in the United States, the Missouri River has been altered, with approximately 32.5 percent of the main stem length impounded and 32.5 percent channelized. These physical alterations to the environment have had effects on the fisheries, but studies examining the effects of alterations have been localized and for short periods of time. In response to the U.S. Fish and Wildlife Service biological opinion, the U.S. Army Corps of Engineers initiated monitoring of the fish community of the Missouri River in 2003. The goal of the Pallid Sturgeon Population Assessment Program is to provide information to detect changes in populations and habitat preferences with time for pallid sturgeon (Scaphirhynchus albus) and native target species in the Missouri River Basin. To determine statistical power of the Pallid Sturgeon Population Assessment Program, a power analysis was conducted using a normal linear mixed model with variance component estimates based on the first 3 years of data (2003 to 2005). In cases where 3 years of data were unavailable, estimates were obtained using those data. It was determined that at least 20 years of data, sampling 12 bends with 8 subsamples per bend, would be required to detect a 5 percent annual decline in most of the target fish populations. Power varied between Zones. Zone 1 (upstream from Lake Sakakawea) did not have any species/gear type combinations with adequate power, whereas Zone 3 (downstream from Gavins Point Dam) had 19 species/gear type combinations with adequate power. With a slight increase in the sampling effort to 12 subsamples per bend, the Pallid Sturgeon Population Assessment Program has adequate power to detect declines in shovelnose sturgeon (S. platorynchus) throughout the entire Missouri River because of large catch rates. The lowest level of non-occurrence (in other words, zero catches) at the bend level for pallid sturgeon was 0.58 using otter trawls in Zone 1. Consequently, the power of the pallid sturgeon models was not as high as other species at the current level of sampling, but an increase in the sampling effort to 16 subsamples for each of 24 bends for 20 years would generate adequate power for the pallid sturgeon in all Zones. Since gear types are selective in their species efficiency, the strength of the Pallid Sturgeon Population Assessment Program approach is using multiple gears that have statistical power to detect population trends at the same time in different fish species within the Missouri River. As often is the case with monitoring studies involving endangered species, the data used to conduct the analyses exhibit some departures from the parametric model assumptions; however, preliminary simulations indicate that the results of this study are appropriate.

Low power and type II errors in recent ophthalmology research.

PubMed

Khan, Zainab; Milko, Jordan; Iqbal, Munir; Masri, Moness; Almeida, David R P

2016-10-01

To investigate the power of unpaired t tests in prospective, randomized controlled trials when these tests failed to detect a statistically significant difference and to determine the frequency of type II errors. Systematic review and meta-analysis. We examined all prospective, randomized controlled trials published between 2010 and 2012 in 4 major ophthalmology journals (Archives of Ophthalmology, British Journal of Ophthalmology, Ophthalmology, and American Journal of Ophthalmology). Studies that used unpaired t tests were included. Power was calculated using the number of subjects in each group, standard deviations, and α = 0.05. The difference between control and experimental means was set to be (1) 20% and (2) 50% of the absolute value of the control's initial conditions. Power and Precision version 4.0 software was used to carry out calculations. Finally, the proportion of articles with type II errors was calculated. β = 0.3 was set as the largest acceptable value for the probability of type II errors. In total, 280 articles were screened. Final analysis included 50 prospective, randomized controlled trials using unpaired t tests. The median power of tests to detect a 50% difference between means was 0.9 and was the same for all 4 journals regardless of the statistical significance of the test. The median power of tests to detect a 20% difference between means ranged from 0.26 to 0.9 for the 4 journals. The median power of these tests to detect a 50% and 20% difference between means was 0.9 and 0.5 for tests that did not achieve statistical significance. A total of 14% and 57% of articles with negative unpaired t tests contained results with β > 0.3 when power was calculated for differences between means of 50% and 20%, respectively. A large portion of studies demonstrate high probabilities of type II errors when detecting small differences between means. The power to detect small difference between means varies across journals. It is, therefore, worthwhile for authors to mention the minimum clinically important difference for individual studies. Journals can consider publishing statistical guidelines for authors to use. Day-to-day clinical decisions rely heavily on the evidence base formed by the plethora of studies available to clinicians. Prospective, randomized controlled clinical trials are highly regarded as a robust study and are used to make important clinical decisions that directly affect patient care. The quality of study designs and statistical methods in major clinical journals is improving overtime, 1 and researchers and journals are being more attentive to statistical methodologies incorporated by studies. The results of well-designed ophthalmic studies with robust methodologies, therefore, have the ability to modify the ways in which diseases are managed. Copyright © 2016 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Comparative efficacy of two battery-powered toothbrushes on dental plaque removal.

PubMed

Ruhlman, C Douglas; Bartizek, Robert D; Biesbrock, Aaron R

2002-01-01

A number of clinical studies have consistently demonstrated that power toothbrushes deliver superior plaque removal compared to manual toothbrushes. Recently, a new power toothbrush (Crest SpinBrush) has been marketed with a design that fundamentally differs from other marketed power toothbrushes. Other power toothbrushes feature a small, round head designed to oscillate for enhanced cleaning between the teeth and below the gumline. The new power toothbrush incorporates a similar round oscillating head in conjunction with fixed bristles, which allows the user to brush with optimal manual brushing technique. The objective of this randomized, examiner-blind, parallel design study was to compare the plaque removal efficacy of a positive control power toothbrush (Colgate Actibrush) to an experimental toothbrush (Crest SpinBrush) following a single use among 59 subjects. Baseline plaque scores were 1.64 and 1.40 for the experimental toothbrush and control toothbrush treatment groups, respectively. With regard to all surfaces examined, the experimental toothbrush delivered an adjusted (via analysis of covariance) mean difference between baseline and post-brushing plaque scores of 0.47, while the control toothbrush delivered an adjusted mean difference of 0.33. On average, the difference between toothbrushes was statistically significant (p = 0.013). Because the covariate slope for the experimental group was statistically significantly greater (p = 0.001) than the slope for the control group, a separate slope model was used. Further analysis demonstrated that the experimental group had statistically significantly greater plaque removal than the control group for baseline plaque scores above 1.43. With respect to buccal surfaces, using a separate slope analysis of covariance, the experimental toothbrush delivered an adjusted mean difference between baseline and post-brushing plaque scores of 0.61, while the control toothbrush delivered an adjusted mean difference of 0.39. This difference between toothbrushes was also statistically significant (p = 0.002). On average, the results on lingual surfaces demonstrated similar directional scores favoring the experimental toothbrush; however these results did not achieve statistical significance. In conclusion, the experimental Crest SpinBrush, with its novel fixed and oscillating bristle design, was found to be more effective than the positive control Colgate Actibrush, which is designed with a small round oscillating cluster of bristles.

Gulf War Logistics: Theory Into Practice

DTIC Science & Technology

1995-04-01

sources are documentary in nature, emphasizing statistics like tonnage of supplies moved and number of troops sustained in the field. Other sources...Washington: GPO, 1993), 207-208. See also, Table 23 in Gulf War Air Power Survey Statistical Compendium. In Vol 3 of Gulf War Air Power Survey...Operational Structures Coursebook , (Maxwell AFB: Air Command and Staff College, 1995), 58. 40"Theater Logistics in the Gulf War: August 1990-December 1991

An Empirical Comparison of Selected Two-Sample Hypothesis Testing Procedures Which Are Locally Most Powerful Under Certain Conditions.

ERIC Educational Resources Information Center

Hoover, H. D.; Plake, Barbara

The relative power of the Mann-Whitney statistic, the t-statistic, the median test, a test based on exceedances (A,B), and two special cases of (A,B) the Tukey quick test and the revised Tukey quick test, was investigated via a Monte Carlo experiment. These procedures were compared across four population probability models: uniform, beta, normal,…

Design of durability test protocol for vehicular fuel cell systems operated in power-follow mode based on statistical results of on-road data

NASA Astrophysics Data System (ADS)

Xu, Liangfei; Reimer, Uwe; Li, Jianqiu; Huang, Haiyan; Hu, Zunyan; Jiang, Hongliang; Janßen, Holger; Ouyang, Minggao; Lehnert, Werner

2018-02-01

City buses using polymer electrolyte membrane (PEM) fuel cells are considered to be the most likely fuel cell vehicles to be commercialized in China. The technical specifications of the fuel cell systems (FCSs) these buses are equipped with will differ based on the powertrain configurations and vehicle control strategies, but can generally be classified into the power-follow and soft-run modes. Each mode imposes different levels of electrochemical stress on the fuel cells. Evaluating the aging behavior of fuel cell stacks under the conditions encountered in fuel cell buses requires new durability test protocols based on statistical results obtained during actual driving tests. In this study, we propose a systematic design method for fuel cell durability test protocols that correspond to the power-follow mode based on three parameters for different fuel cell load ranges. The powertrain configurations and control strategy are described herein, followed by a presentation of the statistical data for the duty cycles of FCSs in one city bus in the demonstration project. Assessment protocols are presented based on the statistical results using mathematical optimization methods, and are compared to existing protocols with respect to common factors, such as time at open circuit voltage and root-mean-square power.

Nonuniform High-Gamma (60–500 Hz) Power Changes Dissociate Cognitive Task and Anatomy in Human Cortex

PubMed Central

Gaona, Charles M.; Sharma, Mohit; Freudenburg, Zachary V.; Breshears, Jonathan D.; Bundy, David T.; Roland, Jarod; Barbour, Dennis L.; Schalk, Gerwin

2011-01-01

High-gamma-band (>60 Hz) power changes in cortical electrophysiology are a reliable indicator of focal, event-related cortical activity. Despite discoveries of oscillatory subthreshold and synchronous suprathreshold activity at the cellular level, there is an increasingly popular view that high-gamma-band amplitude changes recorded from cellular ensembles are the result of asynchronous firing activity that yields wideband and uniform power increases. Others have demonstrated independence of power changes in the low- and high-gamma bands, but to date, no studies have shown evidence of any such independence above 60 Hz. Based on nonuniformities in time-frequency analyses of electrocorticographic (ECoG) signals, we hypothesized that induced high-gamma-band (60–500 Hz) power changes are more heterogeneous than currently understood. Using single-word repetition tasks in six human subjects, we showed that functional responsiveness of different ECoG high-gamma sub-bands can discriminate cognitive task (e.g., hearing, reading, speaking) and cortical locations. Power changes in these sub-bands of the high-gamma range are consistently present within single trials and have statistically different time courses within the trial structure. Moreover, when consolidated across all subjects within three task-relevant anatomic regions (sensorimotor, Broca's area, and superior temporal gyrus), these behavior- and location-dependent power changes evidenced nonuniform trends across the population. Together, the independence and nonuniformity of power changes across a broad range of frequencies suggest that a new approach to evaluating high-gamma-band cortical activity is necessary. These findings show that in addition to time and location, frequency is another fundamental dimension of high-gamma dynamics. PMID:21307246

Statistical analyses support power law distributions found in neuronal avalanches.

PubMed

Klaus, Andreas; Yu, Shan; Plenz, Dietmar

2011-01-01

The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to -1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesis for neuronal avalanches by using more stringent statistical analyses. In particular, we performed the following steps: (i) analysis of finite-size scaling to identify scale-free dynamics in neuronal avalanches, (ii) model parameter estimation to determine the specific exponent of the power law, and (iii) comparison of the power law to alternative model distributions. Consistent with critical state dynamics, avalanche size distributions exhibited robust scaling behavior in which the maximum avalanche size was limited only by the spatial extent of sampling ("finite size" effect). This scale-free dynamics suggests the power law as a model for the distribution of avalanche sizes. Using both the Kolmogorov-Smirnov statistic and a maximum likelihood approach, we found the slope to be close to -1.5, which is in line with previous reports. Finally, the power law model for neuronal avalanches was compared to the exponential and to various heavy-tail distributions based on the Kolmogorov-Smirnov distance and by using a log-likelihood ratio test. Both the power law distribution without and with exponential cut-off provided significantly better fits to the cluster size distributions in neuronal avalanches than the exponential, the lognormal and the gamma distribution. In summary, our findings strongly support the power law scaling in neuronal avalanches, providing further evidence for critical state dynamics in superficial layers of cortex.

Multi-Decadal analysis of Global Trends in Microseism Intensity: A Proxy for Changes in Extremal Storm Activity and Oceanic Wave State

NASA Astrophysics Data System (ADS)

Anthony, R. E.; Aster, R. C.; Rowe, C. A.

2016-12-01

The Earth's seismic noise spectrum features two globally ubiquitous peaks near 8 and 16 s periods (secondary and primary bands) that arise when storm-generated ocean gravity waves are converted to seismic energy, predominantly into Rayleigh waves. Because of its regionally integrative nature, microseism intensity and other seismographic data from long running sites can provide useful proxies for wave state. Expanding an earlier study of global microseism trends (Aster et al., 2010), we analyze digitally-archived, up-to-date (through late 2016) multi-decadal seismic data from stations of global seismographic networks to characterize the spatiotemporal evolution of wave climate over the past >20 years. The IRIS Noise Tool Kit (Bahavair et al., 2013) is used to produce ground motion power spectral density (PSD) estimates in 3-hour overlapping time series segments. The result of this effort is a longer duration and more broadly geographically distributed PSD database than attained in previous studies, particularly for the primary microseism band. Integrating power within the primary and secondary microseism bands enables regional characterization of spatially-integrated trends in wave states and storm event statistics of varying thresholds. The results of these analyses are then interpreted within the context of recognized modes of atmospheric variability, including the particularly strong 2015-2016 El Niño. We note a number of statistically significant increasing trends in both raw microseism power and storm activity occurring at multiple stations in the Northwest Atlantic and Southeast Pacific consistent with generally increased wave heights and storminess in these regions. Such trends in wave activity have the potential to significantly influence coastal environments particularly under rising global sea levels.

Trends in P Value, Confidence Interval, and Power Analysis Reporting in Health Professions Education Research Reports: A Systematic Appraisal.

PubMed

Abbott, Eduardo F; Serrano, Valentina P; Rethlefsen, Melissa L; Pandian, T K; Naik, Nimesh D; West, Colin P; Pankratz, V Shane; Cook, David A

2018-02-01

To characterize reporting of P values, confidence intervals (CIs), and statistical power in health professions education research (HPER) through manual and computerized analysis of published research reports. The authors searched PubMed, Embase, and CINAHL in May 2016, for comparative research studies. For manual analysis of abstracts and main texts, they randomly sampled 250 HPER reports published in 1985, 1995, 2005, and 2015, and 100 biomedical research reports published in 1985 and 2015. Automated computerized analysis of abstracts included all HPER reports published 1970-2015. In the 2015 HPER sample, P values were reported in 69/100 abstracts and 94 main texts. CIs were reported in 6 abstracts and 22 main texts. Most P values (≥77%) were ≤.05. Across all years, 60/164 two-group HPER studies had ≥80% power to detect a between-group difference of 0.5 standard deviations. From 1985 to 2015, the proportion of HPER abstracts reporting a CI did not change significantly (odds ratio [OR] 2.87; 95% CI 1.04, 7.88) whereas that of main texts reporting a CI increased (OR 1.96; 95% CI 1.39, 2.78). Comparison with biomedical studies revealed similar reporting of P values, but more frequent use of CIs in biomedicine. Automated analysis of 56,440 HPER abstracts found 14,867 (26.3%) reporting a P value, 3,024 (5.4%) reporting a CI, and increased reporting of P values and CIs from 1970 to 2015. P values are ubiquitous in HPER, CIs are rarely reported, and most studies are underpowered. Most reported P values would be considered statistically significant.

Flow and clog in a silo with oscillating exit

NASA Astrophysics Data System (ADS)

To, Kiwing; Tai, Hsiang-Ting

2017-09-01

When grains flow out of a silo, flow rate W increases with exit size D . If D is too small, an arch may form and the flow may be blocked at the exit. To recover from clogging, the arch has to be destroyed. Here we construct a two-dimensional silo with movable exit and study the effects of exit oscillation (with amplitude A and frequency f ) on flow rate, clogging, and unclogging of grains through the exit. We find that, if exit oscillates, W remains finite even when D (measured in unit of grain diameter) is only slightly larger than one. Surprisingly, while W increases with oscillation strength Γ ≡4 π2A f2 as expected at small D , W decreases with Γ when D ≥5 due to induced random motion of the grains at the exit. When D is small and oscillation speed v ≡2 π A f is slow, temporary clogging events cause the grains to flow intermittently. In this regime, W depends only on v —a feature consistent to a simple arch breaking mechanism, and the phase boundary of intermittent flow in the D -v plane is consistent to either a power law: D ∝v-7 or an exponential form: D ∝e-D /0.55 . Furthermore, the flow time statistic is Poissonian whereas the recovery time statistic follows a power-law distribution.

A T1 and DTI fused 3D corpus callosum analysis in pre- vs. post-season contact sports players

NASA Astrophysics Data System (ADS)

Lao, Yi; Law, Meng; Shi, Jie; Gajawelli, Niharika; Haas, Lauren; Wang, Yalin; Leporé, Natasha

2015-01-01

Sports related traumatic brain injury (TBI) is a worldwide public health issue, and damage to the corpus callosum (CC) has been considered as an important indicator of TBI. However, contact sports players suffer repeated hits to the head during the course of a season even in the absence of diagnosed concussion, and less is known about their effect on callosal anatomy. In addition, T1-weighted and diffusion tensor brain magnetic resonance images (DTI) have been analyzed separately, but a joint analysis of both types of data may increase statistical power and give a more complete understanding of anatomical correlates of subclinical concussions in these athletes. Here, for the first time, we fuse T1 surface-based morphometry and a new DTI analysis on 3D surface representations of the CCs into a single statistical analysis on these subjects. Our new combined method successfully increases detection power in detecting differences between pre- vs. post-season contact sports players. Alterations are found in the ventral genu, isthmus, and splenium of CC. Our findings may inform future health assessments in contact sports players. The new method here is also the first truly multimodal diffusion and T1-weighted analysis of the CC, and may be useful to detect anatomical changes in the corpus callosum in other multimodal datasets.

The imprint of f(R) gravity on weak gravitational lensing - II. Information content in cosmic shear statistics

NASA Astrophysics Data System (ADS)

Shirasaki, Masato; Nishimichi, Takahiro; Li, Baojiu; Higuchi, Yuichi

2017-04-01

We investigate the information content of various cosmic shear statistics on the theory of gravity. Focusing on the Hu-Sawicki-type f(R) model, we perform a set of ray-tracing simulations and measure the convergence bispectrum, peak counts and Minkowski functionals. We first show that while the convergence power spectrum does have sensitivity to the current value of extra scalar degree of freedom |fR0|, it is largely compensated by a change in the present density amplitude parameter σ8 and the matter density parameter Ωm0. With accurate covariance matrices obtained from 1000 lensing simulations, we then examine the constraining power of the three additional statistics. We find that these probes are indeed helpful to break the parameter degeneracy, which cannot be resolved from the power spectrum alone. We show that especially the peak counts and Minkowski functionals have the potential to rigorously (marginally) detect the signature of modified gravity with the parameter |fR0| as small as 10-5 (10-6) if we can properly model them on small (˜1 arcmin) scale in a future survey with a sky coverage of 1500 deg2. We also show that the signal level is similar among the additional three statistics and all of them provide complementary information to the power spectrum. These findings indicate the importance of combining multiple probes beyond the standard power spectrum analysis to detect possible modifications to general relativity.

[The application of the prospective space-time statistic in early warning of infectious disease].

PubMed

Yin, Fei; Li, Xiao-Song; Feng, Zi-Jian; Ma, Jia-Qi

2007-06-01

To investigate the application of prospective space-time scan statistic in the early stage of detecting infectious disease outbreaks. The prospective space-time scan statistic was tested by mimicking daily prospective analyses of bacillary dysentery data of Chengdu city in 2005 (3212 cases in 102 towns and villages). And the results were compared with that of purely temporal scan statistic. The prospective space-time scan statistic could give specific messages both in spatial and temporal. The results of June indicated that the prospective space-time scan statistic could timely detect the outbreaks that started from the local site, and the early warning message was powerful (P = 0.007). When the merely temporal scan statistic for detecting the outbreak was sent two days later, and the signal was less powerful (P = 0.039). The prospective space-time scan statistic could make full use of the spatial and temporal information in infectious disease data and could timely and effectively detect the outbreaks that start from the local sites. The prospective space-time scan statistic could be an important tool for local and national CDC to set up early detection surveillance systems.

The kappa statistic in rehabilitation research: an examination.

PubMed

Tooth, Leigh R; Ottenbacher, Kenneth J

2004-08-01

The number and sophistication of statistical procedures reported in medical rehabilitation research is increasing. Application of the principles and methods associated with evidence-based practice has contributed to the need for rehabilitation practitioners to understand quantitative methods in published articles. Outcomes measurement and determination of reliability are areas that have experienced rapid change during the past decade. In this study, distinctions between reliability and agreement are examined. Information is presented on analytical approaches for addressing reliability and agreement with the focus on the application of the kappa statistic. The following assumptions are discussed: (1) kappa should be used with data measured on a categorical scale, (2) the patients or objects categorized should be independent, and (3) the observers or raters must make their measurement decisions and judgments independently. Several issues related to using kappa in measurement studies are described, including use of weighted kappa, methods of reporting kappa, the effect of bias and prevalence on kappa, and sample size and power requirements for kappa. The kappa statistic is useful for assessing agreement among raters, and it is being used more frequently in rehabilitation research. Correct interpretation of the kappa statistic depends on meeting the required assumptions and accurate reporting.

Turbulent premixed combustion in V-shaped flames: Characteristics of flame front

NASA Astrophysics Data System (ADS)

Kheirkhah, S.; Gülder, Ö. L.

2013-05-01

Flame front characteristics of turbulent premixed V-shaped flames were investigated experimentally using the Mie scattering and the particle image velocimetry techniques. The experiments were performed at mean streamwise exit velocities of 4.0, 6.2, and 8.6 m/s, along with fuel-air equivalence ratios of 0.7, 0.8, and 0.9. Effects of vertical distance from the flame-holder, mean streamwise exit velocity, and fuel-air equivalence ratio on statistics of the distance between the flame front and the vertical axis, flame brush thickness, flame front curvature, and angle between tangent to the flame front and the horizontal axis were studied. The results show that increasing the vertical distance from the flame-holder and the fuel-air equivalence ratio increase the mean and root-mean-square (RMS) of the distance between the flame front and the vertical axis; however, increasing the mean streamwise exit velocity decreases these statistics. Spectral analysis of the fluctuations of the flame front position depicts that the normalized and averaged power-spectrum-densities collapse and show a power-law relation with the normalized wave number. The flame brush thickness is linearly correlated with RMS of the distance between the flame front and the vertical axis. Analysis of the curvature of the flame front data shows that the mean curvature is independent of the experimental conditions tested and equals to zero. Values of the inverse of the RMS of flame front curvature are similar to those of the integral length scale, suggesting that the large eddies in the flow make a significant contribution in wrinkling of the flame front. Spectral analyses of the flame front curvature as well as the angle between tangent to the flame front and the horizontal axis show that the power-spectrum-densities feature a peak. Value of the inverse of the wave number pertaining to the peak is larger than that of the integral length scale.

The effect of warm-ups with stretching on the isokinetic moments of collegiate men.

PubMed

Park, Hyoung-Kil; Jung, Min-Kyung; Park, Eunkyung; Lee, Chang-Young; Jee, Yong-Seok; Eun, Denny; Cha, Jun-Youl; Yoo, Jaehyun

2018-02-01

Performing warm-ups increases muscle temperature and blood flow, which contributes to improved exercise performance and reduced risk of injuries to muscles and tendons. Stretching increases the range of motion of the joints and is effective for the maintenance and enhancement of exercise performance and flexibility, as well as for injury prevention. However, stretching as a warm-up activity may temporarily decrease muscle strength, muscle power, and exercise performance. This study aimed to clarify the effect of stretching during warm-ups on muscle strength, muscle power, and muscle endurance in a nonathletic population. The subjects of this study consisted of 13 physically active male collegiate students with no medical conditions. A self-assessment questionnaire regarding how well the subjects felt about their physical abilities was administered to measure psychological readiness before and after the warm-up. Subjects performed a non-warm-up, warm-up, or warm-up regimen with stretching prior to the assessment of the isokinetic moments of knee joints. After the measurements, the respective variables were analyzed using nonparametric tests. First, no statistically significant intergroup differences were found in the flexor and extensor peak torques of the knee joints at 60°/sec, which were assessed to measure muscle strength. Second, no statistically significant intergroup differences were found in the flexor and extensor peak torques of the knee joints at 180°/sec, which were assessed to measure muscle power. Third, the total work of the knee joints at 240°/sec, intended to measure muscle endurance, was highest in the aerobic-stretch-warm-ups (ASW) group, but no statistically significant differences were found among the groups. Finally, the psychological readiness for physical activity according to the type of warm-up was significantly higher in ASW. Simple stretching during warm-ups appears to have no effect on variables of exercise physiology in nonathletes who participate in routine recreational sport activities. However, they seem to have a meaningful effect on exercise performance by affording psychological stability, preparation, and confidence in exercise performance.

Machine learning patterns for neuroimaging-genetic studies in the cloud.

PubMed

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.

Evaluating efficiency and statistical power of self-controlled case series and self-controlled risk interval designs in vaccine safety.

PubMed

Li, Rongxia; Stewart, Brock; Weintraub, Eric

2016-01-01

The self-controlled case series (SCCS) and self-controlled risk interval (SCRI) designs have recently become widely used in the field of post-licensure vaccine safety monitoring to detect potential elevated risks of adverse events following vaccinations. The SCRI design can be viewed as a subset of the SCCS method in that a reduced comparison time window is used for the analysis. Compared to the SCCS method, the SCRI design has less statistical power due to fewer events occurring in the shorter control interval. In this study, we derived the asymptotic relative efficiency (ARE) between these two methods to quantify this loss in power in the SCRI design. The equation is formulated as [Formula: see text] (a: control window-length ratio between SCRI and SCCS designs; b: ratio of risk window length and control window length in the SCCS design; and [Formula: see text]: relative risk of exposed window to control window). According to this equation, the relative efficiency declines as the ratio of control-period length between SCRI and SCCS methods decreases, or with an increase in the relative risk [Formula: see text]. We provide an example utilizing data from the Vaccine Safety Datalink (VSD) to study the potential elevated risk of febrile seizure following seasonal influenza vaccine in the 2010-2011 season.

Understanding taxi travel patterns

NASA Astrophysics Data System (ADS)

Cai, Hua; Zhan, Xiaowei; Zhu, Ji; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-09-01

Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of passenger trips, which include only taxi trips occupied with passengers. However, unoccupied trips are also important for urban sustainability issues because they represent potential opportunities to improve the efficiency of the transportation system. Therefore, we need to understand the travel patterns of taxis as an integrated system, instead of focusing only on the occupied trips. In this study we examine GPS trajectory data of 11,880 taxis in Beijing, China for a period of three weeks. Our results show that taxi travel patterns share similar traits with travel patterns of individuals but also exhibit differences. Trip displacement distribution of taxi travels is statistically greater than the exponential distribution and smaller than the truncated power-law distribution. The distribution of short trips (less than 30 miles) can be best fitted with power-law while long trips follow exponential decay. We use radius of gyration to characterize individual taxi's travel distance and find that it does not follow a truncated power-law as observed in previous studies. Spatial and temporal regularities exist in taxi travels. However, with increasing spatial coverage, taxi trips can exhibit dual high probability density centers.

The distribution of spectral index of magnetic field and ion velocity in Pi2 frequency band in BBFs: THEMIS statistics

NASA Astrophysics Data System (ADS)

Wu, Q.; Du, A. M.; Volwerk, M.; Wang, G. Q.

2016-09-01

A statistical study of the THEMIS FGM and ESA data is performed on turbulence of magnetic field and velocity for 218 selected 12 min intervals in BBFs. The spectral index α in the frequency range of 0.005-0.06 Hz are Gaussian distributions. The peaks indexes of total ion velocity Vi and parallel velocity V‖ are 1.95 and 2.07 nearly the spectral index of intermittent low frequency turbulence with large amplitude. However, most probable α of perpendicular velocity V⊥ is about 1.75. It is a little bigger than 5/3 of Kolmogorov (1941). The peak indexes of total magnetic field BT is 1.70 similar to V⊥. Compression magnetic field B‖ are 1.85 which is smaller than 2 and bigger than 5/3 of Kolmogorov (1941). The most probable spectral index of shear B⊥ is about 1.44 which is close to 3/2 of Kraichnan (1965). Max V⊥ have little effect on the power magnitude of VT and V‖ but is positively correlated to spectral index of V⊥. The spectral power of BT, B‖ and B⊥ increase with max perpendicular velocity but spectral indexes of them are negatively correlated to V⊥. The spectral index and the spectral power of magnetic field over the frequency interval 0.005-0.06 Hz is very different from that over 0.08-1 Hz.

Improving accuracy and power with transfer learning using a meta-analytic database.

PubMed

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

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

Finley, Cathy

2014-04-30

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

Blow molding electric drives of Mechanical Engineering

NASA Astrophysics Data System (ADS)

Bukhanov, S. S.; Ramazanov, M. A.; Tsirkunenko, A. T.

2018-03-01

The article considers the questions about the analysis of new possibilities, which gives the use of adjustable electric drives for blowing mechanisms of plastic production. Thus, the use of new semiconductor converters makes it possible not only to compensate the instability of the supply network by using special dynamic voltage regulators, but to improve (correct) the power factor. The calculation of economic efficiency in controlled electric drives of blowing mechanisms is given. On the basis of statistical analysis, the calculation of the reliability parameters of the regulated electric drives’ elements under consideration is given. It is shown that an increase in the reliability of adjustable electric drives is possible both due to overestimation of the electric drive’s installed power, and in simpler schemes with pulse-vector control.

Detecting seasonal and cyclical trends in agricultural runoff water quality-hypothesis tests and block bootstrap power analysis.

PubMed

Uddameri, Venkatesh; Singaraju, Sreeram; Hernandez, E Annette

2018-02-21

Seasonal and cyclic trends in nutrient concentrations at four agricultural drainage ditches were assessed using a dataset generated from a multivariate, multiscale, multiyear water quality monitoring effort in the agriculturally dominant Lower Rio Grande Valley (LRGV) River Watershed in South Texas. An innovative bootstrap sampling-based power analysis procedure was developed to evaluate the ability of Mann-Whitney and Noether tests to discern trends and to guide future monitoring efforts. The Mann-Whitney U test was able to detect significant changes between summer and winter nutrient concentrations at sites with lower depths and unimpeded flows. Pollutant dilution, non-agricultural loadings, and in-channel flow structures (weirs) masked the effects of seasonality. The detection of cyclical trends using the Noether test was highest in the presence of vegetation mainly for total phosphorus and oxidized nitrogen (nitrite + nitrate) compared to dissolved phosphorus and reduced nitrogen (total Kjeldahl nitrogen-TKN). Prospective power analysis indicated that while increased monitoring can lead to higher statistical power, the effect size (i.e., the total number of trend sequences within a time-series) had a greater influence on the Noether test. Both Mann-Whitney and Noether tests provide complementary information on seasonal and cyclic behavior of pollutant concentrations and are affected by different processes. The results from these statistical tests when evaluated in the context of flow, vegetation, and in-channel hydraulic alterations can help guide future data collection and monitoring efforts. The study highlights the need for long-term monitoring of agricultural drainage ditches to properly discern seasonal and cyclical trends.

Analysis of postoperative complications for superficial liposuction: a review of 2398 cases.

PubMed

Kim, Youn Hwan; Cha, Sang Myun; Naidu, Shenthilkumar; Hwang, Weon Jung

2011-02-01

Superficial liposuction has found its application in maximizing and creating a lifting effect to achieve a better aesthetic result. Due to initial high complication rates, these procedures were generally accepted as risky. In a response to the increasing concerns over the safety and efficacy of superficial liposuction, the authors describe their 14-year experience of performing superficial liposuction and analysis of postoperative complications associated with these procedures. From March of 1995 to December of 2008, the authors performed superficial liposuction on 2398 patients. Three subgroups were incorporated according to liposuction methods as follows: power-assisted liposuction alone (subgroup 1), power-assisted liposuction combined with ultrasound energy (subgroup 2), and power-assisted liposuction combined with external ultrasound and postoperative Endermologie (subgroup 3). Statistical analyses for complications were performed among subgroups. The mean age was 42.8 years, mean body mass index was 27.9 kg/m2, and mean volume of total aspiration was 5045 cc. Overall complication rate was 8.6 percent (206 patients). Four cases of skin necroses and two cases of infections were included. The most common complication was postoperative contour irregularity. Power-assisted liposuction combined with external ultrasound with or without postoperative Endermologie was seen to decrease the overall complication rate, contour irregularity, and skin necrosis. There were no statistical differences regarding other complications. Superficial liposuction has potential risks for higher complications compared with conventional suction techniques, especially postoperative contour irregularity, which can be minimized with proper selection of candidates for the procedure, avoiding overzealous suctioning of superficial layer, and using a combination of ultrasound energy techniques.