A standards-based method for compositional analysis by energy dispersive X-ray spectrometry using multivariate statistical analysis: application to multicomponent alloys.

PubMed

Rathi, Monika; Ahrenkiel, S P; Carapella, J J; Wanlass, M W

2013-02-01

Given an unknown multicomponent alloy, and a set of standard compounds or alloys of known composition, can one improve upon popular standards-based methods for energy dispersive X-ray (EDX) spectrometry to quantify the elemental composition of the unknown specimen? A method is presented here for determining elemental composition of alloys using transmission electron microscopy-based EDX with appropriate standards. The method begins with a discrete set of related reference standards of known composition, applies multivariate statistical analysis to those spectra, and evaluates the compositions with a linear matrix algebra method to relate the spectra to elemental composition. By using associated standards, only limited assumptions about the physical origins of the EDX spectra are needed. Spectral absorption corrections can be performed by providing an estimate of the foil thickness of one or more reference standards. The technique was applied to III-V multicomponent alloy thin films: composition and foil thickness were determined for various III-V alloys. The results were then validated by comparing with X-ray diffraction and photoluminescence analysis, demonstrating accuracy of approximately 1% in atomic fraction.

Standard Setting in a Small Scale OSCE: A Comparison of the Modified Borderline-Group Method and the Borderline Regression Method

ERIC Educational Resources Information Center

Wood, Timothy J.; Humphrey-Murto, Susan M.; Norman, Geoffrey R.

2006-01-01

When setting standards, administrators of small-scale OSCEs often face several challenges, including a lack of resources, a lack of available expertise in statistics, and difficulty in recruiting judges. The Modified Borderline-Group Method is a standard setting procedure that compensates for these challenges by using physician examiners and is…

The Content of Statistical Requirements for Authors in Biomedical Research Journals

PubMed Central

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

2016-01-01

Background: Robust statistical designing, sound statistical analysis, and standardized presentation are important to enhance the quality and transparency of biomedical research. This systematic review was conducted to summarize the statistical reporting requirements introduced by biomedical research journals with an impact factor of 10 or above so that researchers are able to give statistical issues’ serious considerations not only at the stage of data analysis but also at the stage of methodological design. Methods: Detailed statistical instructions for authors were downloaded from the homepage of each of the included journals or obtained from the editors directly via email. Then, we described the types and numbers of statistical guidelines introduced by different press groups. Items of statistical reporting guideline as well as particular requirements were summarized in frequency, which were grouped into design, method of analysis, and presentation, respectively. Finally, updated statistical guidelines and particular requirements for improvement were summed up. Results: Totally, 21 of 23 press groups introduced at least one statistical guideline. More than half of press groups can update their statistical instruction for authors gradually relative to issues of new statistical reporting guidelines. In addition, 16 press groups, covering 44 journals, address particular statistical requirements. The most of the particular requirements focused on the performance of statistical analysis and transparency in statistical reporting, including “address issues relevant to research design, including participant flow diagram, eligibility criteria, and sample size estimation,” and “statistical methods and the reasons.” Conclusions: Statistical requirements for authors are becoming increasingly perfected. Statistical requirements for authors remind researchers that they should make sufficient consideration not only in regards to statistical methods during the research design, but also standardized statistical reporting, which would be beneficial in providing stronger evidence and making a greater critical appraisal of evidence more accessible. PMID:27748343

Standard methods for sampling North American freshwater fishes

USGS Publications Warehouse

Bonar, Scott A.; Hubert, Wayne A.; Willis, David W.

2009-01-01

This important reference book provides standard sampling methods recommended by the American Fisheries Society for assessing and monitoring freshwater fish populations in North America. Methods apply to ponds, reservoirs, natural lakes, and streams and rivers containing cold and warmwater fishes. Range-wide and eco-regional averages for indices of abundance, population structure, and condition for individual species are supplied to facilitate comparisons of standard data among populations. Provides information on converting nonstandard to standard data, statistical and database procedures for analyzing and storing standard data, and methods to prevent transfer of invasive species while sampling.

Langley Wind Tunnel Data Quality Assurance-Check Standard Results

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Grubb, John P.; Krieger, William B.; Cler, Daniel L.

2000-01-01

A framework for statistical evaluation, control and improvement of wind funnel measurement processes is presented The methodology is adapted from elements of the Measurement Assurance Plans developed by the National Bureau of Standards (now the National Institute of Standards and Technology) for standards and calibration laboratories. The present methodology is based on the notions of statistical quality control (SQC) together with check standard testing and a small number of customer repeat-run sets. The results of check standard and customer repeat-run -sets are analyzed using the statistical control chart-methods of Walter A. Shewhart long familiar to the SQC community. Control chart results are presented for. various measurement processes in five facilities at Langley Research Center. The processes include test section calibration, force and moment measurements with a balance, and instrument calibration.

Evaluation of PDA Technical Report No 33. Statistical Testing Recommendations for a Rapid Microbiological Method Case Study.

PubMed

Murphy, Thomas; Schwedock, Julie; Nguyen, Kham; Mills, Anna; Jones, David

2015-01-01

New recommendations for the validation of rapid microbiological methods have been included in the revised Technical Report 33 release from the PDA. The changes include a more comprehensive review of the statistical methods to be used to analyze data obtained during validation. This case study applies those statistical methods to accuracy, precision, ruggedness, and equivalence data obtained using a rapid microbiological methods system being evaluated for water bioburden testing. Results presented demonstrate that the statistical methods described in the PDA Technical Report 33 chapter can all be successfully applied to the rapid microbiological method data sets and gave the same interpretation for equivalence to the standard method. The rapid microbiological method was in general able to pass the requirements of PDA Technical Report 33, though the study shows that there can be occasional outlying results and that caution should be used when applying statistical methods to low average colony-forming unit values. Prior to use in a quality-controlled environment, any new method or technology has to be shown to work as designed by the manufacturer for the purpose required. For new rapid microbiological methods that detect and enumerate contaminating microorganisms, additional recommendations have been provided in the revised PDA Technical Report No. 33. The changes include a more comprehensive review of the statistical methods to be used to analyze data obtained during validation. This paper applies those statistical methods to analyze accuracy, precision, ruggedness, and equivalence data obtained using a rapid microbiological method system being validated for water bioburden testing. The case study demonstrates that the statistical methods described in the PDA Technical Report No. 33 chapter can be successfully applied to rapid microbiological method data sets and give the same comparability results for similarity or difference as the standard method. © PDA, Inc. 2015.

Confidence Interval Coverage for Cohen's Effect Size Statistic

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2006-01-01

Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population…

Statistical Process Control: Going to the Limit for Quality.

ERIC Educational Resources Information Center

Training, 1987

1987-01-01

Defines the concept of statistical process control, a quality control method used especially in manufacturing. Generally, concept users set specific standard levels that must be met. Makes the point that although employees work directly with the method, management is responsible for its success within the plant. (CH)

40 CFR 1065.12 - Approval of alternate procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... engine meets all applicable emission standards according to specified procedures. (iii) Use statistical.... (e) We may give you specific directions regarding methods for statistical analysis, or we may approve... statistical tests. Perform the tests as follows: (1) Repeat measurements for all applicable duty cycles at...

Statistical testing of association between menstruation and migraine.

PubMed

Barra, Mathias; Dahl, Fredrik A; Vetvik, Kjersti G

2015-02-01

To repair and refine a previously proposed method for statistical analysis of association between migraine and menstruation. Menstrually related migraine (MRM) affects about 20% of female migraineurs in the general population. The exact pathophysiological link from menstruation to migraine is hypothesized to be through fluctuations in female reproductive hormones, but the exact mechanisms remain unknown. Therefore, the main diagnostic criterion today is concurrency of migraine attacks with menstruation. Methods aiming to exclude spurious associations are wanted, so that further research into these mechanisms can be performed on a population with a true association. The statistical method is based on a simple two-parameter null model of MRM (which allows for simulation modeling), and Fisher's exact test (with mid-p correction) applied to standard 2 × 2 contingency tables derived from the patients' headache diaries. Our method is a corrected version of a previously published flawed framework. To our best knowledge, no other published methods for establishing a menstruation-migraine association by statistical means exist today. The probabilistic methodology shows good performance when subjected to receiver operator characteristic curve analysis. Quick reference cutoff values for the clinical setting were tabulated for assessing association given a patient's headache history. In this paper, we correct a proposed method for establishing association between menstruation and migraine by statistical methods. We conclude that the proposed standard of 3-cycle observations prior to setting an MRM diagnosis should be extended with at least one perimenstrual window to obtain sufficient information for statistical processing. © 2014 American Headache Society.

Cardiac arrest risk standardization using administrative data compared to registry data

PubMed Central

Gaieski, David F.; Donnino, Michael W.; Nelson, Joshua I. M.; Mutter, Eric L.; Carr, Brendan G.; Abella, Benjamin S.; Wiebe, Douglas J.

2017-01-01

Background Methods for comparing hospitals regarding cardiac arrest (CA) outcomes, vital for improving resuscitation performance, rely on data collected by cardiac arrest registries. However, most CA patients are treated at hospitals that do not participate in such registries. This study aimed to determine whether CA risk standardization modeling based on administrative data could perform as well as that based on registry data. Methods and results Two risk standardization logistic regression models were developed using 2453 patients treated from 2000–2015 at three hospitals in an academic health system. Registry and administrative data were accessed for all patients. The outcome was death at hospital discharge. The registry model was considered the “gold standard” with which to compare the administrative model, using metrics including comparing areas under the curve, calibration curves, and Bland-Altman plots. The administrative risk standardization model had a c-statistic of 0.891 (95% CI: 0.876–0.905) compared to a registry c-statistic of 0.907 (95% CI: 0.895–0.919). When limited to only non-modifiable factors, the administrative model had a c-statistic of 0.818 (95% CI: 0.799–0.838) compared to a registry c-statistic of 0.810 (95% CI: 0.788–0.831). All models were well-calibrated. There was no significant difference between c-statistics of the models, providing evidence that valid risk standardization can be performed using administrative data. Conclusions Risk standardization using administrative data performs comparably to standardization using registry data. This methodology represents a new tool that can enable opportunities to compare hospital performance in specific hospital systems or across the entire US in terms of survival after CA. PMID:28783754

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

Woodroffe, J. R.; Brito, T. V.; Jordanova, V. K.

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution were used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. Our study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra,more » Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Does daily nurse staffing match ward workload variability? Three hospitals' experiences.

PubMed

Gabbay, Uri; Bukchin, Michael

2009-01-01

Nurse shortage and rising healthcare resource burdens mean that appropriate workforce use is imperative. This paper aims to evaluate whether daily nursing staffing meets ward workload needs. Nurse attendance and daily nurses' workload capacity in three hospitals were evaluated. Statistical process control was used to evaluate intra-ward nurse workload capacity and day-to-day variations. Statistical process control is a statistics-based method for process monitoring that uses charts with predefined target measure and control limits. Standardization was performed for inter-ward analysis by converting ward-specific crude measures to ward-specific relative measures by dividing observed/expected. Two charts: acceptable and tolerable daily nurse workload intensity, were defined. Appropriate staffing indicators were defined as those exceeding predefined rates within acceptable and tolerable limits (50 percent and 80 percent respectively). A total of 42 percent of the overall days fell within acceptable control limits and 71 percent within tolerable control limits. Appropriate staffing indicators were met in only 33 percent of wards regarding acceptable nurse workload intensity and in only 45 percent of wards regarding tolerable workloads. The study work did not differentiate crude nurse attendance and it did not take into account patient severity since crude bed occupancy was used. Double statistical process control charts and certain staffing indicators were used, which is open to debate. Wards that met appropriate staffing indicators prove the method's feasibility. Wards that did not meet appropriate staffing indicators prove the importance and the need for process evaluations and monitoring. Methods presented for monitoring daily staffing appropriateness are simple to implement either for intra-ward day-to-day variation by using nurse workload capacity statistical process control charts or for inter-ward evaluation using standardized measure of nurse workload intensity. The real challenge will be to develop planning systems and implement corrective interventions such as dynamic and flexible daily staffing, which will face difficulties and barriers. The paper fulfils the need for workforce utilization evaluation. A simple method using available data for daily staffing appropriateness evaluation, which is easy to implement and operate, is presented. The statistical process control method enables intra-ward evaluation, while standardization by converting crude into relative measures enables inter-ward analysis. The staffing indicator definitions enable performance evaluation. This original study uses statistical process control to develop simple standardization methods and applies straightforward statistical tools. This method is not limited to crude measures, rather it uses weighted workload measures such as nursing acuity or weighted nurse level (i.e. grade/band).

Standard deviation and standard error of the mean.

PubMed

Lee, Dong Kyu; In, Junyong; Lee, Sangseok

2015-06-01

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results.

Standard deviation and standard error of the mean

PubMed Central

In, Junyong; Lee, Sangseok

2015-01-01

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results. PMID:26045923

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods

ERIC Educational Resources Information Center

MacKinnon, David P.; Lockwood, Chondra M.; Williams, Jason

2004-01-01

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal…

Comparison of Efficiency of Jackknife and Variance Component Estimators of Standard Errors. Program Statistics Research. Technical Report.

ERIC Educational Resources Information Center

Longford, Nicholas T.

Large scale surveys usually employ a complex sampling design and as a consequence, no standard methods for estimation of the standard errors associated with the estimates of population means are available. Resampling methods, such as jackknife or bootstrap, are often used, with reference to their properties of robustness and reduction of bias. A…

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

PubMed

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

2014-06-01

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

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

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

PubMed

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

2016-10-20

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

Assay of potency of the proposed Fifth International Standard for Gas-Gangrene Antitoxin (Perfringens)

PubMed Central

Prigge, R.; Micke, H.; Krüger, J.

1963-01-01

As part of a collaborative assay of the proposed Fifth International Standard for Gas-Gangrene Antitoxin (Perfringens), five ampoules of the proposed replacement material were assayed in the authors' laboratory against the then current Fourth International Standard. Both in vitro and in vivo methods were used. This paper presents the results and their statistical analysis. The two methods yielded different results which were not likely to have been due to chance, but exact statistical comparison is not possible. It is thought, however, that the differences may be due, at least in part, to differences in the relative proportions of zeta-antitoxin and alpha-antitoxin in the Fourth and Fifth International Standards and the consequent different reactions with the test toxin that was used for titration. PMID:14107746

Data-optimized source modeling with the Backwards Liouville Test–Kinetic method

DOE PAGES

Woodroffe, J. R.; Brito, T. V.; Jordanova, V. K.; ...

2017-09-14

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution were used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. Our study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra,more » Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Quantitative Comparison of Three Standardization Methods Using a One-Way ANOVA for Multiple Mean Comparisons

ERIC Educational Resources Information Center

Barrows, Russell D.

2007-01-01

A one-way ANOVA experiment is performed to determine whether or not the three standardization methods are statistically different in determining the concentration of the three paraffin analytes. The laboratory exercise asks students to combine the three methods in a single analytical procedure of their own design to determine the concentration of…

OSPAR standard method and software for statistical analysis of beach litter data.

PubMed

Schulz, Marcus; van Loon, Willem; Fleet, David M; Baggelaar, Paul; van der Meulen, Eit

2017-09-15

The aim of this study is to develop standard statistical methods and software for the analysis of beach litter data. The optimal ensemble of statistical methods comprises the Mann-Kendall trend test, the Theil-Sen slope estimation, the Wilcoxon step trend test and basic descriptive statistics. The application of Litter Analyst, a tailor-made software for analysing the results of beach litter surveys, to OSPAR beach litter data from seven beaches bordering on the south-eastern North Sea, revealed 23 significant trends in the abundances of beach litter types for the period 2009-2014. Litter Analyst revealed a large variation in the abundance of litter types between beaches. To reduce the effects of spatial variation, trend analysis of beach litter data can most effectively be performed at the beach or national level. Spatial aggregation of beach litter data within a region is possible, but resulted in a considerable reduction in the number of significant trends. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Staubert, R.

1985-01-01

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

A Comparison of Approaches for Setting Proficiency Standards.

ERIC Educational Resources Information Center

Koffler, Stephen L.

This research compared the cut-off scores estimated from an empirical procedure (Contrasting group method) to those determined from a more theoretical process (Nedelsky method). A methodological and statistical framework was also provided for analysis of the data to obtain the most appropriate standard using the empirical procedure. Data were…

Assessment of statistic analysis in non-radioisotopic local lymph node assay (non-RI-LLNA) with alpha-hexylcinnamic aldehyde as an example.

PubMed

Takeyoshi, Masahiro; Sawaki, Masakuni; Yamasaki, Kanji; Kimber, Ian

2003-09-30

The murine local lymph node assay (LLNA) is used for the identification of chemicals that have the potential to cause skin sensitization. However, it requires specific facility and handling procedures to accommodate a radioisotopic (RI) endpoint. We have developed non-radioisotopic (non-RI) endpoint of LLNA based on BrdU incorporation to avoid a use of RI. Although this alternative method appears viable in principle, it is somewhat less sensitive than the standard assay. In this study, we report investigations to determine the use of statistical analysis to improve the sensitivity of a non-RI LLNA procedure with alpha-hexylcinnamic aldehyde (HCA) in two separate experiments. Consequently, the alternative non-RI method required HCA concentrations of greater than 25% to elicit a positive response based on the criterion for classification as a skin sensitizer in the standard LLNA. Nevertheless, dose responses to HCA in the alternative method were consistent in both experiments and we examined whether the use of an endpoint based upon the statistical significance of induced changes in LNC turnover, rather than an SI of 3 or greater, might provide for additional sensitivity. The results reported here demonstrate that with HCA at least significant responses were, in each of two experiments, recorded following exposure of mice to 25% of HCA. These data suggest that this approach may be more satisfactory-at least when BrdU incorporation is measured. However, this modification of the LLNA is rather less sensitive than the standard method if employing statistical endpoint. Taken together the data reported here suggest that a modified LLNA in which BrdU is used in place of radioisotope incorporation shows some promise, but that in its present form, even with the use of a statistical endpoint, lacks some of the sensitivity of the standard method. The challenge is to develop strategies for further refinement of this approach.

[Overview and prospect of syndrome differentiation of hypertension in traditional Chinese medicine].

PubMed

Yang, Xiao-Chen; Xiong, Xing-Jiang; Wang, Jie

2014-01-01

This article is to overview the literature of syndrome differentiation of traditional Chinese medicine on hypertension. According to the theory of disease in combination with syndrome, we concluded syndrome types of hypertension in four aspects, including national standards, industry standards, teaching standards and personal experience. Meanwhile, in order to provide new methods and approaches for normalized research, we integrated modern testing methods and statistical methods to analyze syndrome differentiation for the treatment of hypertension.

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.

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

Estimating the mass variance in neutron multiplicity counting-A comparison of approaches

NASA Astrophysics Data System (ADS)

Dubi, C.; Croft, S.; Favalli, A.; Ocherashvili, A.; Pedersen, B.

2017-12-01

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α , n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

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

Dubi, C.; Croft, S.; Favalli, A.

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Estimating the mass variance in neutron multiplicity counting $-$ A comparison of approaches

DOE PAGES

Dubi, C.; Croft, S.; Favalli, A.; ...

2017-09-14

In the standard practice of neutron multiplicity counting, the first three sampled factorial moments of the event triggered neutron count distribution are used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. This study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra, Italy,more » sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Open-source platform to benchmark fingerprints for ligand-based virtual screening

PubMed Central

2013-01-01

Similarity-search methods using molecular fingerprints are an important tool for ligand-based virtual screening. A huge variety of fingerprints exist and their performance, usually assessed in retrospective benchmarking studies using data sets with known actives and known or assumed inactives, depends largely on the validation data sets used and the similarity measure used. Comparing new methods to existing ones in any systematic way is rather difficult due to the lack of standard data sets and evaluation procedures. Here, we present a standard platform for the benchmarking of 2D fingerprints. The open-source platform contains all source code, structural data for the actives and inactives used (drawn from three publicly available collections of data sets), and lists of randomly selected query molecules to be used for statistically valid comparisons of methods. This allows the exact reproduction and comparison of results for future studies. The results for 12 standard fingerprints together with two simple baseline fingerprints assessed by seven evaluation methods are shown together with the correlations between methods. High correlations were found between the 12 fingerprints and a careful statistical analysis showed that only the two baseline fingerprints were different from the others in a statistically significant way. High correlations were also found between six of the seven evaluation methods, indicating that despite their seeming differences, many of these methods are similar to each other. PMID:23721588

Trends in study design and the statistical methods employed in a leading general medicine journal.

PubMed

Gosho, M; Sato, Y; Nagashima, K; Takahashi, S

2018-02-01

Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design. © 2017 John Wiley & Sons Ltd.

Kappa statistic for the clustered dichotomous responses from physicians and patients

PubMed Central

Kang, Chaeryon; Qaqish, Bahjat; Monaco, Jane; Sheridan, Stacey L.; Cai, Jianwen

2013-01-01

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared to the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. An example of an application to a coronary heart disease prevention study is presented. PMID:23533082

Improved score statistics for meta-analysis in single-variant and gene-level association studies.

PubMed

Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo

2018-06-01

Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.

Performance of Bootstrapping Approaches To Model Test Statistics and Parameter Standard Error Estimation in Structural Equation Modeling.

ERIC Educational Resources Information Center

Nevitt, Jonathan; Hancock, Gregory R.

2001-01-01

Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…

The Standard Model in the history of the Natural Sciences, Econometrics, and the social sciences

NASA Astrophysics Data System (ADS)

Fisher, W. P., Jr.

2010-07-01

In the late 18th and early 19th centuries, scientists appropriated Newton's laws of motion as a model for the conduct of any other field of investigation that would purport to be a science. This early form of a Standard Model eventually informed the basis of analogies for the mathematical expression of phenomena previously studied qualitatively, such as cohesion, affinity, heat, light, electricity, and magnetism. James Clerk Maxwell is known for his repeated use of a formalized version of this method of analogy in lectures, teaching, and the design of experiments. Economists transferring skills learned in physics made use of the Standard Model, especially after Maxwell demonstrated the value of conceiving it in abstract mathematics instead of as a concrete and literal mechanical analogy. Haavelmo's probability approach in econometrics and R. Fisher's Statistical Methods for Research Workers brought a statistical approach to bear on the Standard Model, quietly reversing the perspective of economics and the social sciences relative to that of physics. Where physicists, and Maxwell in particular, intuited scientific method as imposing stringent demands on the quality and interrelations of data, instruments, and theory in the name of inferential and comparative stability, statistical models and methods disconnected theory from data by removing the instrument as an essential component. New possibilities for reconnecting economics and the social sciences to Maxwell's sense of the method of analogy are found in Rasch's probabilistic models for measurement.

Statistical methods used in the public health literature and implications for training of public health professionals

PubMed Central

Hayat, Matthew J.; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L.

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals. PMID:28591190

Statistical methods used in the public health literature and implications for training of public health professionals.

PubMed

Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.

Re-Conceptualization of Modified Angoff Standard Setting: Unified Statistical, Measurement, Cognitive, and Social Psychological Theories

ERIC Educational Resources Information Center

Iyioke, Ifeoma Chika

2013-01-01

This dissertation describes a design for training, in accordance with probability judgment heuristics principles, for the Angoff standard setting method. The new training with instruction, practice, and feedback tailored to the probability judgment heuristics principles was called the Heuristic training and the prevailing Angoff method training…

Introducing Statistical Inference to Biology Students through Bootstrapping and Randomization

ERIC Educational Resources Information Center

Lock, Robin H.; Lock, Patti Frazer

2008-01-01

Bootstrap methods and randomization tests are increasingly being used as alternatives to standard statistical procedures in biology. They also serve as an effective introduction to the key ideas of statistical inference in introductory courses for biology students. We discuss the use of such simulation based procedures in an integrated curriculum…

Quality Space and Launch Requirements, Addendum to AS9100C

DTIC Science & Technology

2015-05-08

45 8.9.1 Statistical Process Control (SPC) .......................................................................... 45...SMC Space and Missile Systems Center SME Subject Matter Expert SOW Statement of Work SPC Statistical Process Control SPO System Program Office SRP...occur without any individual data exceeding the control limits. Control limits are developed using standard statistical methods or other approved

Statistics and Title VII Proof: Prima Facie Case and Rebuttal.

ERIC Educational Resources Information Center

Whitten, David

1978-01-01

The method and means by which statistics can raise a prima facie case of Title VII violation are analyzed. A standard is identified that can be applied to determine whether a statistical disparity is sufficient to shift the burden to the employer to rebut a prima facie case of discrimination. (LBH)

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

PubMed

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

2016-01-13

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

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

PubMed Central

2014-01-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

Descriptive and inferential statistical methods used in burns research.

PubMed

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

2010-05-01

Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals in the fields of biostatistics and epidemiology when using more advanced statistical techniques. Copyright 2009 Elsevier Ltd and ISBI. All rights reserved.

Implementing informative priors for heterogeneity in meta-analysis using meta-regression and pseudo data.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; White, Ian R; Jackson, Dan; Spiegelhalter, David J; Higgins, Julian P T

2016-12-20

Many meta-analyses combine results from only a small number of studies, a situation in which the between-study variance is imprecisely estimated when standard methods are applied. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, providing the potential for more robust inference on the effect size of interest. We present a method for performing Bayesian meta-analysis using data augmentation, in which we represent an informative conjugate prior for between-study variance by pseudo data and use meta-regression for estimation. To assist in this, we derive predictive inverse-gamma distributions for the between-study variance expected in future meta-analyses. These may serve as priors for heterogeneity in new meta-analyses. In a simulation study, we compare approximate Bayesian methods using meta-regression and pseudo data against fully Bayesian approaches based on importance sampling techniques and Markov chain Monte Carlo (MCMC). We compare the frequentist properties of these Bayesian methods with those of the commonly used frequentist DerSimonian and Laird procedure. The method is implemented in standard statistical software and provides a less complex alternative to standard MCMC approaches. An importance sampling approach produces almost identical results to standard MCMC approaches, and results obtained through meta-regression and pseudo data are very similar. On average, data augmentation provides closer results to MCMC, if implemented using restricted maximum likelihood estimation rather than DerSimonian and Laird or maximum likelihood estimation. The methods are applied to real datasets, and an extension to network meta-analysis is described. The proposed method facilitates Bayesian meta-analysis in a way that is accessible to applied researchers. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Reporting guidance considerations from a statistical perspective: overview of tools to enhance the rigour of reporting of randomised trials and systematic reviews.

PubMed

Hutton, Brian; Wolfe, Dianna; Moher, David; Shamseer, Larissa

2017-05-01

Research waste has received considerable attention from the biomedical community. One noteworthy contributor is incomplete reporting in research publications. When detailing statistical methods and results, ensuring analytic methods and findings are completely documented improves transparency. For publications describing randomised trials and systematic reviews, guidelines have been developed to facilitate complete reporting. This overview summarises aspects of statistical reporting in trials and systematic reviews of health interventions. A narrative approach to summarise features regarding statistical methods and findings from reporting guidelines for trials and reviews was taken. We aim to enhance familiarity of statistical details that should be reported in biomedical research among statisticians and their collaborators. We summarise statistical reporting considerations for trials and systematic reviews from guidance documents including the Consolidated Standards of Reporting Trials (CONSORT) Statement for reporting of trials, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Statement for trial protocols, the Statistical Analyses and Methods in the Published Literature (SAMPL) Guidelines for statistical reporting principles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement for systematic reviews and PRISMA for Protocols (PRISMA-P). Considerations regarding sharing of study data and statistical code are also addressed. Reporting guidelines provide researchers with minimum criteria for reporting. If followed, they can enhance research transparency and contribute improve quality of biomedical publications. Authors should employ these tools for planning and reporting of their research. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Kappa statistic for clustered dichotomous responses from physicians and patients.

PubMed

Kang, Chaeryon; Qaqish, Bahjat; Monaco, Jane; Sheridan, Stacey L; Cai, Jianwen

2013-09-20

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study. Copyright © 2013 John Wiley & Sons, Ltd.

A Statistical Review of Alternative Zinc and Copper Extraction from Mineral Fertilizers and Industrial By-Products.

PubMed

Cenciani de Souza, Camila Prado; Aparecida de Abreu, Cleide; Coscione, Aline Renée; Alberto de Andrade, Cristiano; Teixeira, Luiz Antonio Junqueira; Consolini, Flavia

2018-01-01

Rapid, accurate, and low-cost alternative analytical methods for micronutrient quantification in fertilizers are fundamental in QC. The purpose of this study was to evaluate whether zinc (Zn) and copper (Cu) content in mineral fertilizers and industrial by-products determined by the alternative methods USEPA 3051a, 10% HCl, and 10% H2SO4 are statistically equivalent to the standard method, consisting of hot-plate digestion using concentrated HCl. The commercially marketed Zn and Cu sources in Brazil consisted of oxides, carbonate, and sulfate fertilizers and by-products consisting of galvanizing ash, galvanizing sludge, brass ash, and brass or scrap slag. The contents of sources ranged from 15 to 82% and 10 to 45%, respectively, for Zn and Cu. The Zn and Cu contents refer to the variation of the elements found in the different sources evaluated with the concentrated HCl method as shown in Table 1. A protocol based on the following criteria was used for the statistical analysis assessment of the methods: F-test modified by Graybill, t-test for the mean error, and linear correlation coefficient analysis. In terms of equivalents, 10% HCl extraction was equivalent to the standard method for Zn, and the results of the USEPA 3051a and 10% HCl methods indicated that these methods were equivalents for Cu. Therefore, these methods can be considered viable alternatives to the standard method of determination for Cu and Zn in mineral fertilizers and industrial by-products in future research for their complete validation.

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

PubMed

Hu, Liang-ping; Liu, Hui-gang

2005-07-20

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

A new method to address verification bias in studies of clinical screening tests: cervical cancer screening assays as an example.

PubMed

Xue, Xiaonan; Kim, Mimi Y; Castle, Philip E; Strickler, Howard D

2014-03-01

Studies to evaluate clinical screening tests often face the problem that the "gold standard" diagnostic approach is costly and/or invasive. It is therefore common to verify only a subset of negative screening tests using the gold standard method. However, undersampling the screen negatives can lead to substantial overestimation of the sensitivity and underestimation of the specificity of the diagnostic test. Our objective was to develop a simple and accurate statistical method to address this "verification bias." We developed a weighted generalized estimating equation approach to estimate, in a single model, the accuracy (eg, sensitivity/specificity) of multiple assays and simultaneously compare results between assays while addressing verification bias. This approach can be implemented using standard statistical software. Simulations were conducted to assess the proposed method. An example is provided using a cervical cancer screening trial that compared the accuracy of human papillomavirus and Pap tests, with histologic data as the gold standard. The proposed approach performed well in estimating and comparing the accuracy of multiple assays in the presence of verification bias. The proposed approach is an easy to apply and accurate method for addressing verification bias in studies of multiple screening methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Resampling-based Methods in Single and Multiple Testing for Equality of Covariance/Correlation Matrices

PubMed Central

Yang, Yang; DeGruttola, Victor

2016-01-01

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients. PMID:22740584

Resampling-based methods in single and multiple testing for equality of covariance/correlation matrices.

PubMed

Yang, Yang; DeGruttola, Victor

2012-06-22

Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.

An instrument to assess the statistical intensity of medical research papers.

PubMed

Nieminen, Pentti; Virtanen, Jorma I; Vähänikkilä, Hannu

2017-01-01

There is widespread evidence that statistical methods play an important role in original research articles, especially in medical research. The evaluation of statistical methods and reporting in journals suffers from a lack of standardized methods for assessing the use of statistics. The objective of this study was to develop and evaluate an instrument to assess the statistical intensity in research articles in a standardized way. A checklist-type measure scale was developed by selecting and refining items from previous reports about the statistical contents of medical journal articles and from published guidelines for statistical reporting. A total of 840 original medical research articles that were published between 2007-2015 in 16 journals were evaluated to test the scoring instrument. The total sum of all items was used to assess the intensity between sub-fields and journals. Inter-rater agreement was examined using a random sample of 40 articles. Four raters read and evaluated the selected articles using the developed instrument. The scale consisted of 66 items. The total summary score adequately discriminated between research articles according to their study design characteristics. The new instrument could also discriminate between journals according to their statistical intensity. The inter-observer agreement measured by the ICC was 0.88 between all four raters. Individual item analysis showed very high agreement between the rater pairs, the percentage agreement ranged from 91.7% to 95.2%. A reliable and applicable instrument for evaluating the statistical intensity in research papers was developed. It is a helpful tool for comparing the statistical intensity between sub-fields and journals. The novel instrument may be applied in manuscript peer review to identify papers in need of additional statistical review.

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

Consistent Practices for the Probability of Detection (POD) of Fracture Critical Metallic Components Project

NASA Technical Reports Server (NTRS)

Hughitt, Brian; Generazio, Edward (Principal Investigator); Nichols, Charles; Myers, Mika (Principal Investigator); Spencer, Floyd (Principal Investigator); Waller, Jess (Principal Investigator); Wladyka, Jordan (Principal Investigator); Aldrin, John; Burke, Eric; Cerecerez, Laura;

Evaluation of the VIDAS Listeria (LIS) immunoassay for the detection of Listeria in foods using demi-Fraser and Fraser enrichment broths, as modification of AOAC Official Method 999.06 (AOAC Official Method 2004.06).

PubMed

Silbernagel, Karen M; Jechorek, Robert P; Kaufer, Amanda L; Johnson, Ronald L; Aleo, V; Brown, B; Buen, M; Buresh, J; Carson, M; Franklin, J; Ham, P; Humes, L; Husby, G; Hutchins, J; Jechorek, R; Jenkins, J; Kaufer, A; Kexel, N; Kora, L; Lam, L; Lau, D; Leighton, S; Loftis, M; Luc, S; Martin, J; Nacar, I; Nogle, J; Park, J; Schultz, A; Seymore, D; Smith, C; Smith, J; Thou, P; Ulmer, M; Voss, R; Weaver, V

2005-01-01

A multilaboratory study was conducted to compare the VIDAS LIS immunoassay with the standard cultural methods for the detection of Listeria in foods using an enrichment modification of AOAC Official Method 999.06. The modified enrichment protocol was implemented to harmonize the VIDAS LIS assay with the VIDAS LMO2 assay. Five food types--brie cheese, vanilla ice cream, frozen green beans, frozen raw tilapia fish, and cooked roast beef--at 3 inoculation levels, were analyzed by each method. A total of 15 laboratories representing government and industry participated. In this study, 1206 test portions were tested, of which 1170 were used in the statistical analysis. There were 433 positive by the VIDAS LIS assay and 396 positive by the standard culture methods. A Chi-square analysis of each of the 5 food types, at the 3 inoculation levels tested, was performed. The resulting average Chi square analysis, 0.42, indicated that, overall, there are no statistical differences between the VIDAS LIS assay and the standard methods at the 5% level of significance.

Implementing statistical equating for MRCP(UK) Parts 1 and 2.

PubMed

McManus, I C; Chis, Liliana; Fox, Ray; Waller, Derek; Tang, Peter

2014-09-26

The MRCP(UK) exam, in 2008 and 2010, changed the standard-setting of its Part 1 and Part 2 examinations from a hybrid Angoff/Hofstee method to statistical equating using Item Response Theory, the reference group being UK graduates. The present paper considers the implementation of the change, the question of whether the pass rate increased amongst non-UK candidates, any possible role of Differential Item Functioning (DIF), and changes in examination predictive validity after the change. Analysis of data of MRCP(UK) Part 1 exam from 2003 to 2013 and Part 2 exam from 2005 to 2013. Inspection suggested that Part 1 pass rates were stable after the introduction of statistical equating, but showed greater annual variation probably due to stronger candidates taking the examination earlier. Pass rates seemed to have increased in non-UK graduates after equating was introduced, but was not associated with any changes in DIF after statistical equating. Statistical modelling of the pass rates for non-UK graduates found that pass rates, in both Part 1 and Part 2, were increasing year on year, with the changes probably beginning before the introduction of equating. The predictive validity of Part 1 for Part 2 was higher with statistical equating than with the previous hybrid Angoff/Hofstee method, confirming the utility of IRT-based statistical equating. Statistical equating was successfully introduced into the MRCP(UK) Part 1 and Part 2 written examinations, resulting in higher predictive validity than the previous Angoff/Hofstee standard setting. Concerns about an artefactual increase in pass rates for non-UK candidates after equating were shown not to be well-founded. Most likely the changes resulted from a genuine increase in candidate ability, albeit for reasons which remain unclear, coupled with a cognitive illusion giving the impression of a step-change immediately after equating began. Statistical equating provides a robust standard-setting method, with a better theoretical foundation than judgemental techniques such as Angoff, and is more straightforward and requires far less examiner time to provide a more valid result. The present study provides a detailed case study of introducing statistical equating, and issues which may need to be considered with its introduction.

Standardized Thyroid Cancer Mortality in Korea between 1985 and 2010

PubMed Central

Choi, Yun Mi; Jang, Eun Kyung; Kwon, Hyemi; Jeon, Min Ji; Kim, Won Gu; Shong, Young Kee; Kim, Won Bae

2014-01-01

Background The prevalence of thyroid cancer has increased very rapidly in Korea. However, there is no published report focusing on thyroid cancer mortality in Korea. In this study, we aimed to evaluate standardized thyroid cancer mortality using data from Statistics Korea (the Statistical Office of Korea). Methods Population and mortality data from 1985 to 2010 were obtained from Statistics Korea. Age-standardized rates of thyroid cancer mortality were calculated according to the standard population of Korea, as well as World Health Organization (WHO) standard population and International Cancer Survival Standard (ICSS) population weights. Results The crude thyroid cancer mortality rate increased from 0.1 to 0.7 per 100,000 between 1985 and 2010. The pattern was the same for both sexes. The age-standardized mortality rate (ASMR) for thyroid cancer for Korean resident registration population increased from 0.19 to 0.67 between 1985 and 2000. However, it decreased slightly, from 0.67 to 0.55, between 2000 and 2010. When mortality was adjusted using the WHO standard population and ICSS population weights, the ASMR similarly increased until 2000, and then decreased between 2000 and 2010. Conclusion Thyroid cancer mortality increased until 2000 in Korea. It started to decrease from 2000. PMID:25559576

Comparison of ambulatory blood pressure reference standards in children evaluated for hypertension

PubMed Central

Jones, Deborah P.; Richey, Phyllis A.; Alpert, Bruce S.

2009-01-01

Objective The purpose of this study was to systematically compare methods for standardization of blood pressure levels obtained by ambulatory blood pressure monitoring (ABPM) in a group of 111 children studied at our institution. Methods Blood pressure indices, blood pressure loads and standard deviation scores were calculated using he original ABPM and the modified reference standards. Bland—Altman plots and kappa statistics for the level of agreement were generated. Results Overall, the agreement between the two methods was excellent; however, approximately 5% of children were classified differently by one as compared with the other method. Conclusion Depending on which version of the German Working Group’s reference standards is used for interpretation of ABPM data, the classification of the individual as having hypertension or normal blood pressure may vary. PMID:19433980

Analysis of statistical and standard algorithms for detecting muscle onset with surface electromyography.

PubMed

Tenan, Matthew S; Tweedell, Andrew J; Haynes, Courtney A

2017-01-01

The timing of muscle activity is a commonly applied analytic method to understand how the nervous system controls movement. This study systematically evaluates six classes of standard and statistical algorithms to determine muscle onset in both experimental surface electromyography (EMG) and simulated EMG with a known onset time. Eighteen participants had EMG collected from the biceps brachii and vastus lateralis while performing a biceps curl or knee extension, respectively. Three established methods and three statistical methods for EMG onset were evaluated. Linear envelope, Teager-Kaiser energy operator + linear envelope and sample entropy were the established methods evaluated while general time series mean/variance, sequential and batch processing of parametric and nonparametric tools, and Bayesian changepoint analysis were the statistical techniques used. Visual EMG onset (experimental data) and objective EMG onset (simulated data) were compared with algorithmic EMG onset via root mean square error and linear regression models for stepwise elimination of inferior algorithms. The top algorithms for both data types were analyzed for their mean agreement with the gold standard onset and evaluation of 95% confidence intervals. The top algorithms were all Bayesian changepoint analysis iterations where the parameter of the prior (p0) was zero. The best performing Bayesian algorithms were p0 = 0 and a posterior probability for onset determination at 60-90%. While existing algorithms performed reasonably, the Bayesian changepoint analysis methodology provides greater reliability and accuracy when determining the singular onset of EMG activity in a time series. Further research is needed to determine if this class of algorithms perform equally well when the time series has multiple bursts of muscle activity.

Performance of digital RGB reflectance color extraction for plaque lesion

NASA Astrophysics Data System (ADS)

Hashim, Hadzli; Taib, Mohd Nasir; Jailani, Rozita; Sulaiman, Saadiah; Baba, Roshidah

2005-01-01

Several clinical psoriasis lesion groups are been studied for digital RGB color features extraction. Previous works have used samples size that included all the outliers lying beyond the standard deviation factors from the peak histograms. This paper described the statistical performances of the RGB model with and without removing these outliers. Plaque lesion is experimented with other types of psoriasis. The statistical tests are compared with respect to three samples size; the original 90 samples, the first size reduction by removing outliers from 2 standard deviation distances (2SD) and the second size reduction by removing outliers from 1 standard deviation distance (1SD). Quantification of data images through the normal/direct and differential of the conventional reflectance method is considered. Results performances are concluded by observing the error plots with 95% confidence interval and findings of the inference T-tests applied. The statistical tests outcomes have shown that B component for conventional differential method can be used to distinctively classify plaque from the other psoriasis groups in consistent with the error plots finding with an improvement in p-value greater than 0.5.

Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

PubMed

Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

2015-02-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A Simple Graphical Method for Quantification of Disaster Management Surge Capacity Using Computer Simulation and Process-control Tools.

PubMed

Franc, Jeffrey Michael; Ingrassia, Pier Luigi; Verde, Manuela; Colombo, Davide; Della Corte, Francesco

2015-02-01

Surge capacity, or the ability to manage an extraordinary volume of patients, is fundamental for hospital management of mass-casualty incidents. However, quantification of surge capacity is difficult and no universal standard for its measurement has emerged, nor has a standardized statistical method been advocated. As mass-casualty incidents are rare, simulation may represent a viable alternative to measure surge capacity. Hypothesis/Problem The objective of the current study was to develop a statistical method for the quantification of surge capacity using a combination of computer simulation and simple process-control statistical tools. Length-of-stay (LOS) and patient volume (PV) were used as metrics. The use of this method was then demonstrated on a subsequent computer simulation of an emergency department (ED) response to a mass-casualty incident. In the derivation phase, 357 participants in five countries performed 62 computer simulations of an ED response to a mass-casualty incident. Benchmarks for ED response were derived from these simulations, including LOS and PV metrics for triage, bed assignment, physician assessment, and disposition. In the application phase, 13 students of the European Master in Disaster Medicine (EMDM) program completed the same simulation scenario, and the results were compared to the standards obtained in the derivation phase. Patient-volume metrics included number of patients to be triaged, assigned to rooms, assessed by a physician, and disposed. Length-of-stay metrics included median time to triage, room assignment, physician assessment, and disposition. Simple graphical methods were used to compare the application phase group to the derived benchmarks using process-control statistical tools. The group in the application phase failed to meet the indicated standard for LOS from admission to disposition decision. This study demonstrates how simulation software can be used to derive values for objective benchmarks of ED surge capacity using PV and LOS metrics. These objective metrics can then be applied to other simulation groups using simple graphical process-control tools to provide a numeric measure of surge capacity. Repeated use in simulations of actual EDs may represent a potential means of objectively quantifying disaster management surge capacity. It is hoped that the described statistical method, which is simple and reusable, will be useful for investigators in this field to apply to their own research.

A risk-based statistical investigation of the quantification of polymorphic purity of a pharmaceutical candidate by solid-state 19F NMR.

PubMed

Barry, Samantha J; Pham, Tran N; Borman, Phil J; Edwards, Andrew J; Watson, Simon A

2012-01-27

The DMAIC (Define, Measure, Analyse, Improve and Control) framework and associated statistical tools have been applied to both identify and reduce variability observed in a quantitative (19)F solid-state NMR (SSNMR) analytical method. The method had been developed to quantify levels of an additional polymorph (Form 3) in batches of an active pharmaceutical ingredient (API), where Form 1 is the predominant polymorph. In order to validate analyses of the polymorphic form, a single batch of API was used as a standard each time the method was used. The level of Form 3 in this standard was observed to gradually increase over time, the effect not being immediately apparent due to method variability. In order to determine the cause of this unexpected increase and to reduce method variability, a risk-based statistical investigation was performed to identify potential factors which could be responsible for these effects. Factors identified by the risk assessment were investigated using a series of designed experiments to gain a greater understanding of the method. The increase of the level of Form 3 in the standard was primarily found to correlate with the number of repeat analyses, an effect not previously reported in SSNMR literature. Differences in data processing (phasing and linewidth) were found to be responsible for the variability in the method. After implementing corrective actions the variability was reduced such that the level of Form 3 was within an acceptable range of ±1% ww(-1) in fresh samples of API. Copyright © 2011. Published by Elsevier B.V.

Spatial Statistics for Tumor Cell Counting and Classification

NASA Astrophysics Data System (ADS)

Wirjadi, Oliver; Kim, Yoo-Jin; Breuel, Thomas

To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.

Cluster mass inference via random field theory.

PubMed

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

2009-01-01

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

Living systematic reviews: 3. Statistical methods for updating meta-analyses.

PubMed

Simmonds, Mark; Salanti, Georgia; McKenzie, Joanne; Elliott, Julian

2017-11-01

A living systematic review (LSR) should keep the review current as new research evidence emerges. Any meta-analyses included in the review will also need updating as new material is identified. If the aim of the review is solely to present the best current evidence standard meta-analysis may be sufficient, provided reviewers are aware that results may change at later updates. If the review is used in a decision-making context, more caution may be needed. When using standard meta-analysis methods, the chance of incorrectly concluding that any updated meta-analysis is statistically significant when there is no effect (the type I error) increases rapidly as more updates are performed. Inaccurate estimation of any heterogeneity across studies may also lead to inappropriate conclusions. This paper considers four methods to avoid some of these statistical problems when updating meta-analyses: two methods, that is, law of the iterated logarithm and the Shuster method control primarily for inflation of type I error and two other methods, that is, trial sequential analysis and sequential meta-analysis control for type I and II errors (failing to detect a genuine effect) and take account of heterogeneity. This paper compares the methods and considers how they could be applied to LSRs. Copyright © 2017 Elsevier Inc. All rights reserved.

Labor Productivity Standards in Texas School Foodservice Operations

ERIC Educational Resources Information Center

Sherrin, A. Rachelle; Bednar, Carolyn; Kwon, Junehee

2009-01-01

Purpose: Purpose of this research was to investigate utilization of labor productivity standards and variables that affect productivity in Texas school foodservice operations. Methods: A questionnaire was developed, validated, and pilot tested, then mailed to 200 randomly selected Texas school foodservice directors. Descriptive statistics for…

Effects of atmospheric turbulence on microwave and millimeter wave satellite communications systems. [attenuation statistics and antenna design

NASA Technical Reports Server (NTRS)

Devasirvatham, D. M. J.; Hodge, D. B.

1981-01-01

A model of the microwave and millimeter wave link in the presence of atmospheric turbulence is presented with emphasis on satellite communications systems. The analysis is based on standard methods of statistical theory. The results are directly usable by the design engineer.

Cardiac arrest risk standardization using administrative data compared to registry data.

PubMed

Grossestreuer, Anne V; Gaieski, David F; Donnino, Michael W; Nelson, Joshua I M; Mutter, Eric L; Carr, Brendan G; Abella, Benjamin S; Wiebe, Douglas J

2017-01-01

Methods for comparing hospitals regarding cardiac arrest (CA) outcomes, vital for improving resuscitation performance, rely on data collected by cardiac arrest registries. However, most CA patients are treated at hospitals that do not participate in such registries. This study aimed to determine whether CA risk standardization modeling based on administrative data could perform as well as that based on registry data. Two risk standardization logistic regression models were developed using 2453 patients treated from 2000-2015 at three hospitals in an academic health system. Registry and administrative data were accessed for all patients. The outcome was death at hospital discharge. The registry model was considered the "gold standard" with which to compare the administrative model, using metrics including comparing areas under the curve, calibration curves, and Bland-Altman plots. The administrative risk standardization model had a c-statistic of 0.891 (95% CI: 0.876-0.905) compared to a registry c-statistic of 0.907 (95% CI: 0.895-0.919). When limited to only non-modifiable factors, the administrative model had a c-statistic of 0.818 (95% CI: 0.799-0.838) compared to a registry c-statistic of 0.810 (95% CI: 0.788-0.831). All models were well-calibrated. There was no significant difference between c-statistics of the models, providing evidence that valid risk standardization can be performed using administrative data. Risk standardization using administrative data performs comparably to standardization using registry data. This methodology represents a new tool that can enable opportunities to compare hospital performance in specific hospital systems or across the entire US in terms of survival after CA.

Enhancing efficiency and quality of statistical estimation of immunogenicity assay cut points through standardization and automation.

PubMed

Su, Cheng; Zhou, Lei; Hu, Zheng; Weng, Winnie; Subramani, Jayanthi; Tadkod, Vineet; Hamilton, Kortney; Bautista, Ami; Wu, Yu; Chirmule, Narendra; Zhong, Zhandong Don

2015-10-01

Biotherapeutics can elicit immune responses, which can alter the exposure, safety, and efficacy of the therapeutics. A well-designed and robust bioanalytical method is critical for the detection and characterization of relevant anti-drug antibody (ADA) and the success of an immunogenicity study. As a fundamental criterion in immunogenicity testing, assay cut points need to be statistically established with a risk-based approach to reduce subjectivity. This manuscript describes the development of a validated, web-based, multi-tier customized assay statistical tool (CAST) for assessing cut points of ADA assays. The tool provides an intuitive web interface that allows users to import experimental data generated from a standardized experimental design, select the assay factors, run the standardized analysis algorithms, and generate tables, figures, and listings (TFL). It allows bioanalytical scientists to perform complex statistical analysis at a click of the button to produce reliable assay parameters in support of immunogenicity studies. Copyright © 2015 Elsevier B.V. All rights reserved.

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Middle school science curriculum design and 8th grade student achievement in Massachusetts public schools

NASA Astrophysics Data System (ADS)

Clifford, Betsey A.

The Massachusetts Department of Elementary and Secondary Education (DESE) released proposed Science and Technology/Engineering standards in 2013 outlining the concepts that should be taught at each grade level. Previously, standards were in grade spans and each district determined the method of implementation. There are two different methods used teaching middle school science: integrated and discipline-based. In the proposed standards, the Massachusetts DESE uses grade-by-grade standards using an integrated approach. It was not known if there is a statistically significant difference in student achievement on the 8th grade science MCAS assessment for students taught with an integrated or discipline-based approach. The results on the 8th grade science MCAS test from six public school districts from 2010 -- 2013 were collected and analyzed. The methodology used was quantitative. Results of an ANOVA showed that there was no statistically significant difference in overall student achievement between the two curriculum models. Furthermore, there was no statistically significant difference for the various domains: Earth and Space Science, Life Science, Physical Science, and Technology/Engineering. This information is useful for districts hesitant to make the change from a discipline-based approach to an integrated approach. More research should be conducted on this topic with a larger sample size to better support the results.

Comparative study of some robust statistical methods: weighted, parametric, and nonparametric linear regression of HPLC convoluted peak responses using internal standard method in drug bioavailability studies.

PubMed

Korany, Mohamed A; Maher, Hadir M; Galal, Shereen M; Ragab, Marwa A A

2013-05-01

This manuscript discusses the application and the comparison between three statistical regression methods for handling data: parametric, nonparametric, and weighted regression (WR). These data were obtained from different chemometric methods applied to the high-performance liquid chromatography response data using the internal standard method. This was performed on a model drug Acyclovir which was analyzed in human plasma with the use of ganciclovir as internal standard. In vivo study was also performed. Derivative treatment of chromatographic response ratio data was followed by convolution of the resulting derivative curves using 8-points sin x i polynomials (discrete Fourier functions). This work studies and also compares the application of WR method and Theil's method, a nonparametric regression (NPR) method with the least squares parametric regression (LSPR) method, which is considered the de facto standard method used for regression. When the assumption of homoscedasticity is not met for analytical data, a simple and effective way to counteract the great influence of the high concentrations on the fitted regression line is to use WR method. WR was found to be superior to the method of LSPR as the former assumes that the y-direction error in the calibration curve will increase as x increases. Theil's NPR method was also found to be superior to the method of LSPR as the former assumes that errors could occur in both x- and y-directions and that might not be normally distributed. Most of the results showed a significant improvement in the precision and accuracy on applying WR and NPR methods relative to LSPR.

Standardization, evaluation and early-phase method validation of an analytical scheme for batch-consistency N-glycosylation analysis of recombinant produced glycoproteins.

PubMed

Zietze, Stefan; Müller, Rainer H; Brecht, René

2008-03-01

In order to set up a batch-to-batch-consistency analytical scheme for N-glycosylation analysis, several sample preparation steps including enzyme digestions and fluorophore labelling and two HPLC-methods were established. The whole method scheme was standardized, evaluated and validated according to the requirements on analytical testing in early clinical drug development by usage of a recombinant produced reference glycoprotein (RGP). The standardization of the methods was performed by clearly defined standard operation procedures. During evaluation of the methods, the major interest was in the loss determination of oligosaccharides within the analytical scheme. Validation of the methods was performed with respect to specificity, linearity, repeatability, LOD and LOQ. Due to the fact that reference N-glycan standards were not available, a statistical approach was chosen to derive accuracy from the linearity data. After finishing the validation procedure, defined limits for method variability could be calculated and differences observed in consistency analysis could be separated into significant and incidental ones.

Avoid lost discoveries, because of violations of standard assumptions, by using modern robust statistical methods.

PubMed

Wilcox, Rand; Carlson, Mike; Azen, Stan; Clark, Florence

2013-03-01

Recently, there have been major advances in statistical techniques for assessing central tendency and measures of association. The practical utility of modern methods has been documented extensively in the statistics literature, but they remain underused and relatively unknown in clinical trials. Our objective was to address this issue. STUDY DESIGN AND PURPOSE: The first purpose was to review common problems associated with standard methodologies (low power, lack of control over type I errors, and incorrect assessments of the strength of the association). The second purpose was to summarize some modern methods that can be used to circumvent such problems. The third purpose was to illustrate the practical utility of modern robust methods using data from the Well Elderly 2 randomized controlled trial. In multiple instances, robust methods uncovered differences among groups and associations among variables that were not detected by classic techniques. In particular, the results demonstrated that details of the nature and strength of the association were sometimes overlooked when using ordinary least squares regression and Pearson correlation. Modern robust methods can make a practical difference in detecting and describing differences between groups and associations between variables. Such procedures should be applied more frequently when analyzing trial-based data. Copyright © 2013 Elsevier Inc. All rights reserved.

Atmospheric pollution measurement by optical cross correlation methods - A concept

NASA Technical Reports Server (NTRS)

Fisher, M. J.; Krause, F. R.

1971-01-01

Method combines standard spectroscopy with statistical cross correlation analysis of two narrow light beams for remote sensing to detect foreign matter of given particulate size and consistency. Method is applicable in studies of generation and motion of clouds, nuclear debris, ozone, and radiation belts.

Effect of CorrelatedRotational Noise

NASA Astrophysics Data System (ADS)

Hancock, Benjamin; Wagner, Caleb; Baskaran, Aparna

The traditional model of a self-propelled particle (SPP) is one where the body axis along which the particle travels reorients itself through rotational diffusion. If the reorientation process was driven by colored noise, instead of the standard Gaussian white noise, the resulting statistical mechanics cannot be accessed through conventional methods. In this talk we present results comparing three methods of deriving the statistical mechanics of a SPP with a reorientation process driven by colored noise. We illustrate the differences/similarities in the resulting statistical mechanics by their ability to accurately capture the particles response to external aligning fields.

Time-of-Flight Measurements as a Possible Method to Observe Anyonic Statistics

NASA Astrophysics Data System (ADS)

Umucalılar, R. O.; Macaluso, E.; Comparin, T.; Carusotto, I.

2018-06-01

We propose a standard time-of-flight experiment as a method for observing the anyonic statistics of quasiholes in a fractional quantum Hall state of ultracold atoms. The quasihole states can be stably prepared by pinning the quasiholes with localized potentials and a measurement of the mean square radius of the freely expanding cloud, which is related to the average total angular momentum of the initial state, offers direct signatures of the statistical phase. Our proposed method is validated by Monte Carlo calculations for ν =1 /2 and 1 /3 fractional quantum Hall liquids containing a realistic number of particles. Extensions to quantum Hall liquids of light and to non-Abelian anyons are briefly discussed.

Comparison of ambulatory blood pressure reference standards in children evaluated for hypertension.

PubMed

Jones, Deborah P; Richey, Phyllis A; Alpert, Bruce S

2009-06-01

The purpose of this study was to systematically compare methods for standardization of blood pressure levels obtained by ambulatory blood pressure monitoring (ABPM) in a group of 111 children studied at our institution. Blood pressure indices, blood pressure loads and standard deviation scores were calculated using the original ABPM and the modified reference standards. Bland-Altman plots and kappa statistics for the level of agreement were generated. Overall, the agreement between the two methods was excellent; however, approximately 5% of children were classified differently by one as compared with the other method. Depending on which version of the German Working Group's reference standards is used for interpretation of ABPM data, the classification of the individual as having hypertension or normal blood pressure may vary.

Analysis of statistical and standard algorithms for detecting muscle onset with surface electromyography

PubMed Central

Tweedell, Andrew J.; Haynes, Courtney A.

2017-01-01

The timing of muscle activity is a commonly applied analytic method to understand how the nervous system controls movement. This study systematically evaluates six classes of standard and statistical algorithms to determine muscle onset in both experimental surface electromyography (EMG) and simulated EMG with a known onset time. Eighteen participants had EMG collected from the biceps brachii and vastus lateralis while performing a biceps curl or knee extension, respectively. Three established methods and three statistical methods for EMG onset were evaluated. Linear envelope, Teager-Kaiser energy operator + linear envelope and sample entropy were the established methods evaluated while general time series mean/variance, sequential and batch processing of parametric and nonparametric tools, and Bayesian changepoint analysis were the statistical techniques used. Visual EMG onset (experimental data) and objective EMG onset (simulated data) were compared with algorithmic EMG onset via root mean square error and linear regression models for stepwise elimination of inferior algorithms. The top algorithms for both data types were analyzed for their mean agreement with the gold standard onset and evaluation of 95% confidence intervals. The top algorithms were all Bayesian changepoint analysis iterations where the parameter of the prior (p0) was zero. The best performing Bayesian algorithms were p0 = 0 and a posterior probability for onset determination at 60–90%. While existing algorithms performed reasonably, the Bayesian changepoint analysis methodology provides greater reliability and accuracy when determining the singular onset of EMG activity in a time series. Further research is needed to determine if this class of algorithms perform equally well when the time series has multiple bursts of muscle activity. PMID:28489897

AN EMPIRICAL BAYES APPROACH TO COMBINING ESTIMATES OF THE VALUE OF A STATISTICAL LIFE FOR ENVIRONMENTAL POLICY ANALYSIS

EPA Science Inventory

This analysis updates EPA's standard VSL estimate by using a more comprehensive collection of VSL studies that include studies published between 1992 and 2000, as well as applying a more appropriate statistical method. We provide a pooled effect VSL estimate by applying the empi...

Estimation of selected streamflow statistics for a network of low-flow partial-record stations in areas affected by Base Realignment and Closure (BRAC) in Maryland

USGS Publications Warehouse

Ries, Kernell G.; Eng, Ken

2010-01-01

The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment, operated a network of 20 low-flow partial-record stations during 2008 in a region that extends from southwest of Baltimore to the northeastern corner of Maryland to obtain estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of new residents and businesses as a result of military and civilian personnel transfers associated with the Federal Base Realignment and Closure Act of 2005. The estimated streamflow statistics, which include monthly 85-percent duration flows, the 10-year recurrence-interval minimum base flow, and the 7-day, 10-year low flow, are needed to provide a better understanding of the availability of water resources in the area to be affected by base-realignment activities. Streamflow measurements collected for this study at the low-flow partial-record stations and measurements collected previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the streamflow statistics. Three methods were used to estimate the streamflow statistics and two methods were used to select the index streamgages. Of the three methods used to estimate the streamflow statistics, two of them--the Moments and MOVE1 methods--rely on correlating the streamflow measurements at the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to determine the estimates. These methods, recommended for use by the U.S. Geological Survey, generally require about 10 streamflow measurements at the low-flow partial-record station. The third method transfers the streamflow statistics from the index streamgage to the partial-record station based on the average of the ratios of the measured streamflows at the partial-record station to the concurrent streamflows at the index streamgage. This method can be used with as few as one pair of streamflow measurements made on a single streamflow recession at the low-flow partial-record station, although additional pairs of measurements will increase the accuracy of the estimates. Errors associated with the two correlation methods generally were lower than the errors associated with the flow-ratio method, but the advantages of the flow-ratio method are that it can produce reasonably accurate estimates from streamflow measurements much faster and at lower cost than estimates obtained using the correlation methods. The two index-streamgage selection methods were (1) selection based on the highest correlation coefficient between the low-flow partial-record station and the index streamgages, and (2) selection based on Euclidean distance, where the Euclidean distance was computed as a function of geographic proximity and the basin characteristics: drainage area, percentage of forested area, percentage of impervious area, and the base-flow recession time constant, t. Method 1 generally selected index streamgages that were significantly closer to the low-flow partial-record stations than method 2. The errors associated with the estimated streamflow statistics generally were lower for method 1 than for method 2, but the differences were not statistically significant. The flow-ratio method for estimating streamflow statistics at low-flow partial-record stations was shown to be independent from the two correlation-based estimation methods. As a result, final estimates were determined for eight low-flow partial-record stations by weighting estimates from the flow-ratio method with estimates from one of the two correlation methods according to the respective variances of the estimates. Average standard errors of estimate for the final estimates ranged from 90.0 to 7.0 percent, with an average value of 26.5 percent. Average standard errors of estimate for the weighted estimates were, on average, 4.3 percent less than the best average standard errors of estima

Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development

NASA Astrophysics Data System (ADS)

Ghannadpour, Seyyed Saeed; Hezarkhani, Ardeshir

2016-03-01

The U-statistic method is one of the most important structural methods to separate the anomaly from the background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, to use U-statistic method in three-dimensional (3D) condition, U-statistic is applied on the grade of two ideal test examples, by considering sample Z values (elevation). So far, this is the first time that this method has been applied on a 3D condition. To evaluate the performance of 3D U-statistic method and in order to compare U-statistic with one non-structural method, the method of threshold assessment based on median and standard deviation (MSD method) is applied on the two example tests. Results show that the samples indicated by U-statistic method as anomalous are more regular and involve less dispersion than those indicated by the MSD method. So that, according to the location of anomalous samples, denser areas of them can be determined as promising zones. Moreover, results show that at a threshold of U = 0, the total error of misclassification for U-statistic method is much smaller than the total error of criteria of bar {x}+n× s. Finally, 3D model of two test examples for separating anomaly from background using 3D U-statistic method is provided. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the 3D U-spatial statistic method, is additionally provided. This software is compatible with all the geochemical varieties and can be used in similar exploration projects.

A multi-time-step noise reduction method for measuring velocity statistics from particle tracking velocimetry

NASA Astrophysics Data System (ADS)

Machicoane, Nathanaël; López-Caballero, Miguel; Bourgoin, Mickael; Aliseda, Alberto; Volk, Romain

2017-10-01

We present a method to improve the accuracy of velocity measurements for fluid flow or particles immersed in it, based on a multi-time-step approach that allows for cancellation of noise in the velocity measurements. Improved velocity statistics, a critical element in turbulent flow measurements, can be computed from the combination of the velocity moments computed using standard particle tracking velocimetry (PTV) or particle image velocimetry (PIV) techniques for data sets that have been collected over different values of time intervals between images. This method produces Eulerian velocity fields and Lagrangian velocity statistics with much lower noise levels compared to standard PIV or PTV measurements, without the need of filtering and/or windowing. Particle displacement between two frames is computed for multiple different time-step values between frames in a canonical experiment of homogeneous isotropic turbulence. The second order velocity structure function of the flow is computed with the new method and compared to results from traditional measurement techniques in the literature. Increased accuracy is also demonstrated by comparing the dissipation rate of turbulent kinetic energy measured from this function against previously validated measurements.

Quality Control of the Print with the Application of Statistical Methods

NASA Astrophysics Data System (ADS)

Simonenko, K. V.; Bulatova, G. S.; Antropova, L. B.; Varepo, L. G.

2018-04-01

The basis for standardizing the process of offset printing is the control of print quality indicators. The solution of this problem has various approaches, among which the most important are statistical methods. Practical implementation of them for managing the quality of the printing process is very relevant and is reflected in this paper. The possibility of using the method of constructing a Control Card to identify the reasons for the deviation of the optical density for a triad of inks in offset printing is shown.

Statistical analysis of activation and reaction energies with quasi-variational coupled-cluster theory

NASA Astrophysics Data System (ADS)

Black, Joshua A.; Knowles, Peter J.

2018-06-01

The performance of quasi-variational coupled-cluster (QV) theory applied to the calculation of activation and reaction energies has been investigated. A statistical analysis of results obtained for six different sets of reactions has been carried out, and the results have been compared to those from standard single-reference methods. In general, the QV methods lead to increased activation energies and larger absolute reaction energies compared to those obtained with traditional coupled-cluster theory.

20 CFR 634.4 - Statistical standards.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false Statistical standards. 634.4 Section 634.4... System § 634.4 Statistical standards. Recipients shall agree to provide required data following the statistical standards prescribed by the Bureau of Labor Statistics for cooperative statistical programs. ...

20 CFR 634.4 - Statistical standards.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Statistical standards. 634.4 Section 634.4... System § 634.4 Statistical standards. Recipients shall agree to provide required data following the statistical standards prescribed by the Bureau of Labor Statistics for cooperative statistical programs. ...

Appraisal of within- and between-laboratory reproducibility of non-radioisotopic local lymph node assay using flow cytometry, LLNA:BrdU-FCM: comparison of OECD TG429 performance standard and statistical evaluation.

PubMed

Yang, Hyeri; Na, Jihye; Jang, Won-Hee; Jung, Mi-Sook; Jeon, Jun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Lim, Kyung-Min; Bae, SeungJin

2015-05-05

Mouse local lymph node assay (LLNA, OECD TG429) is an alternative test replacing conventional guinea pig tests (OECD TG406) for the skin sensitization test but the use of a radioisotopic agent, (3)H-thymidine, deters its active dissemination. New non-radioisotopic LLNA, LLNA:BrdU-FCM employs a non-radioisotopic analog, 5-bromo-2'-deoxyuridine (BrdU) and flow cytometry. For an analogous method, OECD TG429 performance standard (PS) advises that two reference compounds be tested repeatedly and ECt(threshold) values obtained must fall within acceptable ranges to prove within- and between-laboratory reproducibility. However, this criteria is somewhat arbitrary and sample size of ECt is less than 5, raising concerns about insufficient reliability. Here, we explored various statistical methods to evaluate the reproducibility of LLNA:BrdU-FCM with stimulation index (SI), the raw data for ECt calculation, produced from 3 laboratories. Descriptive statistics along with graphical representation of SI was presented. For inferential statistics, parametric and non-parametric methods were applied to test the reproducibility of SI of a concurrent positive control and the robustness of results were investigated. Descriptive statistics and graphical representation of SI alone could illustrate the within- and between-laboratory reproducibility. Inferential statistics employing parametric and nonparametric methods drew similar conclusion. While all labs passed within- and between-laboratory reproducibility criteria given by OECD TG429 PS based on ECt values, statistical evaluation based on SI values showed that only two labs succeeded in achieving within-laboratory reproducibility. For those two labs that satisfied the within-lab reproducibility, between-laboratory reproducibility could be also attained based on inferential as well as descriptive statistics. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of trauma care using TRISS method: the role of adjusted misclassification rate and adjusted w-statistic.

PubMed

Llullaku, Sadik S; Hyseni, Nexhmi Sh; Bytyçi, Cen I; Rexhepi, Sylejman K

2009-01-15

Major trauma is a leading cause of death worldwide. Evaluation of trauma care using Trauma Injury and Injury Severity Score (TRISS) method is focused in trauma outcome (deaths and survivors). For testing TRISS method TRISS misclassification rate is used. Calculating w-statistic, as a difference between observed and TRISS expected survivors, we compare our trauma care results with the TRISS standard. The aim of this study is to analyze interaction between misclassification rate and w-statistic and to adjust these parameters to be closer to the truth. Analysis of components of TRISS misclassification rate and w-statistic and actual trauma outcome. The component of false negative (FN) (by TRISS method unexpected deaths) has two parts: preventable (Pd) and non-preventable (nonPd) trauma deaths. Pd represents inappropriate trauma care of an institution; otherwise nonpreventable trauma deaths represents errors in TRISS method. Removing patients with preventable trauma deaths we get an Adjusted misclassification rate: (FP + FN - Pd)/N or (b+c-Pd)/N. Substracting nonPd from FN value in w-statistic formula we get an Adjusted w-statistic: [FP-(FN - nonPd)]/N, respectively (FP-Pd)/N, or (b-Pd)/N). Because adjusted formulas clean method from inappropriate trauma care, and clean trauma care from the methods error, TRISS adjusted misclassification rate and adjusted w-statistic gives more realistic results and may be used in researches of trauma outcome.

Trends in incidence of lung cancer in Croatia from 2001 to 2013: gender and regional differences

PubMed Central

Siroglavić, Katarina-Josipa; Polić Vižintin, Marina; Tripković, Ingrid; Šekerija, Mario; Kukulj, Suzana

2017-01-01

Aim To provide an overview of the lung cancer incidence trends in the City of Zagreb (Zagreb), Split-Dalmatia County (SDC), and Croatia in the period from 2001 to 2013. Method Incidence data were obtained from the Croatian National Cancer Registry. For calculating incidence rates per 100 000 population, we used population estimates for the period 2001-2013 from the Croatian Bureau of Statistics. Age-standardized rates of lung cancer incidence were calculated by the direct standardization method using the European Standard Population. To describe incidence trends, we used joinpoint regression analysis. Results Joinpoint analysis showed a statistically significant decrease in lung cancer incidence in men in all regions, with an annual percentage change (APC) of -2.2% for Croatia, 1.9% for Zagreb, and -2.0% for SDC. In women, joinpoint analysis showed a statistically significant increase in the incidence for Croatia, with APC of 1.4%, a statistically significant increase of 1.0% for Zagreb, and no significant change in trend for SDC. In both genders, joinpoint analysis showed a significant decrease in age-standardized incidence rates of lung cancer, with APC of -1.3% for Croatia, -1.1% for Zagreb, and -1.6% for SDC. Conclusion There was an increase in female lung cancer incidence rate and a decrease in male lung cancer incidence rate in Croatia in 2001-20013 period, with similar patterns observed in all the investigated regions. These results highlight the importance of smoking prevention and cessation policies, especially among women and young people. PMID:29094814

Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study

PubMed Central

Nour-Eldein, Hebatallah

2016-01-01

Background: With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. Objectives: To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. Methods: This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Results: Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Conclusion: Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles. PMID:27453839

Statistical analysis of radioimmunoassay. In comparison with bioassay (in Japanese)

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

Nakano, R.

1973-01-01

Using the data of RIA (radioimmunoassay), statistical procedures for dealing with two problems of the linearization of dose response curve and calculation of relative potency were described. There were three methods for linearization of dose response curve of RIA. In each method, the following parameters were shown on the horizontal and vertical axis: dose x, (B/T)/sup -1/; c/x + c, B/T (C: dose which makes B/T 50%); log x, logit B/T. Among them, the last method seems to be most practical. The statistical procedures for bioassay were employed for calculating the relative potency of unknown samples compared to the standardmore » samples from dose response curves of standand and unknown samples using regression coefficient. It is desirable that relative potency is calculated by plotting more than 5 points in the standard curve and plotting more than 2 points in unknow samples. For examining the statistical limit of precision of measuremert, LH activity of gonadotropin in urine was measured and relative potency, precision coefficient and the upper and lower limits of relative potency at 95% confidence limit were calculated. On the other hand, bioassay (by the ovarian ascorbic acid reduction method and anteriol lobe of prostate weighing method) was done in the same samples, and the precision was compared with that of RIA. In these examinations, the upper and lower limits of the relative potency at 95% confidence limit were near each other, while in bioassay, a considerable difference was observed between the upper and lower limits. The necessity of standardization and systematization of the statistical procedures for increasing the precision of RIA was pointed out. (JA)« less

How Does One Assess the Accuracy of Academic Success Predictors? ROC Analysis Applied to University Entrance Factors

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

This article attempts to present a novel application of a method of measuring accuracy for academic success predictors that could be used as a standard. This procedure is known as the receiver operating characteristic (ROC) curve, which comes from statistical decision techniques. The statistical prediction techniques provide predictor models and…

Determining the Number of Component Clusters in the Standard Multivariate Normal Mixture Model Using Model-Selection Criteria.

DTIC Science & Technology

1983-06-16

has been advocated by Gnanadesikan and 𔃾ilk (1969), and others in the literature. This suggests that, if we use the formal signficance test type...American Statistical Asso., 62, 1159-1178. Gnanadesikan , R., and Wilk, M..B. (1969). Data Analytic Methods in Multi- variate Statistical Analysis. In

The Adequacy of Different Robust Statistical Tests in Comparing Two Independent Groups

ERIC Educational Resources Information Center

Pero-Cebollero, Maribel; Guardia-Olmos, Joan

2013-01-01

In the current study, we evaluated various robust statistical methods for comparing two independent groups. Two scenarios for simulation were generated: one of equality and another of population mean differences. In each of the scenarios, 33 experimental conditions were used as a function of sample size, standard deviation and asymmetry. For each…

The role of ultrasound guidance in pediatric caudal block

PubMed Central

Erbüyün, Koray; Açıkgöz, Barış; Ok, Gülay; Yılmaz, Ömer; Temeltaş, Gökhan; Tekin, İdil; Tok, Demet

2016-01-01

Objectives: To compare the time interval of the procedure, possible complications, post-operative pain levels, additional analgesics, and nurse satisfaction in ultrasonography-guided and standard caudal block applications. Methods: This retrospective study was conducted in Celal Bayar University Hospital, Manisa, Turkey, between January and December 2014, included 78 pediatric patients. Caudal block was applied to 2 different groups; one with ultrasound guide, and the other using the standard method. Results: The time interval of the procedure was significantly shorter in the standard application group compared with ultrasound-guided group (p=0.020). Wong-Baker FACES Pain Rating Scale values obtained at the 90th minute was statistically lower in the standard application group compared with ultrasound-guided group (p=0.035). No statistically significant difference was found on the other parameters between the 2 groups. The shorter time interval of the procedure at standard application group should not be considered as a distinctive mark by the pediatric anesthesiologists, because this time difference was as short as seconds. Conclusion: Ultrasound guidance for caudal block applications would neither increase nor decrease the success of the treatment. However, ultrasound guidance should be needed in cases where the detection of sacral anatomy is difficult, especially by palpations. PMID:26837396

A Tool for Estimating Variability in Wood Preservative Treatment Retention

Treesearch

Patricia K. Lebow; Adam M. Taylor; Timothy M. Young

2015-01-01

Composite sampling is standard practice for evaluation of preservative retention levels in preservative-treated wood. Current protocols provide an average retention value but no estimate of uncertainty. Here we describe a statistical method for calculating uncertainty estimates using the standard sampling regime with minimal additional chemical analysis. This tool can...

Tests of Alignment among Assessment, Standards, and Instruction Using Generalized Linear Model Regression

ERIC Educational Resources Information Center

Fulmer, Gavin W.; Polikoff, Morgan S.

2014-01-01

An essential component in school accountability efforts is for assessments to be well-aligned with the standards or curriculum they are intended to measure. However, relatively little prior research has explored methods to determine statistical significance of alignment or misalignment. This study explores analyses of alignment as a special case…

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Standardisation of a European measurement method for organic carbon and elemental carbon in ambient air: results of the field trial campaign and the determination of a measurement uncertainty and working range.

PubMed

Brown, Richard J C; Beccaceci, Sonya; Butterfield, David M; Quincey, Paul G; Harris, Peter M; Maggos, Thomas; Panteliadis, Pavlos; John, Astrid; Jedynska, Aleksandra; Kuhlbusch, Thomas A J; Putaud, Jean-Philippe; Karanasiou, Angeliki

2017-10-18

The European Committee for Standardisation (CEN) Technical Committee 264 'Air Quality' has recently produced a standard method for the measurements of organic carbon and elemental carbon in PM 2.5 within its working group 35 in response to the requirements of European Directive 2008/50/EC. It is expected that this method will be used in future by all Member States making measurements of the carbonaceous content of PM 2.5 . This paper details the results of a laboratory and field measurement campaign and the statistical analysis performed to validate the standard method, assess its uncertainty and define its working range to provide clarity and confidence in the underpinning science for future users of the method. The statistical analysis showed that the expanded combined uncertainty for transmittance protocol measurements of OC, EC and TC is expected to be below 25%, at the 95% level of confidence, above filter loadings of 2 μg cm -2 . An estimation of the detection limit of the method for total carbon was 2 μg cm -2 . As a result of the laboratory and field measurement campaign the EUSAAR2 transmittance measurement protocol was chosen as the basis of the standard method EN 16909:2017.

Boosting Bayesian parameter inference of stochastic differential equation models with methods from statistical physics

NASA Astrophysics Data System (ADS)

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Measured time-series of both precipitation and runoff are known to exhibit highly non-trivial statistical properties. For making reliable probabilistic predictions in hydrology, it is therefore desirable to have stochastic models with output distributions that share these properties. When parameters of such models have to be inferred from data, we also need to quantify the associated parametric uncertainty. For non-trivial stochastic models, however, this latter step is typically very demanding, both conceptually and numerically, and always never done in hydrology. Here, we demonstrate that methods developed in statistical physics make a large class of stochastic differential equation (SDE) models amenable to a full-fledged Bayesian parameter inference. For concreteness we demonstrate these methods by means of a simple yet non-trivial toy SDE model. We consider a natural catchment that can be described by a linear reservoir, at the scale of observation. All the neglected processes are assumed to happen at much shorter time-scales and are therefore modeled with a Gaussian white noise term, the standard deviation of which is assumed to scale linearly with the system state (water volume in the catchment). Even for constant input, the outputs of this simple non-linear SDE model show a wealth of desirable statistical properties, such as fat-tailed distributions and long-range correlations. Standard algorithms for Bayesian inference fail, for models of this kind, because their likelihood functions are extremely high-dimensional intractable integrals over all possible model realizations. The use of Kalman filters is illegitimate due to the non-linearity of the model. Particle filters could be used but become increasingly inefficient with growing number of data points. Hamiltonian Monte Carlo algorithms allow us to translate this inference problem to the problem of simulating the dynamics of a statistical mechanics system and give us access to most sophisticated methods that have been developed in the statistical physics community over the last few decades. We demonstrate that such methods, along with automated differentiation algorithms, allow us to perform a full-fledged Bayesian inference, for a large class of SDE models, in a highly efficient and largely automatized manner. Furthermore, our algorithm is highly parallelizable. For our toy model, discretized with a few hundred points, a full Bayesian inference can be performed in a matter of seconds on a standard PC.

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…

Development of a statistical method to help evaluating the transparency/opacity of decorative thin films

NASA Astrophysics Data System (ADS)

da Silva Oliveira, C. I.; Martinez-Martinez, D.; Al-Rjoub, A.; Rebouta, L.; Menezes, R.; Cunha, L.

2018-04-01

In this paper, we present a statistical method that allows evaluating the degree of a transparency of a thin film. To do so, the color coordinates are measured on different substrates, and the standard deviation is evaluated. In case of low values, the color depends on the film and not on the substrate, and intrinsic colors are obtained. In contrast, transparent films lead to high values of standard deviation, since the value of the color coordinates depends on the substrate. Between both extremes, colored films with a certain degree of transparency can be found. This method allows an objective and simple evaluation of the transparency of any film, improving the subjective visual inspection and avoiding the thickness problems related to optical spectroscopy evaluation. Zirconium oxynitride films deposited on three different substrates (Si, steel and glass) are used for testing the validity of this method, whose results have been validated with optical spectroscopy, and agree with the visual impression of the samples.

Delay, change and bifurcation of the immunofluorescence distribution attractors in health statuses diagnostics and in medical treatment

NASA Astrophysics Data System (ADS)

Galich, Nikolay E.; Filatov, Michael V.

2008-07-01

Communication contains the description of the immunology experiments and the experimental data treatment. New nonlinear methods of immunofluorescence statistical analysis of peripheral blood neutrophils have been developed. We used technology of respiratory burst reaction of DNA fluorescence in the neutrophils cells nuclei due to oxidative activity. The histograms of photon count statistics the radiant neutrophils populations' in flow cytometry experiments are considered. Distributions of the fluorescence flashes frequency as functions of the fluorescence intensity are analyzed. Statistic peculiarities of histograms set for healthy and unhealthy donors allow dividing all histograms on the three classes. The classification is based on three different types of smoothing and long-range scale averaged immunofluorescence distributions and their bifurcation. Heterogeneity peculiarities of long-range scale immunofluorescence distributions allow dividing all histograms on three groups. First histograms group belongs to healthy donors. Two other groups belong to donors with autoimmune and inflammatory diseases. Some of the illnesses are not diagnosed by standards biochemical methods. Medical standards and statistical data of the immunofluorescence histograms for identifications of health and illnesses are interconnected. Possibilities and alterations of immunofluorescence statistics in registration, diagnostics and monitoring of different diseases in various medical treatments have been demonstrated. Health or illness criteria are connected with statistics features of immunofluorescence histograms. Neutrophils populations' fluorescence presents the sensitive clear indicator of health status.

Variations of attractors and wavelet spectra of the immunofluorescence distributions for women in the pregnant period

NASA Astrophysics Data System (ADS)

Galich, Nikolay E.

2008-07-01

Communication contains the description of the immunology data treatment. New nonlinear methods of immunofluorescence statistical analysis of peripheral blood neutrophils have been developed. We used technology of respiratory burst reaction of DNA fluorescence in the neutrophils cells nuclei due to oxidative activity. The histograms of photon count statistics the radiant neutrophils populations' in flow cytometry experiments are considered. Distributions of the fluorescence flashes frequency as functions of the fluorescence intensity are analyzed. Statistic peculiarities of histograms set for women in the pregnant period allow dividing all histograms on the three classes. The classification is based on three different types of smoothing and long-range scale averaged immunofluorescence distributions, their bifurcation and wavelet spectra. Heterogeneity peculiarities of long-range scale immunofluorescence distributions and peculiarities of wavelet spectra allow dividing all histograms on three groups. First histograms group belongs to healthy donors. Two other groups belong to donors with autoimmune and inflammatory diseases. Some of the illnesses are not diagnosed by standards biochemical methods. Medical standards and statistical data of the immunofluorescence histograms for identifications of health and illnesses are interconnected. Peculiarities of immunofluorescence for women in pregnant period are classified. Health or illness criteria are connected with statistics features of immunofluorescence histograms. Neutrophils populations' fluorescence presents the sensitive clear indicator of health status.

[Establishment of the mathematic model of total quantum statistical moment standard similarity for application to medical theoretical research].

PubMed

He, Fu-yuan; Deng, Kai-wen; Huang, Sheng; Liu, Wen-long; Shi, Ji-lian

2013-09-01

The paper aims to elucidate and establish a new mathematic model: the total quantum statistical moment standard similarity (TQSMSS) on the base of the original total quantum statistical moment model and to illustrate the application of the model to medical theoretical research. The model was established combined with the statistical moment principle and the normal distribution probability density function properties, then validated and illustrated by the pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical method for them, and by analysis of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving the Buyanghanwu-decoction extract. The established model consists of four mainly parameters: (1) total quantum statistical moment similarity as ST, an overlapped area by two normal distribution probability density curves in conversion of the two TQSM parameters; (2) total variability as DT, a confidence limit of standard normal accumulation probability which is equal to the absolute difference value between the two normal accumulation probabilities within integration of their curve nodical; (3) total variable probability as 1-Ss, standard normal distribution probability within interval of D(T); (4) total variable probability (1-beta)alpha and (5) stable confident probability beta(1-alpha): the correct probability to make positive and negative conclusions under confident coefficient alpha. With the model, we had analyzed the TQSMS similarities of pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical methods for them were at range of 0.3852-0.9875 that illuminated different pharmacokinetic behaviors of each other; and the TQSMS similarities (ST) of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving Buyanghuanwu-decoction-extract were at range of 0.6842-0.999 2 that showed different constituents with various solvent extracts. The TQSMSS can characterize the sample similarity, by which we can quantitate the correct probability with the test of power under to make positive and negative conclusions no matter the samples come from same population under confident coefficient a or not, by which we can realize an analysis at both macroscopic and microcosmic levels, as an important similar analytical method for medical theoretical research.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Validating Coherence Measurements Using Aligned and Unaligned Coherence Functions

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2006-01-01

This paper describes a novel approach based on the use of coherence functions and statistical theory for sensor validation in a harsh environment. By the use of aligned and unaligned coherence functions and statistical theory one can test for sensor degradation, total sensor failure or changes in the signal. This advanced diagnostic approach and the novel data processing methodology discussed provides a single number that conveys this information. This number as calculated with standard statistical procedures for comparing the means of two distributions is compared with results obtained using Yuen's robust statistical method to create confidence intervals. Examination of experimental data from Kulite pressure transducers mounted in a Pratt & Whitney PW4098 combustor using spectrum analysis methods on aligned and unaligned time histories has verified the effectiveness of the proposed method. All the procedures produce good results which demonstrates how robust the technique is.

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Rolling Bearing Life Prediction-Past, Present, and Future

NASA Technical Reports Server (NTRS)

Zaretsky, E V; Poplawski, J. V.; Miller, C. R.

2000-01-01

Comparisons were made between the life prediction formulas of Lundberg and Palmgren, Ioannides and Harris, and Zaretsky and full-scale ball and roller bearing life data. The effect of Weibull slope on bearing life prediction was determined. Life factors are proposed to adjust the respective life formulas to the normalized statistical life distribution of each bearing type. The Lundberg-Palmgren method resulted in the most conservative life predictions compared to Ioannides and Harris, and Zaretsky methods which produced statistically similar results. Roller profile can have significant effects on bearing life prediction results. Roller edge loading can reduce life by as much as 98 percent. The resultant predicted life not only depends on the life equation used but on the Weibull slope assumed, the least variation occurring with the Zaretsky equation. The load-life exponent p of 10/3 used in the American National Standards Institute (ANSI)/American Bearing Manufacturers Association (ABMA)/International Organization for Standardization (ISO) standards is inconsistent with the majority roller bearings designed and used today.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

Statistical tools for transgene copy number estimation based on real-time PCR.

PubMed

Yuan, Joshua S; Burris, Jason; Stewart, Nathan R; Mentewab, Ayalew; Stewart, C Neal

2007-11-01

As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. Three experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination. These statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Surface microbial contamination in hospitals: A pilot study on methods of sampling and the use of proposed microbiologic standards.

PubMed

Claro, Tânia; O'Reilly, Marese; Daniels, Stephen; Humphreys, Hilary

2015-09-01

Contamination of hospital surfaces by bacteria is increasingly recognized. We assessed commonly touched surfaces using contact plates and Petrifilms (3M, St. Paul, MN) and compared the results against proposed microbiology standards. Toilet door handles were the most heavily contaminated (7.97 ± 0.68 colony forming units [CFU]/cm(2)) and exceeded proposed standards on 74% of occasions. Petrifilms detected statistically higher CFU from bedside lockers. Further research is required on the use of standards and methods of sampling. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Statistical/Documentary Report, 1974 and 1975 Assessments of 17-Year-Old Students, Summary Volume; Functional Literacy Basic Reading Performance.

ERIC Educational Resources Information Center

Gadway, Charles J.; Wilson, H.A.

This document provides statistical data on the 1974 and 1975 Mini-Assessment of Functional Literacy, which was designed to determine the extent of functional literacy among seventeen year olds in America. Also presented are data from comparable test items from the 1971 assessment. Three standards are presented, to allow different methods of…

Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

ERIC Educational Resources Information Center

Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

Alternative Internal Standard Calibration of an Indirect Enzymatic Analytical Method for 2-MCPD Fatty Acid Esters.

PubMed

Koyama, Kazuo; Miyazaki, Kinuko; Abe, Kousuke; Egawa, Yoshitsugu; Fukazawa, Toru; Kitta, Tadashi; Miyashita, Takashi; Nezu, Toru; Nohara, Hidenori; Sano, Takashi; Takahashi, Yukinari; Taniguchi, Hideji; Yada, Hiroshi; Yamazaki, Kumiko; Watanabe, Yomi

2017-06-01

An indirect enzymatic analysis method for the quantification of fatty acid esters of 2-/3-monochloro-1,2-propanediol (2/3-MCPD) and glycidol was developed, using the deuterated internal standard of each free-form component. A statistical method for calibration and quantification of 2-MCPD-d 5 , which is difficult to obtain, is substituted by 3-MCPD-d 5 used for calculation of 3-MCPD. Using data from a previous collaborative study, the current method for the determination of 2-MCPD content using 2-MCPD-d 5 was compared to three alternative new methods using 3-MCPD-d 5 . The regression analysis showed that the alternative methods were unbiased compared to the current method. The relative standard deviation (RSD R ) among the testing laboratories was ≤ 15% and the Horwitz ratio was ≤ 1.0, a satisfactory value.

Monitoring the metering performance of an electronic voltage transformer on-line based on cyber-physics correlation analysis

NASA Astrophysics Data System (ADS)

Zhang, Zhu; Li, Hongbin; Tang, Dengping; Hu, Chen; Jiao, Yang

2017-10-01

Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

Statistical analysis of water-quality data containing multiple detection limits: S-language software for regression on order statistics

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.

Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study.

PubMed

Nour-Eldein, Hebatallah

2016-01-01

With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles.

The Performance of Methods to Test Upper-Level Mediation in the Presence of Nonnormal Data

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.

2008-01-01

A Monte Carlo study compared the statistical performance of standard and robust multilevel mediation analysis methods to test indirect effects for a cluster randomized experimental design under various departures from normality. The performance of these methods was examined for an upper-level mediation process, where the indirect effect is a fixed…

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable

PubMed Central

2012-01-01

Background When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. Methods An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Results Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. Conclusions The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population. PMID:22716998

Statistical definition of relapse: case of family drug court.

PubMed

Alemi, Farrokh; Haack, Mary; Nemes, Susanna

2004-06-01

At any point in time, a patient's return to drug use can be seen either as a temporary event or as a return to persistent use. There is no formal standard for distinguishing persistent drug use from an occasional relapse. This lack of standardization persists although the consequences of either interpretation can be life altering. In a drug court or regulatory situation, for example, misinterpreting relapse as return to drug use could lead to incarceration, loss of child custody, or loss of employment. A clinician who mistakes a client's relapse for persistent drug use may fail to adjust treatment intensity to client's needs. An empirical and standardized method for distinguishing relapse from persistent drug use is needed. This paper provides a tool for clinicians and judges to distinguish relapse from persistent use based on statistical analyses of patterns of client's drug use. To accomplish this, a control chart is created for time-in-between relapses. This paper shows how a statistical limit can be calculated by examining either the client's history or other clients in the same program. If client's time-in-between relapse exceeds the statistical limit, then the client has returned to persistent use. Otherwise, the drug use is temporary. To illustrate the method, it is applied to data from three family drug courts. The approach allows the estimation of control limits based on the client's as well as the court's historical patterns. The approach also allows comparison of courts based on recovery rates.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Probabilistic Component Mode Synthesis of Nondeterministic Substructures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1996-01-01

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. We present a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

USGS Publications Warehouse

Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

2007-01-01

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

Potential errors and misuse of statistics in studies on leakage in endodontics.

PubMed

Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

2013-04-01

To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

Review of research designs and statistical methods employed in dental postgraduate dissertations.

PubMed

Shirahatti, Ravi V; Hegde-Shetiya, Sahana

2015-01-01

There is a need to evaluate the quality of postgraduate dissertations of dentistry submitted to university in the light of the international standards of reporting. We conducted the review with an objective to document the use of sampling methods, measurement standardization, blinding, methods to eliminate bias, appropriate use of statistical tests, appropriate use of data presentation in postgraduate dental research and suggest and recommend modifications. The public access database of the dissertations from Rajiv Gandhi University of Health Sciences was reviewed. Three hundred and thirty-three eligible dissertations underwent preliminary evaluation followed by detailed evaluation of 10% of randomly selected dissertations. The dissertations were assessed based on international reporting guidelines such as strengthening the reporting of observational studies in epidemiology (STROBE), consolidated standards of reporting trials (CONSORT), and other scholarly resources. The data were compiled using MS Excel and SPSS 10.0. Numbers and percentages were used for describing the data. The "in vitro" studies were the most common type of research (39%), followed by observational (32%) and experimental studies (29%). The disciplines conservative dentistry (92%) and prosthodontics (75%) reported high numbers of in vitro research. Disciplines oral surgery (80%) and periodontics (67%) had conducted experimental studies as a major share of their research. Lacunae in the studies included observational studies not following random sampling (70%), experimental studies not following random allocation (75%), not mentioning about blinding, confounding variables and calibrations in measurements, misrepresenting the data by inappropriate data presentation, errors in reporting probability values and not reporting confidence intervals. Few studies showed grossly inappropriate choice of statistical tests and many studies needed additional tests. Overall observations indicated the need to comply with standard guidelines of reporting research.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Convolutional auto-encoder for image denoising of ultra-low-dose CT.

PubMed

Nishio, Mizuho; Nagashima, Chihiro; Hirabayashi, Saori; Ohnishi, Akinori; Sasaki, Kaori; Sagawa, Tomoyuki; Hamada, Masayuki; Yamashita, Tatsuo

2017-08-01

The purpose of this study was to validate a patch-based image denoising method for ultra-low-dose CT images. Neural network with convolutional auto-encoder and pairs of standard-dose CT and ultra-low-dose CT image patches were used for image denoising. The performance of the proposed method was measured by using a chest phantom. Standard-dose and ultra-low-dose CT images of the chest phantom were acquired. The tube currents for standard-dose and ultra-low-dose CT were 300 and 10 mA, respectively. Ultra-low-dose CT images were denoised with our proposed method using neural network, large-scale nonlocal mean, and block-matching and 3D filtering. Five radiologists and three technologists assessed the denoised ultra-low-dose CT images visually and recorded their subjective impressions of streak artifacts, noise other than streak artifacts, visualization of pulmonary vessels, and overall image quality. For the streak artifacts, noise other than streak artifacts, and visualization of pulmonary vessels, the results of our proposed method were statistically better than those of block-matching and 3D filtering (p-values < 0.05). On the other hand, the difference in the overall image quality between our proposed method and block-matching and 3D filtering was not statistically significant (p-value = 0.07272). The p-values obtained between our proposed method and large-scale nonlocal mean were all less than 0.05. Neural network with convolutional auto-encoder could be trained using pairs of standard-dose and ultra-low-dose CT image patches. According to the visual assessment by radiologists and technologists, the performance of our proposed method was superior to that of large-scale nonlocal mean and block-matching and 3D filtering.

Computing physical properties with quantum Monte Carlo methods with statistical fluctuations independent of system size.

PubMed

Assaraf, Roland

2014-12-01

We show that the recently proposed correlated sampling without reweighting procedure extends the locality (asymptotic independence of the system size) of a physical property to the statistical fluctuations of its estimator. This makes the approach potentially vastly more efficient for computing space-localized properties in large systems compared with standard correlated methods. A proof is given for a large collection of noninteracting fragments. Calculations on hydrogen chains suggest that this behavior holds not only for systems displaying short-range correlations, but also for systems with long-range correlations.

Research on Time Selection of Mass Sports in Tibetan Areas Plateau of Gansu Province Based on Environmental Science

NASA Astrophysics Data System (ADS)

Gao, Jike

2018-01-01

Through using the method of literature review, instrument measuring, questionnaire and mathematical statistics, this paper analyzed the current situation in Mass Sports of Tibetan Areas Plateau in Gansu Province. Through experimental test access to Tibetan areas in gansu province of air pollutants and meteorological index data as the foundation, control related national standard and exercise science, statistical analysis of data, the Tibetan plateau, gansu province people participate in physical exercise is dedicated to providing you with scientific methods and appropriate time.

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

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

2015-10-02

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

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example

PubMed Central

Winzer, Klaus-Jürgen; Buchholz, Anika; Schumacher, Martin; Sauerbrei, Willi

2016-01-01

Background Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches. Methods and Findings Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. Conclusions The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases. PMID:26938061

The method of expected number of deaths, 1786-1886-1986.

PubMed

Keiding, N

1987-04-01

"The method of expected number of deaths is an integral part of standardization of vital rates, which is one of the oldest statistical techniques. The expected number of deaths was calculated in 18th century actuarial mathematics...but the method seems to have been forgotten, and was reinvented in connection with 19th century studies of geographical and occupational variations of mortality.... It is noted that standardization of rates is intimately connected to the study of relative mortality, and a short description of very recent developments in the methodology of that area is included." (SUMMARY IN FRE) excerpt

A spatial scan statistic for multiple clusters.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2011-10-01

Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect. Copyright © 2011 Elsevier Inc. All rights reserved.

Fitting a three-parameter lognormal distribution with applications to hydrogeochemical data from the National Uranium Resource Evaluation Program

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

Kane, V.E.

1979-10-01

The standard maximum likelihood and moment estimation procedures are shown to have some undesirable characteristics for estimating the parameters in a three-parameter lognormal distribution. A class of goodness-of-fit estimators is found which provides a useful alternative to the standard methods. The class of goodness-of-fit tests considered include the Shapiro-Wilk and Shapiro-Francia tests which reduce to a weighted linear combination of the order statistics that can be maximized in estimation problems. The weighted-order statistic estimators are compared to the standard procedures in Monte Carlo simulations. Bias and robustness of the procedures are examined and example data sets analyzed including geochemical datamore » from the National Uranium Resource Evaluation Program.« less

Counting Microfiche: The Utilization of the Microform Section of the ANSI Standard Z39.7-1983 "Library Statistics"; Microfiche Curl; and "Poly" or "Cell"?

ERIC Educational Resources Information Center

Caldwell-Wood, Naomi; And Others

1987-01-01

The first of three articles describes procedures for using ANSI statistical methods for estimating the number of pieces in large homogeneous collections of microfiche. The second discusses causes of curl, its control, and measurement, and the third compares the advantages and disadvantages of cellulose acetate and polyester base for microforms.…

A spatial scan statistic for nonisotropic two-level risk cluster.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2012-01-30

Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the hand-foot-mouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster. Copyright © 2011 John Wiley & Sons, Ltd.

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

Zheng, Xiaogang; Biesiada, Marek; Cao, Shuo

A new compilation of 012 angular-size/redshift data for compact radio quasars from very-long-baseline interferometry (VLBI) surveys motivates us to revisit the interaction between dark energy and dark matter with these probes reaching high redshifts z ∼ 3.0. In this paper, we investigate observational constraints on different phenomenological interacting dark energy (IDE) models with the intermediate-luminosity radio quasars acting as individual standard rulers, combined with the newest BAO and CMB observation from Planck results acting as statistical rulers. The results obtained from the MCMC method and other statistical methods including figure of Merit and Information Criteria show that: (1) Compared withmore » the current standard candle data and standard clock data, the intermediate-luminosity radio quasar standard rulers , probing much higher redshifts, could provide comparable constraints on different IDE scenarios. (2) The strong degeneracies between the interaction term and Hubble constant may contribute to alleviate the tension of H {sub 0} between the recent Planck and HST measurements. (3) Concerning the ranking of competing dark energy models, IDE with more free parameters are substantially penalized by the BIC criterion, which agrees very well with the previous results derived from other cosmological probes.« less

Prediction of peak response values of structures with and without TMD subjected to random pedestrian flows

NASA Astrophysics Data System (ADS)

Lievens, Klaus; Van Nimmen, Katrien; Lombaert, Geert; De Roeck, Guido; Van den Broeck, Peter

2016-09-01

In civil engineering and architecture, the availability of high strength materials and advanced calculation techniques enables the construction of slender footbridges, generally highly sensitive to human-induced excitation. Due to the inherent random character of the human-induced walking load, variability on the pedestrian characteristics must be considered in the response simulation. To assess the vibration serviceability of the footbridge, the statistics of the stochastic dynamic response are evaluated by considering the instantaneous peak responses in a time range. Therefore, a large number of time windows are needed to calculate the mean value and standard deviation of the instantaneous peak values. An alternative method to evaluate the statistics is based on the standard deviation of the response and a characteristic frequency as proposed in wind engineering applications. In this paper, the accuracy of this method is evaluated for human-induced vibrations. The methods are first compared for a group of pedestrians crossing a lightly damped footbridge. Small differences of the instantaneous peak value were found by the method using second order statistics. Afterwards, a TMD tuned to reduce the peak acceleration to a comfort value, was added to the structure. The comparison between both methods in made and the accuracy is verified. It is found that the TMD parameters are tuned sufficiently and good agreements between the two methods are found for the estimation of the instantaneous peak response for a strongly damped structure.

Fully Bayesian tests of neutrality using genealogical summary statistics.

PubMed

Drummond, Alexei J; Suchard, Marc A

2008-10-31

Many data summary statistics have been developed to detect departures from neutral expectations of evolutionary models. However questions about the neutrality of the evolution of genetic loci within natural populations remain difficult to assess. One critical cause of this difficulty is that most methods for testing neutrality make simplifying assumptions simultaneously about the mutational model and the population size model. Consequentially, rejecting the null hypothesis of neutrality under these methods could result from violations of either or both assumptions, making interpretation troublesome. Here we harness posterior predictive simulation to exploit summary statistics of both the data and model parameters to test the goodness-of-fit of standard models of evolution. We apply the method to test the selective neutrality of molecular evolution in non-recombining gene genealogies and we demonstrate the utility of our method on four real data sets, identifying significant departures of neutrality in human influenza A virus, even after controlling for variation in population size. Importantly, by employing a full model-based Bayesian analysis, our method separates the effects of demography from the effects of selection. The method also allows multiple summary statistics to be used in concert, thus potentially increasing sensitivity. Furthermore, our method remains useful in situations where analytical expectations and variances of summary statistics are not available. This aspect has great potential for the analysis of temporally spaced data, an expanding area previously ignored for limited availability of theory and methods.

A method to preserve trends in quantile mapping bias correction of climate modeled temperature

NASA Astrophysics Data System (ADS)

Grillakis, Manolis G.; Koutroulis, Aristeidis G.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2017-09-01

Bias correction of climate variables is a standard practice in climate change impact (CCI) studies. Various methodologies have been developed within the framework of quantile mapping. However, it is well known that quantile mapping may significantly modify the long-term statistics due to the time dependency of the temperature bias. Here, a method to overcome this issue without compromising the day-to-day correction statistics is presented. The methodology separates the modeled temperature signal into a normalized and a residual component relative to the modeled reference period climatology, in order to adjust the biases only for the former and preserve the signal of the later. The results show that this method allows for the preservation of the originally modeled long-term signal in the mean, the standard deviation and higher and lower percentiles of temperature. To illustrate the improvements, the methodology is tested on daily time series obtained from five Euro CORDEX regional climate models (RCMs).

The international growth standard for preadolescent and adolescent children: statistical considerations.

PubMed

Cole, T J

2006-12-01

This article discusses statistical considerations for the design of a new study intended to provide an International Growth Standard for Preadolescent and Adolescent Children, including issues such as cross-sectional, longitudinal, and mixed designs; sample-size derivation for the number of populations and number of children per population; modeling of growth centiles of height, weight, and other measurements; and modeling of the adolescent growth spurt. The conclusions are that a mixed longitudinal design will provide information on both growth distance and velocity; samples of children from 5 to 10 sites should be suitable for an international standard (based on political rather than statistical arguments); the samples should be broadly uniform across age but oversampled during puberty, and should include data into adulthood. The LMS method is recommended for constructing measurement centiles, and parametric or semiparametric approaches are available to estimate the timing of the adolescent growth spurt in individuals. If the new standard is to be grafted onto the 2006 World Health Organization (WHO) reference, caution is needed at the join point of 5 years, where children from the new standard are likely to be appreciably more obese than those from the WHO reference, due to the rising trends in obesity and the time gap in data collection between the two surveys.

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

PubMed

Ing, Alex; Schwarzbauer, Christian

2014-01-01

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

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

PubMed Central

Ing, Alex; Schwarzbauer, Christian

2014-01-01

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

Quantifying Cartilage Contact Modulus, Tension Modulus, and Permeability With Hertzian Biphasic Creep

PubMed Central

Moore, A. C.; DeLucca, J. F.; Elliott, D. M.; Burris, D. L.

2016-01-01

This paper describes a new method, based on a recent analytical model (Hertzian biphasic theory (HBT)), to simultaneously quantify cartilage contact modulus, tension modulus, and permeability. Standard Hertzian creep measurements were performed on 13 osteochondral samples from three mature bovine stifles. Each creep dataset was fit for material properties using HBT. A subset of the dataset (N = 4) was also fit using Oyen's method and FEBio, an open-source finite element package designed for soft tissue mechanics. The HBT method demonstrated statistically significant sensitivity to differences between cartilage from the tibial plateau and cartilage from the femoral condyle. Based on the four samples used for comparison, no statistically significant differences were detected between properties from the HBT and FEBio methods. While the finite element method is considered the gold standard for analyzing this type of contact, the expertise and time required to setup and solve can be prohibitive, especially for large datasets. The HBT method agreed quantitatively with FEBio but also offers ease of use by nonexperts, rapid solutions, and exceptional fit quality (R2 = 0.999 ± 0.001, N = 13). PMID:27536012

QCD Precision Measurements and Structure Function Extraction at a High Statistics, High Energy Neutrino Scattering Experiment:. NuSOnG

NASA Astrophysics Data System (ADS)

Adams, T.; Batra, P.; Bugel, L.; Camilleri, L.; Conrad, J. M.; de Gouvêa, A.; Fisher, P. H.; Formaggio, J. A.; Jenkins, J.; Karagiorgi, G.; Kobilarcik, T. R.; Kopp, S.; Kyle, G.; Loinaz, W. A.; Mason, D. A.; Milner, R.; Moore, R.; Morfín, J. G.; Nakamura, M.; Naples, D.; Nienaber, P.; Olness, F. I.; Owens, J. F.; Pate, S. F.; Pronin, A.; Seligman, W. G.; Shaevitz, M. H.; Schellman, H.; Schienbein, I.; Syphers, M. J.; Tait, T. M. P.; Takeuchi, T.; Tan, C. Y.; van de Water, R. G.; Yamamoto, R. K.; Yu, J. Y.

We extend the physics case for a new high-energy, ultra-high statistics neutrino scattering experiment, NuSOnG (Neutrino Scattering On Glass) to address a variety of issues including precision QCD measurements, extraction of structure functions, and the derived Parton Distribution Functions (PDF's). This experiment uses a Tevatron-based neutrino beam to obtain a sample of Deep Inelastic Scattering (DIS) events which is over two orders of magnitude larger than past samples. We outline an innovative method for fitting the structure functions using a parametrized energy shift which yields reduced systematic uncertainties. High statistics measurements, in combination with improved systematics, will enable NuSOnG to perform discerning tests of fundamental Standard Model parameters as we search for deviations which may hint of "Beyond the Standard Model" physics.

Revisiting the Scale-Invariant, Two-Dimensional Linear Regression Method

ERIC Educational Resources Information Center

Patzer, A. Beate C.; Bauer, Hans; Chang, Christian; Bolte, Jan; Su¨lzle, Detlev

2018-01-01

The scale-invariant way to analyze two-dimensional experimental and theoretical data with statistical errors in both the independent and dependent variables is revisited by using what we call the triangular linear regression method. This is compared to the standard least-squares fit approach by applying it to typical simple sets of example data…

Counting at low concentrations: the statistical challenges of verifying ballast water discharge standards

USGS Publications Warehouse

Frazier, Melanie; Miller, A. Whitman; Lee, Henry; Reusser, Deborah A.

2013-01-01

Discharge from the ballast tanks of ships is one of the primary vectors of nonindigenous species in marine environments. To mitigate this environmental and economic threat, international, national, and state entities are establishing regulations to limit the concentration of living organisms that may be discharged from the ballast tanks of ships. The proposed discharge standards have ranged from zero detectable organisms to 3. If standard sampling methods are used, verifying whether ballast discharge complies with these stringent standards will be challenging due to the inherent stochasticity of sampling. Furthermore, at low concentrations, very large volumes of water must be sampled to find enough organisms to accurately estimate concentration. Despite these challenges, adequate sampling protocols comprise a critical aspect of establishing standards because they help define the actual risk level associated with a standard. A standard that appears very stringent may be effectively lax if it is paired with an inadequate sampling protocol. We describe some of the statistical issues associated with sampling at low concentrations to help regulators understand the uncertainties of sampling as well as to inform the development of sampling protocols that ensure discharge standards are adequately implemented.

Evaluating Statistical Process Control (SPC) techniques and computing the uncertainty of force calibrations

NASA Technical Reports Server (NTRS)

Navard, Sharon E.

1989-01-01

In recent years there has been a push within NASA to use statistical techniques to improve the quality of production. Two areas where statistics are used are in establishing product and process quality control of flight hardware and in evaluating the uncertainty of calibration of instruments. The Flight Systems Quality Engineering branch is responsible for developing and assuring the quality of all flight hardware; the statistical process control methods employed are reviewed and evaluated. The Measurement Standards and Calibration Laboratory performs the calibration of all instruments used on-site at JSC as well as those used by all off-site contractors. These calibrations must be performed in such a way as to be traceable to national standards maintained by the National Institute of Standards and Technology, and they must meet a four-to-one ratio of the instrument specifications to calibrating standard uncertainty. In some instances this ratio is not met, and in these cases it is desirable to compute the exact uncertainty of the calibration and determine ways of reducing it. A particular example where this problem is encountered is with a machine which does automatic calibrations of force. The process of force calibration using the United Force Machine is described in detail. The sources of error are identified and quantified when possible. Suggestions for improvement are made.

Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses

PubMed Central

Park, Danny S.; Brown, Brielin; Eng, Celeste; Huntsman, Scott; Hu, Donglei; Torgerson, Dara G.; Burchard, Esteban G.; Zaitlen, Noah

2015-01-01

Motivation: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community. Current summary statistics-based methods rely on global ‘best guess’ reference panels to model the genetic correlation structure of the dataset being studied. This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small. Here, we develop a method, Adapt-Mix, that combines information across all available reference panels to produce estimates of local genetic correlation structure for summary statistics-based methods in arbitrary populations. Results: We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data. We evaluated our method by measuring the performance of two summary statistics-based methods: imputation and joint-testing. When using our method as opposed to the current standard of ‘best guess’ reference panels, we observed a 28% decrease in mean-squared error for imputation and a 73.7% decrease in mean-squared error for joint-testing. Availability and implementation: Our method is publicly available in a software package called ADAPT-Mix available at https://github.com/dpark27/adapt_mix. Contact: noah.zaitlen@ucsf.edu PMID:26072481

Semiquantitative determination of mesophilic, aerobic microorganisms in cocoa products using the Soleris NF-TVC method.

PubMed

Montei, Carolyn; McDougal, Susan; Mozola, Mark; Rice, Jennifer

2014-01-01

The Soleris Non-fermenting Total Viable Count method was previously validated for a wide variety of food products, including cocoa powder. A matrix extension study was conducted to validate the method for use with cocoa butter and cocoa liquor. Test samples included naturally contaminated cocoa liquor and cocoa butter inoculated with natural microbial flora derived from cocoa liquor. A probability of detection statistical model was used to compare Soleris results at multiple test thresholds (dilutions) with aerobic plate counts determined using the AOAC Official Method 966.23 dilution plating method. Results of the two methods were not statistically different at any dilution level in any of the three trials conducted. The Soleris method offers the advantage of results within 24 h, compared to the 48 h required by standard dilution plating methods.

Study of statistical coding for digital TV

NASA Technical Reports Server (NTRS)

Gardenhire, L. W.

1972-01-01

The results are presented for a detailed study to determine a pseudo-optimum statistical code to be installed in a digital TV demonstration test set. Studies of source encoding were undertaken, using redundancy removal techniques in which the picture is reproduced within a preset tolerance. A method of source encoding, which preliminary studies show to be encouraging, is statistical encoding. A pseudo-optimum code was defined and the associated performance of the code was determined. The format was fixed at 525 lines per frame, 30 frames per second, as per commercial standards.

A review of contemporary methods for the presentation of scientific uncertainty.

PubMed

Makinson, K A; Hamby, D M; Edwards, J A

2012-12-01

Graphic methods for displaying uncertainty are often the most concise and informative way to communicate abstract concepts. Presentation methods currently in use for the display and interpretation of scientific uncertainty are reviewed. Numerous subjective and objective uncertainty display methods are presented, including qualitative assessments, node and arrow diagrams, standard statistical methods, box-and-whisker plots,robustness and opportunity functions, contribution indexes, probability density functions, cumulative distribution functions, and graphical likelihood functions.

An Experimental Study of the Effect of Judges' Knowledge of Item Data on Two Forms of the Angoff Standard Setting Method.

ERIC Educational Resources Information Center

Garrido, Mariquita; Payne, David A.

Minimum competency cut-off scores on a statistics exam were estimated under four conditions: the Angoff judging method with item data (n=20), and without data available (n=19); and the Modified Angoff method with (n=19), and without (n=19) item data available to judges. The Angoff method required free response percentage estimates (0-100) percent,…

Standards for reporting fish toxicity tests

USGS Publications Warehouse

Cope, O.B.

1961-01-01

The growing impetus of studies on fish and pesticides focuses attention on the need for standardized reporting procedures. Good methods have been developed for laboratory and field procedures in testing programs and in statistical features of assay experiments; and improvements are being made on methods of collecting and preserving fish, invertebrates, and other materials exposed to economic poisons. On the other had, the reporting of toxicity data in a complete manner has lagged behind, and today's literature is little improved over yesterday's with regard to completeness and susceptibility to interpretation.

Universal immunogenicity validation and assessment during early biotherapeutic development to support a green laboratory.

PubMed

Bautista, Ami C; Zhou, Lei; Jawa, Vibha

2013-10-01

Immunogenicity support during nonclinical biotherapeutic development can be resource intensive if supported by conventional methodologies. A universal indirect species-specific immunoassay can eliminate the need for biotherapeutic-specific anti-drug antibody immunoassays without compromising quality. By implementing the R's of sustainability (reduce, reuse, rethink), conservation of resources and greener laboratory practices were achieved in this study. Statistical analysis across four biotherapeutics supported identification of consistent product performance standards (cut points, sensitivity and reference limits) and a streamlined universal anti-drug antibody immunoassay method implementation strategy. We propose an efficient, fit-for-purpose, scientifically and statistically supported nonclinical immunogenicity assessment strategy. Utilization of a universal method and streamlined validation, while retaining comparability to conventional immunoassays and meeting the industry recommended standards, provides environmental credits in the scientific laboratory. Collectively, individual reductions in critical material consumption, energy usage, waste and non-environment friendly consumables, such as plastic and paper, support a greener laboratory environment.

Statistical inference for template aging

NASA Astrophysics Data System (ADS)

Schuckers, Michael E.

2006-04-01

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

Variation in passing standards for graduation-level knowledge items at UK medical schools.

PubMed

Taylor, Celia A; Gurnell, Mark; Melville, Colin R; Kluth, David C; Johnson, Neil; Wass, Val

2017-06-01

Given the absence of a common passing standard for students at UK medical schools, this paper compares independently set standards for common 'one from five' single-best-answer (multiple-choice) items used in graduation-level applied knowledge examinations and explores potential reasons for any differences. A repeated cross-sectional study was conducted. Participating schools were sent a common set of graduation-level items (55 in 2013-2014; 60 in 2014-2015). Items were selected against a blueprint and subjected to a quality review process. Each school employed its own standard-setting process for the common items. The primary outcome was the passing standard for the common items by each medical school set using the Angoff or Ebel methods. Of 31 invited medical schools, 22 participated in 2013-2014 (71%) and 30 (97%) in 2014-2015. Schools used a mean of 49 and 53 common items in 2013-2014 and 2014-2015, respectively, representing around one-third of the items in the examinations in which they were embedded. Data from 19 (61%) and 26 (84%) schools, respectively, met the inclusion criteria for comparison of standards. There were statistically significant differences in the passing standards set by schools in both years (effect sizes (f 2 ): 0.041 in 2013-2014 and 0.218 in 2014-2015; both p < 0.001). The interquartile range of standards was 5.7 percentage points in 2013-2014 and 6.5 percentage points in 2014-2015. There was a positive correlation between the relative standards set by schools in the 2 years (Pearson's r = 0.57, n = 18, p = 0.014). Time allowed per item, method of standard setting and timing of examination in the curriculum did not have a statistically significant impact on standards. Independently set standards for common single-best-answer items used in graduation-level examinations vary across UK medical schools. Further work to examine standard-setting processes in more detail is needed to help explain this variability and develop methods to reduce it. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

PubMed

Rivas, Elena; Lang, Raymond; Eddy, Sean R

2012-02-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more

PubMed Central

Rivas, Elena; Lang, Raymond; Eddy, Sean R.

2012-01-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases. PMID:22194308

Statistics of baryon correlation functions in lattice QCD

NASA Astrophysics Data System (ADS)

Wagman, Michael L.; Savage, Martin J.; Nplqcd Collaboration

2017-12-01

A systematic analysis of the structure of single-baryon correlation functions calculated with lattice QCD is performed, with a particular focus on characterizing the structure of the noise associated with quantum fluctuations. The signal-to-noise problem in these correlation functions is shown, as long suspected, to result from a sign problem. The log-magnitude and complex phase are found to be approximately described by normal and wrapped normal distributions respectively. Properties of circular statistics are used to understand the emergence of a large time noise region where standard energy measurements are unreliable. Power-law tails in the distribution of baryon correlation functions, associated with stable distributions and "Lévy flights," are found to play a central role in their time evolution. A new method of analyzing correlation functions is considered for which the signal-to-noise ratio of energy measurements is constant, rather than exponentially degrading, with increasing source-sink separation time. This new method includes an additional systematic uncertainty that can be removed by performing an extrapolation, and the signal-to-noise problem reemerges in the statistics of this extrapolation. It is demonstrated that this new method allows accurate results for the nucleon mass to be extracted from the large-time noise region inaccessible to standard methods. The observations presented here are expected to apply to quantum Monte Carlo calculations more generally. Similar methods to those introduced here may lead to practical improvements in analysis of noisier systems.

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

Assessment of opacimeter calibration according to International Standard Organization 10155.

PubMed

Gomes, J F

2001-01-01

This paper compares the calibration method for opacimeters issued by the International Standard Organization (ISO) 10155 with the manual reference method for determination of dust content in stack gases. ISO 10155 requires at least nine operational measurements, corresponding to three operational measurements per each dust emission range within the stack. The procedure is assessed by comparison with previous calibration methods for opacimeters using only two operational measurements from a set of measurements made at stacks from pulp mills. The results show that even if the international standard for opacimeter calibration requires that the calibration curve is to be obtained using 3 x 3 points, a calibration curve derived using 3 points could be, at times, acceptable in statistical terms, provided that the amplitude of individual measurements is low.

Development of a Probabilistic Component Mode Synthesis Method for the Analysis of Non-Deterministic Substructures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1995-01-01

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature, researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. This paper presents a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

Design, analysis, and interpretation of field quality-control data for water-sampling projects

USGS Publications Warehouse

Mueller, David K.; Schertz, Terry L.; Martin, Jeffrey D.; Sandstrom, Mark W.

2015-01-01

The report provides extensive information about statistical methods used to analyze quality-control data in order to estimate potential bias and variability in environmental data. These methods include construction of confidence intervals on various statistical measures, such as the mean, percentiles and percentages, and standard deviation. The methods are used to compare quality-control results with the larger set of environmental data in order to determine whether the effects of bias and variability might interfere with interpretation of these data. Examples from published reports are presented to illustrate how the methods are applied, how bias and variability are reported, and how the interpretation of environmental data can be qualified based on the quality-control analysis.

Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.

PubMed

Pasaniuc, Bogdan; Zaitlen, Noah; Lettre, Guillaume; Chen, Gary K; Tandon, Arti; Kao, W H Linda; Ruczinski, Ingo; Fornage, Myriam; Siscovick, David S; Zhu, Xiaofeng; Larkin, Emma; Lange, Leslie A; Cupples, L Adrienne; Yang, Qiong; Akylbekova, Ermeg L; Musani, Solomon K; Divers, Jasmin; Mychaleckyj, Joe; Li, Mingyao; Papanicolaou, George J; Millikan, Robert C; Ambrosone, Christine B; John, Esther M; Bernstein, Leslie; Zheng, Wei; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Ingles, Sue A; Press, Michael F; Chanock, Stephen J; Deming, Sandra L; Rodriguez-Gil, Jorge L; Palmer, Cameron D; Buxbaum, Sarah; Ekunwe, Lynette; Hirschhorn, Joel N; Henderson, Brian E; Myers, Simon; Haiman, Christopher A; Reich, David; Patterson, Nick; Wilson, James G; Price, Alkes L

2011-04-01

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Validity and reliability of a method for assessment of cervical vertebral maturation.

PubMed

Zhao, Xiao-Guang; Lin, Jiuxiang; Jiang, Jiu-Hui; Wang, Qingzhu; Ng, Sut Hong

2012-03-01

To evaluate the validity and reliability of the cervical vertebral maturation (CVM) method with a longitudinal sample. Eighty-six cephalograms from 18 subjects (5 males and 13 females) were selected from the longitudinal database. Total mandibular length was measured on each film; an increased rate served as the gold standard in examination of the validity of the CVM method. Eleven orthodontists, after receiving intensive training in the CVM method, evaluated all films twice. Kendall's W and the weighted kappa statistic were employed. Kendall's W values were higher than 0.8 at both times, indicating strong interobserver reproducibility, but interobserver agreement was documented twice at less than 50%. A wide range of intraobserver agreement was noted (40.7%-79.1%), and substantial intraobserver reproducibility was proved by kappa values (0.53-0.86). With regard to validity, moderate agreement was reported between the gold standard and observer staging at the initial time (kappa values 0.44-0.61). However, agreement seemed to be unacceptable for clinical use, especially in cervical stage 3 (26.8%). Even though the validity and reliability of the CVM method proved statistically acceptable, we suggest that many other growth indicators should be taken into consideration in evaluating adolescent skeletal maturation.

Resonance Raman of BCC and normal skin

NASA Astrophysics Data System (ADS)

Liu, Cheng-hui; Sriramoju, Vidyasagar; Boydston-White, Susie; Wu, Binlin; Zhang, Chunyuan; Pei, Zhe; Sordillo, Laura; Beckman, Hugh; Alfano, Robert R.

2017-02-01

The Resonance Raman (RR) spectra of basal cell carcinoma (BCC) and normal human skin tissues were analyzed using 532nm laser excitation. RR spectral differences in vibrational fingerprints revealed skin normal and cancerous states tissues. The standard diagnosis criterion for BCC tissues are created by native RR biomarkers and its changes at peak intensity. The diagnostic algorithms for the classification of BCC and normal were generated based on SVM classifier and PCA statistical method. These statistical methods were used to analyze the RR spectral data collected from skin tissues, yielding a diagnostic sensitivity of 98.7% and specificity of 79% compared with pathological reports.

Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans.

PubMed

Bauer, Christian; Sun, Shanhui; Sun, Wenqing; Otis, Justin; Wallace, Audrey; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M; Beichel, Reinhard R

2012-06-01

The purpose of this work was to develop and validate fully automated methods for uptake measurement of cerebellum, liver, and aortic arch in full-body PET/CT scans. Such measurements are of interest in the context of uptake normalization for quantitative assessment of metabolic activity and/or automated image quality control. Cerebellum, liver, and aortic arch regions were segmented with different automated approaches. Cerebella were segmented in PET volumes by means of a robust active shape model (ASM) based method. For liver segmentation, a largest possible hyperellipsoid was fitted to the liver in PET scans. The aortic arch was first segmented in CT images of a PET/CT scan by a tubular structure analysis approach, and the segmented result was then mapped to the corresponding PET scan. For each of the segmented structures, the average standardized uptake value (SUV) was calculated. To generate an independent reference standard for method validation, expert image analysts were asked to segment several cross sections of each of the three structures in 134 F-18 fluorodeoxyglucose (FDG) PET/CT scans. For each case, the true average SUV was estimated by utilizing statistical models and served as the independent reference standard. For automated aorta and liver SUV measurements, no statistically significant scale or shift differences were observed between automated results and the independent standard. In the case of the cerebellum, the scale and shift were not significantly different, if measured in the same cross sections that were utilized for generating the reference. In contrast, automated results were scaled 5% lower on average although not shifted, if FDG uptake was calculated from the whole segmented cerebellum volume. The estimated reduction in total SUV measurement error ranged between 54.7% and 99.2%, and the reduction was found to be statistically significant for cerebellum and aortic arch. With the proposed methods, the authors have demonstrated that automated SUV uptake measurements in cerebellum, liver, and aortic arch agree with expert-defined independent standards. The proposed methods were found to be accurate and showed less intra- and interobserver variability, compared to manual analysis. The approach provides an alternative to manual uptake quantification, which is time-consuming. Such an approach will be important for application of quantitative PET imaging to large scale clinical trials. © 2012 American Association of Physicists in Medicine.

Logical and Methodological Issues Affecting Genetic Studies of Humans Reported in Top Neuroscience Journals.

PubMed

Grabitz, Clara R; Button, Katherine S; Munafò, Marcus R; Newbury, Dianne F; Pernet, Cyril R; Thompson, Paul A; Bishop, Dorothy V M

2018-01-01

Genetics and neuroscience are two areas of science that pose particular methodological problems because they involve detecting weak signals (i.e., small effects) in noisy data. In recent years, increasing numbers of studies have attempted to bridge these disciplines by looking for genetic factors associated with individual differences in behavior, cognition, and brain structure or function. However, different methodological approaches to guarding against false positives have evolved in the two disciplines. To explore methodological issues affecting neurogenetic studies, we conducted an in-depth analysis of 30 consecutive articles in 12 top neuroscience journals that reported on genetic associations in nonclinical human samples. It was often difficult to estimate effect sizes in neuroimaging paradigms. Where effect sizes could be calculated, the studies reporting the largest effect sizes tended to have two features: (i) they had the smallest samples and were generally underpowered to detect genetic effects, and (ii) they did not fully correct for multiple comparisons. Furthermore, only a minority of studies used statistical methods for multiple comparisons that took into account correlations between phenotypes or genotypes, and only nine studies included a replication sample or explicitly set out to replicate a prior finding. Finally, presentation of methodological information was not standardized and was often distributed across Methods sections and Supplementary Material, making it challenging to assemble basic information from many studies. Space limits imposed by journals could mean that highly complex statistical methods were described in only a superficial fashion. In summary, methods that have become standard in the genetics literature-stringent statistical standards, use of large samples, and replication of findings-are not always adopted when behavioral, cognitive, or neuroimaging phenotypes are used, leading to an increased risk of false-positive findings. Studies need to correct not just for the number of phenotypes collected but also for the number of genotypes examined, genetic models tested, and subsamples investigated. The field would benefit from more widespread use of methods that take into account correlations between the factors corrected for, such as spectral decomposition, or permutation approaches. Replication should become standard practice; this, together with the need for larger sample sizes, will entail greater emphasis on collaboration between research groups. We conclude with some specific suggestions for standardized reporting in this area.

Study Methods to Standardize Thermography NDE

NASA Technical Reports Server (NTRS)

Walker, James L.; Workman, Gary L.

1998-01-01

The purpose of this work is to develop thermographic inspection methods and standards for use in evaluating structural composites and aerospace hardware. Qualification techniques and calibration methods are investigated to standardize the thermographic method for use in the field. Along with the inspections of test standards structural hardware, support hardware is designed and fabricated to aid in the thermographic process. Also, a standard operating procedure is developed for performing inspections with the Bales Thermal Image Processor (TIP). Inspections are performed on a broad range of structural composites. These materials include various graphite/epoxies, graphite/cyanide-ester, graphite/silicon-carbide, graphite phenolic and Keviar/epoxy. Also metal honeycomb (titanium and aluminum faceplates over an aluminum honeycomb core) structures are investigated. Various structural shapes are investigated and the thickness of the structures vary from as few as 3 plies to as many as 80 plies. Special emphasis is placed on characterizing defects in attachment holes and bondlines, in addition to those resulting from impact damage and the inclusion of foreign matter. Image processing through statistical analysis and digital filtering is investigated to enhance the quality and quantify the NDE thermal images when necessary.

Study Methods to Standardize Thermography NDE

NASA Technical Reports Server (NTRS)

Walker, James L.; Workman, Gary L.

1998-01-01

The purpose of this work is to develop thermographic inspection methods and standards for use in evaluating structural composites and aerospace hardware. Qualification techniques and calibration methods are investigated to standardize the thermographic method for use in the field. Along with the inspections of test standards structural hardware, support hardware is designed and fabricated to aid in the thermographic process. Also, a standard operating procedure is developed for performing inspections with the Bales Thermal Image Processor (TIP). Inspections are performed on a broad range of structural composites. These materials include graphite/epoxies, graphite/cyanide-ester, graphite/silicon-carbide, graphite phenolic and Kevlar/epoxy. Also metal honeycomb (titanium and aluminum faceplates over an aluminum honeycomb core) structures are investigated. Various structural shapes are investigated and the thickness of the structures vary from as few as 3 plies to as many as 80 plies. Special emphasis is placed on characterizing defects in attachment holes and bondlines, in addition to those resulting from impact damage and the inclusion of foreign matter. Image processing through statistical analysis and digital filtering is investigated to enhance the quality and quantify the NDE thermal images when necessary.

Toward unbiased estimations of the statefinder parameters

NASA Astrophysics Data System (ADS)

Aviles, Alejandro; Klapp, Jaime; Luongo, Orlando

2017-09-01

With the use of simulated supernova catalogs, we show that the statefinder parameters turn out to be poorly and biased estimated by standard cosmography. To this end, we compute their standard deviations and several bias statistics on cosmologies near the concordance model, demonstrating that these are very large, making standard cosmography unsuitable for future and wider compilations of data. To overcome this issue, we propose a new method that consists in introducing the series of the Hubble function into the luminosity distance, instead of considering the usual direct Taylor expansions of the luminosity distance. Moreover, in order to speed up the numerical computations, we estimate the coefficients of our expansions in a hierarchical manner, in which the order of the expansion depends on the redshift of every single piece of data. In addition, we propose two hybrids methods that incorporates standard cosmography at low redshifts. The methods presented here perform better than the standard approach of cosmography both in the errors and bias of the estimated statefinders. We further propose a one-parameter diagnostic to reject non-viable methods in cosmography.

Selection and Evaluation of Priority Domains in Global Energy Internet Standard Development Based on Technology Foresight

NASA Astrophysics Data System (ADS)

Jin, Yang; Ciwei, Gao; Jing, Zhang; Min, Sun; Jie, Yu

2017-05-01

The selection and evaluation of priority domains in Global Energy Internet standard development will help to break through limits of national investment, thus priority will be given to standardizing technical areas with highest urgency and feasibility. Therefore, in this paper, the process of Delphi survey based on technology foresight is put forward, the evaluation index system of priority domains is established, and the index calculation method is determined. Afterwards, statistical method is used to evaluate the alternative domains. Finally the top four priority domains are determined as follows: Interconnected Network Planning and Simulation Analysis, Interconnected Network Safety Control and Protection, Intelligent Power Transmission and Transformation, and Internet of Things.

Explorations in statistics: the log transformation.

PubMed

Curran-Everett, Douglas

2018-06-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This thirteenth installment of Explorations in Statistics explores the log transformation, an established technique that rescales the actual observations from an experiment so that the assumptions of some statistical analysis are better met. A general assumption in statistics is that the variability of some response Y is homogeneous across groups or across some predictor variable X. If the variability-the standard deviation-varies in rough proportion to the mean value of Y, a log transformation can equalize the standard deviations. Moreover, if the actual observations from an experiment conform to a skewed distribution, then a log transformation can make the theoretical distribution of the sample mean more consistent with a normal distribution. This is important: the results of a one-sample t test are meaningful only if the theoretical distribution of the sample mean is roughly normal. If we log-transform our observations, then we want to confirm the transformation was useful. We can do this if we use the Box-Cox method, if we bootstrap the sample mean and the statistic t itself, and if we assess the residual plots from the statistical model of the actual and transformed sample observations.

75 FR 8363 - Office for Civil Rights; Workshop on the HIPAA Privacy Rule's De-Identification Standard; Notice...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-24

... Recovery and Reinvestment Act of 2009 (ARRA),\\1\\ requires HHS to issue guidance on methods for de...). --Methodological Issues Associated with HIPAA Privacy Rule De- Identification. --Statistical Disclosure Control and...

New output improvements for CLASSY

NASA Technical Reports Server (NTRS)

Rassbach, M. E. (Principal Investigator)

1981-01-01

Additional output data and formats for the CLASSY clustering algorithm were developed. Four such aids to the CLASSY user are described. These are: (1) statistical measures; (2) special map types; (3) formats for standard output; and (4) special cluster display method.

Standards of Research.

ERIC Educational Resources Information Center

Crain, Robert L.; Hawley, Willis D.

1982-01-01

Criticizes James Coleman's study, "Public and Private Schools," and points out methodological weaknesses in sampling, testing, data reliability, and statistical methods. Questions assumptions which have led to conclusions justifying federal support, especially tuition tax credits, to private schools. Raises the issue of ethical standards…

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

PubMed

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

2016-08-01

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

The breaking load method - Results and statistical modification from the ASTM interlaboratory test program

NASA Technical Reports Server (NTRS)

Colvin, E. L.; Emptage, M. R.

1992-01-01

The breaking load test provides quantitative stress corrosion cracking data by determining the residual strength of tension specimens that have been exposed to corrosive environments. Eight laboratories have participated in a cooperative test program under the auspices of ASTM Committee G-1 to evaluate the new test method. All eight laboratories were able to distinguish between three tempers of aluminum alloy 7075. The statistical analysis procedures that were used in the test program do not work well in all situations. An alternative procedure using Box-Cox transformations shows a great deal of promise. An ASTM standard method has been drafted which incorporates the Box-Cox procedure.

Statistical methods for astronomical data with upper limits. I - Univariate distributions

NASA Technical Reports Server (NTRS)

Feigelson, E. D.; Nelson, P. I.

1985-01-01

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

Student Learning Outcomes and Pedagogy in Online and Face-to-Face College English Composition: A Mixed Methods Study

ERIC Educational Resources Information Center

Montagne, Lisa

2012-01-01

This mixed methods study combined quantitative statistics and qualitative inquiry to determine if any differences exist between how students in face-to-face and online college English composition courses performed on and demonstrated knowledge of the California state curriculum standards, and to explore the online learning environment in this…

Improving the power of clinical trials of rheumatoid arthritis by using data on continuous scales when analysing response rates: an application of the augmented binary method

PubMed Central

Jenkins, Martin

2016-01-01

Objective. In clinical trials of RA, it is common to assess effectiveness using end points based upon dichotomized continuous measures of disease activity, which classify patients as responders or non-responders. Although dichotomization generally loses statistical power, there are good clinical reasons to use these end points; for example, to allow for patients receiving rescue therapy to be assigned as non-responders. We adopt a statistical technique called the augmented binary method to make better use of the information provided by these continuous measures and account for how close patients were to being responders. Methods. We adapted the augmented binary method for use in RA clinical trials. We used a previously published randomized controlled trial (Oral SyK Inhibition in Rheumatoid Arthritis-1) to assess its performance in comparison to a standard method treating patients purely as responders or non-responders. The power and error rate were investigated by sampling from this study. Results. The augmented binary method reached similar conclusions to standard analysis methods but was able to estimate the difference in response rates to a higher degree of precision. Results suggested that CI widths for ACR responder end points could be reduced by at least 15%, which could equate to reducing the sample size of a study by 29% to achieve the same statistical power. For other end points, the gain was even higher. Type I error rates were not inflated. Conclusion. The augmented binary method shows considerable promise for RA trials, making more efficient use of patient data whilst still reporting outcomes in terms of recognized response end points. PMID:27338084

On the value of incorporating spatial statistics in large-scale geophysical inversions: the SABRe case

NASA Astrophysics Data System (ADS)

Kokkinaki, A.; Sleep, B. E.; Chambers, J. E.; Cirpka, O. A.; Nowak, W.

2010-12-01

Electrical Resistance Tomography (ERT) is a popular method for investigating subsurface heterogeneity. The method relies on measuring electrical potential differences and obtaining, through inverse modeling, the underlying electrical conductivity field, which can be related to hydraulic conductivities. The quality of site characterization strongly depends on the utilized inversion technique. Standard ERT inversion methods, though highly computationally efficient, do not consider spatial correlation of soil properties; as a result, they often underestimate the spatial variability observed in earth materials, thereby producing unrealistic subsurface models. Also, these methods do not quantify the uncertainty of the estimated properties, thus limiting their use in subsequent investigations. Geostatistical inverse methods can be used to overcome both these limitations; however, they are computationally expensive, which has hindered their wide use in practice. In this work, we compare a standard Gauss-Newton smoothness constrained least squares inversion method against the quasi-linear geostatistical approach using the three-dimensional ERT dataset of the SABRe (Source Area Bioremediation) project. The two methods are evaluated for their ability to: a) produce physically realistic electrical conductivity fields that agree with the wide range of data available for the SABRe site while being computationally efficient, and b) provide information on the spatial statistics of other parameters of interest, such as hydraulic conductivity. To explore the trade-off between inversion quality and computational efficiency, we also employ a 2.5-D forward model with corrections for boundary conditions and source singularities. The 2.5-D model accelerates the 3-D geostatistical inversion method. New adjoint equations are developed for the 2.5-D forward model for the efficient calculation of sensitivities. Our work shows that spatial statistics can be incorporated in large-scale ERT inversions to improve the inversion results without making them computationally prohibitive.

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.

PubMed

Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han

2017-03-01

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

Cost-Effectiveness Analysis: a proposal of new reporting standards in statistical analysis

PubMed Central

Bang, Heejung; Zhao, Hongwei

2014-01-01

Cost-effectiveness analysis (CEA) is a method for evaluating the outcomes and costs of competing strategies designed to improve health, and has been applied to a variety of different scientific fields. Yet, there are inherent complexities in cost estimation and CEA from statistical perspectives (e.g., skewness, bi-dimensionality, and censoring). The incremental cost-effectiveness ratio that represents the additional cost per one unit of outcome gained by a new strategy has served as the most widely accepted methodology in the CEA. In this article, we call for expanded perspectives and reporting standards reflecting a more comprehensive analysis that can elucidate different aspects of available data. Specifically, we propose that mean and median-based incremental cost-effectiveness ratios and average cost-effectiveness ratios be reported together, along with relevant summary and inferential statistics as complementary measures for informed decision making. PMID:24605979

A Model for Indexing Medical Documents Combining Statistical and Symbolic Knowledge.

PubMed Central

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-01-01

OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the model’s implementation performances as a result of using semantic relationships is encouraging. PMID:18693792

Measuring the Cobb angle with the iPhone in kyphoses: a reliability study.

PubMed

Jacquot, Frederic; Charpentier, Axelle; Khelifi, Sofiane; Gastambide, Daniel; Rigal, Regis; Sautet, Alain

2012-08-01

Smartphones have gained widespread use in the healthcare field to fulfill a variety of tasks. We developed a small iPhone application to take advantage of the built-in position sensor to measure angles in a variety of spinal deformities. We present a reliability study of this tool in measuring kyphotic angles. Radiographs taken from 20 different patients' charts were presented to a panel of six operators at two different times. Radiographs were measured with the protractor and the iPhone application and statistical analysis was applied to measure intraclass correlation coefficients between both measurement methods, and to measure intra- and interobserver reliability The intraclass correlation coefficient calculated between methods (i.e. CobbMeter application on the iPhone versus standard method with the protractor) was 0.963 for all measures, indicating excellent correlation was obtained between the CobbMeter application and the standard method. The interobserver correlation coefficient was 0.965. The intraobserver ICC was 0.977, indicating excellent reproductibility of measurements at different times for all operators. The interobserver ICC between fellowship trained senior surgeons and general orthopaedic residents was 0.989. Consistently, the ICC for intraobserver and interobserver correlations was higher with the CobbMeter application than with the regular protractor method. This difference was not statistically significant. Measuring kyphotic angles with the iPhone application appears to be a valid procedure and is in no way inferior to the standard way of measuring the Cobb angle in kyphotic deformities.

Efforts to improve international migration statistics: a historical perspective.

PubMed

Kraly, E P; Gnanasekaran, K S

1987-01-01

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

In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI

PubMed Central

Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

2013-01-01

Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a-priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. PMID:23473798

75 FR 37245 - 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-28

... Micropolitan Statistical Areas; Notice #0;#0;Federal Register / Vol. 75, No. 123 / Monday, June 28, 2010... and Micropolitan Statistical Areas AGENCY: Office of Information and Regulatory Affairs, Office of... Statistical Areas. The 2010 standards replace and supersede the 2000 Standards for Defining Metropolitan and...

Generalized t-statistic for two-group classification.

PubMed

Komori, Osamu; Eguchi, Shinto; Copas, John B

2015-06-01

In the classic discriminant model of two multivariate normal distributions with equal variance matrices, the linear discriminant function is optimal both in terms of the log likelihood ratio and in terms of maximizing the standardized difference (the t-statistic) between the means of the two distributions. In a typical case-control study, normality may be sensible for the control sample but heterogeneity and uncertainty in diagnosis may suggest that a more flexible model is needed for the cases. We generalize the t-statistic approach by finding the linear function which maximizes a standardized difference but with data from one of the groups (the cases) filtered by a possibly nonlinear function U. We study conditions for consistency of the method and find the function U which is optimal in the sense of asymptotic efficiency. Optimality may also extend to other measures of discriminatory efficiency such as the area under the receiver operating characteristic curve. The optimal function U depends on a scalar probability density function which can be estimated non-parametrically using a standard numerical algorithm. A lasso-like version for variable selection is implemented by adding L1-regularization to the generalized t-statistic. Two microarray data sets in the study of asthma and various cancers are used as motivating examples. © 2014, The International Biometric Society.

[Reliability and reproducibility of the Fitzpatrick phototype scale for skin sensitivity to ultraviolet light].

PubMed

Sánchez, Guillermo; Nova, John; Arias, Nilsa; Peña, Bibiana

2008-12-01

The Fitzpatrick phototype scale has been used to determine skin sensitivity to ultraviolet light. The reliability of this scale in estimating sensitivity permits risk evaluation of skin cancer based on phototype. Reliability and changes in intra and inter-observer concordance was determined for the Fitzpatrick phototype scale after the assessment methods for establishing the phototype were standardized. An analytical study of intra and inter-observer concordance was performed. The Fitzpatrick phototype scale was standardized using focus group methodology. To determine intra and inter-observer agreement, the weighted kappa statistical method was applied. The standardization effect was measured using the equal kappa contrast hypothesis and Wald test for dependent measurements. The phototype scale was applied to 155 patients over 15 years of age who were assessed four times by two independent observers. The sample was drawn from patients of the Centro Dermatol6gico Federico Lleras Acosta. During the pre-standardization phase, the baseline and six-week inter-observer weighted kappa were 0.31 and 0.40, respectively. The intra-observer kappa values for observers A and B were 0.47 and 0.51, respectively. After the standardization process, the baseline and six-week inter-observer weighted kappa values were 0.77, and 0.82, respectively. Intra-observer kappa coefficients for observers A and B were 0.78 and 0.82. Statistically significant differences were found between coefficients before and after standardization (p<0.001) in all comparisons. Following a standardization exercise, the Fitzpatrick phototype scale yielded reliable, reproducible and consistent results.

10 CFR 431.329 - Enforcement.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Metal Halide Lamp Ballasts and Fixtures Energy Conservation Standards § 431.329 Enforcement. Process for Metal Halide Lamp Ballasts. This section sets forth procedures DOE will follow in pursuing alleged... with the following statistical sampling procedures for metal halide lamp ballasts, with the methods...

Quasi-experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: A Systematic Review.

PubMed

Alsaggaf, Rotana; O'Hara, Lyndsay M; Stafford, Kristen A; Leekha, Surbhi; Harris, Anthony D

2018-02-01

OBJECTIVE A systematic review of quasi-experimental studies in the field of infectious diseases was published in 2005. The aim of this study was to assess improvements in the design and reporting of quasi-experiments 10 years after the initial review. We also aimed to report the statistical methods used to analyze quasi-experimental data. DESIGN Systematic review of articles published from January 1, 2013, to December 31, 2014, in 4 major infectious disease journals. METHODS Quasi-experimental studies focused on infection control and antibiotic resistance were identified and classified based on 4 criteria: (1) type of quasi-experimental design used, (2) justification of the use of the design, (3) use of correct nomenclature to describe the design, and (4) statistical methods used. RESULTS Of 2,600 articles, 173 (7%) featured a quasi-experimental design, compared to 73 of 2,320 articles (3%) in the previous review (P<.01). Moreover, 21 articles (12%) utilized a study design with a control group; 6 (3.5%) justified the use of a quasi-experimental design; and 68 (39%) identified their design using the correct nomenclature. In addition, 2-group statistical tests were used in 75 studies (43%); 58 studies (34%) used standard regression analysis; 18 (10%) used segmented regression analysis; 7 (4%) used standard time-series analysis; 5 (3%) used segmented time-series analysis; and 10 (6%) did not utilize statistical methods for comparisons. CONCLUSIONS While some progress occurred over the decade, it is crucial to continue improving the design and reporting of quasi-experimental studies in the fields of infection control and antibiotic resistance to better evaluate the effectiveness of important interventions. Infect Control Hosp Epidemiol 2018;39:170-176.

Using statistical and machine learning to help institutions detect suspicious access to electronic health records

PubMed Central

Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

Objective To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. Methods From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. Results The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. Limitations The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. Conclusion The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs. PMID:21672912

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

PubMed Central

Lee, Juneyoung; Kim, Kyung Won; Choi, Sang Hyun; Huh, Jimi

2015-01-01

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies. PMID:26576107

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

PubMed

Counsell, Alyssa; Harlow, Lisa L

2017-05-01

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

Application of Digital Image Analysis to Determine Pancreatic Islet Mass and Purity in Clinical Islet Isolation and Transplantation

PubMed Central

Wang, Ling-jia; Kissler, Hermann J; Wang, Xiaojun; Cochet, Olivia; Krzystyniak, Adam; Misawa, Ryosuke; Golab, Karolina; Tibudan, Martin; Grzanka, Jakub; Savari, Omid; Grose, Randall; Kaufman, Dixon B; Millis, Michael; Witkowski, Piotr

2015-01-01

Pancreatic islet mass, represented by islet equivalent (IEQ), is the most important parameter in decision making for clinical islet transplantation. To obtain IEQ, the sample of islets is routinely counted manually under a microscope and discarded thereafter. Islet purity, another parameter in islet processing, is routinely acquired by estimation only. In this study, we validated our digital image analysis (DIA) system developed using the software of Image Pro Plus for islet mass and purity assessment. Application of the DIA allows to better comply with current good manufacturing practice (cGMP) standards. Human islet samples were captured as calibrated digital images for the permanent record. Five trained technicians participated in determination of IEQ and purity by manual counting method and DIA. IEQ count showed statistically significant correlations between the manual method and DIA in all sample comparisons (r >0.819 and p < 0.0001). Statistically significant difference in IEQ between both methods was found only in High purity 100μL sample group (p = 0.029). As far as purity determination, statistically significant differences between manual assessment and DIA measurement was found in High and Low purity 100μL samples (p<0.005), In addition, islet particle number (IPN) and the IEQ/IPN ratio did not differ statistically between manual counting method and DIA. In conclusion, the DIA used in this study is a reliable technique in determination of IEQ and purity. Islet sample preserved as a digital image and results produced by DIA can be permanently stored for verification, technical training and islet information exchange between different islet centers. Therefore, DIA complies better with cGMP requirements than the manual counting method. We propose DIA as a quality control tool to supplement the established standard manual method for islets counting and purity estimation. PMID:24806436

DISSCO: direct imputation of summary statistics allowing covariates

PubMed Central

Xu, Zheng; Duan, Qing; Yan, Song; Chen, Wei; Li, Mingyao; Lange, Ethan; Li, Yun

2015-01-01

Background: Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates. Methods: We analytically show that in the absence of covariates, correlation among association summary statistics is indeed the same as that among the corresponding genotypes, thus serving as a theoretical justification for the recently proposed methods. We continue to prove that in the presence of covariates, correlation among association summary statistics becomes the partial correlation of the corresponding genotypes controlling for covariates. We therefore develop direct imputation of summary statistics allowing covariates (DISSCO). Results: We consider two real-life scenarios where the correlation and partial correlation likely make practical difference: (i) association studies in admixed populations; (ii) association studies in presence of other confounding covariate(s). Application of DISSCO to real datasets under both scenarios shows at least comparable, if not better, performance compared with existing correlation-based methods, particularly for lower frequency variants. For example, DISSCO can reduce the absolute deviation from the truth by 3.9–15.2% for variants with minor allele frequency <5%. Availability and implementation: http://www.unc.edu/∼yunmli/DISSCO. Contact: yunli@med.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25810429

Methodological issues when comparing hearing thresholds of a group with population standards: the case of the ferry engineers.

PubMed

Dobie, Robert A

2006-10-01

To discuss appropriate and inappropriate methods for comparing distributions of hearing thresholds of a study group with distributions in population standards and to determine whether the thresholds of Washington State Ferries engineers are different from those of men in the general population, using both frequency-by-frequency comparisons and analysis of audiometric shape. The most recent hearing conservation program audiograms of 321 noise-exposed engineers, ages 35 to 64, were compared with the predictions of Annexes A, B, and C from ANSI S3.44. There was no screening by history or otoscopy; all audiograms were included. 95% confidence intervals (95% CIs) were calculated for the engineers' median thresholds for each ear, for the better ear (defined two ways), and for the binaural average. For Annex B, where 95% CIs are also available, it was possible to calculate z scores for the differences between Annex B and the engineers' better ears. Bulge depth, an audiometric shape statistic, measured curvature between 1 and 6 kHz. Engineers' better-ear median thresholds were worse than those in Annex A but (except at 1 kHz) were as good as or better than those in Annexes B and C, which are more appropriate for comparison to an unscreened noise-exposed group like the engineers. Average bulge depth for the engineers was similar to that of the Annex B standard (no added occupational noise) and was much less than that of audiograms created by using the standard with added occupational noise between 90 and 100 dBA. Audiograms from groups that have been selected for a particular exposure, but, without regard to severity, can appropriately be compared with population standards, if certain pitfalls are avoided. For unscreened study groups with large age-sex subgroups, a simple method to assess statistical significance, taking into consideration uncertainties in both the study group and the comparison standard, is the calculation of z scores for the proportion of better-ear thresholds above the Annex B median. A less powerful method combines small age-sex subgroups after age correction. Small threshold differences, even if statistically significant, may not be due to genuine differences in hearing sensitivity between study group and standard. Audiometric shape analysis offers an independent dimension of comparison between the study group and audiograms predicted from the ANSI S3.44 standard, with and without occupational noise exposure. Important pitfalls in comparison to population standards include nonrandom selection of study groups, inappropriate choice of population standard, use of the right and left ear thresholds instead of the better-ear threshold for comparison to Annex B, and comparing means with medians. The thresholds of the engineers in this study were similar to published standards for an unscreened population.

WHO Working Group on revision of the Manual of Laboratory Methods for Testing DTP Vaccines-Report of two meetings held on 20-21 July 2006 and 28-30 March 2007, Geneva, Switzerland.

PubMed

Corbel, Michael J; Das, Rose Gaines; Lei, Dianliang; Xing, Dorothy K L; Horiuchi, Yoshinobu; Dobbelaer, Roland

2008-04-07

This report reflects the discussion and conclusions of a WHO group of experts from National Regulatory Authorities (NRAs), National Control Laboratories (NCLs), vaccine industries and other relevant institutions involved in standardization and control of diphtheria, tetanus and pertussis vaccines (DTP), held on 20-21 July 2006 and 28-30 March 2007, in Geneva Switzerland for the revision of WHO Manual for quality control of DTP vaccines. Taking into account recent developments and standardization in quality control methods and the revision of WHO recommendations for D, T, P vaccines, and a need for updating the manual has been recognized. In these two meetings the current situation of quality control methods in terms of potency, safety and identity tests for DTP vaccines and statistical analysis of data were reviewed. Based on the WHO recommendations and recent validation of testing methods, the content of current manual were reviewed and discussed. The group agreed that the principles to be observed in selecting methods included identifying those critical for assuring safety, efficacy and quality and which were consistent with WHO recommendations/requirements. Methods that were well recognized but not yet included in current Recommendations should be taken into account. These would include in vivo and/or in vitro methods for determining potency, safety testing and identity. The statistical analysis of the data should be revised and updated. It was noted that the mouse based assays for toxoid potency were still quite widely used and it was desirable to establish appropriate standards for these to enable the results to be related to the standard guinea pig assays. The working group was met again to review the first drafts and to input further suggestions or amendments to the contributions of the drafting groups. The revised manual was to be finalized and published by WHO.

Baseline models of trace elements in major aquifers of the United States

USGS Publications Warehouse

Lee, L.; Helsel, D.

2005-01-01

Trace-element concentrations in baseline samples from a survey of aquifers used as potable-water supplies in the United States are summarized using methods appropriate for data with multiple detection limits. The resulting statistical distribution models are used to develop summary statistics and estimate probabilities of exceeding water-quality standards. The models are based on data from the major aquifer studies of the USGS National Water Quality Assessment (NAWQA) Program. These data were produced with a nationally-consistent sampling and analytical framework specifically designed to determine the quality of the most important potable groundwater resources during the years 1991-2001. The analytical data for all elements surveyed contain values that were below several detection limits. Such datasets are referred to as multiply-censored data. To address this issue, a robust semi-parametric statistical method called regression on order statistics (ROS) is employed. Utilizing the 90th-95th percentile as an arbitrary range for the upper limits of expected baseline concentrations, the models show that baseline concentrations of dissolved Ba and Zn are below 500 ??g/L. For the same percentile range, dissolved As, Cu and Mo concentrations are below 10 ??g/L, and dissolved Ag, Be, Cd, Co, Cr, Ni, Pb, Sb and Se are below 1-5 ??g/L. These models are also used to determine the probabilities that potable ground waters exceed drinking water standards. For dissolved Ba, Cr, Cu, Pb, Ni, Mo and Se, the likelihood of exceeding the US Environmental Protection Agency standards at the well-head is less than 1-1.5%. A notable exception is As, which has approximately a 7% chance of exceeding the maximum contaminant level (10 ??g/L) at the well head.

The effect of using graphic organizers in the teaching of standard biology

NASA Astrophysics Data System (ADS)

Pepper, Wade Louis, Jr.

This study was conducted to determine if the use of graphic organizers in the teaching of standard biology would increase student achievement, involvement and quality of activities. The subjects were 10th grade standard biology students in a large southern inner city high school. The study was conducted over a six-week period in an instructional setting using action research as the investigative format. After calculation of the homogeneity between classes, random selection was used to determine the graphic organizer class and the control class. The graphic organizer class was taught unit material through a variety of instructional methods along with the use of teacher generated graphic organizers. The control class was taught the same unit material using the same instructional methods, but without the use of graphic organizers. Data for the study were gathered from in-class written assignments, teacher-generated tests and text-generated tests, and rubric scores of an out-of-class written assignment and project. Also, data were gathered from student reactions, comments, observations and a teacher's research journal. Results were analyzed using descriptive statistics and qualitative interpretation. By comparing statistical results, it was determined that the use of graphic organizers did not make a statistically significant difference in the understanding of biological concepts and retention of factual information. Furthermore, the use of graphic organizers did not make a significant difference in motivating students to fulfill all class assignments with quality efforts and products. However, based upon student reactions and comments along with observations by the researcher, graphic organizers were viewed by the students as a favorable and helpful instructional tool. In lieu of statistical results, student gains from instructional activities using graphic organizers were positive and merit the continuation of their use as an instructional tool.

Investigation of Magnetic Field Phenomena in the Ionosphere

DTIC Science & Technology

1979-01-01

several days so that a statistical measure of comparison may be developed, i.e. how well the fluxgate magnetometer replicates the standard values Because...Fig. 7 schematically 15 shows these changes. 4) Transients in the sensor to amplifier lines have caused failures of the chopper transitor . Back to back...weakness of this method is that the drop out must be longer than 100 ms. However, drop outs of durations shorter than this are statistically very small

Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.

PubMed

de Nijs, Robin

2015-07-21

In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.

Mode-Stirred Method Implementation for HIRF Susceptibility Testing and Results Comparison with Anechoic Method

NASA Technical Reports Server (NTRS)

Nguyen, Truong X.; Ely, Jay J.; Koppen, Sandra V.

2001-01-01

This paper describes the implementation of mode-stirred method for susceptibility testing according to the current DO-160D standard. Test results on an Engine Data Processor using the implemented procedure and the comparisons with the standard anechoic test results are presented. The comparison experimentally shows that the susceptibility thresholds found in mode-stirred method are consistently higher than anechoic. This is consistent with the recent statistical analysis finding by NIST that the current calibration procedure overstates field strength by a fixed amount. Once the test results are adjusted for this value, the comparisons with the anechoic results are excellent. The results also show that test method has excellent chamber to chamber repeatability. Several areas for improvements to the current procedure are also identified and implemented.

Using the Bootstrap Method to Evaluate the Critical Range of Misfit for Polytomous Rasch Fit Statistics.

PubMed

Seol, Hyunsoo

2016-06-01

The purpose of this study was to apply the bootstrap procedure to evaluate how the bootstrapped confidence intervals (CIs) for polytomous Rasch fit statistics might differ according to sample sizes and test lengths in comparison with the rule-of-thumb critical value of misfit. A total of 25 simulated data sets were generated to fit the Rasch measurement and then a total of 1,000 replications were conducted to compute the bootstrapped CIs under each of 25 testing conditions. The results showed that rule-of-thumb critical values for assessing the magnitude of misfit were not applicable because the infit and outfit mean square error statistics showed different magnitudes of variability over testing conditions and the standardized fit statistics did not exactly follow the standard normal distribution. Further, they also do not share the same critical range for the item and person misfit. Based on the results of the study, the bootstrapped CIs can be used to identify misfitting items or persons as they offer a reasonable alternative solution, especially when the distributions of the infit and outfit statistics are not well known and depend on sample size. © The Author(s) 2016.

An operational definition of a statistically meaningful trend.

PubMed

Bryhn, Andreas C; Dimberg, Peter H

2011-04-28

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

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia.

PubMed

Park, Hae-Jeong; Kwon, Jun Soo; Youn, Tak; Pae, Ji Soo; Kim, Jae-Jin; Kim, Myung-Sun; Ha, Kyoo-Seob

2002-11-01

We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG. Copyright 2002 Wiley-Liss, Inc.

Testing for independence in J×K contingency tables with complex sample survey data.

PubMed

Lipsitz, Stuart R; Fitzmaurice, Garrett M; Sinha, Debajyoti; Hevelone, Nathanael; Giovannucci, Edward; Hu, Jim C

2015-09-01

The test of independence of row and column variables in a (J×K) contingency table is a widely used statistical test in many areas of application. For complex survey samples, use of the standard Pearson chi-squared test is inappropriate due to correlation among units within the same cluster. Rao and Scott (1981, Journal of the American Statistical Association 76, 221-230) proposed an approach in which the standard Pearson chi-squared statistic is multiplied by a design effect to adjust for the complex survey design. Unfortunately, this test fails to exist when one of the observed cell counts equals zero. Even with the large samples typical of many complex surveys, zero cell counts can occur for rare events, small domains, or contingency tables with a large number of cells. Here, we propose Wald and score test statistics for independence based on weighted least squares estimating equations. In contrast to the Rao-Scott test statistic, the proposed Wald and score test statistics always exist. In simulations, the score test is found to perform best with respect to type I error. The proposed method is motivated by, and applied to, post surgical complications data from the United States' Nationwide Inpatient Sample (NIS) complex survey of hospitals in 2008. © 2015, The International Biometric Society.

Prostate Cancer Research Training in Health Disparities for Undergraduates (PCaRT)

DTIC Science & Technology

2011-03-01

objective is to use statistical methods to evaluate the role of meat , fish, The role of meat , fish and eggs in prostate cancer risk among African-American...The role of meat , fish, eggs and diary products in prostate cancer risk among African-Americans. (Poster) 5. Robertino Simpson, Fisk University...Navigator Lovell A. Jones, Ph.D. * Research Ethics Dr. C. Freund Hazard Communication Standard Training Mr. D. Powell Blood Borne Pathogen Standard

Heavy flavor decay of Zγ at CDF

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

Timothy M. Harrington-Taber

2013-01-01

Diboson production is an important and frequently measured parameter of the Standard Model. This analysis considers the previously neglected pmore » $$\\bar{p}$$ →Z γ→ b$$\\bar{b}$$ channel, as measured at the Collider Detector at Fermilab. Using the entire Tevatron Run II dataset, the measured result is consistent with Standard Model predictions, but the statistical error associated with this method of measurement limits the strength of this correlation.« less

A direct sensitivity approach to predict hourly ozone resulting from compliance with the National Ambient Air Quality Standard.

PubMed

Simon, Heather; Baker, Kirk R; Akhtar, Farhan; Napelenok, Sergey L; Possiel, Norm; Wells, Benjamin; Timin, Brian

2013-03-05

In setting primary ambient air quality standards, the EPA's responsibility under the law is to establish standards that protect public health. As part of the current review of the ozone National Ambient Air Quality Standard (NAAQS), the US EPA evaluated the health exposure and risks associated with ambient ozone pollution using a statistical approach to adjust recent air quality to simulate just meeting the current standard level, without specifying emission control strategies. One drawback of this purely statistical concentration rollback approach is that it does not take into account spatial and temporal heterogeneity of ozone response to emissions changes. The application of the higher-order decoupled direct method (HDDM) in the community multiscale air quality (CMAQ) model is discussed here to provide an example of a methodology that could incorporate this variability into the risk assessment analyses. Because this approach includes a full representation of the chemical production and physical transport of ozone in the atmosphere, it does not require assumed background concentrations, which have been applied to constrain estimates from past statistical techniques. The CMAQ-HDDM adjustment approach is extended to measured ozone concentrations by determining typical sensitivities at each monitor location and hour of the day based on a linear relationship between first-order sensitivities and hourly ozone values. This approach is demonstrated by modeling ozone responses for monitor locations in Detroit and Charlotte to domain-wide reductions in anthropogenic NOx and VOCs emissions. As seen in previous studies, ozone response calculated using HDDM compared well to brute-force emissions changes up to approximately a 50% reduction in emissions. A new stepwise approach is developed here to apply this method to emissions reductions beyond 50% allowing for the simulation of more stringent reductions in ozone concentrations. Compared to previous rollback methods, this application of modeled sensitivities to ambient ozone concentrations provides a more realistic spatial response of ozone concentrations at monitors inside and outside the urban core and at hours of both high and low ozone concentrations.

Statistical mechanics of broadcast channels using low-density parity-check codes.

PubMed

Nakamura, Kazutaka; Kabashima, Yoshiyuki; Morelos-Zaragoza, Robert; Saad, David

2003-03-01

We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.

A new exact and more powerful unconditional test of no treatment effect from binary matched pairs.

PubMed

Lloyd, Chris J

2008-09-01

We consider the problem of testing for a difference in the probability of success from matched binary pairs. Starting with three standard inexact tests, the nuisance parameter is first estimated and then the residual dependence is eliminated by maximization, producing what I call an E+M P-value. The E+M P-value based on McNemar's statistic is shown numerically to dominate previous suggestions, including partially maximized P-values as described in Berger and Sidik (2003, Statistical Methods in Medical Research 12, 91-108). The latter method, however, may have computational advantages for large samples.

A Method of Relating General Circulation Model Simulated Climate to the Observed Local Climate. Part I: Seasonal Statistics.

NASA Astrophysics Data System (ADS)

Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David

1990-10-01

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

Conceptual and statistical problems associated with the use of diversity indices in ecology.

PubMed

Barrantes, Gilbert; Sandoval, Luis

2009-09-01

Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.

Brain fingerprinting field studies comparing P300-MERMER and P300 brainwave responses in the detection of concealed information.

PubMed

Farwell, Lawrence A; Richardson, Drew C; Richardson, Graham M

2013-08-01

Brain fingerprinting detects concealed information stored in the brain by measuring brainwave responses. We compared P300 and P300-MERMER event-related brain potentials for error rate/accuracy and statistical confidence in four field/real-life studies. 76 tests detected presence or absence of information regarding (1) real-life events including felony crimes; (2) real crimes with substantial consequences (either a judicial outcome, i.e., evidence admitted in court, or a $100,000 reward for beating the test); (3) knowledge unique to FBI agents; and (4) knowledge unique to explosives (EOD/IED) experts. With both P300 and P300-MERMER, error rate was 0 %: determinations were 100 % accurate, no false negatives or false positives; also no indeterminates. Countermeasures had no effect. Median statistical confidence for determinations was 99.9 % with P300-MERMER and 99.6 % with P300. Brain fingerprinting methods and scientific standards for laboratory and field applications are discussed. Major differences in methods that produce different results are identified. Markedly different methods in other studies have produced over 10 times higher error rates and markedly lower statistical confidences than those of these, our previous studies, and independent replications. Data support the hypothesis that accuracy, reliability, and validity depend on following the brain fingerprinting scientific standards outlined herein.

The impact of a scheduling change on ninth grade high school performance on biology benchmark exams and the California Standards Test

NASA Astrophysics Data System (ADS)

Leonardi, Marcelo

The primary purpose of this study was to examine the impact of a scheduling change from a trimester 4x4 block schedule to a modified hybrid schedule on student achievement in ninth grade biology courses. This study examined the impact of the scheduling change on student achievement through teacher created benchmark assessments in Genetics, DNA, and Evolution and on the California Standardized Test in Biology. The secondary purpose of this study examined the ninth grade biology teacher perceptions of ninth grade biology student achievement. Using a mixed methods research approach, data was collected both quantitatively and qualitatively as aligned to research questions. Quantitative methods included gathering data from departmental benchmark exams and California Standardized Test in Biology and conducting multiple analysis of covariance and analysis of covariance to determine significance differences. Qualitative methods include journal entries questions and focus group interviews. The results revealed a statistically significant increase in scores on both the DNA and Evolution benchmark exams. DNA and Evolution benchmark exams showed significant improvements from a change in scheduling format. The scheduling change was responsible for 1.5% of the increase in DNA benchmark scores and 2% of the increase in Evolution benchmark scores. The results revealed a statistically significant decrease in scores on the Genetics Benchmark exam as a result of the scheduling change. The scheduling change was responsible for 1% of the decrease in Genetics benchmark scores. The results also revealed a statistically significant increase in scores on the CST Biology exam. The scheduling change was responsible for .7% of the increase in CST Biology scores. Results of the focus group discussions indicated that all teachers preferred the modified hybrid schedule over the trimester schedule and that it improved student achievement.

Approaches for estimating minimal clinically important differences in systemic lupus erythematosus.

PubMed

Rai, Sharan K; Yazdany, Jinoos; Fortin, Paul R; Aviña-Zubieta, J Antonio

2015-06-03

A minimal clinically important difference (MCID) is an important concept used to determine whether a medical intervention improves perceived outcomes in patients. Prior to the introduction of the concept in 1989, studies focused primarily on statistical significance. As most recent clinical trials in systemic lupus erythematosus (SLE) have failed to show significant effects, determining a clinically relevant threshold for outcome scores (that is, the MCID) of existing instruments may be critical for conducting and interpreting meaningful clinical trials as well as for facilitating the establishment of treatment recommendations for patients. To that effect, methods to determine the MCID can be divided into two well-defined categories: distribution-based and anchor-based approaches. Distribution-based approaches are based on statistical characteristics of the obtained samples. There are various methods within the distribution-based approach, including the standard error of measurement, the standard deviation, the effect size, the minimal detectable change, the reliable change index, and the standardized response mean. Anchor-based approaches compare the change in a patient-reported outcome to a second, external measure of change (that is, one that is more clearly understood, such as a global assessment), which serves as the anchor. Finally, the Delphi technique can be applied as an adjunct to defining a clinically important difference. Despite an abundance of methods reported in the literature, little work in MCID estimation has been done in the context of SLE. As the MCID can help determine the effect of a given therapy on a patient and add meaning to statistical inferences made in clinical research, we believe there ought to be renewed focus on this area. Here, we provide an update on the use of MCIDs in clinical research, review some of the work done in this area in SLE, and propose an agenda for future research.

Design and Test of Pseudorandom Number Generator Using a Star Network of Lorenz Oscillators

NASA Astrophysics Data System (ADS)

Cho, Kenichiro; Miyano, Takaya

We have recently developed a chaos-based stream cipher based on augmented Lorenz equations as a star network of Lorenz subsystems. In our method, the augmented Lorenz equations are used as a pseudorandom number generator. In this study, we propose a new method based on the augmented Lorenz equations for generating binary pseudorandom numbers and evaluate its security using the statistical tests of SP800-22 published by the National Institute for Standards and Technology in comparison with the performances of other chaotic dynamical models used as binary pseudorandom number generators. We further propose a faster version of the proposed method and evaluate its security using the statistical tests of TestU01 published by L’Ecuyer and Simard.

Test Statistics and Confidence Intervals to Establish Noninferiority between Treatments with Ordinal Categorical Data.

PubMed

Zhang, Fanghong; Miyaoka, Etsuo; Huang, Fuping; Tanaka, Yutaka

2015-01-01

The problem for establishing noninferiority is discussed between a new treatment and a standard (control) treatment with ordinal categorical data. A measure of treatment effect is used and a method of specifying noninferiority margin for the measure is provided. Two Z-type test statistics are proposed where the estimation of variance is constructed under the shifted null hypothesis using U-statistics. Furthermore, the confidence interval and the sample size formula are given based on the proposed test statistics. The proposed procedure is applied to a dataset from a clinical trial. A simulation study is conducted to compare the performance of the proposed test statistics with that of the existing ones, and the results show that the proposed test statistics are better in terms of the deviation from nominal level and the power.

Reducing the standard deviation in multiple-assay experiments where the variation matters but the absolute value does not.

PubMed

Echenique-Robba, Pablo; Nelo-Bazán, María Alejandra; Carrodeguas, José A

2013-01-01

When the value of a quantity x for a number of systems (cells, molecules, people, chunks of metal, DNA vectors, so on) is measured and the aim is to replicate the whole set again for different trials or assays, despite the efforts for a near-equal design, scientists might often obtain quite different measurements. As a consequence, some systems' averages present standard deviations that are too large to render statistically significant results. This work presents a novel correction method of a very low mathematical and numerical complexity that can reduce the standard deviation of such results and increase their statistical significance. Two conditions are to be met: the inter-system variations of x matter while its absolute value does not, and a similar tendency in the values of x must be present in the different assays (or in other words, the results corresponding to different assays must present a high linear correlation). We demonstrate the improvements this method offers with a cell biology experiment, but it can definitely be applied to any problem that conforms to the described structure and requirements and in any quantitative scientific field that deals with data subject to uncertainty.

Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.

PubMed

Austin, Peter C

2016-12-30

Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Study on the criteria for assessing skull-face correspondence in craniofacial superimposition.

PubMed

Ibáñez, Oscar; Valsecchi, Andrea; Cavalli, Fabio; Huete, María Isabel; Campomanes-Alvarez, Blanca Rosario; Campomanes-Alvarez, Carmen; Vicente, Ricardo; Navega, David; Ross, Ann; Wilkinson, Caroline; Jankauskas, Rimantas; Imaizumi, Kazuhiko; Hardiman, Rita; Jayaprakash, Paul Thomas; Ruiz, Elena; Molinero, Francisco; Lestón, Patricio; Veselovskaya, Elizaveta; Abramov, Alexey; Steyn, Maryna; Cardoso, Joao; Humpire, Daniel; Lusnig, Luca; Gibelli, Daniele; Mazzarelli, Debora; Gaudio, Daniel; Collini, Federica; Damas, Sergio

2016-11-01

Craniofacial superimposition has the potential to be used as an identification method when other traditional biological techniques are not applicable due to insufficient quality or absence of ante-mortem and post-mortem data. Despite having been used in many countries as a method of inclusion and exclusion for over a century it lacks standards. Thus, the purpose of this research is to provide forensic practitioners with standard criteria for analysing skull-face relationships. Thirty-seven experts from 16 different institutions participated in this study, which consisted of evaluating 65 criteria for assessing skull-face anatomical consistency on a sample of 24 different skull-face superimpositions. An unbiased statistical analysis established the most objective and discriminative criteria. Results did not show strong associations, however, important insights to address lack of standards were provided. In addition, a novel methodology for understanding and standardizing identification methods based on the observation of morphological patterns has been proposed. Crown Copyright © 2016. Published by Elsevier Ireland Ltd. All rights reserved.

RAId_aPS: MS/MS Analysis with Multiple Scoring Functions and Spectrum-Specific Statistics

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

2010-01-01

Statistically meaningful comparison/combination of peptide identification results from various search methods is impeded by the lack of a universal statistical standard. Providing an -value calibration protocol, we demonstrated earlier the feasibility of translating either the score or heuristic -value reported by any method into the textbook-defined -value, which may serve as the universal statistical standard. This protocol, although robust, may lose spectrum-specific statistics and might require a new calibration when changes in experimental setup occur. To mitigate these issues, we developed a new MS/MS search tool, RAId_aPS, that is able to provide spectrum-specific -values for additive scoring functions. Given a selection of scoring functions out of RAId score, K-score, Hyperscore and XCorr, RAId_aPS generates the corresponding score histograms of all possible peptides using dynamic programming. Using these score histograms to assign -values enables a calibration-free protocol for accurate significance assignment for each scoring function. RAId_aPS features four different modes: (i) compute the total number of possible peptides for a given molecular mass range, (ii) generate the score histogram given a MS/MS spectrum and a scoring function, (iii) reassign -values for a list of candidate peptides given a MS/MS spectrum and the scoring functions chosen, and (iv) perform database searches using selected scoring functions. In modes (iii) and (iv), RAId_aPS is also capable of combining results from different scoring functions using spectrum-specific statistics. The web link is http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/raid_aps/index.html. Relevant binaries for Linux, Windows, and Mac OS X are available from the same page. PMID:21103371

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

PubMed

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

2018-01-01

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

Flow Cytometry of Human Primary Epidermal and Follicular Keratinocytes

PubMed Central

Gragnani, Alfredo; Ipolito, Michelle Zampieri; Sobral, Christiane S; Brunialti, Milena Karina Coló; Salomão, Reinaldo; Ferreira, Lydia Masako

2008-01-01

Objective: The aim of this study was to characterize using flow cytometry cultured human primary keratinocytes isolated from the epidermis and hair follicles by different methods. Methods: Human keratinocytes derived from discarded fragments of total skin and scalp hair follicles from patients who underwent plastic surgery in the Plastic Surgery Division at UNIFESP were used. The epidermal keratinocytes were isolated by using 3 different methods: the standard method, upon exposure to trypsin for 30 minutes; the second, by treatment with dispase for 18 hours and with trypsin for 10 minutes; and the third, by treatment with dispase for 18 hours and with trypsin for 30 minutes. Follicular keratinocytes were isolated using the standard method. Results: On comparing the group treated with dispase for 18 hours and with trypsin for 10 minutes with the group treated with dispase for 18 hours and with trypsin for 30 minutes, it was observed that the first group presented the largest number of viable cells, the smallest number of cells in late apoptosis and necrosis with statistical significance, and no difference in apoptosis. When we compared the group treated with dispase for 18 hours and with trypsin for 10 minutes with the group treated with trypsin, the first group presented the largest number of viable cells, the smallest number of cells in apoptosis with statistical significance, and no difference in late apoptosis and necrosis. When we compared the results of the group treated with dispase for 18 hours and with trypsin for 10 minutes with the results for follical isolation, there was a statistical difference in apoptosis and viable cells. Conclusion: The isolation method of treatment with dispase for 18 hours and with trypsin for 10 minutes produced the largest number of viable cells and the smallest number of cells in apoptosis/necrosis. PMID:18350110

Integrating Formal Methods and Testing 2002

NASA Technical Reports Server (NTRS)

Cukic, Bojan

2002-01-01

Traditionally, qualitative program verification methodologies and program testing are studied in separate research communities. None of them alone is powerful and practical enough to provide sufficient confidence in ultra-high reliability assessment when used exclusively. Significant advances can be made by accounting not only tho formal verification and program testing. but also the impact of many other standard V&V techniques, in a unified software reliability assessment framework. The first year of this research resulted in the statistical framework that, given the assumptions on the success of the qualitative V&V and QA procedures, significantly reduces the amount of testing needed to confidently assess reliability at so-called high and ultra-high levels (10-4 or higher). The coming years shall address the methodologies to realistically estimate the impacts of various V&V techniques to system reliability and include the impact of operational risk to reliability assessment. Combine formal correctness verification, process and product metrics, and other standard qualitative software assurance methods with statistical testing with the aim of gaining higher confidence in software reliability assessment for high-assurance applications. B) Quantify the impact of these methods on software reliability. C) Demonstrate that accounting for the effectiveness of these methods reduces the number of tests needed to attain certain confidence level. D) Quantify and justify the reliability estimate for systems developed using various methods.

A comparison of data-driven groundwater vulnerability assessment methods

USGS Publications Warehouse

Sorichetta, Alessandro; Ballabio, Cristiano; Masetti, Marco; Robinson, Gilpin R.; Sterlacchini, Simone

2013-01-01

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations.

PubMed

Negeri, Zelalem F; Shaikh, Mateen; Beyene, Joseph

2018-05-11

Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Methods for estimating low-flow statistics for Massachusetts streams

USGS Publications Warehouse

Ries, Kernell G.; Friesz, Paul J.

2000-01-01

Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The streamgaging stations had from 2 to 81 years of record, with a mean record length of 37 years. The low-flow partial-record stations had from 8 to 36 streamflow measurements, with a median of 14 measurements. All basin characteristics were determined from digital map data. The basin characteristics that were statistically significant in most of the final regression equations were drainage area, the area of stratified-drift deposits per unit of stream length plus 0.1, mean basin slope, and an indicator variable that was 0 in the eastern region and 1 in the western region of Massachusetts. The equations were developed by use of weighted-least-squares regression analyses, with weights assigned proportional to the years of record and inversely proportional to the variances of the streamflow statistics for the stations. Standard errors of prediction ranged from 70.7 to 17.5 percent for the equations to predict the 7-day, 10-year low flow and 50-percent duration flow, respectively. The equations are not applicable for use in the Southeast Coastal region of the State, or where basin characteristics for the selected ungaged site are outside the ranges of those for the stations used in the regression analyses. A World Wide Web application was developed that provides streamflow statistics for data collection stations from a data base and for ungaged sites by measuring the necessary basin characteristics for the site and solving the regression equations. Output provided by the Web application for ungaged sites includes a map of the drainage-basin boundary determined for the site, the measured basin characteristics, the estimated streamflow statistics, and 90-percent prediction intervals for the estimates. An equation is provided for combining regression and correlation estimates to obtain improved estimates of the streamflow statistics for low-flow partial-record stations. An equation is also provided for combining regression and drainage-area ratio estimates to obtain improved e

Comparison of methods for determination of total oil sands-derived naphthenic acids in water samples.

PubMed

Hughes, Sarah A; Huang, Rongfu; Mahaffey, Ashley; Chelme-Ayala, Pamela; Klamerth, Nikolaus; Meshref, Mohamed N A; Ibrahim, Mohamed D; Brown, Christine; Peru, Kerry M; Headley, John V; Gamal El-Din, Mohamed

2017-11-01

There are several established methods for the determination of naphthenic acids (NAs) in waters associated with oil sands mining operations. Due to their highly complex nature, measured concentration and composition of NAs vary depending on the method used. This study compared different common sample preparation techniques, analytical instrument methods, and analytical standards to measure NAs in groundwater and process water samples collected from an active oil sands operation. In general, the high- and ultrahigh-resolution methods, namely high performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOF-MS) and Orbitrap mass spectrometry (Orbitrap-MS), were within an order of magnitude of the Fourier transform infrared spectroscopy (FTIR) methods. The gas chromatography mass spectrometry (GC-MS) methods consistently had the highest NA concentrations and greatest standard error. Total NAs concentration was not statistically different between sample preparation of solid phase extraction and liquid-liquid extraction. Calibration standards influenced quantitation results. This work provided a comprehensive understanding of the inherent differences in the various techniques available to measure NAs and hence the potential differences in measured amounts of NAs in samples. Results from this study will contribute to the analytical method standardization for NA analysis in oil sands related water samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Utilization of Statistical Data and Domain Knowledge in Complex Cases.

PubMed

Zhang, Qin; Yao, Quanying

2018-05-01

The dynamic uncertain causality graph (DUCG) is a newly presented framework for uncertain causality representation and probabilistic reasoning. It has been successfully applied to online fault diagnoses of large, complex industrial systems, and decease diagnoses. This paper extends the DUCG to model more complex cases than what could be previously modeled, e.g., the case in which statistical data are in different groups with or without overlap, and some domain knowledge and actions (new variables with uncertain causalities) are introduced. In other words, this paper proposes to use -mode, -mode, and -mode of the DUCG to model such complex cases and then transform them into either the standard -mode or the standard -mode. In the former situation, if no directed cyclic graph is involved, the transformed result is simply a Bayesian network (BN), and existing inference methods for BNs can be applied. In the latter situation, an inference method based on the DUCG is proposed. Examples are provided to illustrate the methodology.

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

USGS Publications Warehouse

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Methods for estimating selected low-flow frequency statistics for unregulated streams in Kentucky

USGS Publications Warehouse

Martin, Gary R.; Arihood, Leslie D.

2010-01-01

This report provides estimates of, and presents methods for estimating, selected low-flow frequency statistics for unregulated streams in Kentucky including the 30-day mean low flows for recurrence intervals of 2 and 5 years (30Q2 and 30Q5) and the 7-day mean low flows for recurrence intervals of 5, 10, and 20 years (7Q2, 7Q10, and 7Q20). Estimates of these statistics are provided for 121 U.S. Geological Survey streamflow-gaging stations with data through the 2006 climate year, which is the 12-month period ending March 31 of each year. Data were screened to identify the periods of homogeneous, unregulated flows for use in the analyses. Logistic-regression equations are presented for estimating the annual probability of the selected low-flow frequency statistics being equal to zero. Weighted-least-squares regression equations were developed for estimating the magnitude of the nonzero 30Q2, 30Q5, 7Q2, 7Q10, and 7Q20 low flows. Three low-flow regions were defined for estimating the 7-day low-flow frequency statistics. The explicit explanatory variables in the regression equations include total drainage area and the mapped streamflow-variability index measured from a revised statewide coverage of this characteristic. The percentage of the station low-flow statistics correctly classified as zero or nonzero by use of the logistic-regression equations ranged from 87.5 to 93.8 percent. The average standard errors of prediction of the weighted-least-squares regression equations ranged from 108 to 226 percent. The 30Q2 regression equations have the smallest standard errors of prediction, and the 7Q20 regression equations have the largest standard errors of prediction. The regression equations are applicable only to stream sites with low flows unaffected by regulation from reservoirs and local diversions of flow and to drainage basins in specified ranges of basin characteristics. Caution is advised when applying the equations for basins with characteristics near the applicable limits and for basins with karst drainage features.

Preparation of fatty acid methyl esters for gas-chromatographic analysis of marine lipids: insight studies.

PubMed

Carvalho, Ana P; Malcata, F Xavier

2005-06-29

Assays for fatty acid composition in biological materials are commonly carried out by gas chromatography, after conversion of the lipid material into the corresponding methyl esters (FAME) via suitable derivatization reactions. Quantitative derivatization depends on the type of catalyst and processing conditions employed, as well as the solubility of said sample in the reaction medium. Most literature pertinent to derivatization has focused on differential comparison between alternative methods; although useful to find out the best method for a particular sample, additional studies on factors that may affect each step of FAME preparation are urged. In this work, the influence of various parameters in each step of derivatization reactions was studied, using both cod liver oil and microalgal biomass as model systems. The accuracies of said methodologies were tested via comparison with the AOCS standard method, whereas their reproducibility was assessed by analysis of variance of (replicated) data. Alkaline catalysts generated lower levels of long-chain unsaturated FAME than acidic ones. Among these, acetyl chloride and BF(3) were statistically equivalent to each other. The standard method, which involves alkaline treatment of samples before acidic methylation with BF(3), provided equivalent results when compared with acidic methylation with BF(3) alone. Polarity of the reaction medium was found to be of the utmost importance in the process: intermediate values of polarity [e.g., obtained by a 1:1 (v/v) mixture of methanol with diethyl ether or toluene] provided amounts of extracted polyunsaturated fatty acids statistically higher than those obtained via the standard method.

Same Content, Different Methods: Comparing Lecture, Engaged Classroom, and Simulation.

PubMed

Raleigh, Meghan F; Wilson, Garland Anthony; Moss, David Alan; Reineke-Piper, Kristen A; Walden, Jeffrey; Fisher, Daniel J; Williams, Tracy; Alexander, Christienne; Niceler, Brock; Viera, Anthony J; Zakrajsek, Todd

2018-02-01

There is a push to use classroom technology and active teaching methods to replace didactic lectures as the most prevalent format for resident education. This multisite collaborative cohort study involving nine residency programs across the United States compared a standard slide-based didactic lecture, a facilitated group discussion via an engaged classroom, and a high-fidelity, hands-on simulation scenario for teaching the topic of acute dyspnea. The primary outcome was knowledge retention at 2 to 4 weeks. Each teaching method was assigned to three different residency programs in the collaborative according to local resources. Learning objectives were determined by faculty. Pre- and posttest questions were validated and utilized as a measurement of knowledge retention. Each site administered the pretest, taught the topic of acute dyspnea utilizing their assigned method, and administered a posttest 2 to 4 weeks later. Differences between the groups were compared using paired t-tests. A total of 146 residents completed the posttest, and scores increased from baseline across all groups. The average score increased 6% in the standard lecture group (n=47), 11% in the engaged classroom (n=53), and 9% in the simulation group (n=56). The differences in improvement between engaged classroom and simulation were not statistically significant. Compared to standard lecture, both engaged classroom and high-fidelity simulation were associated with a statistically significant improvement in knowledge retention. Knowledge retention after engaged classroom and high-fidelity simulation did not significantly differ. More research is necessary to determine if different teaching methods result in different levels of comfort and skill with actual patient care.

On-demand Reporting of Risk-adjusted and Smoothed Rates for Quality Profiling in ACS NSQIP.

PubMed

Cohen, Mark E; Liu, Yaoming; Huffman, Kristopher M; Ko, Clifford Y; Hall, Bruce L

2016-12-01

Surgical quality improvement depends on hospitals having accurate and timely information about comparative performance. Profiling accuracy is improved by risk adjustment and shrinkage adjustment to stabilize estimates. These adjustments are included in ACS NSQIP reports, where hospital odds ratios (OR) are estimated using hierarchical models built on contemporaneous data. However, the timeliness of feedback remains an issue. We describe an alternative, nonhierarchical approach, which yields risk- and shrinkage-adjusted rates. In contrast to our "Traditional" NSQIP method, this approach uses preexisting equations, built on historical data, which permits hospitals to have near immediate access to profiling results. We compared our traditional method to this new "on-demand" approach with respect to outlier determinations, kappa statistics, and correlations between logged OR and standardized rates, for 12 models (4 surgical groups by 3 outcomes). When both methods used the same contemporaneous data, there were similar numbers of hospital outliers and correlations between logged OR and standardized rates were high. However, larger differences were observed when the effect of contemporaneous versus historical data was added to differences in statistical methodology. The on-demand, nonhierarchical approach provides results similar to the traditional hierarchical method and offers immediacy, an "over-time" perspective, application to a broader range of models and data subsets, and reporting of more easily understood rates. Although the nonhierarchical method results are now available "on-demand" in a web-based application, the hierarchical approach has advantages, which support its continued periodic publication as the gold standard for hospital profiling in the program.

Validation of a low cost computer-based method for quantification of immunohistochemistry-stained sections.

PubMed

Montgomery, Jill D; Hensler, Heather R; Jacobson, Lisa P; Jenkins, Frank J

2008-07-01

The aim of the present study was to determine if the Alpha DigiDoc RT system would be an effective method of quantifying immunohistochemical staining as compared with a manual counting method, which is considered the gold standard. Two readers were used to count 31 samples by both methods. The results obtained using the Bland-Altman for concordance deemed no statistical difference between the 2 methods. Thus, the Alpha DigiDoc RT system is an effective, low cost method to quantify immunohistochemical data.

In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI.

PubMed

Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

2013-05-15

Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. Published by Elsevier B.V.

Sex Differences in Diabetes Mellitus Mortality Trends in Brazil, 1980-2012

PubMed Central

Brito, Alexandre dos Santos; Pinheiro, Rejane Sobrino; Cabral, Cristiane da Silva; de Camargo, Thais Medina Coeli Rochel

2016-01-01

Aims To investigate the hypothesis that the change from the female predominance of diabetes mellitus to a standard of equality or even male preponderance can already be observed in Brazilian mortality statistics. Methods Data on deaths for which diabetes mellitus was listed as the underlying cause were obtained from the Brazilian Mortality Information System for the years 1980 to 2012. The mortality data were also analyzed according to the multiple causes of death approach from 2001 to 2012. The population data came from the Brazilian Institute of Geography and Statistics. The mortality rates were standardized to the world population. We used a log-linear joinpoint regression to evaluate trends in age-standardized mortality rates (ASMR). Results From 1980 to 2012, we found a marked increment in the diabetes ASMR among Brazilian men and a less sharp increase in the rate among women, with the latter period (2003–2012) showing a slight decrease among women, though it was not statistically significant. Conclusions The results of this study suggest that diabetes mellitus in Brazil has changed from a pattern of higher mortality among women compared to men to equality or even male predominance. PMID:27275600

A practical method of estimating standard error of age in the fission track dating method

USGS Publications Warehouse

Johnson, N.M.; McGee, V.E.; Naeser, C.W.

1979-01-01

A first-order approximation formula for the propagation of error in the fission track age equation is given by PA = C[P2s+P2i+P2??-2rPsPi] 1 2, where PA, Ps, Pi and P?? are the percentage error of age, of spontaneous track density, of induced track density, and of neutron dose, respectively, and C is a constant. The correlation, r, between spontaneous are induced track densities is a crucial element in the error analysis, acting generally to improve the standard error of age. In addition, the correlation parameter r is instrumental is specifying the level of neutron dose, a controlled variable, which will minimize the standard error of age. The results from the approximation equation agree closely with the results from an independent statistical model for the propagation of errors in the fission-track dating method. ?? 1979.

Integrated Data Collection Analysis (IDCA) Program - Statistical Analysis of RDX Standard Data Sets

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

Sandstrom, Mary M.; Brown, Geoffrey W.; Preston, Daniel N.

2015-10-30

The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard. The material was tested as a well-characterized standard several times during the proficiency study to assess differences among participants and the range of results that may arise for well-behaved explosive materials. The analyses show that there are detectable differences among the results from IDCA participants. While these differences are statisticallymore » significant, most of them can be disregarded for comparison purposes to assess potential variability when laboratories attempt to measure identical samples using methods assumed to be nominally the same. The results presented in this report include the average sensitivity results for the IDCA participants and the ranges of values obtained. The ranges represent variation about the mean values of the tests of between 26% and 42%. The magnitude of this variation is attributed to differences in operator, method, and environment as well as the use of different instruments that are also of varying age. The results appear to be a good representation of the broader safety testing community based on the range of methods, instruments, and environments included in the IDCA Proficiency Test.« less

Comparison of measurement methods with a mixed effects procedure accounting for replicated evaluations (COM3PARE): method comparison algorithm implementation for head and neck IGRT positional verification.

PubMed

Roy, Anuradha; Fuller, Clifton D; Rosenthal, David I; Thomas, Charles R

2015-08-28

Comparison of imaging measurement devices in the absence of a gold-standard comparator remains a vexing problem; especially in scenarios where multiple, non-paired, replicated measurements occur, as in image-guided radiotherapy (IGRT). As the number of commercially available IGRT presents a challenge to determine whether different IGRT methods may be used interchangeably, an unmet need conceptually parsimonious and statistically robust method to evaluate the agreement between two methods with replicated observations. Consequently, we sought to determine, using an previously reported head and neck positional verification dataset, the feasibility and utility of a Comparison of Measurement Methods with the Mixed Effects Procedure Accounting for Replicated Evaluations (COM3PARE), a unified conceptual schema and analytic algorithm based upon Roy's linear mixed effects (LME) model with Kronecker product covariance structure in a doubly multivariate set-up, for IGRT method comparison. An anonymized dataset consisting of 100 paired coordinate (X/ measurements from a sequential series of head and neck cancer patients imaged near-simultaneously with cone beam CT (CBCT) and kilovoltage X-ray (KVX) imaging was used for model implementation. Software-suggested CBCT and KVX shifts for the lateral (X), vertical (Y) and longitudinal (Z) dimensions were evaluated for bias, inter-method (between-subject variation), intra-method (within-subject variation), and overall agreement using with a script implementing COM3PARE with the MIXED procedure of the statistical software package SAS (SAS Institute, Cary, NC, USA). COM3PARE showed statistically significant bias agreement and difference in inter-method between CBCT and KVX was observed in the Z-axis (both p - value<0.01). Intra-method and overall agreement differences were noted as statistically significant for both the X- and Z-axes (all p - value<0.01). Using pre-specified criteria, based on intra-method agreement, CBCT was deemed preferable for X-axis positional verification, with KVX preferred for superoinferior alignment. The COM3PARE methodology was validated as feasible and useful in this pilot head and neck cancer positional verification dataset. COM3PARE represents a flexible and robust standardized analytic methodology for IGRT comparison. The implemented SAS script is included to encourage other groups to implement COM3PARE in other anatomic sites or IGRT platforms.

Journal of Air Transportation, Volume 12, No. 1

NASA Technical Reports Server (NTRS)

Bowers, Brent D. (Editor); Kabashkin, Igor (Editor)

2007-01-01

Topics discussed include: a) Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods; b) Financial Comparisons across Different Business Models in the Canadian Airline Industry; c) Carving a Niche for the "No-Frills" Carrier, Air Arabia, in Oil-Rich Skies; d) Situational Leadership in Air Traffic Control; and e) The Very Light Jet Arrives: Stakeholders and Their Perceptions.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

PubMed Central

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

2018-01-01

Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393

Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review.

PubMed

Zaki, Rafdzah; Bulgiba, Awang; Ismail, Roshidi; Ismail, Noor Azina

2012-01-01

Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future.

Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review

PubMed Central

Zaki, Rafdzah; Bulgiba, Awang; Ismail, Roshidi; Ismail, Noor Azina

2012-01-01

Background Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Methodology/Findings Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. Conclusions This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future. PMID:22662248

Comparing generalized ensemble methods for sampling of systems with many degrees of freedom

DOE PAGES

Lincoff, James; Sasmal, Sukanya; Head-Gordon, Teresa

2016-11-03

Here, we compare two standard replica exchange methods using temperature and dielectric constant as the scaling variables for independent replicas against two new corresponding enhanced sampling methods based on non-equilibrium statistical cooling (temperature) or descreening (dielectric). We test the four methods on a rough 1D potential as well as for alanine dipeptide in water, for which their relatively small phase space allows for the ability to define quantitative convergence metrics. We show that both dielectric methods are inferior to the temperature enhanced sampling methods, and in turn show that temperature cool walking (TCW) systematically outperforms the standard temperature replica exchangemore » (TREx) method. We extend our comparisons of the TCW and TREx methods to the 5 residue met-enkephalin peptide, in which we evaluate the Kullback-Leibler divergence metric to show that the rate of convergence between two independent trajectories is faster for TCW compared to TREx. Finally we apply the temperature methods to the 42 residue amyloid-β peptide in which we find non-negligible differences in the disordered ensemble using TCW compared to the standard TREx. All four methods have been made available as software through the OpenMM Omnia software consortium.« less

Comparing generalized ensemble methods for sampling of systems with many degrees of freedom.

PubMed

Lincoff, James; Sasmal, Sukanya; Head-Gordon, Teresa

2016-11-07

We compare two standard replica exchange methods using temperature and dielectric constant as the scaling variables for independent replicas against two new corresponding enhanced sampling methods based on non-equilibrium statistical cooling (temperature) or descreening (dielectric). We test the four methods on a rough 1D potential as well as for alanine dipeptide in water, for which their relatively small phase space allows for the ability to define quantitative convergence metrics. We show that both dielectric methods are inferior to the temperature enhanced sampling methods, and in turn show that temperature cool walking (TCW) systematically outperforms the standard temperature replica exchange (TREx) method. We extend our comparisons of the TCW and TREx methods to the 5 residue met-enkephalin peptide, in which we evaluate the Kullback-Leibler divergence metric to show that the rate of convergence between two independent trajectories is faster for TCW compared to TREx. Finally we apply the temperature methods to the 42 residue amyloid-β peptide in which we find non-negligible differences in the disordered ensemble using TCW compared to the standard TREx. All four methods have been made available as software through the OpenMM Omnia software consortium (http://www.omnia.md/).

Methods in pharmacoepidemiology: a review of statistical analyses and data reporting in pediatric drug utilization studies.

PubMed

Sequi, Marco; Campi, Rita; Clavenna, Antonio; Bonati, Maurizio

2013-03-01

To evaluate the quality of data reporting and statistical methods performed in drug utilization studies in the pediatric population. Drug utilization studies evaluating all drug prescriptions to children and adolescents published between January 1994 and December 2011 were retrieved and analyzed. For each study, information on measures of exposure/consumption, the covariates considered, descriptive and inferential analyses, statistical tests, and methods of data reporting was extracted. An overall quality score was created for each study using a 12-item checklist that took into account the presence of outcome measures, covariates of measures, descriptive measures, statistical tests, and graphical representation. A total of 22 studies were reviewed and analyzed. Of these, 20 studies reported at least one descriptive measure. The mean was the most commonly used measure (18 studies), but only five of these also reported the standard deviation. Statistical analyses were performed in 12 studies, with the chi-square test being the most commonly performed test. Graphs were presented in 14 papers. Sixteen papers reported the number of drug prescriptions and/or packages, and ten reported the prevalence of the drug prescription. The mean quality score was 8 (median 9). Only seven of the 22 studies received a score of ≥10, while four studies received a score of <6. Our findings document that only a few of the studies reviewed applied statistical methods and reported data in a satisfactory manner. We therefore conclude that the methodology of drug utilization studies needs to be improved.

Investigation of interpolation techniques for the reconstruction of the first dimension of comprehensive two-dimensional liquid chromatography-diode array detector data.

PubMed

Allen, Robert C; Rutan, Sarah C

2011-10-31

Simulated and experimental data were used to measure the effectiveness of common interpolation techniques during chromatographic alignment of comprehensive two-dimensional liquid chromatography-diode array detector (LC×LC-DAD) data. Interpolation was used to generate a sufficient number of data points in the sampled first chromatographic dimension to allow for alignment of retention times from different injections. Five different interpolation methods, linear interpolation followed by cross correlation, piecewise cubic Hermite interpolating polynomial, cubic spline, Fourier zero-filling, and Gaussian fitting, were investigated. The fully aligned chromatograms, in both the first and second chromatographic dimensions, were analyzed by parallel factor analysis to determine the relative area for each peak in each injection. A calibration curve was generated for the simulated data set. The standard error of prediction and percent relative standard deviation were calculated for the simulated peak for each technique. The Gaussian fitting interpolation technique resulted in the lowest standard error of prediction and average relative standard deviation for the simulated data. However, upon applying the interpolation techniques to the experimental data, most of the interpolation methods were not found to produce statistically different relative peak areas from each other. While most of the techniques were not statistically different, the performance was improved relative to the PARAFAC results obtained when analyzing the unaligned data. Copyright © 2011 Elsevier B.V. All rights reserved.

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

NASA Astrophysics Data System (ADS)

Maffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, Alessandro

2018-03-01

Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 ns or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20% and 30%, compared to docking scoring or to standard MM-GBSA rescoring.

Connecting Communities to Health Research: Development of the Project CONNECT Minority Research Registry

PubMed Central

Green, Melissa A.; Kim, Mimi M.; Barber, Sharrelle; Odulana, Abedowale A.; Godley, Paul A.; Howard, Daniel L.; Corbie-Smith, Giselle M.

2013-01-01

Introduction Prevention and treatment standards are based on evidence obtained in behavioral and clinical research. However, racial and ethnic minorities remain relatively absent from the science that develops these standards. While investigators have successfully recruited participants for individual studies using tailored recruitment methods, these strategies require considerable time and resources. Research registries, typically developed around a disease or condition, serve as a promising model for a targeted recruitment method to increase minority participation in health research. This study assessed the tailored recruitment methods used to populate a health research registry targeting African-American community members. Methods We describe six recruitment methods applied between September 2004 and October 2008 to recruit members into a health research registry. Recruitment included direct (existing studies, public databases, community outreach) and indirect methods (radio, internet, and email) targeting the general population, local universities, and African American communities. We conducted retrospective analysis of the recruitment by method using descriptive statistics, frequencies, and chi-square statistics. Results During the recruitment period, 608 individuals enrolled in the research registry. The majority of enrollees were African American, female, and in good health. Direct and indirect methods were identified as successful strategies for subgroups. Findings suggest significant associations between recruitment methods and age, presence of existing health condition, prior research participation, and motivation to join the registry. Conclusions A health research registry can be a successful tool to increase minority awareness of research opportunities. Multi-pronged recruitment approaches are needed to reach diverse subpopulations. PMID:23340183

An analytic technique for statistically modeling random atomic clock errors in estimation

NASA Technical Reports Server (NTRS)

Fell, P. J.

1981-01-01

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Statistics of the stochastically forced Lorenz attractor by the Fokker-Planck equation and cumulant expansions.

PubMed

Allawala, Altan; Marston, J B

2016-11-01

We investigate the Fokker-Planck description of the equal-time statistics of the three-dimensional Lorenz attractor with additive white noise. The invariant measure is found by computing the zero (or null) mode of the linear Fokker-Planck operator as a problem of sparse linear algebra. Two variants are studied: a self-adjoint construction of the linear operator and the replacement of diffusion with hyperdiffusion. We also access the low-order statistics of the system by a perturbative expansion in equal-time cumulants. A comparison is made to statistics obtained by the standard approach of accumulation via direct numerical simulation. Theoretical and computational aspects of the Fokker-Planck and cumulant expansion methods are discussed.

Development of modern human subadult age and sex estimation standards using multi-slice computed tomography images from medical examiner's offices

NASA Astrophysics Data System (ADS)

Stock, Michala K.; Stull, Kyra E.; Garvin, Heather M.; Klales, Alexandra R.

2016-10-01

Forensic anthropologists are routinely asked to estimate a biological profile (i.e., age, sex, ancestry and stature) from a set of unidentified remains. In contrast to the abundance of collections and techniques associated with adult skeletons, there is a paucity of modern, documented subadult skeletal material, which limits the creation and validation of appropriate forensic standards. Many are forced to use antiquated methods derived from small sample sizes, which given documented secular changes in the growth and development of children, are not appropriate for application in the medico-legal setting. Therefore, the aim of this project is to use multi-slice computed tomography (MSCT) data from a large, diverse sample of modern subadults to develop new methods to estimate subadult age and sex for practical forensic applications. The research sample will consist of over 1,500 full-body MSCT scans of modern subadult individuals (aged birth to 20 years) obtained from two U.S. medical examiner's offices. Statistical analysis of epiphyseal union scores, long bone osteometrics, and os coxae landmark data will be used to develop modern subadult age and sex estimation standards. This project will result in a database of information gathered from the MSCT scans, as well as the creation of modern, statistically rigorous standards for skeletal age and sex estimation in subadults. Furthermore, the research and methods developed in this project will be applicable to dry bone specimens, MSCT scans, and radiographic images, thus providing both tools and continued access to data for forensic practitioners in a variety of settings.

Statistical analysis of loopy belief propagation in random fields

NASA Astrophysics Data System (ADS)

Yasuda, Muneki; Kataoka, Shun; Tanaka, Kazuyuki

2015-10-01

Loopy belief propagation (LBP), which is equivalent to the Bethe approximation in statistical mechanics, is a message-passing-type inference method that is widely used to analyze systems based on Markov random fields (MRFs). In this paper, we propose a message-passing-type method to analytically evaluate the quenched average of LBP in random fields by using the replica cluster variation method. The proposed analytical method is applicable to general pairwise MRFs with random fields whose distributions differ from each other and can give the quenched averages of the Bethe free energies over random fields, which are consistent with numerical results. The order of its computational cost is equivalent to that of standard LBP. In the latter part of this paper, we describe the application of the proposed method to Bayesian image restoration, in which we observed that our theoretical results are in good agreement with the numerical results for natural images.

Corpus-based Statistical Screening for Phrase Identification

PubMed Central

Kim, Won; Wilbur, W. John

2000-01-01

Purpose: The authors study the extraction of useful phrases from a natural language database by statistical methods. The aim is to leverage human effort by providing preprocessed phrase lists with a high percentage of useful material. Method: The approach is to develop six different scoring methods that are based on different aspects of phrase occurrence. The emphasis here is not on lexical information or syntactic structure but rather on the statistical properties of word pairs and triples that can be obtained from a large database. Measurements: The Unified Medical Language System (UMLS) incorporates a large list of humanly acceptable phrases in the medical field as a part of its structure. The authors use this list of phrases as a gold standard for validating their methods. A good method is one that ranks the UMLS phrases high among all phrases studied. Measurements are 11-point average precision values and precision-recall curves based on the rankings. Result: The authors find of six different scoring methods that each proves effective in identifying UMLS quality phrases in a large subset of MEDLINE. These methods are applicable both to word pairs and word triples. All six methods are optimally combined to produce composite scoring methods that are more effective than any single method. The quality of the composite methods appears sufficient to support the automatic placement of hyperlinks in text at the site of highly ranked phrases. Conclusion: Statistical scoring methods provide a promising approach to the extraction of useful phrases from a natural language database for the purpose of indexing or providing hyperlinks in text. PMID:10984469

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

PubMed Central

2012-01-01

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

DISSCO: direct imputation of summary statistics allowing covariates.

PubMed

Xu, Zheng; Duan, Qing; Yan, Song; Chen, Wei; Li, Mingyao; Lange, Ethan; Li, Yun

2015-08-01

Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates. We analytically show that in the absence of covariates, correlation among association summary statistics is indeed the same as that among the corresponding genotypes, thus serving as a theoretical justification for the recently proposed methods. We continue to prove that in the presence of covariates, correlation among association summary statistics becomes the partial correlation of the corresponding genotypes controlling for covariates. We therefore develop direct imputation of summary statistics allowing covariates (DISSCO). We consider two real-life scenarios where the correlation and partial correlation likely make practical difference: (i) association studies in admixed populations; (ii) association studies in presence of other confounding covariate(s). Application of DISSCO to real datasets under both scenarios shows at least comparable, if not better, performance compared with existing correlation-based methods, particularly for lower frequency variants. For example, DISSCO can reduce the absolute deviation from the truth by 3.9-15.2% for variants with minor allele frequency <5%. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

DECONV-TOOL: An IDL based deconvolution software package

NASA Technical Reports Server (NTRS)

Varosi, F.; Landsman, W. B.

1992-01-01

There are a variety of algorithms for deconvolution of blurred images, each having its own criteria or statistic to be optimized in order to estimate the original image data. Using the Interactive Data Language (IDL), we have implemented the Maximum Likelihood, Maximum Entropy, Maximum Residual Likelihood, and sigma-CLEAN algorithms in a unified environment called DeConv_Tool. Most of the algorithms have as their goal the optimization of statistics such as standard deviation and mean of residuals. Shannon entropy, log-likelihood, and chi-square of the residual auto-correlation are computed by DeConv_Tool for the purpose of determining the performance and convergence of any particular method and comparisons between methods. DeConv_Tool allows interactive monitoring of the statistics and the deconvolved image during computation. The final results, and optionally, the intermediate results, are stored in a structure convenient for comparison between methods and review of the deconvolution computation. The routines comprising DeConv_Tool are available via anonymous FTP through the IDL Astronomy User's Library.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution.

PubMed

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-08

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al . 2012 Proc. R. Soc. A 468 , 1799-1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi-Dirac or Bose-Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas.

Assessment of variations in thermal cycle life data of thermal barrier coated rods

NASA Astrophysics Data System (ADS)

Hendricks, R. C.; McDonald, G.

An analysis of thermal cycle life data for 22 thermal barrier coated (TBC) specimens was conducted. The Zr02-8Y203/NiCrAlY plasma spray coated Rene 41 rods were tested in a Mach 0.3 Jet A/air burner flame. All specimens were subjected to the same coating and subsequent test procedures in an effort to control three parametric groups; material properties, geometry and heat flux. Statistically, the data sample space had a mean of 1330 cycles with a standard deviation of 520 cycles. The data were described by normal or log-normal distributions, but other models could also apply; the sample size must be increased to clearly delineate a statistical failure model. The statistical methods were also applied to adhesive/cohesive strength data for 20 TBC discs of the same composition, with similar results. The sample space had a mean of 9 MPa with a standard deviation of 4.2 MPa.

Assessment of variations in thermal cycle life data of thermal barrier coated rods

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Mcdonald, G.

1981-01-01

An analysis of thermal cycle life data for 22 thermal barrier coated (TBC) specimens was conducted. The Zr02-8Y203/NiCrAlY plasma spray coated Rene 41 rods were tested in a Mach 0.3 Jet A/air burner flame. All specimens were subjected to the same coating and subsequent test procedures in an effort to control three parametric groups; material properties, geometry and heat flux. Statistically, the data sample space had a mean of 1330 cycles with a standard deviation of 520 cycles. The data were described by normal or log-normal distributions, but other models could also apply; the sample size must be increased to clearly delineate a statistical failure model. The statistical methods were also applied to adhesive/cohesive strength data for 20 TBC discs of the same composition, with similar results. The sample space had a mean of 9 MPa with a standard deviation of 4.2 MPa.

Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

PubMed

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

2018-04-01

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

Pattern statistics on Markov chains and sensitivity to parameter estimation

PubMed Central

Nuel, Grégory

2006-01-01

Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). Results: In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation. PMID:17044916

Pattern statistics on Markov chains and sensitivity to parameter estimation.

PubMed

Nuel, Grégory

2006-10-17

In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of sigma, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.

Better Than Counting: Density Profiles from Force Sampling

NASA Astrophysics Data System (ADS)

de las Heras, Daniel; Schmidt, Matthias

2018-05-01

Calculating one-body density profiles in equilibrium via particle-based simulation methods involves counting of events of particle occurrences at (histogram-resolved) space points. Here, we investigate an alternative method based on a histogram of the local force density. Via an exact sum rule, the density profile is obtained with a simple spatial integration. The method circumvents the inherent ideal gas fluctuations. We have tested the method in Monte Carlo, Brownian dynamics, and molecular dynamics simulations. The results carry a statistical uncertainty smaller than that of the standard counting method, reducing therefore the computation time.

[Comparison between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection].

PubMed

Sun, Zong-ke; Wu, Rong; Ding, Pei; Xue, Jin-Rong

2006-07-01

To compare between rapid detection method of enzyme substrate technique and multiple-tube fermentation technique in water coliform bacteria detection. Using inoculated and real water samples to compare the equivalence and false positive rate between two methods. Results demonstrate that enzyme substrate technique shows equivalence with multiple-tube fermentation technique (P = 0.059), false positive rate between the two methods has no statistical difference. It is suggested that enzyme substrate technique can be used as a standard method for water microbiological safety evaluation.

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

NASA Astrophysics Data System (ADS)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)

Comparison of a novel fixation device with standard suturing methods for spinal cord stimulators.

PubMed

Bowman, Richard G; Caraway, David; Bentley, Ishmael

2013-01-01

Spinal cord stimulation is a well-established treatment for chronic neuropathic pain of the trunk or limbs. Currently, the standard method of fixation is to affix the leads of the neuromodulation device to soft tissue, fascia or ligament, through the use of manually tying general suture. A novel semiautomated device is proposed that may be advantageous to the current standard. Comparison testing in an excised caprine spine and simulated bench top model was performed. Three tests were performed: 1) perpendicular pull from fascia of caprine spine; 2) axial pull from fascia of caprine spine; and 3) axial pull from Mylar film. Six samples of each configuration were tested for each scenario. Standard 2-0 Ethibond was compared with a novel semiautomated device (Anulex fiXate). Upon completion of testing statistical analysis was performed for each scenario. For perpendicular pull in the caprine spine, the failure load for standard suture was 8.95 lbs with a standard deviation of 1.39 whereas for fiXate the load was 15.93 lbs with a standard deviation of 2.09. For axial pull in the caprine spine, the failure load for standard suture was 6.79 lbs with a standard deviation of 1.55 whereas for fiXate the load was 12.31 lbs with a standard deviation of 4.26. For axial pull in Mylar film, the failure load for standard suture was 10.87 lbs with a standard deviation of 1.56 whereas for fiXate the load was 19.54 lbs with a standard deviation of 2.24. These data suggest a novel semiautomated device offers a method of fixation that may be utilized in lieu of standard suturing methods as a means of securing neuromodulation devices. Data suggest the novel semiautomated device in fact may provide a more secure fixation than standard suturing methods. © 2012 International Neuromodulation Society.

A statistical method for lung tumor segmentation uncertainty in PET images based on user inference.

PubMed

Zheng, Chaojie; Wang, Xiuying; Feng, Dagan

2015-01-01

PET has been widely accepted as an effective imaging modality for lung tumor diagnosis and treatment. However, standard criteria for delineating tumor boundary from PET are yet to develop largely due to relatively low quality of PET images, uncertain tumor boundary definition, and variety of tumor characteristics. In this paper, we propose a statistical solution to segmentation uncertainty on the basis of user inference. We firstly define the uncertainty segmentation band on the basis of segmentation probability map constructed from Random Walks (RW) algorithm; and then based on the extracted features of the user inference, we use Principle Component Analysis (PCA) to formulate the statistical model for labeling the uncertainty band. We validated our method on 10 lung PET-CT phantom studies from the public RIDER collections [1] and 16 clinical PET studies where tumors were manually delineated by two experienced radiologists. The methods were validated using Dice similarity coefficient (DSC) to measure the spatial volume overlap. Our method achieved an average DSC of 0.878 ± 0.078 on phantom studies and 0.835 ± 0.039 on clinical studies.

Valid statistical inference methods for a case-control study with missing data.

PubMed

Tian, Guo-Liang; Zhang, Chi; Jiang, Xuejun

2018-04-01

The main objective of this paper is to derive the valid sampling distribution of the observed counts in a case-control study with missing data under the assumption of missing at random by employing the conditional sampling method and the mechanism augmentation method. The proposed sampling distribution, called the case-control sampling distribution, can be used to calculate the standard errors of the maximum likelihood estimates of parameters via the Fisher information matrix and to generate independent samples for constructing small-sample bootstrap confidence intervals. Theoretical comparisons of the new case-control sampling distribution with two existing sampling distributions exhibit a large difference. Simulations are conducted to investigate the influence of the three different sampling distributions on statistical inferences. One finding is that the conclusion by the Wald test for testing independency under the two existing sampling distributions could be completely different (even contradictory) from the Wald test for testing the equality of the success probabilities in control/case groups under the proposed distribution. A real cervical cancer data set is used to illustrate the proposed statistical methods.

Using statistical and machine learning to help institutions detect suspicious access to electronic health records.

PubMed

Boxwala, Aziz A; Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs.

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

NASA Astrophysics Data System (ADS)

Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

Correcting for population structure and kinship using the linear mixed model: theory and extensions.

PubMed

Hoffman, Gabriel E

2013-01-01

Population structure and kinship are widespread confounding factors in genome-wide association studies (GWAS). It has been standard practice to include principal components of the genotypes in a regression model in order to account for population structure. More recently, the linear mixed model (LMM) has emerged as a powerful method for simultaneously accounting for population structure and kinship. The statistical theory underlying the differences in empirical performance between modeling principal components as fixed versus random effects has not been thoroughly examined. We undertake an analysis to formalize the relationship between these widely used methods and elucidate the statistical properties of each. Moreover, we introduce a new statistic, effective degrees of freedom, that serves as a metric of model complexity and a novel low rank linear mixed model (LRLMM) to learn the dimensionality of the correction for population structure and kinship, and we assess its performance through simulations. A comparison of the results of LRLMM and a standard LMM analysis applied to GWAS data from the Multi-Ethnic Study of Atherosclerosis (MESA) illustrates how our theoretical results translate into empirical properties of the mixed model. Finally, the analysis demonstrates the ability of the LRLMM to substantially boost the strength of an association for HDL cholesterol in Europeans.

Conventionalism and Methodological Standards in Contending with Skepticism about Uncertainty

NASA Astrophysics Data System (ADS)

Brumble, K. C.

2012-12-01

What it means to measure and interpret confidence and uncertainty in a result is often particular to a specific scientific community and its methodology of verification. Additionally, methodology in the sciences varies greatly across disciplines and scientific communities. Understanding the accuracy of predictions of a particular science thus depends largely upon having an intimate working knowledge of the methods, standards, and conventions utilized and underpinning discoveries in that scientific field. Thus, valid criticism of scientific predictions and discoveries must be conducted by those who are literate in the field in question: they must have intimate working knowledge of the methods of the particular community and of the particular research under question. The interpretation and acceptance of uncertainty is one such shared, community-based convention. In the philosophy of science, this methodological and community-based way of understanding scientific work is referred to as conventionalism. By applying the conventionalism of historian and philosopher of science Thomas Kuhn to recent attacks upon methods of multi-proxy mean temperature reconstructions, I hope to illuminate how climate skeptics and their adherents fail to appreciate the need for community-based fluency in the methodological standards for understanding uncertainty shared by the wider climate science community. Further, I will flesh out a picture of climate science community standards of evidence and statistical argument following the work of philosopher of science Helen Longino. I will describe how failure to appreciate the conventions of professionalism and standards of evidence accepted in the climate science community results in the application of naïve falsification criteria. Appeal to naïve falsification in turn has allowed scientists outside the standards and conventions of the mainstream climate science community to consider themselves and to be judged by climate skeptics as valid critics of particular statistical reconstructions with naïve and misapplied methodological criticism. Examples will include the skeptical responses to multi-proxy mean temperature reconstructions and congressional hearings criticizing the work of Michael Mann et al.'s Hockey Stick.

Connecting communities to health research: development of the Project CONNECT minority research registry.

PubMed

Green, Melissa A; Kim, Mimi M; Barber, Sharrelle; Odulana, Abedowale A; Godley, Paul A; Howard, Daniel L; Corbie-Smith, Giselle M

2013-05-01

Prevention and treatment standards are based on evidence obtained in behavioral and clinical research. However, racial and ethnic minorities remain relatively absent from the science that develops these standards. While investigators have successfully recruited participants for individual studies using tailored recruitment methods, these strategies require considerable time and resources. Research registries, typically developed around a disease or condition, serve as a promising model for a targeted recruitment method to increase minority participation in health research. This study assessed the tailored recruitment methods used to populate a health research registry targeting African-American community members. We describe six recruitment methods applied between September 2004 and October 2008 to recruit members into a health research registry. Recruitment included direct (existing studies, public databases, community outreach) and indirect methods (radio, internet, and email) targeting the general population, local universities, and African American communities. We conducted retrospective analysis of the recruitment by method using descriptive statistics, frequencies, and chi-square statistics. During the recruitment period, 608 individuals enrolled in the research registry. The majority of enrollees were African American, female, and in good health. Direct and indirect methods were identified as successful strategies for subgroups. Findings suggest significant associations between recruitment methods and age, presence of existing health condition, prior research participation, and motivation to join the registry. A health research registry can be a successful tool to increase minority awareness of research opportunities. Multi-pronged recruitment approaches are needed to reach diverse subpopulations. Copyright © 2013. Published by Elsevier Inc.

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

Flow cytometry of human primary epidermal and follicular keratinocytes.

PubMed

Gragnani, Alfredo; Ipolito, Michelle Zampieri; Sobral, Christiane S; Brunialti, Milena Karina Coló; Salomão, Reinaldo; Ferreira, Lydia Masako

2008-02-19

The aim of this study was to characterize using flow cytometry cultured human primary keratinocytes isolated from the epidermis and hair follicles by different methods. Human keratinocytes derived from discarded fragments of total skin and scalp hair follicles from patients who underwent plastic surgery in the Plastic Surgery Division at UNIFESP were used. The epidermal keratinocytes were isolated by using 3 different methods: the standard method, upon exposure to trypsin for 30 minutes; the second, by treatment with dispase for 18 hours and with trypsin for 10 minutes; and the third, by treatment with dispase for 18 hours and with trypsin for 30 minutes. Follicular keratinocytes were isolated using the standard method. On comparing the group treated with dispase for 18 hours and with trypsin for 10 minutes with the group treated with dispase for 18 hours and with trypsin for 30 minutes, it was observed that the first group presented the largest number of viable cells, the smallest number of cells in late apoptosis and necrosis with statistical significance, and no difference in apoptosis. When we compared the group treated with dispase for 18 hours and with trypsin for 10 minutes with the group treated with trypsin, the first group presented the largest number of viable cells, the smallest number of cells in apoptosis with statistical significance, and no difference in late apoptosis and necrosis. When we compared the results of the group treated with dispase for 18 hours and with trypsin for 10 minutes with the results for follical isolation, there was a statistical difference in apoptosis and viable cells. The isolation method of treatment with dispase for 18 hours and with trypsin for 10 minutes produced the largest number of viable cells and the smallest number of cells in apoptosis/necrosis.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Statistics in the pharmacy literature.

PubMed

Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R

2004-09-01

Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.

Interview with Antony John Kunnan on Language Assessment

ERIC Educational Resources Information Center

Nimehchisalem, Vahid

2015-01-01

Antony John Kunnan is a language assessment specialist. His research interests are fairness of tests and testing practice, assessment literacy, research methods and statistics, ethics and standards, and language assessment policy. His most recent publications include a four-volume edited collection of 140 chapters titled "The Companion to…

A Deterministic Annealing Approach to Clustering AIRS Data

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Braverman, Amy; Ruzmaikin, Alexander

2012-01-01

We will examine the validity of means and standard deviations as a basis for climate data products. We will explore the conditions under which these two simple statistics are inadequate summaries of the underlying empirical probability distributions by contrasting them with a nonparametric, method called Deterministic Annealing technique

76 FR 647 - Energy Conservation Program: Test Procedures for Electric Motors and Small Electric Motors

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-05

... determination method (AEDM) for small electric motors, including the statistical requirements to substantiate... restriction to a particular application or type of application; or (2) Standard operating characteristics or... application, and which can be used in most general purpose applications. [[Page 652

How does new evidence change our estimates of probabilities? Carnap's formula revisited

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik; Quintana, Chris

1992-01-01

The formula originally proposed by R. Carnap in his analysis of induction is reviewed and its natural generalization is presented. A situation is considered where the probability of a certain event is determined without using standard statistical methods due to the lack of observation.

Multiple Contact Dates and SARS Incubation Periods

PubMed Central

2004-01-01

Many severe acute respiratory syndrome (SARS) patients have multiple possible incubation periods due to multiple contact dates. Multiple contact dates cannot be used in standard statistical analytic techniques, however. I present a simple spreadsheet-based method that uses multiple contact dates to calculate the possible incubation periods of SARS. PMID:15030684

A comparison of two surveillance systems for deaths related to violent injury

PubMed Central

Comstock, R; Mallonee, S; Jordan, F

2005-01-01

Objective: To compare violent injury death reporting by the statewide Medical Examiner and Vital Statistics Office surveillance systems in Oklahoma. Methods: Using a standard study definition for violent injury death, the sensitivity and predictive value positive (PVP) of the Medical Examiner and Vital Statistics violent injury death reporting systems in Oklahoma in 2001 were evaluated. Results: Altogether 776 violent injury deaths were identified (violent injury death rate: 22.4 per 100 000 population) including 519 (66.9%) suicides, 248 (32.0%) homicides, and nine (1.2%) unintentional firearm deaths. The Medical Examiner system over-reported homicides and the Vital Statistics system under-reported homicides and suicides and over-reported unintentional firearm injury deaths. When compared with the standard, the Medical Examiner and Vital Statistics systems had sensitivities of 99.2% and 90.7% (respectively) and PVPs of 95.0% and 99.1% for homicide, sensitivities of 99.2% and 93.1% and PVPs of 100% and 99.0% for suicide, and sensitivities of 100% and 100% and PVPs of 100% and 31.0% for unintentional firearm deaths. Conclusions: Both the Vital Statistics and Medical Examiner systems contain valuable data and when combined can work synergistically to provide violent injury death information while also serving as quality control checks for each other. Preventable errors within both systems can be reduced by increasing training, addressing sources of human error, and expanding computer quality assurance programming. A standardized nationwide Medical Examiners' coding system and a national violent death reporting system that merges multiple public health and criminal justice datasets would enhance violent injury surveillance and prevention efforts. PMID:15691992

Robust tissue-air volume segmentation of MR images based on the statistics of phase and magnitude: Its applications in the display of susceptibility-weighted imaging of the brain.

PubMed

Du, Yiping P; Jin, Zhaoyang

2009-10-01

To develop a robust algorithm for tissue-air segmentation in magnetic resonance imaging (MRI) using the statistics of phase and magnitude of the images. A multivariate measure based on the statistics of phase and magnitude was constructed for tissue-air volume segmentation. The standard deviation of first-order phase difference and the standard deviation of magnitude were calculated in a 3 x 3 x 3 kernel in the image domain. To improve differentiation accuracy, the uniformity of phase distribution in the kernel was also calculated and linear background phase introduced by field inhomogeneity was corrected. The effectiveness of the proposed volume segmentation technique was compared to a conventional approach that uses the magnitude data alone. The proposed algorithm was shown to be more effective and robust in volume segmentation in both synthetic phantom and susceptibility-weighted images of human brain. Using our proposed volume segmentation method, veins in the peripheral regions of the brain were well depicted in the minimum-intensity projection of the susceptibility-weighted images. Using the additional statistics of phase, tissue-air volume segmentation can be substantially improved compared to that using the statistics of magnitude data alone. (c) 2009 Wiley-Liss, Inc.

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

PubMed

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

2017-11-01

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

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

Evaluating concentration estimation errors in ELISA microarray experiments

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

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

Statistical segmentation of multidimensional brain datasets

NASA Astrophysics Data System (ADS)

Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

Jets and Metastability in Quantum Mechanics and Quantum Field Theory

NASA Astrophysics Data System (ADS)

Farhi, David

I give a high level overview of the state of particle physics in the introduction, accessible without any background in the field. I discuss improvements of theoretical and statistical methods used for collider physics. These include telescoping jets, a statistical method which was claimed to allow jet searches to increase their sensitivity by considering several interpretations of each event. We find that indeed multiple interpretations extend the power of searches, for both simple counting experiments and powerful multivariate fitting experiments, at least for h → bb¯ at the LHC. Then I propose a method for automation of background calculations using SCET by appropriating the technology of Monte Carlo generators such as MadGraph. In the third chapter I change gears and discuss the future of the universe. It has long been known that our pocket of the standard model is unstable; there is a lower-energy configuration in a remote part of the configuration space, to which our universe will, eventually, decay. While the timescales involved are on the order of 10400 years (depending on how exactly one counts) and thus of no immediate worry, I discuss the shortcomings of the standard methods and propose a more physically motivated derivation for the decay rate. I then make various observations about the structure of decays in quantum field theory.

Wavelength dependence of position angle in polarization standards

NASA Astrophysics Data System (ADS)

Dolan, J. F.; Tapia, S.

1986-08-01

Eleven of the 15 stars on Serkowski's (1974) list of "Standard Stars with Large Interstellar Polarization" were investigated to determine whether the orientation of the plane of their linear polarization showed any dependence on wavelength. Nine of the eleven stars exhibited a statistically significant wavelength dependence of position angle when measured with an accuracy of ≡0°.1 standard deviation. For the majority of these stars, the effect is caused primarily by intrinsic polarization. The calibration of polarimeter position angles in a celestial coordinate frame must evidently be done at the 0°.1 level of accuracy by using only carefully selected standard stars or by using other astronomical or laboratory methods.

Wavelength dependence of position angle in polarization standards. [of stellar systems

NASA Technical Reports Server (NTRS)

Dolan, J. F.; Tapia, S.

1986-01-01

Eleven of the 15 stars on Serkowski's (1974) list of 'Standard Stars with Large Interstellar Polarization' were investigated to determine whether the orientation of the plane of their linear polarization showed any dependence on wavelength. Nine of the eleven stars exhibited a statistically significant wavelength dependence of position angle when measured with an accuracy of about 0.1 deg standard deviation. For the majority of these stars, the effect is caused primarily by intrinsic polarization. The calibration of polarimeter position angles in a celestial coordinate frame must evidently be done at the 0.1 deg level of accuracy by using only carefully selected standard stars or by using other astronomical or laboratory methods.

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

A model for indexing medical documents combining statistical and symbolic knowledge.

PubMed

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-10-11

To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.

The application of the statistical classifying models for signal evaluation of the gas sensors analyzing mold contamination of the building materials

NASA Astrophysics Data System (ADS)

Majerek, Dariusz; Guz, Łukasz; Suchorab, Zbigniew; Łagód, Grzegorz; Sobczuk, Henryk

2017-07-01

Mold that develops on moistened building barriers is a major cause of the Sick Building Syndrome (SBS). Fungal contamination is normally evaluated using standard biological methods which are time-consuming and require a lot of manual labor. Fungi emit Volatile Organic Compounds (VOC) that can be detected in the indoor air using several techniques of detection e.g. chromatography. VOCs can be also detected using gas sensors arrays. All array sensors generate particular voltage signals that ought to be analyzed using properly selected statistical methods of interpretation. This work is focused on the attempt to apply statistical classifying models in evaluation of signals from gas sensors matrix to analyze the air sampled from the headspace of various types of the building materials at different level of contamination but also clean reference materials.

Tipping points in the arctic: eyeballing or statistical significance?

PubMed

Carstensen, Jacob; Weydmann, Agata

2012-02-01

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

A Science and Risk-Based Pragmatic Methodology for Blend and Content Uniformity Assessment.

PubMed

Sayeed-Desta, Naheed; Pazhayattil, Ajay Babu; Collins, Jordan; Doshi, Chetan

2018-04-01

This paper describes a pragmatic approach that can be applied in assessing powder blend and unit dosage uniformity of solid dose products at Process Design, Process Performance Qualification, and Continued/Ongoing Process Verification stages of the Process Validation lifecycle. The statistically based sampling, testing, and assessment plan was developed due to the withdrawal of the FDA draft guidance for industry "Powder Blends and Finished Dosage Units-Stratified In-Process Dosage Unit Sampling and Assessment." This paper compares the proposed Grouped Area Variance Estimate (GAVE) method with an alternate approach outlining the practicality and statistical rationalization using traditional sampling and analytical methods. The approach is designed to fit solid dose processes assuring high statistical confidence in both powder blend uniformity and dosage unit uniformity during all three stages of the lifecycle complying with ASTM standards as recommended by the US FDA.

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

USGS Publications Warehouse

Southard, Rodney E.

2013-01-01

The weather and precipitation patterns in Missouri vary considerably from year to year. In 2008, the statewide average rainfall was 57.34 inches and in 2012, the statewide average rainfall was 30.64 inches. This variability in precipitation and resulting streamflow in Missouri underlies the necessity for water managers and users to have reliable streamflow statistics and a means to compute select statistics at ungaged locations for a better understanding of water availability. Knowledge of surface-water availability is dependent on the streamflow data that have been collected and analyzed by the U.S. Geological Survey for more than 100 years at approximately 350 streamgages throughout Missouri. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, computed streamflow statistics at streamgages through the 2010 water year, defined periods of drought and defined methods to estimate streamflow statistics at ungaged locations, and developed regional regression equations to compute selected streamflow statistics at ungaged locations. Streamflow statistics and flow durations were computed for 532 streamgages in Missouri and in neighboring States of Missouri. For streamgages with more than 10 years of record, Kendall’s tau was computed to evaluate for trends in streamflow data. If trends were detected, the variable length method was used to define the period of no trend. Water years were removed from the dataset from the beginning of the record for a streamgage until no trend was detected. Low-flow frequency statistics were then computed for the entire period of record and for the period of no trend if 10 or more years of record were available for each analysis. Three methods are presented for computing selected streamflow statistics at ungaged locations. The first method uses power curve equations developed for 28 selected streams in Missouri and neighboring States that have multiple streamgages on the same streams. Statistical estimates on one of these streams can be calculated at an ungaged location that has a drainage area that is between 40 percent of the drainage area of the farthest upstream streamgage and within 150 percent of the drainage area of the farthest downstream streamgage along the stream of interest. The second method may be used on any stream with a streamgage that has operated for 10 years or longer and for which anthropogenic effects have not changed the low-flow characteristics at the ungaged location since collection of the streamflow data. A ratio of drainage area of the stream at the ungaged location to the drainage area of the stream at the streamgage was computed to estimate the statistic at the ungaged location. The range of applicability is between 40- and 150-percent of the drainage area of the streamgage, and the ungaged location must be located on the same stream as the streamgage. The third method uses regional regression equations to estimate selected low-flow frequency statistics for unregulated streams in Missouri. This report presents regression equations to estimate frequency statistics for the 10-year recurrence interval and for the N-day durations of 1, 2, 3, 7, 10, 30, and 60 days. Basin and climatic characteristics were computed using geographic information system software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses based on existing digital geospatial data and previous studies. Spatial analyses for geographical bias in the predictive accuracy of the regional regression equations defined three low-flow regions with the State representing the three major physiographic provinces in Missouri. Region 1 includes the Central Lowlands, Region 2 includes the Ozark Plateaus, and Region 3 includes the Mississippi Alluvial Plain. A total of 207 streamgages were used in the regression analyses for the regional equations. Of the 207 U.S. Geological Survey streamgages, 77 were located in Region 1, 120 were located in Region 2, and 10 were located in Region 3. Streamgages located outside of Missouri were selected to extend the range of data used for the independent variables in the regression analyses. Streamgages included in the regression analyses had 10 or more years of record and were considered to be affected minimally by anthropogenic activities or trends. Regional regression analyses identified three characteristics as statistically significant for the development of regional equations. For Region 1, drainage area, longest flow path, and streamflow-variability index were statistically significant. The range in the standard error of estimate for Region 1 is 79.6 to 94.2 percent. For Region 2, drainage area and streamflow variability index were statistically significant, and the range in the standard error of estimate is 48.2 to 72.1 percent. For Region 3, drainage area and streamflow-variability index also were statistically significant with a range in the standard error of estimate of 48.1 to 96.2 percent. Limitations on the use of estimating low-flow frequency statistics at ungaged locations are dependent on the method used. The first method outlined for use in Missouri, power curve equations, were developed to estimate the selected statistics for ungaged locations on 28 selected streams with multiple streamgages located on the same stream. A second method uses a drainage-area ratio to compute statistics at an ungaged location using data from a single streamgage on the same stream with 10 or more years of record. Ungaged locations on these streams may use the ratio of the drainage area at an ungaged location to the drainage area at a streamgage location to scale the selected statistic value from the streamgage location to the ungaged location. This method can be used if the drainage area of the ungaged location is within 40 to 150 percent of the streamgage drainage area. The third method is the use of the regional regression equations. The limits for the use of these equations are based on the ranges of the characteristics used as independent variables and that streams must be affected minimally by anthropogenic activities.

Spatial Ensemble Postprocessing of Precipitation Forecasts Using High Resolution Analyses

NASA Astrophysics Data System (ADS)

Lang, Moritz N.; Schicker, Irene; Kann, Alexander; Wang, Yong

2017-04-01

Ensemble prediction systems are designed to account for errors or uncertainties in the initial and boundary conditions, imperfect parameterizations, etc. However, due to sampling errors and underestimation of the model errors, these ensemble forecasts tend to be underdispersive, and to lack both reliability and sharpness. To overcome such limitations, statistical postprocessing methods are commonly applied to these forecasts. In this study, a full-distributional spatial post-processing method is applied to short-range precipitation forecasts over Austria using Standardized Anomaly Model Output Statistics (SAMOS). Following Stauffer et al. (2016), observation and forecast fields are transformed into standardized anomalies by subtracting a site-specific climatological mean and dividing by the climatological standard deviation. Due to the need of fitting only a single regression model for the whole domain, the SAMOS framework provides a computationally inexpensive method to create operationally calibrated probabilistic forecasts for any arbitrary location or for all grid points in the domain simultaneously. Taking advantage of the INCA system (Integrated Nowcasting through Comprehensive Analysis), high resolution analyses are used for the computation of the observed climatology and for model training. The INCA system operationally combines station measurements and remote sensing data into real-time objective analysis fields at 1 km-horizontal resolution and 1 h-temporal resolution. The precipitation forecast used in this study is obtained from a limited area model ensemble prediction system also operated by ZAMG. The so called ALADIN-LAEF provides, by applying a multi-physics approach, a 17-member forecast at a horizontal resolution of 10.9 km and a temporal resolution of 1 hour. The performed SAMOS approach statistically combines the in-house developed high resolution analysis and ensemble prediction system. The station-based validation of 6 hour precipitation sums shows a mean improvement of more than 40% in CRPS when compared to bilinearly interpolated uncalibrated ensemble forecasts. The validation on randomly selected grid points, representing the true height distribution over Austria, still indicates a mean improvement of 35%. The applied statistical model is currently set up for 6-hourly and daily accumulation periods, but will be extended to a temporal resolution of 1-3 hours within a new probabilistic nowcasting system operated by ZAMG.

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

PubMed

Zhou, Xiang

2017-12-01

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z -scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

Compliance with Standard Precautions and Associated Factors among Healthcare Workers in Gondar University Comprehensive Specialized Hospital, Northwest Ethiopia

PubMed Central

Haile, Tariku Gebre

2017-01-01

Background. In many studies, compliance with standard precautions among healthcare workers was reported to be inadequate. Objective. The aim of this study was to assess compliance with standard precautions and associated factors among healthcare workers in northwest Ethiopia. Methods. An institution-based cross-sectional study was conducted from March 01 to April 30, 2014. Simple random sampling technique was used to select participants. Data were entered into Epi info 3.5.1 and were exported to SPSS version 20.0 for statistical analysis. Multivariate logistic regression analyses were computed and adjusted odds ratio with 95% confidence interval was calculated to identify associated factors. Results. The proportion of healthcare workers who always comply with standard precautions was found to be 12%. Being a female healthcare worker (AOR [95% CI] 2.18 [1.12–4.23]), higher infection risk perception (AOR [95% CI] 3.46 [1.67–7.18]), training on standard precautions (AOR [95% CI] 2.90 [1.20–7.02]), accessibility of personal protective equipment (AOR [95% CI] 2.87 [1.41–5.86]), and management support (AOR [95% CI] 2.23 [1.11–4.53]) were found to be statistically significant. Conclusion and Recommendation. Compliance with standard precautions among the healthcare workers is very low. Interventions which include training of healthcare workers on standard precautions and consistent management support are recommended. PMID:28191020

Sequential neural text compression.

PubMed

Schmidhuber, J; Heil, S

1996-01-01

The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions "compress" and "gzip"). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.

Improving the Knowledge and Attitude on 'Standard Days Method' of Family Planning Through a Promotional Program Among Indian Postgraduate Students.

PubMed

Menachery, Philby Babu; Noronha, Judith Angelitta; Fernanades, Sweety

2017-08-01

The 'Standard Days Method' is a fertility awareness-based method of family planning that identifies day 8 through day 19 of the menstrual cycle as fertile days during which a woman is likely to conceive with unprotected intercourse. The study was aimed to determine the effectiveness of a promotional program on the 'Standard Days Method' in terms of improving the knowledge scores and attitude scores. A pre-experimental one-group pretest-posttest research design was adopted. The samples included 365 female postgraduate students from selected colleges of Udupi Taluk, Karnataka. The data was collected using self-administered questionnaires. The plan for the promotional program was also established. The findings of the study were analyzed using the descriptive and inferential statistics. The mean pretest and posttest knowledge scores were computed, and it was found that there was an increase in the mean knowledge score from 8.96 ± 3.84 to 32.64 ± 5.59, respectively. It was observed that the promotional program on 'Standard Days Method' was effective in improving the knowledge ( p  < 0.001) and attitude ( p  < 0.001) of the postgraduate students. The promotional program on Standard Days Method of family planning was effective in improving the knowledge and attitude of the postgraduate female students. This will enable the women to adopt this method and plan their pregnancies naturally and reduce the side effects of using oral contraceptives.

Fish: A New Computer Program for Friendly Introductory Statistics Help

ERIC Educational Resources Information Center

Brooks, Gordon P.; Raffle, Holly

2005-01-01

All introductory statistics students must master certain basic descriptive statistics, including means, standard deviations and correlations. Students must also gain insight into such complex concepts as the central limit theorem and standard error. This article introduces and describes the Friendly Introductory Statistics Help (FISH) computer…

An ROC-type measure of diagnostic accuracy when the gold standard is continuous-scale.

PubMed

Obuchowski, Nancy A

2006-02-15

ROC curves and summary measures of accuracy derived from them, such as the area under the ROC curve, have become the standard for describing and comparing the accuracy of diagnostic tests. Methods for estimating ROC curves rely on the existence of a gold standard which dichotomizes patients into disease present or absent. There are, however, many examples of diagnostic tests whose gold standards are not binary-scale, but rather continuous-scale. Unnatural dichotomization of these gold standards leads to bias and inconsistency in estimates of diagnostic accuracy. In this paper, we propose a non-parametric estimator of diagnostic test accuracy which does not require dichotomization of the gold standard. This estimator has an interpretation analogous to the area under the ROC curve. We propose a confidence interval for test accuracy and a statistical test for comparing accuracies of tests from paired designs. We compare the performance (i.e. CI coverage, type I error rate, power) of the proposed methods with several alternatives. An example is presented where the accuracies of two quick blood tests for measuring serum iron concentrations are estimated and compared.

Selected Streamflow Statistics for Streamgaging Stations in Delaware, 2003

USGS Publications Warehouse

Ries, Kernell G.

2004-01-01

Flow-duration and low-flow frequency statistics were calculated for 15 streamgaging stations in Delaware, in cooperation with the Delaware Geological Survey. The flow-duration statistics include the 1-, 2-, 5-, 10-, 20-, 30-, 40-, 50-, 60-, 70-, 80-, 90-, 95-, 98-, and 99-percent duration discharges. The low-flow frequency statistics include the average discharges for 1, 7, 14, 30, 60, 90, and 120 days that recur, on average, once in 1.01, 2, 5, 10, 20, 50, and 100 years. The statistics were computed using U.S. Geological Survey computer programs that can be downloaded from the World Wide Web at no cost. The computer programs automate standard U.S. Geological Survey methods for computing the statistics. Documentation is provided at the Web sites for the individual programs. The computed statistics are presented in tabular format on a separate page for each station, along with the station name, station number, the location, the period of record, and remarks.

Unbiased Scanning Method and Data Banking Approach Using Ultra-High Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry for Quantitative Comparison of Metabolite Exposure in Plasma across Species Analyzed at Different Dates.

PubMed

Gao, Hongying; Deng, Shibing; Obach, R Scott

2015-12-01

An unbiased scanning methodology using ultra high-performance liquid chromatography coupled with high-resolution mass spectrometry was used to bank data and plasma samples for comparing the data generated at different dates. This method was applied to bank the data generated earlier in animal samples and then to compare the exposure to metabolites in animal versus human for safety assessment. With neither authentic standards nor prior knowledge of the identities and structures of metabolites, full scans for precursor ions and all ion fragments (AIF) were employed with a generic gradient LC method to analyze plasma samples at positive and negative polarity, respectively. In a total of 22 tested drugs and metabolites, 21 analytes were detected using this unbiased scanning method except that naproxen was not detected due to low sensitivity at negative polarity and interference at positive polarity; and 4'- or 5-hydroxy diclofenac was not separated by a generic UPLC method. Statistical analysis of the peak area ratios of the analytes versus the internal standard in five repetitive analyses over approximately 1 year demonstrated that the analysis variation was significantly different from sample instability. The confidence limits for comparing the exposure using peak area ratio of metabolites in animal plasma versus human plasma measured over approximately 1 year apart were comparable to the analysis undertaken side by side on the same days. These statistical analysis results showed it was feasible to compare data generated at different dates with neither authentic standards nor prior knowledge of the analytes.

Extracting Information about the Rotator Cuff from Magnetic Resonance Images Using Deterministic and Random Techniques

PubMed Central

De Los Ríos, F. A.; Paluszny, M.

2015-01-01

We consider some methods to extract information about the rotator cuff based on magnetic resonance images; the study aims to define an alternative method of display that might facilitate the detection of partial tears in the supraspinatus tendon. Specifically, we are going to use families of ellipsoidal triangular patches to cover the humerus head near the affected area. These patches are going to be textured and displayed with the information of the magnetic resonance images using the trilinear interpolation technique. For the generation of points to texture each patch, we propose a new method that guarantees the uniform distribution of its points using a random statistical method. Its computational cost, defined as the average computing time to generate a fixed number of points, is significantly lower as compared with deterministic and other standard statistical techniques. PMID:25650281

Estimation of social value of statistical life using willingness-to-pay method in Nanjing, China.

PubMed

Yang, Zhao; Liu, Pan; Xu, Xin

2016-10-01

Rational decision making regarding the safety related investment programs greatly depends on the economic valuation of traffic crashes. The primary objective of this study was to estimate the social value of statistical life in the city of Nanjing in China. A stated preference survey was conducted to investigate travelers' willingness to pay for traffic risk reduction. Face-to-face interviews were conducted at stations, shopping centers, schools, and parks in different districts in the urban area of Nanjing. The respondents were categorized into two groups, including motorists and non-motorists. Both the binary logit model and mixed logit model were developed for the two groups of people. The results revealed that the mixed logit model is superior to the fixed coefficient binary logit model. The factors that significantly affect people's willingness to pay for risk reduction include income, education, gender, age, drive age (for motorists), occupation, whether the charged fees were used to improve private vehicle equipment (for motorists), reduction in fatality rate, and change in travel cost. The Monte Carlo simulation method was used to generate the distribution of value of statistical life (VSL). Based on the mixed logit model, the VSL had a mean value of 3,729,493 RMB ($586,610) with a standard deviation of 2,181,592 RMB ($343,142) for motorists; and a mean of 3,281,283 RMB ($505,318) with a standard deviation of 2,376,975 RMB ($366,054) for non-motorists. Using the tax system to illustrate the contribution of different income groups to social funds, the social value of statistical life was estimated. The average social value of statistical life was found to be 7,184,406 RMB ($1,130,032). Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical Association Criteria in Forensic Psychiatry–A criminological evaluation of casuistry

PubMed Central

Gheorghiu, V; Buda, O; Popescu, I; Trandafir, MS

2011-01-01

Purpose. Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients–subjects to forensic examination. Material and method. The statistic trial is a retrospective, document–based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily analyzed in order to summarize the data within the National Institute of Forensic Medicine, Bucharest, Romania (INML), with one of the group variables being ‘particularities of the psychiatric patient history’, containing the items ‘forensic onset’, ‘commitments within the last year prior to the examination’ and ‘absence of commitments within the last year prior to the examination’. The method used was the Kendall bivariate correlation. For this study, the authors separately analyze only the two items regarding commitments by other correlation alternatives and by modern, elaborate statistical analyses, i.e. recording of the standard case study variables, Kendall bivariate correlation, cross tabulation, factor analysis and hierarchical cluster analysis. Results. The results are varied, from theoretically presumed clinical nosography (such as schizophrenia or manic depression), to non–presumed (conduct disorders) or unexpected behavioral acts, and therefore difficult to interpret. Conclusions. One took into consideration the features of the batch as well as the results of the previous standard correlation of the whole statistical lot. The authors emphasize the role of medical security measures that are actually applied in the therapeutic management in general and in risk and second offence management in particular, as well as the role of forensic psychiatric examinations in the detection of certain aspects related to the monitoring of mental patients. PMID:21505571

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

PubMed

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

2017-06-01

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

Application of FT-IR Classification Method in Silica-Plant Extracts Composites Quality Testing

NASA Astrophysics Data System (ADS)

Bicu, A.; Drumea, V.; Mihaiescu, D. E.; Purcareanu, B.; Florea, M. A.; Trică, B.; Vasilievici, G.; Draga, S.; Buse, E.; Olariu, L.

2018-06-01

Our present work is concerned with the validation and quality testing efforts of mesoporous silica - plant extracts composites, in order to sustain the standardization process of plant-based pharmaceutical products. The synthesis of the silica support were performed by using a TEOS based synthetic route and CTAB as a template, at room temperature and normal pressure. The silica support was analyzed by advanced characterization methods (SEM, TEM, BET, DLS and FT-IR), and loaded with Calendula officinalis and Salvia officinalis standardized extracts. Further desorption studies were performed in order to prove the sustained release properties of the final materials. Intermediate and final product identification was performed by a FT-IR classification method, using the MID-range of the IR spectra, and statistical representative samples from repetitive synthetic stages. The obtained results recommend this analytical method as a fast and cost effective alternative to the classic identification methods.

Rapid microbiological assay of serum vitamin B12 by electronic counter

PubMed Central

Stuart, J.; Sklaroff, S. A.

1966-01-01

A new method of measuring the growth of Lactobacillus leichmannii is reported. Its adoption for the estimation of serum vitamin B12 levels shortens the incubation period required to five hours at 45°C. The method is compared statistically with a standard method of estimation, requiring incubation at 37°C., by duplicate determinations on 106 hospital patients. The significance of the apparently decreased accuracy of the new method at low serum levels is discussed, and a re-appraisal of the optimum growth temperature of Lactobacillus leichmannii suggested. PMID:5904982

Rapid microbiological assay of serum vitamin B 12 by electronic counter.

PubMed

Stuart, J; Sklaroff, S A

1966-01-01

A new method of measuring the growth of Lactobacillus leichmannii is reported. Its adoption for the estimation of serum vitamin B(12) levels shortens the incubation period required to five hours at 45 degrees C. The method is compared statistically with a standard method of estimation, requiring incubation at 37 degrees C., by duplicate determinations on 106 hospital patients. The significance of the apparently decreased accuracy of the new method at low serum levels is discussed, and a re-appraisal of the optimum growth temperature of Lactobacillus leichmannii suggested.

Evaluation on the use of cerium in the NBL Titrimetric Method

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

Zebrowski, J.P.; Orlowicz, G.J.; Johnson, K.D.

An alternative to potassium dichromate as titrant in the New Brunswick Laboratory Titrimetric Method for uranium analysis was sought since chromium in the waste makes disposal difficult. Substitution of a ceric-based titrant was statistically evaluated. Analysis of the data indicated statistically equivalent precisions for the two methods, but a significant overall bias of +0.035% for the ceric titrant procedure. The cause of the bias was investigated, alterations to the procedure were made, and a second statistical study was performed. This second study revealed no statistically significant bias, nor any analyst-to-analyst variation in the ceric titration procedure. A statistically significant day-to-daymore » variation was detected, but this was physically small (0.01 5%) and was only detected because of the within-day precision of the method. The added mean and standard deviation of the %RD for a single measurement was found to be 0.031%. A comparison with quality control blind dichromate titration data again indicated similar overall precision. Effects of ten elements on the ceric titration`s performance was determined. Co, Ti, Cu, Ni, Na, Mg, Gd, Zn, Cd, and Cr in previous work at NBL these impurities did not interfere with the potassium dichromate titrant. This study indicated similar results for the ceric titrant, with the exception of Ti. All the elements (excluding Ti and Cr), caused no statistically significant bias in uranium measurements at levels of 10 mg impurity per 20-40 mg uranium. The presence of Ti was found to cause a bias of {minus}0.05%; this is attributed to the presence of sulfate ions, resulting in precipitation of titanium sulfate and occlusion of uranium. A negative bias of 0.012% was also statistically observed in the samples containing chromium impurities.« less

New method of determination of spot welding-adhesive joint fatigue life using full field strain evolution

NASA Astrophysics Data System (ADS)

Sadowski, T.; Kneć, M.

2016-04-01

Fatigue tests were conducted since more than two hundred years ago. Despite this long period, as fatigue phenomena are very complex, assessment of fatigue response of standard materials or composites still requires a long time. Quite precise way to estimate fatigue parameters is to test at least 30 standardized specimens for the analysed material and further statistical post processing is required. In case of structural elements analysis like hybrid joints (Figure 1), the situation is much more complex as more factors influence the fatigue load capacity due to much more complicated structure of the joint in comparison to standard materials specimen, i.e. occurrence of: welded hot spots or rivets, adhesive layers, local notches creating the stress concentrations, etc. In order to shorten testing time some rapid methods are known: Locati's method [1] - step by step load increments up to failure, Prot's method [2] - constant increase of the load amplitude up to failure; Lehr's method [2] - seeking for the point during regular fatigue loading when an increase of temperature or strains become non-linear. The present article proposes new method of the fatigue response assessment - combination of the Locati's and Lehr's method.

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory; determination of dissolved arsenic, boron, lithium, selenium, strontium, thallium, and vanadium using inductively coupled plasma-mass spectrometry

USGS Publications Warehouse

Garbarino, John R.

1999-01-01

The inductively coupled plasma?mass spectrometric (ICP?MS) methods have been expanded to include the determination of dissolved arsenic, boron, lithium, selenium, strontium, thallium, and vanadium in filtered, acidified natural water. Method detection limits for these elements are now 10 to 200 times lower than by former U.S. Geological Survey (USGS) methods, thus providing lower variability at ambient concentrations. The bias and variability of the method was determined by using results from spike recoveries, standard reference materials, and validation samples. Spike recoveries at 5 to 10 times the method detection limit and 75 micrograms per liter in reagent-water, surface-water, and groundwater matrices averaged 93 percent for seven replicates, although selected elemental recoveries in a ground-water matrix with an extremely high iron sulfate concentration were negatively biased by 30 percent. Results for standard reference materials were within 1 standard deviation of the most probable value. Statistical analysis of the results from about 60 filtered, acidified natural-water samples indicated that there was no significant difference between ICP?MS and former USGS official methods of analysis.

77 FR 34044 - National Committee on Vital and Health Statistics: Meeting Standards Subcommittee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-08

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Committee on Vital and Health Statistics: Meeting... Health Statistics (NCVHS); Subcommittee on Standards. Time and Date: June 20, 2012, 9 a.m.-5 p.m. EST..., Executive Secretary, NCVHS, National Center for Health Statistics, Centers for Disease Control and...

The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine

PubMed Central

Tu, Li-ping; Chen, Jing-bo; Hu, Xiao-juan; Zhang, Zhi-feng

2016-01-01

Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods. Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L * a * b * of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results. The L * a * b * values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions. At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible. PMID:28050555

The characterization and certification of a quantitative reference material for Legionella detection and quantification by qPCR.

PubMed

Baume, M; Garrelly, L; Facon, J P; Bouton, S; Fraisse, P O; Yardin, C; Reyrolle, M; Jarraud, S

2013-06-01

The characterization and certification of a Legionella DNA quantitative reference material as a primary measurement standard for Legionella qPCR. Twelve laboratories participated in a collaborative certification campaign. A candidate reference DNA material was analysed through PCR-based limiting dilution assays (LDAs). The validated data were used to statistically assign both a reference value and an associated uncertainty to the reference material. This LDA method allowed for the direct quantification of the amount of Legionella DNA per tube in genomic units (GU) and the determination of the associated uncertainties. This method could be used for the certification of all types of microbiological standards for qPCR. The use of this primary standard will improve the accuracy of Legionella qPCR measurements and the overall consistency of these measurements among different laboratories. The extensive use of this certified reference material (CRM) has been integrated in the French standard NF T90-471 (April 2010) and in the ISO Technical Specification 12 869 (Anon 2012 International Standardisation Organisation) for validating qPCR methods and ensuring the reliability of these methods. © 2013 The Society for Applied Microbiology.

The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.

PubMed

Qi, Zhen; Tu, Li-Ping; Chen, Jing-Bo; Hu, Xiao-Juan; Xu, Jia-Tuo; Zhang, Zhi-Feng

2016-01-01

Background and Goal . The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods . Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L * a * b * of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results . The L * a * b * values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions . At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible.

The effect of instructional methodology on high school students natural sciences standardized tests scores

NASA Astrophysics Data System (ADS)

Powell, P. E.

Educators have recently come to consider inquiry based instruction as a more effective method of instruction than didactic instruction. Experience based learning theory suggests that student performance is linked to teaching method. However, research is limited on inquiry teaching and its effectiveness on preparing students to perform well on standardized tests. The purpose of the study to investigate whether one of these two teaching methodologies was more effective in increasing student performance on standardized science tests. The quasi experimental quantitative study was comprised of two stages. Stage 1 used a survey to identify teaching methods of a convenience sample of 57 teacher participants and determined level of inquiry used in instruction to place participants into instructional groups (the independent variable). Stage 2 used analysis of covariance (ANCOVA) to compare posttest scores on a standardized exam by teaching method. Additional analyses were conducted to examine the differences in science achievement by ethnicity, gender, and socioeconomic status by teaching methodology. Results demonstrated a statistically significant gain in test scores when taught using inquiry based instruction. Subpopulation analyses indicated all groups showed improved mean standardized test scores except African American students. The findings benefit teachers and students by presenting data supporting a method of content delivery that increases teacher efficacy and produces students with a greater cognition of science content that meets the school's mission and goals.

[Application of statistics on chronic-diseases-relating observational research papers].

PubMed

Hong, Zhi-heng; Wang, Ping; Cao, Wei-hua

2012-09-01

To study the application of statistics on Chronic-diseases-relating observational research papers which were recently published in the Chinese Medical Association Magazines, with influential index above 0.5. Using a self-developed criterion, two investigators individually participated in assessing the application of statistics on Chinese Medical Association Magazines, with influential index above 0.5. Different opinions reached an agreement through discussion. A total number of 352 papers from 6 magazines, including the Chinese Journal of Epidemiology, Chinese Journal of Oncology, Chinese Journal of Preventive Medicine, Chinese Journal of Cardiology, Chinese Journal of Internal Medicine and Chinese Journal of Endocrinology and Metabolism, were reviewed. The rate of clear statement on the following contents as: research objectives, t target audience, sample issues, objective inclusion criteria and variable definitions were 99.43%, 98.57%, 95.43%, 92.86% and 96.87%. The correct rates of description on quantitative and qualitative data were 90.94% and 91.46%, respectively. The rates on correctly expressing the results, on statistical inference methods related to quantitative, qualitative data and modeling were 100%, 95.32% and 87.19%, respectively. 89.49% of the conclusions could directly response to the research objectives. However, 69.60% of the papers did not mention the exact names of the study design, statistically, that the papers were using. 11.14% of the papers were in lack of further statement on the exclusion criteria. Percentage of the papers that could clearly explain the sample size estimation only taking up as 5.16%. Only 24.21% of the papers clearly described the variable value assignment. Regarding the introduction on statistical conduction and on database methods, the rate was only 24.15%. 18.75% of the papers did not express the statistical inference methods sufficiently. A quarter of the papers did not use 'standardization' appropriately. As for the aspect of statistical inference, the rate of description on statistical testing prerequisite was only 24.12% while 9.94% papers did not even employ the statistical inferential method that should be used. The main deficiencies on the application of Statistics used in papers related to Chronic-diseases-related observational research were as follows: lack of sample-size determination, variable value assignment description not sufficient, methods on statistics were not introduced clearly or properly, lack of consideration for pre-requisition regarding the use of statistical inferences.

Never too old for anonymity: a statistical standard for demographic data sharing via the HIPAA Privacy Rule

PubMed Central

Benitez, Kathleen; Masys, Daniel

2010-01-01

Objective Healthcare organizations must de-identify patient records before sharing data. Many organizations rely on the Safe Harbor Standard of the HIPAA Privacy Rule, which enumerates 18 identifiers that must be suppressed (eg, ages over 89). An alternative model in the Privacy Rule, known as the Statistical Standard, can facilitate the sharing of more detailed data, but is rarely applied because of a lack of published methodologies. The authors propose an intuitive approach to de-identifying patient demographics in accordance with the Statistical Standard. Design The authors conduct an analysis of the demographics of patient cohorts in five medical centers developed for the NIH-sponsored Electronic Medical Records and Genomics network, with respect to the US census. They report the re-identification risk of patient demographics disclosed according to the Safe Harbor policy and the relative risk rate for sharing such information via alternative policies. Measurements The re-identification risk of Safe Harbor demographics ranged from 0.01% to 0.19%. The findings show alternative de-identification models can be created with risks no greater than Safe Harbor. The authors illustrate that the disclosure of patient ages over the age of 89 is possible when other features are reduced in granularity. Limitations The de-identification approach described in this paper was evaluated with demographic data only and should be evaluated with other potential identifiers. Conclusion Alternative de-identification policies to the Safe Harbor model can be derived for patient demographics to enable the disclosure of values that were previously suppressed. The method is generalizable to any environment in which population statistics are available. PMID:21169618

Comparison of statistical algorithms for detecting homogeneous river reaches along a longitudinal continuum

NASA Astrophysics Data System (ADS)

Leviandier, Thierry; Alber, A.; Le Ber, F.; Piégay, H.

2012-02-01

Seven methods designed to delineate homogeneous river segments, belonging to four families, namely — tests of homogeneity, contrast enhancing, spatially constrained classification, and hidden Markov models — are compared, firstly on their principles, then on a case study, and on theoretical templates. These templates contain patterns found in the case study but not considered in the standard assumptions of statistical methods, such as gradients and curvilinear structures. The influence of data resolution, noise and weak satisfaction of the assumptions underlying the methods is investigated. The control of the number of reaches obtained in order to achieve meaningful comparisons is discussed. No method is found that outperforms all the others on all trials. However, the methods with sequential algorithms (keeping at order n + 1 all breakpoints found at order n) fail more often than those running complete optimisation at any order. The Hubert-Kehagias method and Hidden Markov Models are the most successful at identifying subpatterns encapsulated within the templates. Ergodic Hidden Markov Models are, moreover, liable to exhibit transition areas.

Statistical prediction with Kanerva's sparse distributed memory

NASA Technical Reports Server (NTRS)

Rogers, David

1989-01-01

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of near- or over-capacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of sparse distributed memory and for which the standard formulation of SDM is a special case. This viewpoint suggests possible enhancements to the SDM model, including a procedure for improving the predictiveness of the system based on Holland's work with genetic algorithms, and a method for improving the capacity of SDM even when used as an associative memory.

Changing health care worker behavior in relation to respiratory disease transmission with a novel training approach that uses biosimulation.

PubMed

Carrico, Ruth M; Coty, Mary B; Goss, Linda K; Lajoie, Andrew S

2007-02-01

This pilot study was conducted to determine whether supplementing standard classroom training methods regarding respiratory disease transmission with a visual demonstration could improve the use of personal protective equipment among emergency department nurses. Participants included 20 emergency department registered nurses randomized into 2 groups: control and intervention. The intervention group received supplemental training using the visual demonstration of respiratory particle dispersion. Both groups were then observed throughout their work shifts as they provided care during January-March 2005. Participants who received supplemental visual training correctly utilized personal protective equipment statistically more often than did participants who received only the standard classroom training. Supplementing the standard training methods with a visual demonstration can improve the use of personal protective equipment during care of patients exhibiting respiratory symptoms.

Leak Rate Quantification Method for Gas Pressure Seals with Controlled Pressure Differential

NASA Technical Reports Server (NTRS)

Daniels, Christopher C.; Braun, Minel J.; Oravec, Heather A.; Mather, Janice L.; Taylor, Shawn C.

2015-01-01

An enhancement to the pressure decay leak rate method with mass point analysis solved deficiencies in the standard method. By adding a control system, a constant gas pressure differential across the test article was maintained. As a result, the desired pressure condition was met at the onset of the test, and the mass leak rate and measurement uncertainty were computed in real-time. The data acquisition and control system were programmed to automatically stop when specified criteria were met. Typically, the test was stopped when a specified level of measurement uncertainty was attained. Using silicone O-ring test articles, the new method was compared with the standard method that permitted the downstream pressure to be non-constant atmospheric pressure. The two methods recorded comparable leak rates, but the new method recorded leak rates with significantly lower measurement uncertainty, statistical variance, and test duration. Utilizing this new method in leak rate quantification, projects will reduce cost and schedule, improve test results, and ease interpretation between data sets.

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

PubMed

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

2016-01-30

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

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

PubMed Central

Yoon, Hyun Jung; Hwang, Hye Sun; Moon, Jung Won; Lee, Kyung Soo

2015-01-01

Objective To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Materials and Methods Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Results Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Conclusion Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT. PMID:26357505

Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition.

PubMed

Hébert-Dufresne, Laurent; Grochow, Joshua A; Allard, Antoine

2016-08-18

We introduce a network statistic that measures structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and interpretable at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard network fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. Yet, the onion spectrum reveals much more information about a network, and at multiple scales; for example, it can be used to quantify node heterogeneity, degree correlations, centrality, and tree- or lattice-likeness. Furthermore, unlike the k-core decomposition, the combined degree-onion spectrum immediately gives a clear local picture of the network around each node which allows the detection of interesting subgraphs whose topological structure differs from the global network organization. This local description can also be leveraged to easily generate samples from the ensemble of networks with a given joint degree-onion distribution. We demonstrate the utility of the onion spectrum for understanding both static and dynamic properties on several standard graph models and on many real-world networks.

Development of Growth Charts of Pakistani Children Aged 4-15 Years Using Quantile Regression: A Cross-sectional Study

PubMed Central

Khan, Nazeer; Siddiqui, Junaid S; Baig-Ansari, Naila

2018-01-01

Background Growth charts are essential tools used by pediatricians as well as public health researchers in assessing and monitoring the well-being of pediatric populations. Development of these growth charts, especially for children above five years of age, is challenging and requires current anthropometric data and advanced statistical analysis. These growth charts are generally presented as a series of smooth centile curves. A number of modeling approaches are available for generating growth charts and applying these on national datasets is important for generating country-specific reference growth charts. Objective To demonstrate that quantile regression (QR) as a viable statistical approach to construct growth reference charts and to assess the applicability of the World Health Organization (WHO) 2007 growth standards to a large Pakistani population of school-going children. Methodology This is a secondary data analysis using anthropometric data of 9,515 students from a Pakistani survey conducted between 2007 and 2014 in four cities of Pakistan. Growth reference charts were created using QR as well as the LMS (Box-Cox transformation (L), the median (M), and the generalized coefficient of variation (S)) method and then compared with WHO 2007 growth standards. Results Centile values estimated by the LMS method and QR procedure had few differences. The centile values attained from QR procedure of BMI-for-age, weight-for-age, and height-for-age of Pakistani children were lower than the standard WHO 2007 centile. Conclusion QR should be considered as an alternative method to develop growth charts for its simplicity and lack of necessity to transform data. WHO 2007 standards are not suitable for Pakistani children. PMID:29632748

Development of Growth Charts of Pakistani Children Aged 4-15 Years Using Quantile Regression: A Cross-sectional Study.

PubMed

Iftikhar, Sundus; Khan, Nazeer; Siddiqui, Junaid S; Baig-Ansari, Naila

2018-02-02

Background Growth charts are essential tools used by pediatricians as well as public health researchers in assessing and monitoring the well-being of pediatric populations. Development of these growth charts, especially for children above five years of age, is challenging and requires current anthropometric data and advanced statistical analysis. These growth charts are generally presented as a series of smooth centile curves. A number of modeling approaches are available for generating growth charts and applying these on national datasets is important for generating country-specific reference growth charts. Objective To demonstrate that quantile regression (QR) as a viable statistical approach to construct growth reference charts and to assess the applicability of the World Health Organization (WHO) 2007 growth standards to a large Pakistani population of school-going children. Methodology This is a secondary data analysis using anthropometric data of 9,515 students from a Pakistani survey conducted between 2007 and 2014 in four cities of Pakistan. Growth reference charts were created using QR as well as the LMS (Box-Cox transformation (L), the median (M), and the generalized coefficient of variation (S)) method and then compared with WHO 2007 growth standards. Results Centile values estimated by the LMS method and QR procedure had few differences. The centile values attained from QR procedure of BMI-for-age, weight-for-age, and height-for-age of Pakistani children were lower than the standard WHO 2007 centile. Conclusion QR should be considered as an alternative method to develop growth charts for its simplicity and lack of necessity to transform data. WHO 2007 standards are not suitable for Pakistani children.

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Verification of learner’s differences by team-based learning in biochemistry classes

PubMed Central

2017-01-01

Purpose We tested the effect of team-based learning (TBL) on medical education through the second-year premedical students’ TBL scores in biochemistry classes over 5 years. Methods We analyzed the results based on test scores before and after the students’ debate. The groups of students for statistical analysis were divided as follows: group 1 comprised the top-ranked students, group 3 comprised the low-ranked students, and group 2 comprised the medium-ranked students. Therefore, group T comprised 382 students (the total number of students in group 1, 2, and 3). To calibrate the difficulty of the test, original scores were converted into standardized scores. We determined the differences of the tests using Student t-test, and the relationship between scores before, and after the TBL using linear regression tests. Results Although there was a decrease in the lowest score, group T and 3 showed a significant increase in both original and standardized scores; there was also an increase in the standardized score of group 3. There was a positive correlation between the pre- and the post-debate scores in group T, and 2. And the beta values of the pre-debate scores and “the changes between the pre- and post-debate scores” were statistically significant in both original and standardized scores. Conclusion TBL is one of the educational methods for helping students improve their grades, particularly those of low-ranked students. PMID:29207457

Defining standardized protocols for determining the efficacy of a postmilking teat disinfectant following experimental exposure of teats to mastitis pathogens.

PubMed

Schukken, Y H; Rauch, B J; Morelli, J

2013-04-01

The objective of this paper was to define standardized protocols for determining the efficacy of a postmilking teat disinfectant following experimental exposure of teats to both Staphylococcus aureus and Streptococcus agalactiae. The standardized protocols describe the selection of cows and herds and define the critical points in performing experimental exposure, performing bacterial culture, evaluating the culture results, and finally performing statistical analyses and reporting of the results. The protocols define both negative control and positive control trials. For negative control trials, the protocol states that an efficacy of reducing new intramammary infections (IMI) of at least 40% is required for a teat disinfectant to be considered effective. For positive control trials, noninferiority to a control disinfectant with a published efficacy of reducing new IMI of at least 70% is required. Sample sizes for both negative and positive control trials are calculated. Positive control trials are expected to require a large trial size. Statistical analysis methods are defined and, in the proposed methods, the rate of IMI may be analyzed using generalized linear mixed models. The efficacy of the test product can be evaluated while controlling for important covariates and confounders in the trial. Finally, standards for reporting are defined and reporting considerations are discussed. The use of the defined protocol is shown through presentation of the results of a recent trial of a test product against a negative control. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Quantitative comparison of tympanic membrane displacements using two optical methods to recover the optical phase

NASA Astrophysics Data System (ADS)

Santiago-Lona, Cynthia V.; Hernández-Montes, María del Socorro; Mendoza-Santoyo, Fernando; Esquivel-Tejeda, Jesús

2018-02-01

The study and quantification of the tympanic membrane (TM) displacements add important information to advance the knowledge about the hearing process. A comparative statistical analysis between two commonly used demodulation methods employed to recover the optical phase in digital holographic interferometry, namely the fast Fourier transform and phase-shifting interferometry, is presented as applied to study thin tissues such as the TM. The resulting experimental TM surface displacement data are used to contrast both methods through the analysis of variance and F tests. Data are gathered when the TMs are excited with continuous sound stimuli at levels 86, 89 and 93 dB SPL for the frequencies of 800, 1300 and 2500 Hz under the same experimental conditions. The statistical analysis shows repeatability in z-direction displacements with a standard deviation of 0.086, 0.098 and 0.080 μm using the Fourier method, and 0.080, 0.104 and 0.055 μm with the phase-shifting method at a 95% confidence level for all frequencies. The precision and accuracy are evaluated by means of the coefficient of variation; the results with the Fourier method are 0.06143, 0.06125, 0.06154 and 0.06154, 0.06118, 0.06111 with phase-shifting. The relative error between both methods is 7.143, 6.250 and 30.769%. On comparing the measured displacements, the results indicate that there is no statistically significant difference between both methods for frequencies at 800 and 1300 Hz; however, errors and other statistics increase at 2500 Hz.

The space of ultrametric phylogenetic trees.

PubMed

Gavryushkin, Alex; Drummond, Alexei J

2016-08-21

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data. Hence the question of statistical consistency of such methods is equivalent to the consistency of the summary of the sample. More generally, statistical consistency is ensured by the tree space used to analyse the sample. In this paper, we consider two standard parameterisations of phylogenetic time-trees used in evolutionary models: inter-coalescent interval lengths and absolute times of divergence events. For each of these parameterisations we introduce a natural metric space on ultrametric phylogenetic trees. We compare the introduced spaces with existing models of tree space and formulate several formal requirements that a metric space on phylogenetic trees must possess in order to be a satisfactory space for statistical analysis, and justify them. We show that only a few known constructions of the space of phylogenetic trees satisfy these requirements. However, our results suggest that these basic requirements are not enough to distinguish between the two metric spaces we introduce and that the choice between metric spaces requires additional properties to be considered. Particularly, that the summary tree minimising the square distance to the trees from the sample might be different for different parameterisations. This suggests that further fundamental insight is needed into the problem of statistical consistency of phylogenetic inference methods. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Structural damage detection based on stochastic subspace identification and statistical pattern recognition: I. Theory

NASA Astrophysics Data System (ADS)

Ren, W. X.; Lin, Y. Q.; Fang, S. E.

2011-11-01

One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.

Simplified estimation of age-specific reference intervals for skewed data.

PubMed

Wright, E M; Royston, P

1997-12-30

Age-specific reference intervals are commonly used in medical screening and clinical practice, where interest lies in the detection of extreme values. Many different statistical approaches have been published on this topic. The advantages of a parametric method are that they necessarily produce smooth centile curves, the entire density is estimated and an explicit formula is available for the centiles. The method proposed here is a simplified version of a recent approach proposed by Royston and Wright. Basic transformations of the data and multiple regression techniques are combined to model the mean, standard deviation and skewness. Using these simple tools, which are implemented in almost all statistical computer packages, age-specific reference intervals may be obtained. The scope of the method is illustrated by fitting models to several real data sets and assessing each model using goodness-of-fit techniques.

76 FR 9696 - Equipment Price Forecasting in Energy Conservation Standards Analysis

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-22

... for particular efficiency design options, an empirical experience curve fit to the available data may be used to forecast future costs of such design option technologies. If a statistical evaluation indicates a low level of confidence in estimates of the design option cost trend, this method should not be...

Show the Data, Don't Conceal Them

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2011-01-01

Current standards of data presentation and analysis in biological journals often fall short of ideal. This is the first of a planned series of short articles, to be published in a number of journals, aiming to highlight the principles of clear data presentation and appropriate statistical analysis. This article considers the methods used to show…

Standard and Robust Methods in Regression Imputation

ERIC Educational Resources Information Center

Moraveji, Behjat; Jafarian, Koorosh

2014-01-01

The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…

Sample sizes needed for specified margins of relative error in the estimates of the repeatability and reproducibility standard deviations.

PubMed

McClure, Foster D; Lee, Jung K

2005-01-01

Sample size formulas are developed to estimate the repeatability and reproducibility standard deviations (Sr and S(R)) such that the actual error in (Sr and S(R)) relative to their respective true values, sigmar and sigmaR, are at predefined levels. The statistical consequences associated with AOAC INTERNATIONAL required sample size to validate an analytical method are discussed. In addition, formulas to estimate the uncertainties of (Sr and S(R)) were derived and are provided as supporting documentation. Formula for the Number of Replicates Required for a Specified Margin of Relative Error in the Estimate of the Repeatability Standard Deviation.

Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique

NASA Astrophysics Data System (ADS)

Van de Casteele, Elke; Parizel, Paul; Sijbers, Jan

2012-03-01

Adaptive statistical iterative reconstruction (ASiR) is a new reconstruction algorithm used in the field of medical X-ray imaging. This new reconstruction method combines the idealized system representation, as we know it from the standard Filtered Back Projection (FBP) algorithm, and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. It studies how noise propagates through the reconstruction steps, feeds this model back into the loop and iteratively reduces noise in the reconstructed image without affecting spatial resolution. In this paper the effect of ASiR on the contrast to noise ratio is studied using the low contrast module of the Catphan phantom. The experiments were done on a GE LightSpeed VCT system at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to the standard FBP method. For the same contrast to noise ratio the images from ASiR can be obtained using 60% less current, leading to a reduction in dose of the same amount.

Quantification of heterogeneity observed in medical images.

PubMed

Brooks, Frank J; Grigsby, Perry W

2013-03-02

There has been much recent interest in the quantification of visually evident heterogeneity within functional grayscale medical images, such as those obtained via magnetic resonance or positron emission tomography. In the case of images of cancerous tumors, variations in grayscale intensity imply variations in crucial tumor biology. Despite these considerable clinical implications, there is as yet no standardized method for measuring the heterogeneity observed via these imaging modalities. In this work, we motivate and derive a statistical measure of image heterogeneity. This statistic measures the distance-dependent average deviation from the smoothest intensity gradation feasible. We show how this statistic may be used to automatically rank images of in vivo human tumors in order of increasing heterogeneity. We test this method against the current practice of ranking images via expert visual inspection. We find that this statistic provides a means of heterogeneity quantification beyond that given by other statistics traditionally used for the same purpose. We demonstrate the effect of tumor shape upon our ranking method and find the method applicable to a wide variety of clinically relevant tumor images. We find that the automated heterogeneity rankings agree very closely with those performed visually by experts. These results indicate that our automated method may be used reliably to rank, in order of increasing heterogeneity, tumor images whether or not object shape is considered to contribute to that heterogeneity. Automated heterogeneity ranking yields objective results which are more consistent than visual rankings. Reducing variability in image interpretation will enable more researchers to better study potential clinical implications of observed tumor heterogeneity.

78 FR 65317 - National Committee on Vital and Health Statistics: Meeting Standards Subcommittee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Committee on Vital and Health Statistics: Meeting... Health Statistics (NCVHS) Subcommittee on Standards. Time and Date: November 12, 2013 8:30 a.m.-5:30 p.m. EST. Place: Centers for Disease Control and Prevention, National Center for Health Statistics, 3311...

78 FR 54470 - National Committee on Vital and Health Statistics: Meeting Standards Subcommittee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-04

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Committee on Vital and Health Statistics: Meeting... Health Statistics (NCVHS) Subcommittee on Standards Time and Date: September 18, 2013 8:30 p.m.--5:00 p.m. EDT. Place: Centers for Disease Control and Prevention, National Center for Health Statistics, 3311...

78 FR 942 - National Committee on Vital and Health Statistics: Meeting Standards Subcommittee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-07

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Committee on Vital and Health Statistics: Meeting... Health Statistics (NCVHS) Subcommittee on Standards. Time and Date: February 27, 2013 9:30 a.m.-5:00 p.m... electronic claims attachments. The National Committee on Vital Health Statistics is the public advisory body...

78 FR 34100 - National Committee on Vital and Health Statistics: Meeting Standards Subcommittee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Committee on Vital and Health Statistics: Meeting... Health Statistics (NCVHS) Subcommittee on Standards. Time and Date: June 17, 2013 1:00 p.m.-5:00 p.m. e.d..., National Center for Health Statistics, 3311 Toledo Road, Auditorium B & C, Hyattsville, Maryland 20782...

Medical cost analysis: application to colorectal cancer data from the SEER Medicare database.

PubMed

Bang, Heejung

2005-10-01

Incompleteness is a key feature of most survival data. Numerous well established statistical methodologies and algorithms exist for analyzing life or failure time data. However, induced censorship invalidates the use of those standard analytic tools for some survival-type data such as medical costs. In this paper, some valid methods currently available for analyzing censored medical cost data are reviewed. Some cautionary findings under different assumptions are envisioned through application to medical costs from colorectal cancer patients. Cost analysis should be suitably planned and carefully interpreted under various meaningful scenarios even with judiciously selected statistical methods. This approach would be greatly helpful to policy makers who seek to prioritize health care expenditures and to assess the elements of resource use.

Metrology Standards for Quantitative Imaging Biomarkers

PubMed Central

Obuchowski, Nancy A.; Kessler, Larry G.; Raunig, David L.; Gatsonis, Constantine; Huang, Erich P.; Kondratovich, Marina; McShane, Lisa M.; Reeves, Anthony P.; Barboriak, Daniel P.; Guimaraes, Alexander R.; Wahl, Richard L.

2015-01-01

Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies. © RSNA, 2015 PMID:26267831

Predictive onboard flow control for packet switching satellites

NASA Technical Reports Server (NTRS)

Bobinsky, Eric A.

1992-01-01

We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

Optimization Methods in Sherpa

NASA Astrophysics Data System (ADS)

Siemiginowska, Aneta; Nguyen, Dan T.; Doe, Stephen M.; Refsdal, Brian L.

2009-09-01

Forward fitting is a standard technique used to model X-ray data. A statistic, usually assumed weighted chi^2 or Poisson likelihood (e.g. Cash), is minimized in the fitting process to obtain a set of the best model parameters. Astronomical models often have complex forms with many parameters that can be correlated (e.g. an absorbed power law). Minimization is not trivial in such setting, as the statistical parameter space becomes multimodal and finding the global minimum is hard. Standard minimization algorithms can be found in many libraries of scientific functions, but they are usually focused on specific functions. However, Sherpa designed as general fitting and modeling application requires very robust optimization methods that can be applied to variety of astronomical data (X-ray spectra, images, timing, optical data etc.). We developed several optimization algorithms in Sherpa targeting a wide range of minimization problems. Two local minimization methods were built: Levenberg-Marquardt algorithm was obtained from MINPACK subroutine LMDIF and modified to achieve the required robustness; and Nelder-Mead simplex method has been implemented in-house based on variations of the algorithm described in the literature. A global search Monte-Carlo method has been implemented following a differential evolution algorithm presented by Storn and Price (1997). We will present the methods in Sherpa and discuss their usage cases. We will focus on the application to Chandra data showing both 1D and 2D examples. This work is supported by NASA contract NAS8-03060 (CXC).

On Teaching about the Coefficient of Variation in Introductory Statistics Courses

ERIC Educational Resources Information Center

Trafimow, David

2014-01-01

The standard deviation is related to the mean by virtue of the coefficient of variation. Teachers of statistics courses can make use of that fact to make the standard deviation more comprehensible for statistics students.

Equivalent statistics and data interpretation.

PubMed

Francis, Gregory

2017-08-01

Recent reform efforts in psychological science have led to a plethora of choices for scientists to analyze their data. A scientist making an inference about their data must now decide whether to report a p value, summarize the data with a standardized effect size and its confidence interval, report a Bayes Factor, or use other model comparison methods. To make good choices among these options, it is necessary for researchers to understand the characteristics of the various statistics used by the different analysis frameworks. Toward that end, this paper makes two contributions. First, it shows that for the case of a two-sample t test with known sample sizes, many different summary statistics are mathematically equivalent in the sense that they are based on the very same information in the data set. When the sample sizes are known, the p value provides as much information about a data set as the confidence interval of Cohen's d or a JZS Bayes factor. Second, this equivalence means that different analysis methods differ only in their interpretation of the empirical data. At first glance, it might seem that mathematical equivalence of the statistics suggests that it does not matter much which statistic is reported, but the opposite is true because the appropriateness of a reported statistic is relative to the inference it promotes. Accordingly, scientists should choose an analysis method appropriate for their scientific investigation. A direct comparison of the different inferential frameworks provides some guidance for scientists to make good choices and improve scientific practice.

Evaluation of an alternate method for sampling benthic macroinvertebrates in low-gradient streams sampled as part of the National Rivers and Streams Assessment.

PubMed

Flotemersch, Joseph E; North, Sheila; Blocksom, Karen A

2014-02-01

Benthic macroinvertebrates are sampled in streams and rivers as one of the assessment elements of the US Environmental Protection Agency's National Rivers and Streams Assessment. In a 2006 report, the recommendation was made that different yet comparable methods be evaluated for different types of streams (e.g., low gradient vs. high gradient). Consequently, a research element was added to the 2008-2009 National Rivers and Streams Assessment to conduct a side-by-side comparison of the standard macroinvertebrate sampling method with an alternate method specifically designed for low-gradient wadeable streams and rivers that focused more on stream edge habitat. Samples were collected using each method at 525 sites in five of nine aggregate ecoregions located in the conterminous USA. Methods were compared using the benthic macroinvertebrate multimetric index developed for the 2006 Wadeable Streams Assessment. Statistical analysis did not reveal any trends that would suggest the overall assessment of low-gradient streams on a regional or national scale would change if the alternate method was used rather than the standard sampling method, regardless of the gradient cutoff used to define low-gradient streams. Based on these results, the National Rivers and Streams Survey should continue to use the standard field method for sampling all streams.

Measuring and monitoring biological diversity: Standard methods for mammals

USGS Publications Warehouse

Wilson, Don E.; Cole, F. Russell; Nichols, James D.; Rudran, Rasanayagam; Foster, Mercedes S.

1996-01-01

Measuring and Monitoring Biological Diversity: Standard Methods for Mammals provides a comprehensive manual for designing and implementing inventories of mammalian biodiversity anywhere in the world and for any group, from rodents to open-country grazers. The book emphasizes formal estimation approaches, which supply data that can be compared across habitats and over time. Beginning with brief natural histories of the twenty-six orders of living mammals, the book details the field techniques—observation, capture, and sign interpretation—appropriate to different species. The contributors provide guidelines for study design, discuss survey planning, describe statistical techniques, and outline methods of translating field data into electronic formats. Extensive appendixes address such issues as the ethical treatment of animals in research, human health concerns, preserving voucher specimens, and assessing age, sex, and reproductive condition in mammals.Useful in both developed and developing countries, this volume and the Biological Diversity Handbook Series as a whole establish essential standards for a key aspect of conservation biology and resource management.

From plastic to gold: a unified classification scheme for reference standards in medical image processing

NASA Astrophysics Data System (ADS)

Lehmann, Thomas M.

2002-05-01

Reliable evaluation of medical image processing is of major importance for routine applications. Nonetheless, evaluation is often omitted or methodically defective when novel approaches or algorithms are introduced. Adopted from medical diagnosis, we define the following criteria to classify reference standards: 1. Reliance, if the generation or capturing of test images for evaluation follows an exactly determined and reproducible protocol. 2. Equivalence, if the image material or relationships considered within an algorithmic reference standard equal real-life data with respect to structure, noise, or other parameters of importance. 3. Independence, if any reference standard relies on a different procedure than that to be evaluated, or on other images or image modalities than that used routinely. This criterion bans the simultaneous use of one image for both, training and test phase. 4. Relevance, if the algorithm to be evaluated is self-reproducible. If random parameters or optimization strategies are applied, reliability of the algorithm must be shown before the reference standard is applied for evaluation. 5. Significance, if the number of reference standard images that are used for evaluation is sufficient large to enable statistically founded analysis. We demand that a true gold standard must satisfy the Criteria 1 to 3. Any standard only satisfying two criteria, i.e., Criterion 1 and Criterion 2 or Criterion 1 and Criterion 3, is referred to as silver standard. Other standards are termed to be from plastic. Before exhaustive evaluation based on gold or silver standards is performed, its relevance must be shown (Criterion 4) and sufficient tests must be carried out to found statistical analysis (Criterion 5). In this paper, examples are given for each class of reference standards.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

PubMed

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

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal

PubMed Central

Park, Ji Eun; Han, Kyunghwa; Sung, Yu Sub; Chung, Mi Sun; Koo, Hyun Jung; Yoon, Hee Mang; Choi, Young Jun; Lee, Seung Soo; Kim, Kyung Won; Shin, Youngbin; An, Suah; Cho, Hyo-Min

2017-01-01

Objective To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary. PMID:29089821

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2017-01-01

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

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

DOE PAGES

Jeffrey, N.; Abdalla, F. B.; Lahav, O.; ...

2018-05-15

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three different mass map reconstruction methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion method, taking no account of survey masks or noise. The Wiener filter is well motivated for Gaussian density fields in a Bayesian framework. The GLIMPSE method uses sparsity, with the aim of reconstructing non-linearities in themore » density field. We compare these methods with a series of tests on the public Dark Energy Survey (DES) Science Verification (SV) data and on realistic DES simulations. The Wiener filter and GLIMPSE methods offer substantial improvement on the standard smoothed KS with a range of metrics. For both the Wiener filter and GLIMPSE convergence reconstructions we present a 12% improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods' abilities to find mass peaks, we measure the difference between peak counts from simulated {\\Lambda}CDM shear catalogues and catalogues with no mass fluctuations. This is a standard data vector when inferring cosmology from peak statistics. The maximum signal-to-noise value of these peak statistic data vectors was increased by a factor of 3.5 for the Wiener filter and by a factor of 9 using GLIMPSE. With simulations we measure the reconstruction of the harmonic phases, showing that the concentration of the phase residuals is improved 17% by GLIMPSE and 18% by the Wiener filter. We show that the correlation between the reconstructions from data and the foreground redMaPPer clusters is increased 18% by the Wiener filter and 32% by GLIMPSE. [Abridged]« less

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

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

Jeffrey, N.; et al.

2018-01-26

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three different mass map reconstruction methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion method, taking no account of survey masks or noise. The Wiener filter is well motivated for Gaussian density fields in a Bayesian framework. The GLIMPSE method uses sparsity, with the aim of reconstructing non-linearities in themore » density field. We compare these methods with a series of tests on the public Dark Energy Survey (DES) Science Verification (SV) data and on realistic DES simulations. The Wiener filter and GLIMPSE methods offer substantial improvement on the standard smoothed KS with a range of metrics. For both the Wiener filter and GLIMPSE convergence reconstructions we present a 12% improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods' abilities to find mass peaks, we measure the difference between peak counts from simulated {\\Lambda}CDM shear catalogues and catalogues with no mass fluctuations. This is a standard data vector when inferring cosmology from peak statistics. The maximum signal-to-noise value of these peak statistic data vectors was increased by a factor of 3.5 for the Wiener filter and by a factor of 9 using GLIMPSE. With simulations we measure the reconstruction of the harmonic phases, showing that the concentration of the phase residuals is improved 17% by GLIMPSE and 18% by the Wiener filter. We show that the correlation between the reconstructions from data and the foreground redMaPPer clusters is increased 18% by the Wiener filter and 32% by GLIMPSE. [Abridged]« less

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

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

Jeffrey, N.; Abdalla, F. B.; Lahav, O.

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three different mass map reconstruction methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion method, taking no account of survey masks or noise. The Wiener filter is well motivated for Gaussian density fields in a Bayesian framework. The GLIMPSE method uses sparsity, with the aim of reconstructing non-linearities in themore » density field. We compare these methods with a series of tests on the public Dark Energy Survey (DES) Science Verification (SV) data and on realistic DES simulations. The Wiener filter and GLIMPSE methods offer substantial improvement on the standard smoothed KS with a range of metrics. For both the Wiener filter and GLIMPSE convergence reconstructions we present a 12% improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods' abilities to find mass peaks, we measure the difference between peak counts from simulated {\\Lambda}CDM shear catalogues and catalogues with no mass fluctuations. This is a standard data vector when inferring cosmology from peak statistics. The maximum signal-to-noise value of these peak statistic data vectors was increased by a factor of 3.5 for the Wiener filter and by a factor of 9 using GLIMPSE. With simulations we measure the reconstruction of the harmonic phases, showing that the concentration of the phase residuals is improved 17% by GLIMPSE and 18% by the Wiener filter. We show that the correlation between the reconstructions from data and the foreground redMaPPer clusters is increased 18% by the Wiener filter and 32% by GLIMPSE. [Abridged]« less

A Fresh Start for Flood Estimation in Ungauged Basins

NASA Astrophysics Data System (ADS)

Woods, R. A.

2017-12-01

The two standard methods for flood estimation in ungauged basins, regression-based statistical models and rainfall-runoff models using a design rainfall event, have survived relatively unchanged as the methods of choice for more than 40 years. Their technical implementation has developed greatly, but the models' representation of hydrological processes has not, despite a large volume of hydrological research. I suggest it is time to introduce more hydrology into flood estimation. The reliability of the current methods can be unsatisfactory. For example, despite the UK's relatively straightforward hydrology, regression estimates of the index flood are uncertain by +/- a factor of two (for a 95% confidence interval), an impractically large uncertainty for design. The standard error of rainfall-runoff model estimates is not usually known, but available assessments indicate poorer reliability than statistical methods. There is a practical need for improved reliability in flood estimation. Two promising candidates to supersede the existing methods are (i) continuous simulation by rainfall-runoff modelling and (ii) event-based derived distribution methods. The main challenge with continuous simulation methods in ungauged basins is to specify the model structure and parameter values, when calibration data are not available. This has been an active area of research for more than a decade, and this activity is likely to continue. The major challenges for the derived distribution method in ungauged catchments include not only the correct specification of model structure and parameter values, but also antecedent conditions (e.g. seasonal soil water balance). However, a much smaller community of researchers are active in developing or applying the derived distribution approach, and as a result slower progress is being made. A change in needed: surely we have learned enough about hydrology in the last 40 years that we can make a practical hydrological advance on our methods for flood estimation! A shift to new methods for flood estimation will not be taken lightly by practitioners. However, the standard for change is clear - can we develop new methods which give significant improvements in reliability over those existing methods which are demonstrably unsatisfactory?

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

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

PubMed

Henderson, G; Fahey, T; McGuire, W

2007-10-17

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

Examining the Reproducibility of 6 Published Studies in Public Health Services and Systems Research.

PubMed

Harris, Jenine K; B Wondmeneh, Sarah; Zhao, Yiqiang; Leider, Jonathon P

2018-02-23

Research replication, or repeating a study de novo, is the scientific standard for building evidence and identifying spurious results. While replication is ideal, it is often expensive and time consuming. Reproducibility, or reanalysis of data to verify published findings, is one proposed minimum alternative standard. While a lack of research reproducibility has been identified as a serious and prevalent problem in biomedical research and a few other fields, little work has been done to examine the reproducibility of public health research. We examined reproducibility in 6 studies from the public health services and systems research subfield of public health research. Following the methods described in each of the 6 papers, we computed the descriptive and inferential statistics for each study. We compared our results with the original study results and examined the percentage differences in descriptive statistics and differences in effect size, significance, and precision of inferential statistics. All project work was completed in 2017. We found consistency between original and reproduced results for each paper in at least 1 of the 4 areas examined. However, we also found some inconsistency. We identified incorrect transcription of results and omitting detail about data management and analyses as the primary contributors to the inconsistencies. Increasing reproducibility, or reanalysis of data to verify published results, can improve the quality of science. Researchers, journals, employers, and funders can all play a role in improving the reproducibility of science through several strategies including publishing data and statistical code, using guidelines to write clear and complete methods sections, conducting reproducibility reviews, and incentivizing reproducible science.

Guidelines for Assessment and Instruction in Statistics Education (GAISE): extending GAISE into nursing education.

PubMed

Hayat, Matthew J

2014-04-01

Statistics coursework is usually a core curriculum requirement for nursing students at all degree levels. The American Association of Colleges of Nursing (AACN) establishes curriculum standards for academic nursing programs. However, the AACN provides little guidance on statistics education and does not offer standardized competency guidelines or recommendations about course content or learning objectives. Published standards may be used in the course development process to clarify course content and learning objectives. This article includes suggestions for implementing and integrating recommendations given in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) report into statistics education for nursing students. Copyright 2014, SLACK Incorporated.

Standard Errors and Confidence Intervals of Norm Statistics for Educational and Psychological Tests.

PubMed

Oosterhuis, Hannah E M; van der Ark, L Andries; Sijtsma, Klaas

2016-11-14

Norm statistics allow for the interpretation of scores on psychological and educational tests, by relating the test score of an individual test taker to the test scores of individuals belonging to the same gender, age, or education groups, et cetera. Given the uncertainty due to sampling error, one would expect researchers to report standard errors for norm statistics. In practice, standard errors are seldom reported; they are either unavailable or derived under strong distributional assumptions that may not be realistic for test scores. We derived standard errors for four norm statistics (standard deviation, percentile ranks, stanine boundaries and Z-scores) under the mild assumption that the test scores are multinomially distributed. A simulation study showed that the standard errors were unbiased and that corresponding Wald-based confidence intervals had good coverage. Finally, we discuss the possibilities for applying the standard errors in practical test use in education and psychology. The procedure is provided via the R function check.norms, which is available in the mokken package.

The Next-Generation PCR-Based Quantification Method for Ambient Waters: Digital PCR.

PubMed

Cao, Yiping; Griffith, John F; Weisberg, Stephen B

2016-01-01

Real-time quantitative PCR (qPCR) is increasingly being used for ambient water monitoring, but development of digital polymerase chain reaction (digital PCR) has the potential to further advance the use of molecular techniques in such applications. Digital PCR refines qPCR by partitioning the sample into thousands to millions of miniature reactions that are examined individually for binary endpoint results, with DNA density calculated from the fraction of positives using Poisson statistics. This direct quantification removes the need for standard curves, eliminating the labor and materials associated with creating and running standards with each batch, and removing biases associated with standard variability and mismatching amplification efficiency between standards and samples. Confining reactions and binary endpoint measurements to small partitions also leads to other performance advantages, including reduced susceptibility to inhibition, increased repeatability and reproducibility, and increased capacity to measure multiple targets in one analysis. As such, digital PCR is well suited for ambient water monitoring applications and is particularly advantageous as molecular methods move toward autonomous field application.

Growth rate measurement in free jet experiments

NASA Astrophysics Data System (ADS)

Charpentier, Jean-Baptiste; Renoult, Marie-Charlotte; Crumeyrolle, Olivier; Mutabazi, Innocent

2017-07-01

An experimental method was developed to measure the growth rate of the capillary instability for free liquid jets. The method uses a standard shadow-graph imaging technique to visualize a jet, produced by extruding a liquid through a circular orifice, and a statistical analysis of the entire jet. The analysis relies on the computation of the standard deviation of a set of jet profiles, obtained in the same experimental conditions. The principle and robustness of the method are illustrated with a set of emulated jet profiles. The method is also applied to free falling jet experiments conducted for various Weber numbers and two low-viscosity solutions: a Newtonian and a viscoelastic one. Growth rate measurements are found in good agreement with linear stability theory in the Rayleigh's regime, as expected from previous studies. In addition, the standard deviation curve is used to obtain an indirect measurement of the initial perturbation amplitude and to identify beads on a string structure on the jet. This last result serves to demonstrate the capability of the present technique to explore in the future the dynamics of viscoelastic liquid jets.

Determination of the moisture content of instant noodles: interlaboratory study.

PubMed

Hakoda, Akiko; Kasama, Hirotaka; Sakaida, Kenichi; Suzuki, Tadanao; Yasui, Akemi

2006-01-01

Determination of the moisture content of instant noodles, currently under discussion by the Codex Alimentarius Commission (CAC) requires 2 methods: one for fried noodles and the other for nonfried noodles. The method to determine the moisture content of fried noodles by drying at 105 degrees C for 2 h used in the Japanese Agricultural Standard (JAS) system of Japan can be applied to this purpose. In the present study, the JAS method for fried noodles was modified to be suitable for nonfried noodles by extending the drying time to 4 h. An interlaboratory study was conducted to evaluate interlaboratory performance statistics for these 2 methods. Ten participating laboratories each analyzed 5 test materials of fried and nonfried noodles as blind duplicates. After removal of outliers statistically, the repeatability (RSDr) and the reproducibility (RSD(R)) of these methods were 1.6-2.6 and 3.9-4.8% for fried noodles, and 0.3-1.5 and 1.3-2.9% for nonfried noodles, respectively.

Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

PubMed

Campos-Filho, N; Franco, E L

1989-02-01

A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

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

PubMed

Lifshits, A M

1979-01-01

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

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Inference of median difference based on the Box-Cox model in randomized clinical trials.

PubMed

Maruo, K; Isogawa, N; Gosho, M

2015-05-10

In randomized clinical trials, many medical and biological measurements are not normally distributed and are often skewed. The Box-Cox transformation is a powerful procedure for comparing two treatment groups for skewed continuous variables in terms of a statistical test. However, it is difficult to directly estimate and interpret the location difference between the two groups on the original scale of the measurement. We propose a helpful method that infers the difference of the treatment effect on the original scale in a more easily interpretable form. We also provide statistical analysis packages that consistently include an estimate of the treatment effect, covariance adjustments, standard errors, and statistical hypothesis tests. The simulation study that focuses on randomized parallel group clinical trials with two treatment groups indicates that the performance of the proposed method is equivalent to or better than that of the existing non-parametric approaches in terms of the type-I error rate and power. We illustrate our method with cluster of differentiation 4 data in an acquired immune deficiency syndrome clinical trial. Copyright © 2015 John Wiley & Sons, Ltd.

Automated finite element modeling of the lumbar spine: Using a statistical shape model to generate a virtual population of models.

PubMed

Campbell, J Q; Petrella, A J

2016-09-06

Population-based modeling of the lumbar spine has the potential to be a powerful clinical tool. However, developing a fully parameterized model of the lumbar spine with accurate geometry has remained a challenge. The current study used automated methods for landmark identification to create a statistical shape model of the lumbar spine. The shape model was evaluated using compactness, generalization ability, and specificity. The primary shape modes were analyzed visually, quantitatively, and biomechanically. The biomechanical analysis was performed by using the statistical shape model with an automated method for finite element model generation to create a fully parameterized finite element model of the lumbar spine. Functional finite element models of the mean shape and the extreme shapes (±3 standard deviations) of all 17 shape modes were created demonstrating the robust nature of the methods. This study represents an advancement in finite element modeling of the lumbar spine and will allow population-based modeling in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Effect of General Statistical Fiber Misalignment on Predicted Damage Initiation in Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2014-01-01

A micromechanical method is employed for the prediction of unidirectional composites in which the fiber orientation can possess various statistical misalignment distributions. The method relies on the probability-weighted averaging of the appropriate concentration tensor, which is established by the micromechanical procedure. This approach provides access to the local field quantities throughout the constituents, from which initiation of damage in the composite can be predicted. In contrast, a typical macromechanical procedure can determine the effective composite elastic properties in the presence of statistical fiber misalignment, but cannot provide the local fields. Fully random fiber distribution is presented as a special case using the proposed micromechanical method. Results are given that illustrate the effects of various amounts of fiber misalignment in terms of the standard deviations of in-plane and out-of-plane misalignment angles, where normal distributions have been employed. Damage initiation envelopes, local fields, effective moduli, and strengths are predicted for polymer and ceramic matrix composites with given normal distributions of misalignment angles, as well as fully random fiber orientation.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution

PubMed Central

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-01

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A 468, 1799–1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi–Dirac or Bose–Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas. PMID:24399919

[Study on commercial specification of atractylodes based on Delphi method].

PubMed

Wang, Hao; Chen, Li-Xiao; Huang, Lu-Qi; Zhang, Tian-Tian; Li, Ying; Zheng, Yu-Guang

2016-03-01

This research adopts "Delphi method" to evaluate atractylodes traditional traits and rank correlation. By using methods of mathematical statistics the relationship of the traditional identification indicators and atractylodes goods rank correlation was analyzed, It is found that the main characteristics affectingatractylodes commodity specifications and grades of main characters wereoil points of transaction,color of transaction,color of surface,grain of transaction,texture of transaction andspoilage. The study points out that the original "seventy-six kinds of medicinal materials commodity specification standards of atractylodes differentiate commodity specification" is not in conformity with the actual market situation, we need to formulate corresponding atractylodes medicinal products specifications and grades.This study combined with experimental results "Delphi method" and the market actual situation, proposed the new draft atractylodes commodity specifications and grades, as the new atractylodes commodity specifications and grades standards. It provides a reference and theoretical basis. Copyright© by the Chinese Pharmaceutical Association.

The Survival of Morse Cone-Connection Implants with Platform Switch.

PubMed

Cassetta, Michele; Di Mambro, Alfonso; Giansanti, Matteo; Brandetti, Giulia

2016-01-01

The aim of this prospective clinical study was to evaluate the survival up to 5 years of Morse cone-connection implants with platform switch considering the influence of biologically relevant, anatomical, and stress-related variables. STROBE guidelines were followed. Seven hundred forty-eight implants were inserted in 350 patients. Follow-up visits were scheduled at the time of stagetwo surgery (2 months later) and at 6, 12, 24, 36, and 60 months. All implants were initially loaded with a cemented provisional acrylic restoration. The definitive metal-ceramic restorations were cemented at the 6-month follow-up. Implant cumulative survival rates (CSRs) were calculated using life table actuarial method. Survival data were also analyzed by the log-rank test and Cox regression. The statistical analysis was conducted at the patient level. P ≤ .05 was considered as an indicator of statistical significance. During the follow-up (mean: 40 months; SD: 20.27), 28 patients were considered failed (8%). The CSR and its standard error (SE) was 92% ± 2.17%. Patients with implant-supported single crowns had a CSR of 90%, whereas those with implant-supported fixed dental prostheses had a CSR of 93%. The implant diameter (P = .0399) and implant length (P = .0441) were statistically significant. The probability of failure was almost 75% lower for patients with wide rather than standard implants, 91% lower for patients with long implants, and 69% lower for patients with standard implants compared with short implants. The use of Morse cone-connection implants with platform switch is a safe and reliable treatment method. Stress-related variables influence the risk of failure confirming the importance of biomechanical factors in the longevity of osseointegrated implants; thus, the clinician may obtain better results if attention is paid to these factors.

A Comparison of pical Root Resorption in Incisors after Fixed Orthodontic Treatment with Standard Edgewise and Straight Wire (MBT) Method

PubMed Central

Zahed Zahedani, SM; Oshagh, M; Momeni Danaei, Sh; Roeinpeikar, SMM

2013-01-01

Statement of Problem: One of the major outcomes of orthodontic treatment is the apical root resorption of teeth moved during the treatment. Identifying the possible risk factors, are necessary for every orthodontist. Purpose: The aim of this study was to compare the rate of apical root resorption after fixed orthodontic treatment with standard edgewise and straight wire (MBT) method, and also to evaluate other factors effecting the rate of root resorption in orthodontic treatments. Materials and Method: In this study, parallel periapical radiographs of 127 patients imaging a total of 737 individual teeth, were collected. A total of 76 patients were treated by standard edgewise and 51 patients by straight wire method. The periapical radiographs were scanned and then the percentage of root resorption was calculated by Photoshop software. The data were analyzed by Paired-Samples t-test and the Generalized Linear Model adopting the SPSS 15.0. Results: In patients treated with straight wire method (MBT), mean root resorption was 18.26% compared to 14.82% in patients treated with standard edgewise technique (p< .05). Male patients had higher rate of root resorption,statistically significant (p< .05). Age at onset of treatment, duration of treatment, type of dental occlusion, premolar extractions and the use of intermaxillary elastics had no significant effect on the root resorption in this study. Conclusion: Having more root resorption in the straight wire method and less in the standard edgewise technique can be attributed to more root movement in pre-adjusted MBT technique due to the brackets employed in this method. PMID:24724131

Study on Standard Fatigue Vehicle Load Model

NASA Astrophysics Data System (ADS)

Huang, H. Y.; Zhang, J. P.; Li, Y. H.

2018-02-01

Based on the measured data of truck from three artery expressways in Guangdong Province, the statistical analysis of truck weight was conducted according to axle number. The standard fatigue vehicle model applied to industrial areas in the middle and late was obtained, which adopted equivalence damage principle, Miner linear accumulation law, water discharge method and damage ratio theory. Compared with the fatigue vehicle model Specified by the current bridge design code, the proposed model has better applicability. It is of certain reference value for the fatigue design of bridge in China.

How Historical Information Can Improve Extreme Value Analysis of Coastal Water Levels

NASA Astrophysics Data System (ADS)

Le Cozannet, G.; Bulteau, T.; Idier, D.; Lambert, J.; Garcin, M.

2016-12-01

The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces outliers, those particularly extreme values distant from the others. In a recent work (Bulteau et al., 2015), we investigated how historical information of past events reported in archives can reduce statistical uncertainties and relativize such outlying observations. We adapted a Bayesian Markov Chain Monte Carlo method, initially developed in the hydrology field (Reis and Stedinger, 2005), to the specific case of coastal water levels. We applied this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide gauge measurements and 8 historical events since 1890, the results showed a significant decrease in statistical uncertainties on return levels when historical information is used. Also, Xynthia's water level no longer appeared as an outlier and we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data until the end of 2009 of the same order of magnitude as the standard estimative probability using data until the end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

Evaluation of a low-cost commercially available extraction device for assessing lead bioaccessibility in contaminated soils.

PubMed

Nelson, Clay M; Gilmore, Thomas M; Harrington, M; Scheckel, Kirk G; Miller, Bradley W; Bradham, Karen D

2013-03-01

The U.S. EPA's in vitro bioaccessibility (IVBA) method 9200.1-86 defines a validated analytical procedure for the determination of lead bioaccessibility in contaminated soils. The method requires the use of a custom-fabricated extraction device that uses a heated water bath for sample incubation. In an effort to improve ease of use, increase sample throughput, and reduce equipment acquisition and maintenance costs, an alternative low-cost, commercially available extraction device capable of sample incubation via heated air and end-over-end rotation was evaluated. An intra-laboratory study was conducted to compare lead bioaccessibility values derived using the two extraction devices. IVBA values were not statistically different (α = 0.05) between the two extraction devices for any of the soils (n = 6) evaluated in this study, with an average difference in mean lead IVBA of 0.8% (s.d. = 0.5%). The commercially available extraction device was able to generate accurate lead IVBA data as compared to the U.S. EPA's expected value for a National Institute of Standards and Technology standard reference material soil. The relative percent differences between high and low IVBA values for each soil, a measure of instrument precision, were also not statistically different (α = 0.05) between the two extraction devices. The statistical agreement of lead IVBA values observed using the two extraction devices supports the use of a low-cost, commercially available extraction device as a reliable alternative to a custom-fabricated device as required by EPA method 9200.1-86.

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

PubMed

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

2015-11-03

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

A Generalized Form of Context-Dependent Psychophysiological Interactions (gPPI): A Comparison to Standard Approaches

PubMed Central

McLaren, Donald G.; Ries, Michele L.; Xu, Guofan; Johnson, Sterling C.

2012-01-01

Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike Information Criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings. PMID:22484411

Validation of Physics Standardized Test Items

NASA Astrophysics Data System (ADS)

Marshall, Jill

2008-10-01

The Texas Physics Assessment Team (TPAT) examined the Texas Assessment of Knowledge and Skills (TAKS) to determine whether it is a valid indicator of physics preparation for future course work and employment, and of the knowledge and skills needed to act as an informed citizen in a technological society. We categorized science items from the 2003 and 2004 10th and 11th grade TAKS by content area(s) covered, knowledge and skills required to select the correct answer, and overall quality. We also analyzed a 5000 student sample of item-level results from the 2004 11th grade exam using standard statistical methods employed by test developers (factor analysis and Item Response Theory). Triangulation of our results revealed strengths and weaknesses of the different methods of analysis. The TAKS was found to be only weakly indicative of physics preparation and we make recommendations for increasing the validity of standardized physics testing..

Methods for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma

USGS Publications Warehouse

Esralew, Rachel A.; Smith, S. Jerrod

2010-01-01

Flow statistics can be used to provide decision makers with surface-water information needed for activities such as water-supply permitting, flow regulation, and other water rights issues. Flow statistics could be needed at any location along a stream. Most often, streamflow statistics are needed at ungaged sites, where no flow data are available to compute the statistics. Methods are presented in this report for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma. Flow statistics included the (1) annual (period of record), (2) seasonal (summer-autumn and winter-spring), and (3) 12 monthly duration statistics, including the 20th, 50th, 80th, 90th, and 95th percentile flow exceedances, and the annual mean-flow (mean of daily flows for the period of record). Flow statistics were calculated from daily streamflow information collected from 235 streamflow-gaging stations throughout Oklahoma and areas in adjacent states. A drainage-area ratio method is the preferred method for estimating flow statistics at an ungaged location that is on a stream near a gage. The method generally is reliable only if the drainage-area ratio of the two sites is between 0.5 and 1.5. Regression equations that relate flow statistics to drainage-basin characteristics were developed for the purpose of estimating selected flow-duration and annual mean-flow statistics for ungaged streams that are not near gaging stations on the same stream. Regression equations were developed from flow statistics and drainage-basin characteristics for 113 unregulated gaging stations. Separate regression equations were developed by using U.S. Geological Survey streamflow-gaging stations in regions with similar drainage-basin characteristics. These equations can increase the accuracy of regression equations used for estimating flow-duration and annual mean-flow statistics at ungaged stream locations in Oklahoma. Streamflow-gaging stations were grouped by selected drainage-basin characteristics by using a k-means cluster analysis. Three regions were identified for Oklahoma on the basis of the clustering of gaging stations and a manual delineation of distinguishable hydrologic and geologic boundaries: Region 1 (western Oklahoma excluding the Oklahoma and Texas Panhandles), Region 2 (north- and south-central Oklahoma), and Region 3 (eastern and central Oklahoma). A total of 228 regression equations (225 flow-duration regressions and three annual mean-flow regressions) were developed using ordinary least-squares and left-censored (Tobit) multiple-regression techniques. These equations can be used to estimate 75 flow-duration statistics and annual mean-flow for ungaged streams in the three regions. Drainage-basin characteristics that were statistically significant independent variables in the regression analyses were (1) contributing drainage area; (2) station elevation; (3) mean drainage-basin elevation; (4) channel slope; (5) percentage of forested canopy; (6) mean drainage-basin hillslope; (7) soil permeability; and (8) mean annual, seasonal, and monthly precipitation. The accuracy of flow-duration regression equations generally decreased from high-flow exceedance (low-exceedance probability) to low-flow exceedance (high-exceedance probability) . This decrease may have happened because a greater uncertainty exists for low-flow estimates and low-flow is largely affected by localized geology that was not quantified by the drainage-basin characteristics selected. The standard errors of estimate of regression equations for Region 1 (western Oklahoma) were substantially larger than those standard errors for other regions, especially for low-flow exceedances. These errors may be a result of greater variability in low flow because of increased irrigation activities in this region. Regression equations may not be reliable for sites where the drainage-basin characteristics are outside the range of values of independent vari

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-07-25

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

The critical role of NIR spectroscopy and statistical process control (SPC) strategy towards captopril tablets (25 mg) manufacturing process understanding: a case study.

PubMed

Curtivo, Cátia Panizzon Dal; Funghi, Nathália Bitencourt; Tavares, Guilherme Diniz; Barbosa, Sávio Fujita; Löbenberg, Raimar; Bou-Chacra, Nádia Araci

2015-05-01

In this work, near-infrared spectroscopy (NIRS) method was used to evaluate the uniformity of dosage units of three captopril 25 mg tablets commercial batches. The performance of the calibration method was assessed by determination of Q value (0.9986), standard error of estimation (C-set SEE = 1.956), standard error of prediction (V-set SEP = 2.076) as well as the consistency (106.1%). These results indicated the adequacy of the selected model. The method validation revealed the agreement of the reference high pressure liquid chromatography (HPLC) and NIRS methods. The process evaluation using the NIRS method showed that the variability was due to common causes and delivered predictable results consistently. Cp and Cpk values were, respectively, 2.05 and 1.80. These results revealed a non-centered process in relation to the average target (100% w/w), in the specified range (85-115%). The probability of failure was 21:100 million tablets of captopril. The NIRS in combination with the method of multivariate calibration, partial least squares (PLS) regression, allowed the development of methodology for the uniformity of dosage units evaluation of captopril tablets 25 mg. The statistical process control strategy associated with NIRS method as PAT played a critical role in understanding of the sources and degree of variation and its impact on the process. This approach led towards a better process understanding and provided the sound scientific basis for its continuous improvement.

Compensation of matrix effects in gas chromatography-mass spectrometry analysis of pesticides using a combination of matrix matching and multiple isotopically labeled internal standards.

PubMed

Tsuchiyama, Tomoyuki; Katsuhara, Miki; Nakajima, Masahiro

2017-11-17

In the multi-residue analysis of pesticides using GC-MS, the quantitative results are adversely affected by a phenomenon known as the matrix effect. Although the use of matrix-matched standards is considered to be one of the most practical solutions to this problem, complete removal of the matrix effect is difficult in complex food matrices owing to their inconsistency. As a result, residual matrix effects can introduce analytical errors. To compensate for residual matrix effects, we have developed a novel method that employs multiple isotopically labeled internal standards (ILIS). The matrix effects of ILIS and pesticides were evaluated in spiked matrix extracts of various agricultural commodities, and the obtained data were subjected to simple statistical analysis. Based on the similarities between the patterns of variation in the analytical response, a total of 32 isotopically labeled compounds were assigned to 338 pesticides as internal standards. It was found that by utilizing multiple ILIS, residual matrix effects could be effectively compensated. The developed method exhibited superior quantitative performance compared with the common single-internal-standard method. The proposed method is more feasible for regulatory purposes than that using only predetermined correction factors and is considered to be promising for practical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Composite Linear Models | Division of Cancer Prevention

Cancer.gov

By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty

Report to the Higher Education Policy Commission. West Virginia Higher Education Facilities Information System Statewide Institution Report.

ERIC Educational Resources Information Center

West Virginia Higher Education Policy Commission, 2004

2004-01-01

The West Virginia Higher Education Facilities Information System was formed as a method for instituting statewide standardization of space use and classification; to serve as a vehicle for statewide data acquisition; and to provide statistical data that contributes to detailed institutional planning analysis. The result thus far is the production…

Analysis of variance calculations for irregular experiments

Treesearch

Jonathan W. Wright

1977-01-01

Irregular experiments may be more useful than much smaller regular experiments and can be analyzed statistically without undue expenditure of time. For a few missing plots, standard methods of calculating missing-plot values can be used. For more missing plots (up to 10 percent), seedlot means or randomly chosen plot means of the same seedlot can be substituted for...

NHEXAS PHASE I MARYLAND STUDY--STANDARD OPERATING PROCEDURE FOR EXPLORATORY DATA ANALYSIS AND SUMMARY STATISTICS (D05)

EPA Science Inventory

This SOP describes the methods and procedures for two types of QA procedures: spot checks of hand entered data, and QA procedures for co-located and split samples. The spot checks were used to determine whether the error rate goal for the input of hand entered data was being att...

Volcano plots in analyzing differential expressions with mRNA microarrays.

PubMed

Li, Wentian

2012-12-01

A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.

Statistical Characterization and Classification of Edge-Localized Plasma Instabilities

NASA Astrophysics Data System (ADS)

Webster, A. J.; Dendy, R. O.

2013-04-01

The statistics of edge-localized plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability distribution for the waiting times between ELMs: the Weibull distribution. This is confirmed empirically by a statistically rigorous comparison with a large data set from the Joint European Torus. The successful characterization of ELM waiting times enables future work to progress in various ways. Here we present a quantitative classification of ELM types, complementary to phenomenological approaches. It also informs us about the nature of ELM processes, such as whether they are random or deterministic. The methods are extremely general and can be applied to numerous other quasiperiodic intermittent phenomena.

TREATMENT SWITCHING: STATISTICAL AND DECISION-MAKING CHALLENGES AND APPROACHES.

PubMed

Latimer, Nicholas R; Henshall, Chris; Siebert, Uwe; Bell, Helen

2016-01-01

Treatment switching refers to the situation in a randomized controlled trial where patients switch from their randomly assigned treatment onto an alternative. Often, switching is from the control group onto the experimental treatment. In this instance, a standard intention-to-treat analysis does not identify the true comparative effectiveness of the treatments under investigation. We aim to describe statistical methods for adjusting for treatment switching in a comprehensible way for nonstatisticians, and to summarize views on these methods expressed by stakeholders at the 2014 Adelaide International Workshop on Treatment Switching in Clinical Trials. We describe three statistical methods used to adjust for treatment switching: marginal structural models, two-stage adjustment, and rank preserving structural failure time models. We draw upon discussion heard at the Adelaide International Workshop to explore the views of stakeholders on the acceptability of these methods. Stakeholders noted that adjustment methods are based on assumptions, the validity of which may often be questionable. There was disagreement on the acceptability of adjustment methods, but consensus that when these are used, they should be justified rigorously. The utility of adjustment methods depends upon the decision being made and the processes used by the decision-maker. Treatment switching makes estimating the true comparative effect of a new treatment challenging. However, many decision-makers have reservations with adjustment methods. These, and how they affect the utility of adjustment methods, require further exploration. Further technical work is required to develop adjustment methods to meet real world needs, to enhance their acceptability to decision-makers.

Determination of polarimetric parameters of honey by near-infrared transflectance spectroscopy.

PubMed

García-Alvarez, M; Ceresuela, S; Huidobro, J F; Hermida, M; Rodríguez-Otero, J L

2002-01-30

NIR transflectance spectroscopy was used to determine polarimetric parameters (direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides) and sucrose in honey. In total, 156 honey samples were collected during 1992 (45 samples), 1995 (56 samples), and 1996 (55 samples). Samples were analyzed by NIR spectroscopy and polarimetric methods. Calibration (118 samples) and validation (38 samples) sets were made up; honeys from the three years were included in both sets. Calibrations were performed by modified partial least-squares regression and scatter correction by standard normal variation and detrend methods. For direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides, good statistics (bias, SEV, and R(2)) were obtained for the validation set, and no statistically (p = 0.05) significant differences were found between instrumental and polarimetric methods for these parameters. Statistical data for sucrose were not as good as those of the other parameters. Therefore, NIR spectroscopy is not an effective method for quantitative analysis of sucrose in these honey samples. However, NIR spectroscopy may be an acceptable method for semiquantitative evaluation of sucrose for honeys, such as those in our study, containing up to 3% of sucrose. Further work is necessary to validate the uncertainty at higher levels.

Physics of Electronic Materials

NASA Astrophysics Data System (ADS)

Rammer, Jørgen

2017-03-01

1. Quantum mechanics; 2. Quantum tunneling; 3. Standard metal model; 4. Standard conductor model; 5. Electric circuit theory; 6. Quantum wells; 7. Particle in a periodic potential; 8. Bloch currents; 9. Crystalline solids; 10. Semiconductor doping; 11. Transistors; 12. Heterostructures; 13. Mesoscopic physics; 14. Arithmetic, logic and machines; Appendix A. Principles of quantum mechanics; Appendix B. Dirac's delta function; Appendix C. Fourier analysis; Appendix D. Classical mechanics; Appendix E. Wave function properties; Appendix F. Transfer matrix properties; Appendix G. Momentum; Appendix H. Confined particles; Appendix I. Spin and quantum statistics; Appendix J. Statistical mechanics; Appendix K. The Fermi-Dirac distribution; Appendix L. Thermal current fluctuations; Appendix M. Gaussian wave packets; Appendix N. Wave packet dynamics; Appendix O. Screening by symmetry method; Appendix P. Commutation and common eigenfunctions; Appendix Q. Interband coupling; Appendix R. Common crystal structures; Appendix S. Effective mass approximation; Appendix T. Integral doubling formula; Bibliography; Index.

Mapping Norway - a Method to Register and Survey the Status of Accessibility

NASA Astrophysics Data System (ADS)

Michaelis, Sven; Bögelsack, Kathrin

2018-05-01

The Norwegian mapping authority has developed a standard method for mapping accessibility mostly for people with limited or no walking abilities in urban and recreational areas. We choose an object-orientated approach where points, lines and polygons represents objects in the environment. All data are stored in a geospatial database, so they can be presented as web map and analyzed using GIS software. By the end of 2016 more than 160 municipalities are mapped using that method. The aim of this project is to establish a national standard for mapping and to provide a geodatabase that shows the status of accessibility throughout Norway. The data provide a useful tool for national statistics, local planning authorities and private users. First results show that accessibility is low and Norway still faces many challenges to meet the government's goals for Universal Design.

Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

NASA Astrophysics Data System (ADS)

Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

2016-03-01

Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

Liquid chromatography/tandem mass spectrometry method to determine boldenone in bovine liver tissues.

PubMed

Granja, Rodrigo H M M; Salerno, Alessandro G; de Lima, Andreia C; Montalvo, Cynthia; Reche, Karine V G; Giannotti, Fabio M; Wanschel, Amarylis C B A

2014-01-01

Boldenone, an androgenic steroid, is forbidden for use in meat production in most countries worldwide. Residues of this drug in food present a potential risk to consumers. A sensitive LC/MS/MS method for analysis of 17β-boldenone using boldenone-d3 as an internal standard was developed. An enzymatic hydrolysis and extraction using ethyl acetate, methanol, and hexane were performed in the sample preparation. Parameters such as decision limit (CCα), detection capability (CCβ), precision, recovery, and ruggedness were evaluated according to the Brazilian Regulation 24/2009 (equivalent to European Union Decision 2002/657/EC) and International Organization for Standardization/International Electrotechnical Commission 17025:2005. CCα and CCβ were determined to be 0.17 and 0.29 μg/kg, respectively. Average recoveries from bovine liver samples fortified with 1, 1.5, and 2 μg/kg were around 100%. A complete statistical analysis was performed on the results obtained, including an estimation of the method uncertainty. The method is considered robust after being subjected to day-to-day analytical variations and has been used as a standard method in Brazil to report boldenone levels in bovine liver.

Multi-classification of cell deformation based on object alignment and run length statistic.

PubMed

Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang

2014-01-01

Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

Extractive-spectrophotometric determination of disopyramide and irbesartan in their pharmaceutical formulation

NASA Astrophysics Data System (ADS)

Abdellatef, Hisham E.

2007-04-01

Picric acid, bromocresol green, bromothymol blue, cobalt thiocyanate and molybdenum(V) thiocyanate have been tested as spectrophotometric reagents for the determination of disopyramide and irbesartan. Reaction conditions have been optimized to obtain coloured comoplexes of higher sensitivity and longer stability. The absorbance of ion-pair complexes formed were found to increases linearity with increases in concentrations of disopyramide and irbesartan which were corroborated by correction coefficient values. The developed methods have been successfully applied for the determination of disopyramide and irbesartan in bulk drugs and pharmaceutical formulations. The common excipients and additives did not interfere in their determination. The results obtained by the proposed methods have been statistically compared by means of student t-test and by the variance ratio F-test. The validity was assessed by applying the standard addition technique. The results were compared statistically with the official or reference methods showing a good agreement with high precision and accuracy.

Uncertainty Analysis of Instrument Calibration and Application

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

PubMed Central

Beichel, Reinhard R.; Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian; Chang, Tangel; Plichta, Kristin A.; Smith, Brian J.; Sunderland, John J.; Graham, Michael M.; Sonka, Milan; Buatti, John M.

2016-01-01

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction. PMID:27277044

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

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

Beichel, Reinhard R., E-mail: reinhard-beichel@uiowa.edu; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242; Department of Internal Medicine, University of Iowa, Iowa City, Iowa 52242

Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behaviormore » of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.« less

An Analysis Methodology for the Gamma-ray Large Area Space Telescope

NASA Technical Reports Server (NTRS)

Morris, Robin D.; Cohen-Tanugi, Johann

2004-01-01

The Large Area Telescope (LAT) instrument on the Gamma Ray Large Area Space Telescope (GLAST) has been designed to detect high-energy gamma rays and determine their direction of incidence and energy. We propose a reconstruction algorithm based on recent advances in statistical methodology. This method, alternative to the standard event analysis inherited from high energy collider physics experiments, incorporates more accurately the physical processes occurring in the detector, and makes full use of the statistical information available. It could thus provide a better estimate of the direction and energy of the primary photon.

Tolerancing aspheres based on manufacturing statistics

NASA Astrophysics Data System (ADS)

Wickenhagen, S.; Möhl, A.; Fuchs, U.

2017-11-01

A standard way of tolerancing optical elements or systems is to perform a Monte Carlo based analysis within a common optical design software package. Although, different weightings and distributions are assumed they are all counting on statistics, which usually means several hundreds or thousands of systems for reliable results. Thus, employing these methods for small batch sizes is unreliable, especially when aspheric surfaces are involved. The huge database of asphericon was used to investigate the correlation between the given tolerance values and measured data sets. The resulting probability distributions of these measured data were analyzed aiming for a robust optical tolerancing process.

Micro-foundations for macroeconomics: New set-up based on statistical physics

NASA Astrophysics Data System (ADS)

Yoshikawa, Hiroshi

2016-12-01

Modern macroeconomics is built on "micro foundations." Namely, optimization of micro agent such as consumer and firm is explicitly analyzed in model. Toward this goal, standard model presumes "the representative" consumer/firm, and analyzes its behavior in detail. However, the macroeconomy consists of 107 consumers and 106 firms. For the purpose of analyzing such macro system, it is meaningless to pursue the micro behavior in detail. In this respect, there is no essential difference between economics and physics. The method of statistical physics can be usefully applied to the macroeconomy, and provides Keynesian economics with correct micro-foundations.

Ultra-low-dose computed tomographic angiography with model-based iterative reconstruction compared with standard-dose imaging after endovascular aneurysm repair: a prospective pilot study.

PubMed

Naidu, Sailen G; Kriegshauser, J Scott; Paden, Robert G; He, Miao; Wu, Qing; Hara, Amy K

2014-12-01

An ultra-low-dose radiation protocol reconstructed with model-based iterative reconstruction was compared with our standard-dose protocol. This prospective study evaluated 20 men undergoing surveillance-enhanced computed tomography after endovascular aneurysm repair. All patients underwent standard-dose and ultra-low-dose venous phase imaging; images were compared after reconstruction with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Objective measures of aortic contrast attenuation and image noise were averaged. Images were subjectively assessed (1 = worst, 5 = best) for diagnostic confidence, image noise, and vessel sharpness. Aneurysm sac diameter and endoleak detection were compared. Quantitative image noise was 26% less with ultra-low-dose model-based iterative reconstruction than with standard-dose adaptive statistical iterative reconstruction and 58% less than with ultra-low-dose adaptive statistical iterative reconstruction. Average subjective noise scores were not different between ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction (3.8 vs. 4.0, P = .25). Subjective scores for diagnostic confidence were better with standard-dose adaptive statistical iterative reconstruction than with ultra-low-dose model-based iterative reconstruction (4.4 vs. 4.0, P = .002). Vessel sharpness was decreased with ultra-low-dose model-based iterative reconstruction compared with standard-dose adaptive statistical iterative reconstruction (3.3 vs. 4.1, P < .0001). Ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction aneurysm sac diameters were not significantly different (4.9 vs. 4.9 cm); concordance for the presence of endoleak was 100% (P < .001). Compared with a standard-dose technique, an ultra-low-dose model-based iterative reconstruction protocol provides comparable image quality and diagnostic assessment at a 73% lower radiation dose.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

Value assignment and uncertainty evaluation for single-element reference solutions

NASA Astrophysics Data System (ADS)

Possolo, Antonio; Bodnar, Olha; Butler, Therese A.; Molloy, John L.; Winchester, Michael R.

2018-06-01

A Bayesian statistical procedure is proposed for value assignment and uncertainty evaluation for the mass fraction of the elemental analytes in single-element solutions distributed as NIST standard reference materials. The principal novelty that we describe is the use of information about relative differences observed historically between the measured values obtained via gravimetry and via high-performance inductively coupled plasma optical emission spectrometry, to quantify the uncertainty component attributable to between-method differences. This information is encapsulated in a prior probability distribution for the between-method uncertainty component, and it is then used, together with the information provided by current measurement data, to produce a probability distribution for the value of the measurand from which an estimate and evaluation of uncertainty are extracted using established statistical procedures.

Vehicle track segmentation using higher order random fields

DOE PAGES

Quach, Tu -Thach

2017-01-09

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Automatic detection of health changes using statistical process control techniques on measured transfer times of elderly.

PubMed

Baldewijns, Greet; Luca, Stijn; Nagels, William; Vanrumste, Bart; Croonenborghs, Tom

2015-01-01

It has been shown that gait speed and transfer times are good measures of functional ability in elderly. However, data currently acquired by systems that measure either gait speed or transfer times in the homes of elderly people require manual reviewing by healthcare workers. This reviewing process is time-consuming. To alleviate this burden, this paper proposes the use of statistical process control methods to automatically detect both positive and negative changes in transfer times. Three SPC techniques: tabular CUSUM, standardized CUSUM and EWMA, known for their ability to detect small shifts in the data, are evaluated on simulated transfer times. This analysis shows that EWMA is the best-suited method with a detection accuracy of 82% and an average detection time of 9.64 days.

Vehicle track segmentation using higher order random fields

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

Quach, Tu -Thach

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

A Comparison of pical Root Resorption in Incisors after Fixed Orthodontic Treatment with Standard Edgewise and Straight Wire (MBT) Method.

PubMed

Zahed Zahedani, Sm; Oshagh, M; Momeni Danaei, Sh; Roeinpeikar, Smm

2013-09-01

One of the major outcomes of orthodontic treatment is the apical root resorption of teeth moved during the treatment. Identifying the possible risk factors, are necessary for every orthodontist. The aim of this study was to compare the rate of apical root resorption after fixed orthodontic treatment with standard edgewise and straight wire (MBT) method, and also to evaluate other factors effecting the rate of root resorption in orthodontic treatments. In this study, parallel periapical radiographs of 127 patients imaging a total of 737 individual teeth, were collected. A total of 76 patients were treated by standard edgewise and 51 patients by straight wire method. The periapical radiographs were scanned and then the percentage of root resorption was calculated by Photoshop software. The data were analyzed by Paired-Samples t-test and the Generalized Linear Model adopting the SPSS 15.0. In patients treated with straight wire method (MBT), mean root resorption was 18.26% compared to 14.82% in patients treated with standard edgewise technique (p< .05). Male patients had higher rate of root resorption,statistically significant (p< .05). Age at onset of treatment, duration of treatment, type of dental occlusion, premolar extractions and the use of intermaxillary elastics had no significant effect on the root resorption in this study. Having more root resorption in the straight wire method and less in the standard edgewise technique can be attributed to more root movement in pre-adjusted MBT technique due to the brackets employed in this method.

Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results.

PubMed

Pfeifer, Mischa D; Scholkmann, Felix; Labruyère, Rob

2017-01-01

Even though research in the field of functional near-infrared spectroscopy (fNIRS) has been performed for more than 20 years, consensus on signal processing methods is still lacking. A significant knowledge gap exists between established researchers and those entering the field. One major issue regularly observed in publications from researchers new to the field is the failure to consider possible signal contamination by hemodynamic changes unrelated to neurovascular coupling (i.e., scalp blood flow and systemic blood flow). This might be due to the fact that these researchers use the signal processing methods provided by the manufacturers of their measurement device without an advanced understanding of the performed steps. The aim of the present study was to investigate how different signal processing approaches (including and excluding approaches that partially correct for the possible signal contamination) affect the results of a typical functional neuroimaging study performed with fNIRS. In particular, we evaluated one standard signal processing method provided by a commercial company and compared it to three customized approaches. We thereby investigated the influence of the chosen method on the statistical outcome of a clinical data set (task-evoked motor cortex activity). No short-channels were used in the present study and therefore two types of multi-channel corrections based on multiple long-channels were applied. The choice of the signal processing method had a considerable influence on the outcome of the study. While methods that ignored the contamination of the fNIRS signals by task-evoked physiological noise yielded several significant hemodynamic responses over the whole head, the statistical significance of these findings disappeared when accounting for part of the contamination using a multi-channel regression. We conclude that adopting signal processing methods that correct for physiological confounding effects might yield more realistic results in cases where multi-distance measurements are not possible. Furthermore, we recommend using manufacturers' standard signal processing methods only in case the user has an advanced understanding of every signal processing step performed.

Pitfalls of national routine death statistics for maternal mortality study.

PubMed

Saucedo, Monica; Bouvier-Colle, Marie-Hélène; Chantry, Anne A; Lamarche-Vadel, Agathe; Rey, Grégoire; Deneux-Tharaux, Catherine

2014-11-01

The lessons learned from the study of maternal deaths depend on the accuracy of data. Our objective was to assess time trends in the underestimation of maternal mortality (MM) in the national routine death statistics in France and to evaluate their current accuracy for the selection and causes of maternal deaths. National data obtained by enhanced methods in 1989, 1999, and 2007-09 were used as the gold standard to assess time trends in the underestimation of MM ratios (MMRs) in death statistics. Enhanced data and death statistics for 2007-09 were further compared by characterising false negatives (FNs) and false positives (FPs). The distribution of cause-specific MMRs, as assessed by each system, was described. Underestimation of MM in death statistics decreased from 55.6% in 1989 to 11.4% in 2007-09 (P < 0.001). In 2007-09, of 787 pregnancy-associated deaths, 254 were classified as maternal by the enhanced system and 211 by the death statistics; 34% of maternal deaths in the enhanced system were FNs in the death statistics, and 20% of maternal deaths in the death statistics were FPs. The hierarchy of causes of MM differed between the two systems. The discordances were mainly explained by the lack of precision in the drafting of death certificates by clinicians. Although the underestimation of MM in routine death statistics has decreased substantially over time, one third of maternal deaths remain unidentified, and the main causes of death are incorrectly identified in these data. Defining relevant priorities in maternal health requires the use of enhanced methods for MM study. © 2014 John Wiley & Sons Ltd.

Do regional methods really help reduce uncertainties in flood frequency analyses?

NASA Astrophysics Data System (ADS)

Cong Nguyen, Chi; Payrastre, Olivier; Gaume, Eric

2013-04-01

Flood frequency analyses are often based on continuous measured series at gauge sites. However, the length of the available data sets is usually too short to provide reliable estimates of extreme design floods. To reduce the estimation uncertainties, the analyzed data sets have to be extended either in time, making use of historical and paleoflood data, or in space, merging data sets considered as statistically homogeneous to build large regional data samples. Nevertheless, the advantage of the regional analyses, the important increase of the size of the studied data sets, may be counterbalanced by the possible heterogeneities of the merged sets. The application and comparison of four different flood frequency analysis methods to two regions affected by flash floods in the south of France (Ardèche and Var) illustrates how this balance between the number of records and possible heterogeneities plays in real-world applications. The four tested methods are: (1) a local statistical analysis based on the existing series of measured discharges, (2) a local analysis valuating the existing information on historical floods, (3) a standard regional flood frequency analysis based on existing measured series at gauged sites and (4) a modified regional analysis including estimated extreme peak discharges at ungauged sites. Monte Carlo simulations are conducted to simulate a large number of discharge series with characteristics similar to the observed ones (type of statistical distributions, number of sites and records) to evaluate to which extent the results obtained on these case studies can be generalized. These two case studies indicate that even small statistical heterogeneities, which are not detected by the standard homogeneity tests implemented in regional flood frequency studies, may drastically limit the usefulness of such approaches. On the other hand, these result show that the valuation of information on extreme events, either historical flood events at gauged sites or estimated extremes at ungauged sites in the considered region, is an efficient way to reduce uncertainties in flood frequency studies.

Compiling mortality statistics from civil registration systems in Viet Nam: the long road ahead.

PubMed

Rao, Chalapati; Osterberger, Brigitta; Anh, Tran Dam; MacDonald, Malcolm; Chúc, Nguyen Thi Kim; Hill, Peter S

2010-01-01

Accurate mortality statistics, needed for population health assessment, health policy and research, are best derived from data in vital registration systems. However, mortality statistics from vital registration systems are not available for several countries including Viet Nam. We used a mixed methods case study approach to assess vital registration operations in 2006 in three provinces in Viet Nam (Hòa Bình, Thùa Thiên-Hué and Bình Duong), and provide recommendations to strengthen vital registration systems in the country. For each province we developed life tables from population and mortality data compiled by sex and age group. Demographic methods were used to estimate completeness of death registration as an indicator of vital registration performance. Qualitative methods (document review, key informant interviews and focus group discussions) were used to assess administrative, technical and societal aspects of vital registration systems. Completeness of death registration was low in all three provinces. Problems were identified with the legal framework for registration of early neonatal deaths and deaths of temporary residents or migrants. The system does not conform to international standards for reporting cause of death or for recording detailed statistics by age, sex and cause of death. Capacity-building along with an intersectoral coordination committee involving the Ministries of Justice and Health and the General Statistics Office would improve the vital registration system, especially with regard to procedures for death registration. There appears to be strong political support for sentinel surveillance systems to generate reliable mortality statistics in Viet Nam.

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

PubMed Central

Jha, Abhinav K.; Mena, Esther; Caffo, Brian; Ashrafinia, Saeed; Rahmim, Arman; Frey, Eric; Subramaniam, Rathan M.

2017-01-01

Abstract. Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis. PMID:28331883

Machine Learning Methods for Production Cases Analysis

NASA Astrophysics Data System (ADS)

Mokrova, Nataliya V.; Mokrov, Alexander M.; Safonova, Alexandra V.; Vishnyakov, Igor V.

2018-03-01

Approach to analysis of events occurring during the production process were proposed. Described machine learning system is able to solve classification tasks related to production control and hazard identification at an early stage. Descriptors of the internal production network data were used for training and testing of applied models. k-Nearest Neighbors and Random forest methods were used to illustrate and analyze proposed solution. The quality of the developed classifiers was estimated using standard statistical metrics, such as precision, recall and accuracy.

Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

PubMed

Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

2010-01-01

In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

A supervised learning approach for Crohn's disease detection using higher-order image statistics and a novel shape asymmetry measure.

PubMed

Mahapatra, Dwarikanath; Schueffler, Peter; Tielbeek, Jeroen A W; Buhmann, Joachim M; Vos, Franciscus M

2013-10-01

Increasing incidence of Crohn's disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy. Current MRI approaches assess rate of contrast enhancement and bowel wall thickness, and rely on extensive manual segmentation for accurate analysis. We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD. Low-level features like intensity and texture are used with shape asymmetry information to distinguish between diseased and normal regions. Particular emphasis is laid on a novel entropy-based shape asymmetry method and higher-order statistics like skewness and kurtosis. Multi-scale feature extraction renders the method robust. Experiments on real patient data show that our features achieve a high level of accuracy and perform better than two competing methods.

Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

PubMed

Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

2015-02-10

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

78 FR 9055 - National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-07

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards Staff, Announces the..., Medical Systems Administrator, Classifications and Public Health Data Standards Staff, NCHS, 3311 Toledo...

Uncertainty visualisation in the Model Web

NASA Astrophysics Data System (ADS)

Gerharz, L. E.; Autermann, C.; Hopmann, H.; Stasch, C.; Pebesma, E.

2012-04-01

Visualisation of geospatial data as maps is a common way to communicate spatially distributed information. If temporal and furthermore uncertainty information are included in the data, efficient visualisation methods are required. For uncertain spatial and spatio-temporal data, numerous visualisation methods have been developed and proposed, but only few tools for visualisation of data in a standardised way exist. Furthermore, usually they are realised as thick clients, and lack functionality of handling data coming from web services as it is envisaged in the Model Web. We present an interactive web tool for visualisation of uncertain spatio-temporal data developed in the UncertWeb project. The client is based on the OpenLayers JavaScript library. OpenLayers provides standard map windows and navigation tools, i.e. pan, zoom in/out, to allow interactive control for the user. Further interactive methods are implemented using jStat, a JavaScript library for statistics plots developed in UncertWeb, and flot. To integrate the uncertainty information into existing standards for geospatial data, the Uncertainty Markup Language (UncertML) was applied in combination with OGC Observations&Measurements 2.0 and JavaScript Object Notation (JSON) encodings for vector and NetCDF for raster data. The client offers methods to visualise uncertain vector and raster data with temporal information. Uncertainty information considered for the tool are probabilistic and quantified attribute uncertainties which can be provided as realisations or samples, full probability distributions functions and statistics. Visualisation is supported for uncertain continuous and categorical data. In the client, the visualisation is realised using a combination of different methods. Based on previously conducted usability studies, a differentiation between expert (in statistics or mapping) and non-expert users has been indicated as useful. Therefore, two different modes are realised together in the tool: (i) adjacent maps showing data and uncertainty separately, and (ii) multidimensional mapping providing different visualisation methods in combination to explore the spatial, temporal and uncertainty distribution of the data. Adjacent maps allow a simpler visualisation by separating value and uncertainty maps for non-experts and a first overview. The multidimensional approach allows a more complex exploration of the data for experts by browsing through the different dimensions. It offers the visualisation of maps, statistic plots and time series in different windows and sliders to interactively move through time, space and uncertainty (thresholds).

Methodological choices affect cancer incidence rates: a cohort study.

PubMed

Brooke, Hannah L; Talbäck, Mats; Feychting, Maria; Ljung, Rickard

2017-01-19

Incidence rates are fundamental to epidemiology, but their magnitude and interpretation depend on methodological choices. We aimed to examine the extent to which the definition of the study population affects cancer incidence rates. All primary cancer diagnoses in Sweden between 1958 and 2010 were identified from the national Cancer Register. Age-standardized and age-specific incidence rates of 29 cancer subtypes between 2000 and 2010 were calculated using four definitions of the study population: persons resident in Sweden 1) based on general population statistics; 2) with no previous subtype-specific cancer diagnosis; 3) with no previous cancer diagnosis except non-melanoma skin cancer; and 4) with no previous cancer diagnosis of any type. We calculated absolute and relative differences between methods. Age-standardized incidence rates calculated using general population statistics ranged from 6% lower (prostate cancer, incidence rate difference: -13.5/100,000 person-years) to 8% higher (breast cancer in women, incidence rate difference: 10.5/100,000 person-years) than incidence rates based on individuals with no previous subtype-specific cancer diagnosis. Age-standardized incidence rates in persons with no previous cancer of any type were up to 10% lower (bladder cancer in women) than rates in those with no previous subtype-specific cancer diagnosis; however, absolute differences were <5/100,000 person-years for all cancer subtypes. For some cancer subtypes incidence rates vary depending on the definition of the study population. For these subtypes, standardized incidence ratios calculated using general population statistics could be misleading. Moreover, etiological arguments should be used to inform methodological choices during study design.

Simultaneous Estimation of Ofloxacin, Clotrimazole, and Lignocaine Hydrochloride in Their Combined Ear-Drop Formulation by Two Spectrophotometric Methods.

PubMed

Bodiwala, Kunjan; Shah, Shailesh; Patel, Yogini; Prajapati, Pintu; Marolia, Bhavin; Kalyankar, Gajanan

2017-01-01

Two sensitive, accurate, and precise spectrophotometric methods have been developed and validated for the simultaneous estimation of ofloxacin (OFX), clotrimazole (CLZ), and lignocaine hydrochloride (LGN) in their combined dosage form (ear drops) without prior separation. The derivative ratio spectra method (method 1) includes the measurement of OFX and CLZ at zero-crossing points (ZCPs) of each other obtained from the ratio derivative spectra using standard LGN as a divisor, whereas the measurement of LGN at the ZCP of CLZ is obtained from the ratio derivative spectra using standard OFX as a divisor. The double divisor-ratio derivative method (method 2) includes the measurement of each drug at its amplitude in the double divisor-ratio spectra obtained using a standard mixture of the other two drugs as the divisor. Both methods were found to be linear (correlation coefficients of >0.996) over the ranges of 3-15, 10-50, and 20-100 μg/mL for OFX, CLZ, and LGN, respectively; precise (RSD of <2%); and accurate (recovery of >98%) for the estimation of each drug. The developed methods were successfully applied for the estimation of these drugs in a marketed ear-drop formulation. Excipients and other ingredients did not interfere with the estimation of these drugs. Both methods were statistically compared using the t-test.

A Comparison of Student Understanding of Seasons Using Inquiry and Didactic Teaching Methods

NASA Astrophysics Data System (ADS)

Ashcraft, Paul G.

2006-02-01

Student performance on open-ended questions concerning seasons in a university physical science content course was examined to note differences between classes that experienced inquiry using a 5-E lesson planning model and those that experienced the same content with a traditional, didactic lesson. The class examined is a required content course for elementary education majors and understanding the seasons is part of the university's state's elementary science standards. The two self-selected groups of students showed no statistically significant differences in pre-test scores, while there were statistically significant differences between the groups' post-test scores with those who participated in inquiry-based activities scoring higher. There were no statistically significant differences between the pre-test and the post-test for the students who experienced didactic teaching, while there were statistically significant improvements for the students who experienced the 5-E lesson.

Stereological Analysis of Liver Biopsy Histology Sections as a Reference Standard for Validating Non-Invasive Liver Fat Fraction Measurements by MRI

PubMed Central

St. Pierre, Tim G.; House, Michael J.; Bangma, Sander J.; Pang, Wenjie; Bathgate, Andrew; Gan, Eng K.; Ayonrinde, Oyekoya T.; Bhathal, Prithi S.; Clouston, Andrew; Olynyk, John K.; Adams, Leon A.

2016-01-01

Background and Aims Validation of non-invasive methods of liver fat quantification requires a reference standard. However, using standard histopathology assessment of liver biopsies is problematical because of poor repeatability. We aimed to assess a stereological method of measuring volumetric liver fat fraction (VLFF) in liver biopsies and to use the method to validate a magnetic resonance imaging method for measurement of VLFF. Methods VLFFs were measured in 59 subjects (1) by three independent analysts using a stereological point counting technique combined with the Delesse principle on liver biopsy histological sections and (2) by three independent analysts using the HepaFat-Scan® technique on magnetic resonance images of the liver. Bland Altman statistics and intraclass correlation (IC) were used to assess the repeatability of each method and the bias between the methods of liver fat fraction measurement. Results Inter-analyst repeatability coefficients for the stereology and HepaFat-Scan® methods were 8.2 (95% CI 7.7–8.8)% and 2.4 (95% CI 2.2–2.5)% VLFF respectively. IC coefficients were 0.86 (95% CI 0.69–0.93) and 0.990 (95% CI 0.985–0.994) respectively. Small biases (≤3.4%) were observable between two pairs of analysts using stereology while no significant biases were observable between any of the three pairs of analysts using HepaFat-Scan®. A bias of 1.4±0.5% VLFF was observed between the HepaFat-Scan® method and the stereological method. Conclusions Repeatability of the stereological method is superior to the previously reported performance of assessment of hepatic steatosis by histopathologists and is a suitable reference standard for validating non-invasive methods of measurement of VLFF. PMID:27501242

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

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

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

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

PubMed

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

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

Sulfuric acid/hydrogen peroxide digestion and colorimetric a collaborative study.

PubMed

Christians, D K; Aspelund, T G; Brayton, S V; Roberts, L L

1991-01-01

Seven laboratories participated in a collaborative study of a method for determination of phosphorus in meat and meat products. Samples are digested in sulfuric acid and hydrogen peroxide; digestion is complete in approximately 10 min. Phosphorus is determined by colorimetric analysis of a dilute aliquot of the sample digest. The collaborators analyzed 3 sets of blind duplicate samples from each of 6 classes of meat (U.S. Department of Agriculture classifications): smoked ham, water-added ham, canned ham, pork sausage, cooked sausage, and hamburger. The calibration curve was linear over the range of standard solutions prepared (phosphorus levels from 0.05 to 1.00%); levels in the collaborative study samples ranged from 0.10 to 0.30%. Standard deviations for repeatability (sr) and reproducibility (SR) ranged from 0.004 to 0.012 and 0.007 to 0.014, respectively. Corresponding relative standard deviations (RSDr and RSDR, respectively) ranged from 1.70 to 7.28% and 3.50 to 9.87%. Six laboratories analyzed samples by both the proposed method and AOAC method 24.016 (14th Ed.). One laboratory reported results by the proposed method only. Statistical evaluations indicated no significant difference between the 2 methods. The method has been adopted official first action by AOAC.

On statistical inference in time series analysis of the evolution of road safety.

PubMed

Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

2013-11-01

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

Statistical reporting inconsistencies in experimental philosophy

PubMed Central

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

2018-01-01

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

75 FR 39265 - National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards Staff, Announces the... Prevention, Classifications and Public Health Data Standards, 3311 Toledo Road, Room 2337, Hyattsville, MD...

78 FR 53148 - National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-28

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards Staff, Announces the... Administrator, Classifications and Public Health Data Standards Staff, NCHS, 3311 Toledo Road, Room 2337...

75 FR 56549 - National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-16

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention National Center for Health Statistics (NCHS), Classifications and Public Health Data Standards Staff, Announces the... Public Health Data Standards Staff, NCHS, 3311 Toledo Road, Room 2337, Hyattsville, Maryland 20782, e...

Statistics as Unbiased Estimators: Exploring the Teaching of Standard Deviation

ERIC Educational Resources Information Center

Wasserman, Nicholas H.; Casey, Stephanie; Champion, Joe; Huey, Maryann

2017-01-01

This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator--not just a descriptive statistic for the variation (spread) in data--is related to teachers' instruction regarding standard deviation, particularly…

Douglas-fir survival and growth in response to spring planting date and depth

Treesearch

R. O. Strothmann

1971-01-01

Douglas-fir seedlings were planted by four methods in late February and late March on hot, south-facing slopes in northwestern California. Besides standard planting, the techniques used included deep planting at two different depths, and shading the lower stem. The differences in survival after 3 growing seasons were not statistically significant, but deep planting had...

IMPLEMENTATION AND VALIDATION OF STATISTICAL TESTS IN RESEARCH'S SOFTWARE HELPING DATA COLLECTION AND PROTOCOLS ANALYSIS IN SURGERY.

PubMed

Kuretzki, Carlos Henrique; Campos, Antônio Carlos Ligocki; Malafaia, Osvaldo; Soares, Sandramara Scandelari Kusano de Paula; Tenório, Sérgio Bernardo; Timi, Jorge Rufino Ribas

2016-03-01

The use of information technology is often applied in healthcare. With regard to scientific research, the SINPE(c) - Integrated Electronic Protocols was created as a tool to support researchers, offering clinical data standardization. By the time, SINPE(c) lacked statistical tests obtained by automatic analysis. Add to SINPE(c) features for automatic realization of the main statistical methods used in medicine . The study was divided into four topics: check the interest of users towards the implementation of the tests; search the frequency of their use in health care; carry out the implementation; and validate the results with researchers and their protocols. It was applied in a group of users of this software in their thesis in the strict sensu master and doctorate degrees in one postgraduate program in surgery. To assess the reliability of the statistics was compared the data obtained both automatically by SINPE(c) as manually held by a professional in statistics with experience with this type of study. There was concern for the use of automatic statistical tests, with good acceptance. The chi-square, Mann-Whitney, Fisher and t-Student were considered as tests frequently used by participants in medical studies. These methods have been implemented and thereafter approved as expected. The incorporation of the automatic SINPE (c) Statistical Analysis was shown to be reliable and equal to the manually done, validating its use as a research tool for medical research.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

NASA Astrophysics Data System (ADS)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

Statistical inference from multiple iTRAQ experiments without using common reference standards.

PubMed

Herbrich, Shelley M; Cole, Robert N; West, Keith P; Schulze, Kerry; Yager, James D; Groopman, John D; Christian, Parul; Wu, Lee; O'Meally, Robert N; May, Damon H; McIntosh, Martin W; Ruczinski, Ingo

2013-02-01

Isobaric tags for relative and absolute quantitation (iTRAQ) is a prominent mass spectrometry technology for protein identification and quantification that is capable of analyzing multiple samples in a single experiment. Frequently, iTRAQ experiments are carried out using an aliquot from a pool of all samples, or "masterpool", in one of the channels as a reference sample standard to estimate protein relative abundances in the biological samples and to combine abundance estimates from multiple experiments. In this manuscript, we show that using a masterpool is counterproductive. We obtain more precise estimates of protein relative abundance by using the available biological data instead of the masterpool and do not need to occupy a channel that could otherwise be used for another biological sample. In addition, we introduce a simple statistical method to associate proteomic data from multiple iTRAQ experiments with a numeric response and show that this approach is more powerful than the conventionally employed masterpool-based approach. We illustrate our methods using data from four replicate iTRAQ experiments on aliquots of the same pool of plasma samples and from a 406-sample project designed to identify plasma proteins that covary with nutrient concentrations in chronically undernourished children from South Asia.

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

PubMed

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

2014-06-28

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

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

75 FR 53925 - Sea Turtle Conservation; Shrimp and Summer Flounder Trawling Requirements

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-02

... because of the statistical probability the candidate TED may not achieve the standard (i.e., control TED... the test with 4 turtle captures because of the statistical probability the candidate TED may not... because of the statistical probability the candidate TED may not achieve the standard (i.e., [[Page 53930...

Evaluation of air quality zone classification methods based on ambient air concentration exposure.

PubMed

Freeman, Brian; McBean, Ed; Gharabaghi, Bahram; Thé, Jesse

2017-05-01

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO 2 and 8-hr O 3 within a zone that meets the compliance requirements of each method. The first method, the "3 Strike" method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method. A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

Do the methods used to analyse missing data really matter? An examination of data from an observational study of Intermediate Care patients.

PubMed

Kaambwa, Billingsley; Bryan, Stirling; Billingham, Lucinda

2012-06-27

Missing data is a common statistical problem in healthcare datasets from populations of older people. Some argue that arbitrarily assuming the mechanism responsible for the missingness and therefore the method for dealing with this missingness is not the best option-but is this always true? This paper explores what happens when extra information that suggests that a particular mechanism is responsible for missing data is disregarded and methods for dealing with the missing data are chosen arbitrarily. Regression models based on 2,533 intermediate care (IC) patients from the largest evaluation of IC done and published in the UK to date were used to explain variation in costs, EQ-5D and Barthel index. Three methods for dealing with missingness were utilised, each assuming a different mechanism as being responsible for the missing data: complete case analysis (assuming missing completely at random-MCAR), multiple imputation (assuming missing at random-MAR) and Heckman selection model (assuming missing not at random-MNAR). Differences in results were gauged by examining the signs of coefficients as well as the sizes of both coefficients and associated standard errors. Extra information strongly suggested that missing cost data were MCAR. The results show that MCAR and MAR-based methods yielded similar results with sizes of most coefficients and standard errors differing by less than 3.4% while those based on MNAR-methods were statistically different (up to 730% bigger). Significant variables in all regression models also had the same direction of influence on costs. All three mechanisms of missingness were shown to be potential causes of the missing EQ-5D and Barthel data. The method chosen to deal with missing data did not seem to have any significant effect on the results for these data as they led to broadly similar conclusions with sizes of coefficients and standard errors differing by less than 54% and 322%, respectively. Arbitrary selection of methods to deal with missing data should be avoided. Using extra information gathered during the data collection exercise about the cause of missingness to guide this selection would be more appropriate.

Evaluation of the effectiveness of thoracic sympathectomy in the treatment of primary hyperhidrosis of hands and armpits using the measurement of skin resistance

PubMed Central

Jabłoński, Sławomir; Rzepkowska-Misiak, Beata; Piskorz, Łukasz; Brocki, Marian; Wcisło, Szymon; Smigielski, Jacek; Kordiak, Jacek

2012-01-01

Introduction Hyperhidrosis is excessive sweating beyond the needs of thermoregulation. It is disease which mostly affects young people, often carrying a considerable amount of socio-economic implications. Thoracic sympathectomy is now considered to be the "gold standard" in the treatment of idiopathic hyperhidrosis of hands and armpits. Aim Assessment of early effectiveness of thoracic sympathectomy using skin resistance measurements performed before surgery and in the postoperative period. Material and methods A group of 20 patients with idiopathic excessive sweating of hands and the armpit was enrolled in the study. Patients underwent two-stage thoracic sympathectomy with resection of Th2-Th4 ganglions. The skin resistance measurements were made at six previously designated points on the day of surgery and the first day after the operation. Results In all operated patients we obtained complete remission of symptoms on the first day after the surgery. Inhibition of sweating was confirmed using the standard starch iodine (Minor) test. At all measurement points we obtained a statistically significant increase of skin resistance, assuming p < 0.05. To check whether there is a statistically significant difference in the results before and after surgery we used sequence pairs Wilcoxon test. Conclusions Thoracic sympathectomy is an effective curative treatment for primary hyperhidrosis of hands and armpits. Statistically significant increase of skin resistance in all cases is a good method of assessing the effectiveness of the above surgery in the early postoperative period. PMID:23256019

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

PubMed Central

Valkenborg, Dirk; Baggerman, Geert; Vanaerschot, Manu; Witters, Erwin; Dujardin, Jean-Claude; Burzykowski, Tomasz; Berg, Maya

2013-01-01

Abstract Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approaches on LC-MS metabolomics experiments, which do not require the use of internal standards. According to variability measures, each normalization method performs relatively well, showing that the use of any normalization method will greatly improve data-analysis originating from multiple experimental runs. In the second part, we apply cyclic-Loess normalization to a Leishmania sample. This normalization method allows the removal of systematic variability between two measurement blocks over time and maintains the differential metabolites. In conclusion, normalization allows for pooling datasets from different measurement blocks over time and increases the statistical power of the analysis, hence paving the way to increase the scale of LC-MS metabolomics experiments. From our investigation, we recommend data-driven normalization methods over model-driven normalization methods, if only a few internal standards were used. Moreover, data-driven normalization methods are the best option to normalize datasets from untargeted LC-MS experiments. PMID:23808607

Development and evaluation of thin-layer chromatography-digital image-based analysis for the quantitation of the botanical pesticide azadirachtin in agricultural matrixes and commercial formulations: comparison with ELISA.

PubMed

Tanuja, Penmatsa; Venugopal, Namburi; Sashidhar, Rao Beedu

2007-01-01

A simple thin-layer chromatography-digital image-based analytical method has been developed for the quantitation of the botanical pesticide, azadirachtin. The method was validated by analyzing azadirachtin in the spiked food matrixes and processed commercial pesticide formulations, using acidified vanillin reagent as a postchromatographic derivatizing agent. The separated azadirachtin was clearly identified as a green spot. The Rf value was found to be 0.55, which was similar to that of a reference standard. A standard calibration plot was established using a reference standard, based on the linear regression analysis [r2 = 0.996; y = 371.43 + (634.82)x]. The sensitivity of the method was found to be 0.875 microg azadirachtin. Spiking studies conducted at the 1 ppm (microg/g) level in various agricultural matrixes, such as brinjal, tomato, coffee, and cotton seeds, revealed the recoveries of azadirachtin in the range of 67-92%. Azadirachtin content of commercial neem formulations analyzed by the method was in the range of 190-1825 ppm (microg/mL). Further, the present method was compared with an immunoanalytical method enzyme-linked immonosorbent assay developed earlier in our laboratory. Statistical comparison of the 2 methods, using Fischer's F-test, indicated no significant difference in variance, suggesting that both methods are comparable.

An empirical analysis of the distribution of the duration of overshoots in a stationary gaussian stochastic process

NASA Technical Reports Server (NTRS)

Parrish, R. S.; Carter, M. C.

1974-01-01

This analysis utilizes computer simulation and statistical estimation. Realizations of stationary gaussian stochastic processes with selected autocorrelation functions are computer simulated. Analysis of the simulated data revealed that the mean and the variance of a process were functionally dependent upon the autocorrelation parameter and crossing level. Using predicted values for the mean and standard deviation, by the method of moments, the distribution parameters was estimated. Thus, given the autocorrelation parameter, crossing level, mean, and standard deviation of a process, the probability of exceeding the crossing level for a particular length of time was calculated.

A new mathematical approach for the estimation of the AUC and its variability under different experimental designs in preclinical studies.

PubMed

Navarro-Fontestad, Carmen; González-Álvarez, Isabel; Fernández-Teruel, Carlos; Bermejo, Marival; Casabó, Vicente Germán

2012-01-01

The aim of the present work was to develop a new mathematical method for estimating the area under the curve (AUC) and its variability that could be applied in different preclinical experimental designs and amenable to be implemented in standard calculation worksheets. In order to assess the usefulness of the new approach, different experimental scenarios were studied and the results were compared with those obtained with commonly used software: WinNonlin® and Phoenix WinNonlin®. The results do not show statistical differences among the AUC values obtained by both procedures, but the new method appears to be a better estimator of the AUC standard error, measured as the coverage of 95% confidence interval. In this way, the new proposed method demonstrates to be as useful as WinNonlin® software when it was applicable. Copyright © 2011 John Wiley & Sons, Ltd.

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

PubMed

Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

2016-12-01

: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.