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

PubMed

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

2014-03-01

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

Experimental toxicology: Issues of statistics, experimental design, and replication.

PubMed

Briner, Wayne; Kirwan, Jeral

2017-01-01

The difficulty of replicating experiments has drawn considerable attention. Issues with replication occur for a variety of reasons ranging from experimental design to laboratory errors to inappropriate statistical analysis. Here we review a variety of guidelines for statistical analysis, design, and execution of experiments in toxicology. In general, replication can be improved by using hypothesis driven experiments with adequate sample sizes, randomization, and blind data collection techniques. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean

Study/experimental/research design: much more than statistics.

PubMed

Knight, Kenneth L

2010-01-01

The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes "Methods" sections hard to read and understand. To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results.

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.

Atmospheric statistics for aerospace vehicle operations

NASA Technical Reports Server (NTRS)

Smith, O. E.; Batts, G. W.

1993-01-01

Statistical analysis of atmospheric variables was performed for the Shuttle Transportation System (STS) design trade studies and the establishment of launch commit criteria. Atmospheric constraint statistics have been developed for the NASP test flight, the Advanced Launch System, and the National Launch System. The concepts and analysis techniques discussed in the paper are applicable to the design and operations of any future aerospace vehicle.

A Data Warehouse Architecture for DoD Healthcare Performance Measurements.

DTIC Science & Technology

1999-09-01

design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse of healthcare metrics. With the DoD healthcare...framework, this thesis defines a methodology to design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse...21 F. INABILITY TO CONDUCT HELATHCARE ANALYSIS

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

PubMed

Kratochwill, Thomas R; Levin, Joel R

2014-04-01

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

[Again review of research design and statistical methods of Chinese Journal of Cardiology].

PubMed

Kong, Qun-yu; Yu, Jin-ming; Jia, Gong-xian; Lin, Fan-li

2012-11-01

To re-evaluate and compare the research design and the use of statistical methods in Chinese Journal of Cardiology. Summary the research design and statistical methods in all of the original papers in Chinese Journal of Cardiology all over the year of 2011, and compared the result with the evaluation of 2008. (1) There is no difference in the distribution of the design of researches of between the two volumes. Compared with the early volume, the use of survival regression and non-parameter test are increased, while decreased in the proportion of articles with no statistical analysis. (2) The proportions of articles in the later volume are significant lower than the former, such as 6(4%) with flaws in designs, 5(3%) with flaws in the expressions, 9(5%) with the incomplete of analysis. (3) The rate of correction of variance analysis has been increased, so as the multi-group comparisons and the test of normality. The error rate of usage has been decreased form 17% to 25% without significance in statistics due to the ignorance of the test of homogeneity of variance. Many improvements showed in Chinese Journal of Cardiology such as the regulation of the design and statistics. The homogeneity of variance should be paid more attention in the further application.

Study/Experimental/Research Design: Much More Than Statistics

PubMed Central

Knight, Kenneth L.

2010-01-01

Abstract Context: The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes “Methods” sections hard to read and understand. Objective: To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. Description: The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Advantages: Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results. PMID:20064054

Statistical Analysis of Research Data | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

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

PubMed

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

2014-10-01

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

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

PubMed

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

2014-04-01

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

Teaching Principles of Linkage and Gene Mapping with the Tomato.

ERIC Educational Resources Information Center

Hawk, James A.; And Others

1980-01-01

A three-point linkage system in tomatoes is used to explain concepts of gene mapping, linking and statistical analysis. The system is designed for teaching the effective use of statistics, and the power of genetic analysis from statistical analysis of phenotypic ratios. (Author/SA)

Quantitative Methods for Analysing Joint Questionnaire Data: Exploring the Role of Joint in Force Design

DTIC Science & Technology

2015-08-01

the nine questions. The Statistical Package for the Social Sciences ( SPSS ) [11] was used to conduct statistical analysis on the sample. Two types...constructs. SPSS was again used to conduct statistical analysis on the sample. This time factor analysis was conducted. Factor analysis attempts to...Business Research Methods and Statistics using SPSS . P432. 11 IBM SPSS Statistics . (2012) 12 Burns, R.B., Burns, R.A. (2008) ‘Business Research

Multi-reader ROC studies with split-plot designs: a comparison of statistical methods.

PubMed

Obuchowski, Nancy A; Gallas, Brandon D; Hillis, Stephen L

2012-12-01

Multireader imaging trials often use a factorial design, in which study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of this design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper, the authors compare three methods of analysis for the split-plot design. Three statistical methods are presented: the Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean analysis-of-variance approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power, and confidence interval coverage of the three test statistics. The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% confidence intervals falls close to the nominal coverage for small and large sample sizes. The split-plot multireader, multicase study design can be statistically efficient compared to the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rates, similar power, and nominal confidence interval coverage, are available for this study design. Copyright © 2012 AUR. All rights reserved.

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean differences, simple and multiple linear regression, ANOVA tests, and Chi-Squared distribution.

Statistical Reform in School Psychology Research: A Synthesis

ERIC Educational Resources Information Center

Swaminathan, Hariharan; Rogers, H. Jane

2007-01-01

Statistical reform in school psychology research is discussed in terms of research designs, measurement issues, statistical modeling and analysis procedures, interpretation and reporting of statistical results, and finally statistics education.

Investigation of Weibull statistics in fracture analysis of cast aluminum

NASA Technical Reports Server (NTRS)

Holland, Frederic A., Jr.; Zaretsky, Erwin V.

1989-01-01

The fracture strengths of two large batches of A357-T6 cast aluminum coupon specimens were compared by using two-parameter Weibull analysis. The minimum number of these specimens necessary to find the fracture strength of the material was determined. The applicability of three-parameter Weibull analysis was also investigated. A design methodology based on the combination of elementary stress analysis and Weibull statistical analysis is advanced and applied to the design of a spherical pressure vessel shell. The results from this design methodology are compared with results from the applicable ASME pressure vessel code.

Targeting Change: Assessing a Faculty Learning Community Focused on Increasing Statistics Content in Life Science Curricula

ERIC Educational Resources Information Center

Parker, Loran Carleton; Gleichsner, Alyssa M.; Adedokun, Omolola A.; Forney, James

2016-01-01

Transformation of research in all biological fields necessitates the design, analysis and, interpretation of large data sets. Preparing students with the requisite skills in experimental design, statistical analysis, and interpretation, and mathematical reasoning will require both curricular reform and faculty who are willing and able to integrate…

Design and analysis of multiple diseases genome-wide association studies without controls.

PubMed

Chen, Zhongxue; Huang, Hanwen; Ng, Hon Keung Tony

2012-11-15

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls. Copyright © 2012 Elsevier B.V. All rights reserved.

Research Design and Statistics for Applied Linguistics.

ERIC Educational Resources Information Center

Hatch, Evelyn; Farhady, Hossein

An introduction to the conventions of research design and statistical analysis is presented for graduate students of applied linguistics. The chapters cover such concepts as the definition of research, variables, research designs, research report formats, sorting and displaying data, probability and hypothesis testing, comparing means,…

Statistical models for the analysis and design of digital polymerase chain (dPCR) experiments

USGS Publications Warehouse

Dorazio, Robert; Hunter, Margaret

2015-01-01

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log–log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model’s parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Statistical Models for the Analysis and Design of Digital Polymerase Chain Reaction (dPCR) Experiments.

PubMed

Dorazio, Robert M; Hunter, Margaret E

2015-11-03

Statistical methods for the analysis and design of experiments using digital PCR (dPCR) have received only limited attention and have been misused in many instances. To address this issue and to provide a more general approach to the analysis of dPCR data, we describe a class of statistical models for the analysis and design of experiments that require quantification of nucleic acids. These models are mathematically equivalent to generalized linear models of binomial responses that include a complementary, log-log link function and an offset that is dependent on the dPCR partition volume. These models are both versatile and easy to fit using conventional statistical software. Covariates can be used to specify different sources of variation in nucleic acid concentration, and a model's parameters can be used to quantify the effects of these covariates. For purposes of illustration, we analyzed dPCR data from different types of experiments, including serial dilution, evaluation of copy number variation, and quantification of gene expression. We also showed how these models can be used to help design dPCR experiments, as in selection of sample sizes needed to achieve desired levels of precision in estimates of nucleic acid concentration or to detect differences in concentration among treatments with prescribed levels of statistical power.

Study Designs and Statistical Analyses for Biomarker Research

PubMed Central

Gosho, Masahiko; Nagashima, Kengo; Sato, Yasunori

2012-01-01

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

Experimental Quiet Sprocket Design and Noise Reduction in Tracked Vehicles

DTIC Science & Technology

1981-04-01

Track and Suspension Noise Reduction Statistical Energy Analysis Mechanical Impedance Measurement Finite Element Modal Analysis\\Noise Sources 2...shape and idler attachment are different. These differen- ces were investigated using the concepts of statistical energy analysis for hull generated noise...element r,’calculated from Statistical Energy Analysis . Such an approach will be valid within reasonable limits for frequencies of about 200 Hz and

[Prosthodontic research design from the standpoint of statistical analysis: learning and knowing the research design].

PubMed

Tanoue, Naomi

2007-10-01

For any kind of research, "Research Design" is the most important. The design is used to structure the research, to show how all of the major parts of the research project. It is necessary for all the researchers to begin the research after planning research design for what is the main theme, what is the background and reference, what kind of data is needed, and what kind of analysis is needed. It seems to be a roundabout route, but, in fact, it will be a shortcut. The research methods must be appropriate to the objectives of the study. Regarding the hypothesis-testing research that is the traditional style of the research, the research design based on statistics is undoubtedly necessary considering that the research basically proves "a hypothesis" with data and statistics theory. On the subject of the clinical trial, which is the clinical version of the hypothesis-testing research, the statistical method must be mentioned in a clinical trial planning. This report describes the basis of the research design for a prosthodontics study.

A statistical package for computing time and frequency domain analysis

NASA Technical Reports Server (NTRS)

Brownlow, J.

1978-01-01

The spectrum analysis (SPA) program is a general purpose digital computer program designed to aid in data analysis. The program does time and frequency domain statistical analyses as well as some preanalysis data preparation. The capabilities of the SPA program include linear trend removal and/or digital filtering of data, plotting and/or listing of both filtered and unfiltered data, time domain statistical characterization of data, and frequency domain statistical characterization of data.

Analysis of half diallel mating designs I: a practical analysis procedure for ANOVA approximation.

Treesearch

G.R. Johnson; J.N. King

1998-01-01

Procedures to analyze half-diallel mating designs using the SAS statistical package are presented. The procedure requires two runs of PROC and VARCOMP and results in estimates of additive and non-additive genetic variation. The procedures described can be modified to work on most statistical software packages which can compute variance component estimates. The...

Statistical Considerations of Food Allergy Prevention Studies.

PubMed

Bahnson, Henry T; du Toit, George; Lack, Gideon

Clinical studies to prevent the development of food allergy have recently helped reshape public policy recommendations on the early introduction of allergenic foods. These trials are also prompting new research, and it is therefore important to address the unique design and analysis challenges of prevention trials. We highlight statistical concepts and give recommendations that clinical researchers may wish to adopt when designing future study protocols and analysis plans for prevention studies. Topics include selecting a study sample, addressing internal and external validity, improving statistical power, choosing alpha and beta, analysis innovations to address dilution effects, and analysis methods to deal with poor compliance, dropout, and missing data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Rare-Variant Association Analysis: Study Designs and Statistical Tests

PubMed Central

Lee, Seunggeung; Abecasis, Gonçalo R.; Boehnke, Michael; Lin, Xihong

2014-01-01

Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions. PMID:24995866

[Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

PubMed

Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

2018-01-01

To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

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

PubMed

Shadish, William R

2014-04-01

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

STATISTICAL SAMPLING AND DATA ANALYSIS

EPA Science Inventory

Research is being conducted to develop approaches to improve soil and sediment sampling techniques, measurement design and geostatistics, and data analysis via chemometric, environmetric, and robust statistical methods. Improvements in sampling contaminated soil and other hetero...

Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers

ERIC Educational Resources Information Center

Keiffer, Greggory L.; Lane, Forrest C.

2016-01-01

Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…

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

PubMed

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

2016-01-01

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

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

PubMed

Becker, Betsy Jane; Aloe, Ariel M; Duvendack, Maren; Stanley, T D; Valentine, Jeffrey C; Fretheim, Atle; Tugwell, Peter

2017-09-01

To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences. Copyright © 2017 Elsevier Inc. All rights reserved.

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 Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

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

AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments

ERIC Educational Resources Information Center

Osler, James Edward, II

2015-01-01

This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…

Analysis of Sensitivity Experiments - An Expanded Primer

DTIC Science & Technology

2017-03-08

diehard practitioners. The difficulty associated with mastering statistical inference presents a true dilemma. Statistics is an extremely applied...lost, perhaps forever. In other words, when on this safari, you need a guide. This report is designed to be a guide, of sorts. It focuses on analytical...estimated accurately if our analysis is to have real meaning. For this reason, the sensitivity test procedure is designed to concentrate measurements

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

A new statistic for the analysis of circular data in gamma-ray astronomy

NASA Technical Reports Server (NTRS)

Protheroe, R. J.

1985-01-01

A new statistic is proposed for the analysis of circular data. The statistic is designed specifically for situations where a test of uniformity is required which is powerful against alternatives in which a small fraction of the observations is grouped in a small range of directions, or phases.

Statistical Analysis of Research Data | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general

A comparison of InVivoStat with other statistical software packages for analysis of data generated from animal experiments.

PubMed

Clark, Robin A; Shoaib, Mohammed; Hewitt, Katherine N; Stanford, S Clare; Bate, Simon T

2012-08-01

InVivoStat is a free-to-use statistical software package for analysis of data generated from animal experiments. The package is designed specifically for researchers in the behavioural sciences, where exploiting the experimental design is crucial for reliable statistical analyses. This paper compares the analysis of three experiments conducted using InVivoStat with other widely used statistical packages: SPSS (V19), PRISM (V5), UniStat (V5.6) and Statistica (V9). We show that InVivoStat provides results that are similar to those from the other packages and, in some cases, are more advanced. This investigation provides evidence of further validation of InVivoStat and should strengthen users' confidence in this new software package.

Multi-Reader ROC studies with Split-Plot Designs: A Comparison of Statistical Methods

PubMed Central

Obuchowski, Nancy A.; Gallas, Brandon D.; Hillis, Stephen L.

2012-01-01

Rationale and Objectives Multi-reader imaging trials often use a factorial design, where study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of the design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper we compare three methods of analysis for the split-plot design. Materials and Methods Three statistical methods are presented: Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean ANOVA approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power and confidence interval coverage of the three test statistics. Results The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% CIs fall close to the nominal coverage for small and large sample sizes. Conclusions The split-plot MRMC study design can be statistically efficient compared with the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rate, similar power, and nominal CI coverage, are available for this study design. PMID:23122570

Uncertainty Analysis for DAM Projects.

DTIC Science & Technology

1987-09-01

overwhelming majority of articles published on the use of statistical methodology for geotechnical engineering focus on performance predictions and design ...Results of the present study do not support the adoption of more esoteric statistical procedures except on a special case basis or in research ...influence that recommended statistical procedures might have had on the Carters Project, had they been applied during planning and design phases

The Design and Analysis of Transposon-Insertion Sequencing Experiments

PubMed Central

Chao, Michael C.; Abel, Sören; Davis, Brigid M.; Waldor, Matthew K.

2016-01-01

Preface Transposon-insertion sequencing (TIS) is a powerful approach that can be widely applied to genome-wide definition of loci that are required for growth in diverse conditions. However, experimental design choices and stochastic biological processes can heavily influence the results of TIS experiments and affect downstream statistical analysis. Here, we discuss TIS experimental parameters and how these factors relate to the benefits and limitations of the various statistical frameworks that can be applied to computational analysis of TIS data. PMID:26775926

More on Time Series Designs: A Reanalysis of Mayer and Kozlow's Data.

ERIC Educational Resources Information Center

Willson, Victor L.

1982-01-01

Differentiating between time-series design and time-series analysis, examines design considerations and reanalyzes data previously reported by Mayer and Kozlow in this journal. The current analysis supports the analysis performed by Mayer and Kozlow but puts the results on a somewhat firmer statistical footing. (Author/JN)

Web 2.0 Articles: Content Analysis and a Statistical Model to Predict Recognition of the Need for New Instructional Design Strategies

ERIC Educational Resources Information Center

Liu, Leping; Maddux, Cleborne D.

2008-01-01

This article presents a study of Web 2.0 articles intended to (a) analyze the content of what is written and (b) develop a statistical model to predict whether authors' write about the need for new instructional design strategies and models. Eighty-eight technology articles were subjected to lexical analysis and a logistic regression model was…

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

Labby, Z.

Physicists are often expected to have a solid grounding in experimental design and statistical analysis, sometimes filling in when biostatisticians or other experts are not available for consultation. Unfortunately, graduate education on these topics is seldom emphasized and few opportunities for continuing education exist. Clinical physicists incorporate new technology and methods into their practice based on published literature. A poor understanding of experimental design and analysis could Result in inappropriate use of new techniques. Clinical physicists also improve current practice through quality initiatives that require sound experimental design and analysis. Academic physicists with a poor understanding of design and analysismore » may produce ambiguous (or misleading) results. This can Result in unnecessary rewrites, publication rejection, and experimental redesign (wasting time, money, and effort). This symposium will provide a practical review of error and uncertainty, common study designs, and statistical tests. Instruction will primarily focus on practical implementation through examples and answer questions such as: where would you typically apply the test/design and where is the test/design typically misapplied (i.e., common pitfalls)? An analysis of error and uncertainty will also be explored using biological studies and associated modeling as a specific use case. Learning Objectives: Understand common experimental testing and clinical trial designs, what questions they can answer, and how to interpret the results Determine where specific statistical tests are appropriate and identify common pitfalls Understand the how uncertainty and error are addressed in biological testing and associated biological modeling.« less

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.

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

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

PubMed

Festing, M F

2001-01-01

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

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.

Biotrichotomy: The Neuroscientific and Neurobiological Systemology, Epistemology, and Methodology of the Tri-Squared Test and Tri-Center Analysis in Biostatistics

ERIC Educational Resources Information Center

Osler, James Edward

2015-01-01

This monograph provides a neuroscience-based systemological, epistemological, and methodological rational for the design of an advanced and novel parametric statistical analytics designed for the biological sciences referred to as "Biotrichotomy". The aim of this new arena of statistics is to provide dual metrics designed to analyze the…

Research Education in Undergraduate Occupational Therapy Programs.

ERIC Educational Resources Information Center

Petersen, Paul; And Others

1992-01-01

Of 63 undergraduate occupational therapy programs surveyed, the 38 responses revealed some common areas covered: elementary descriptive statistics, validity, reliability, and measurement. Areas underrepresented include statistical analysis with or without computers, research design, and advanced statistics. (SK)

For the Love of Statistics: Appreciating and Learning to Apply Experimental Analysis and Statistics through Computer Programming Activities

ERIC Educational Resources Information Center

Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.

2016-01-01

For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…

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.

Considerations for the design, analysis and presentation of in vivo studies.

PubMed

Ranstam, J; Cook, J A

2017-03-01

To describe, explain and give practical suggestions regarding important principles and key methodological challenges in the study design, statistical analysis, and reporting of results from in vivo studies. Pre-specifying endpoints and analysis, recognizing the common underlying assumption of statistically independent observations, performing sample size calculations, and addressing multiplicity issues are important parts of an in vivo study. A clear reporting of results and informative graphical presentations of data are other important parts. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

PubMed

Harshbarger, Jayson; Kratz, Anton; Carninci, Piero

2017-01-07

Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.

Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets

PubMed Central

Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

2013-01-01

Purpose: With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. Methods: A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. Results: The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. Conclusions: The work demonstrates the viability of the design approach and the software tool for analysis of large data sets. PMID:24320426

Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets.

PubMed

Mayo, Charles; Conners, Steve; Warren, Christopher; Miller, Robert; Court, Laurence; Popple, Richard

2013-11-01

With emergence of clinical outcomes databases as tools utilized routinely within institutions, comes need for software tools to support automated statistical analysis of these large data sets and intrainstitutional exchange from independent federated databases to support data pooling. In this paper, the authors present a design approach and analysis methodology that addresses both issues. A software application was constructed to automate analysis of patient outcomes data using a wide range of statistical metrics, by combining use of C#.Net and R code. The accuracy and speed of the code was evaluated using benchmark data sets. The approach provides data needed to evaluate combinations of statistical measurements for ability to identify patterns of interest in the data. Through application of the tools to a benchmark data set for dose-response threshold and to SBRT lung data sets, an algorithm was developed that uses receiver operator characteristic curves to identify a threshold value and combines use of contingency tables, Fisher exact tests, Welch t-tests, and Kolmogorov-Smirnov tests to filter the large data set to identify values demonstrating dose-response. Kullback-Leibler divergences were used to provide additional confirmation. The work demonstrates the viability of the design approach and the software tool for analysis of large data sets.

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

PubMed

Cairns, David A

2011-03-01

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

Power Analysis in Two-Level Unbalanced Designs

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2010-01-01

Previous work on statistical power has discussed mainly single-level designs or 2-level balanced designs with random effects. Although balanced experiments are common, in practice balance cannot always be achieved. Work on class size is one example of unbalanced designs. This study provides methods for power analysis in 2-level unbalanced designs…

Introductory Statistics Students' Conceptual Understanding of Study Design and Conclusions

NASA Astrophysics Data System (ADS)

Fry, Elizabeth Brondos

Recommended learning goals for students in introductory statistics courses include the ability to recognize and explain the key role of randomness in designing studies and in drawing conclusions from those studies involving generalizations to a population or causal claims (GAISE College Report ASA Revision Committee, 2016). The purpose of this study was to explore introductory statistics students' understanding of the distinct roles that random sampling and random assignment play in study design and the conclusions that can be made from each. A study design unit lasting two and a half weeks was designed and implemented in four sections of an undergraduate introductory statistics course based on modeling and simulation. The research question that this study attempted to answer is: How does introductory statistics students' conceptual understanding of study design and conclusions (in particular, unbiased estimation and establishing causation) change after participating in a learning intervention designed to promote conceptual change in these areas? In order to answer this research question, a forced-choice assessment called the Inferences from Design Assessment (IDEA) was developed as a pretest and posttest, along with two open-ended assignments, a group quiz and a lab assignment. Quantitative analysis of IDEA results and qualitative analysis of the group quiz and lab assignment revealed that overall, students' mastery of study design concepts significantly increased after the unit, and the great majority of students successfully made the appropriate connections between random sampling and generalization, and between random assignment and causal claims. However, a small, but noticeable portion of students continued to demonstrate misunderstandings, such as confusion between random sampling and random assignment.

The use of analysis of variance procedures in biological studies

USGS Publications Warehouse

Williams, B.K.

1987-01-01

The analysis of variance (ANOVA) is widely used in biological studies, yet there remains considerable confusion among researchers about the interpretation of hypotheses being tested. Ambiguities arise when statistical designs are unbalanced, and in particular when not all combinations of design factors are represented in the data. This paper clarifies the relationship among hypothesis testing, statistical modelling and computing procedures in ANOVA for unbalanced data. A simple two-factor fixed effects design is used to illustrate three common parametrizations for ANOVA models, and some associations among these parametrizations are developed. Biologically meaningful hypotheses for main effects and interactions are given in terms of each parametrization, and procedures for testing the hypotheses are described. The standard statistical computing procedures in ANOVA are given along with their corresponding hypotheses. Throughout the development unbalanced designs are assumed and attention is given to problems that arise with missing cells.

Assessment of Reliable Change Using 95% Credible Intervals for the Differences in Proportions: A Statistical Analysis for Case-Study Methodology.

PubMed

Unicomb, Rachael; Colyvas, Kim; Harrison, Elisabeth; Hewat, Sally

2015-06-01

Case-study methodology studying change is often used in the field of speech-language pathology, but it can be criticized for not being statistically robust. Yet with the heterogeneous nature of many communication disorders, case studies allow clinicians and researchers to closely observe and report on change. Such information is valuable and can further inform large-scale experimental designs. In this research note, a statistical analysis for case-study data is outlined that employs a modification to the Reliable Change Index (Jacobson & Truax, 1991). The relationship between reliable change and clinical significance is discussed. Example data are used to guide the reader through the use and application of this analysis. A method of analysis is detailed that is suitable for assessing change in measures with binary categorical outcomes. The analysis is illustrated using data from one individual, measured before and after treatment for stuttering. The application of this approach to assess change in categorical, binary data has potential application in speech-language pathology. It enables clinicians and researchers to analyze results from case studies for their statistical and clinical significance. This new method addresses a gap in the research design literature, that is, the lack of analysis methods for noncontinuous data (such as counts, rates, proportions of events) that may be used in case-study designs.

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

PubMed

Campbell, Gregory; Yue, Lilly Q

2016-01-01

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

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.

A new statistical methodology predicting chip failure probability considering electromigration

NASA Astrophysics Data System (ADS)

Sun, Ted

In this research thesis, we present a new approach to analyze chip reliability subject to electromigration (EM) whose fundamental causes and EM phenomenon happened in different materials are presented in this thesis. This new approach utilizes the statistical nature of EM failure in order to assess overall EM risk. It includes within-die temperature variations from the chip's temperature map extracted by an Electronic Design Automation (EDA) tool to estimate the failure probability of a design. Both the power estimation and thermal analysis are performed in the EDA flow. We first used the traditional EM approach to analyze the design with a single temperature across the entire chip that involves 6 metal and 5 via layers. Next, we used the same traditional approach but with a realistic temperature map. The traditional EM analysis approach and that coupled with a temperature map and the comparison between the results of considering and not considering temperature map are presented in in this research. A comparison between these two results confirms that using a temperature map yields a less pessimistic estimation of the chip's EM risk. Finally, we employed the statistical methodology we developed considering a temperature map and different use-condition voltages and frequencies to estimate the overall failure probability of the chip. The statistical model established considers the scaling work with the usage of traditional Black equation and four major conditions. The statistical result comparisons are within our expectations. The results of this statistical analysis confirm that the chip level failure probability is higher i) at higher use-condition frequencies for all use-condition voltages, and ii) when a single temperature instead of a temperature map across the chip is considered. In this thesis, I start with an overall review on current design types, common flows, and necessary verifications and reliability checking steps used in this IC design industry. Furthermore, the important concepts about "Scripting Automation" which is used in all the integration of using diversified EDA tools in this research work are also described in detail with several examples and my completed coding works are also put in the appendix for your reference. Hopefully, this construction of my thesis will give readers a thorough understanding about my research work from the automation of EDA tools to the statistical data generation, from the nature of EM to the statistical model construction, and the comparisons among the traditional EM analysis and the statistical EM analysis approaches.

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

PubMed

Rosenbaum, Paul R

2011-09-01

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

Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

PubMed

Schlenker, Evelyn

2016-01-01

This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.

The emergence of modern statistics in agricultural science: analysis of variance, experimental design and the reshaping of research at Rothamsted Experimental Station, 1919-1933.

PubMed

Parolini, Giuditta

2015-01-01

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the mathematician and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher's methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians' tools and expertise into the station research programme. Fisher's statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them.

Complexities and potential pitfalls of clinical study design and data analysis in assisted reproduction.

PubMed

Patounakis, George; Hill, Micah J

2018-06-01

The purpose of the current review is to describe the common pitfalls in design and statistical analysis of reproductive medicine studies. It serves to guide both authors and reviewers toward reducing the incidence of spurious statistical results and erroneous conclusions. The large amount of data gathered in IVF cycles leads to problems with multiplicity, multicollinearity, and over fitting of regression models. Furthermore, the use of the word 'trend' to describe nonsignificant results has increased in recent years. Finally, methods to accurately account for female age in infertility research models are becoming more common and necessary. The pitfalls of study design and analysis reviewed provide a framework for authors and reviewers to approach clinical research in the field of reproductive medicine. By providing a more rigorous approach to study design and analysis, the literature in reproductive medicine will have more reliable conclusions that can stand the test of time.

Parallel auto-correlative statistics with VTK.

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

Pebay, Philippe Pierre; Bennett, Janine Camille

2013-08-01

This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

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

PubMed

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

2014-01-01

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

Technological Tools in the Introductory Statistics Classroom: Effects on Student Understanding of Inferential Statistics

ERIC Educational Resources Information Center

Meletiou-Mavrotheris, Maria

2004-01-01

While technology has become an integral part of introductory statistics courses, the programs typically employed are professional packages designed primarily for data analysis rather than for learning. Findings from several studies suggest that use of such software in the introductory statistics classroom may not be very effective in helping…

Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.

PubMed

Hilgers, Ralf-Dieter; Bogdan, Malgorzata; Burman, Carl-Fredrik; Dette, Holger; Karlsson, Mats; König, Franz; Male, Christoph; Mentré, France; Molenberghs, Geert; Senn, Stephen

2018-05-11

IDeAl (Integrated designs and analysis of small population clinical trials) is an EU funded project developing new statistical design and analysis methodologies for clinical trials in small population groups. Here we provide an overview of IDeAl findings and give recommendations to applied researchers. The description of the findings is broken down by the nine scientific IDeAl work packages and summarizes results from the project's more than 60 publications to date in peer reviewed journals. In addition, we applied text mining to evaluate the publications and the IDeAl work packages' output in relation to the design and analysis terms derived from in the IRDiRC task force report on small population clinical trials. The results are summarized, describing the developments from an applied viewpoint. The main result presented here are 33 practical recommendations drawn from the work, giving researchers a comprehensive guidance to the improved methodology. In particular, the findings will help design and analyse efficient clinical trials in rare diseases with limited number of patients available. We developed a network representation relating the hot topics developed by the IRDiRC task force on small population clinical trials to IDeAl's work as well as relating important methodologies by IDeAl's definition necessary to consider in design and analysis of small-population clinical trials. These network representation establish a new perspective on design and analysis of small-population clinical trials. IDeAl has provided a huge number of options to refine the statistical methodology for small-population clinical trials from various perspectives. A total of 33 recommendations developed and related to the work packages help the researcher to design small population clinical trial. The route to improvements is displayed in IDeAl-network representing important statistical methodological skills necessary to design and analysis of small-population clinical trials. The methods are ready for use.

Shock and Vibration Symposium (59th) Held in Albuquerque, New Mexico on 18-20 October 1988. Volume 4

DTIC Science & Technology

1988-12-01

program to support TOPEX spacecraft design, Statistical energy analysis modeling of nonstructural mass on lightweight equipment panels using VAPEPS...and Stress estimation and statistical energy analysis of the Magellan spacecraft solar array using VAPEPS; Dynamic measurement -- An automated

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.

PubMed

Shardell, Michelle; Harris, Anthony D; El-Kamary, Samer S; Furuno, Jon P; Miller, Ram R; Perencevich, Eli N

2007-10-01

Quasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.

Statistical Tolerance and Clearance Analysis for Assembly

NASA Technical Reports Server (NTRS)

Lee, S.; Yi, C.

1996-01-01

Tolerance is inevitable because manufacturing exactly equal parts is known to be impossible. Furthermore, the specification of tolerances is an integral part of product design since tolerances directly affect the assemblability, functionality, manufacturability, and cost effectiveness of a product. In this paper, we present statistical tolerance and clearance analysis for the assembly. Our proposed work is expected to make the following contributions: (i) to help the designers to evaluate products for assemblability, (ii) to provide a new perspective to tolerance problems, and (iii) to provide a tolerance analysis tool which can be incorporated into a CAD or solid modeling system.

Which statistics should tropical biologists learn?

PubMed

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

2011-09-01

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

The Relationship between Visual Analysis and Five Statistical Analyses in a Simple AB Single-Case Research Design

ERIC Educational Resources Information Center

Brossart, Daniel F.; Parker, Richard I.; Olson, Elizabeth A.; Mahadevan, Lakshmi

2006-01-01

This study explored some practical issues for single-case researchers who rely on visual analysis of graphed data, but who also may consider supplemental use of promising statistical analysis techniques. The study sought to answer three major questions: (a) What is a typical range of effect sizes from these analytic techniques for data from…

Effects of Instructional Design with Mental Model Analysis on Learning.

ERIC Educational Resources Information Center

Hong, Eunsook

This paper presents a model for systematic instructional design that includes mental model analysis together with the procedures used in developing computer-based instructional materials in the area of statistical hypothesis testing. The instructional design model is based on the premise that the objective for learning is to achieve expert-like…

Statistical Analysis for the Solomon Four-Group Design. Research Report 99-06.

ERIC Educational Resources Information Center

van Engelenburg, Gijsbert

The Solomon four-group design (R. Solomon, 1949) is a very useful experimental design to investigate the main effect of a pretest and the interaction of pretest and treatment. Although the design was proposed half a century ago, no proper data analysis techniques have been available. This paper describes how data from the Solomon four-group design…

Design of radar receivers

NASA Astrophysics Data System (ADS)

Sokolov, M. A.

This handbook treats the design and analysis of of pulsed radar receivers, with emphasis on elements (especially IC elements) that implement optimal and suboptimal algorithms. The design methodology is developed from the viewpoint of statistical communications theory. Particular consideration is given to the synthesis of single-channel and multichannel detectors, the design of analog and digital signal-processing devices, and the analysis of IF amplifiers.

The Design and Analysis of Salmonid Tagging Studies in the Columbia Basin : Volume II: Experiment Salmonid Survival with Combined PIT-CWT Tagging.

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

Newman, Ken

1997-06-01

Experiment designs to estimate the effect of transportation on survival and return rates of Columbia River system salmonids are discussed along with statistical modeling techniques. Besides transportation, river flow and dam spill are necessary components in the design and analysis otherwise questions as to the effects of reservoir drawdowns and increased dam spill may never be satisfactorily answered. Four criteria for comparing different experiment designs are: (1) feasibility, (2) clarity of results, (3) scope of inference, and (4) time to learn. In this report, alternative designs for conducting experimental manipulations of smolt tagging studies to study effects of river operationsmore » such as flow levels, spill fractions, and transporting outmigrating salmonids around dams in the Columbia River system are presented. The principles of study design discussed in this report have broad implications for the many studies proposed to investigate both smolt and adult survival relationships. The concepts are illustrated for the case of the design and analysis of smolt transportation experiments. The merits of proposed transportation studies should be measured relative to these principles of proper statistical design and analysis.« less

[Evaluative designs in public health: methodological considerations].

PubMed

López, Ma José; Marí-Dell'Olmo, Marc; Pérez-Giménez, Anna; Nebot, Manel

2011-06-01

Evaluation of public health interventions poses numerous methodological challenges. Randomization of individuals is not always feasible and interventions are usually composed of multiple factors. To face these challenges, certain elements, such as the selection of the most appropriate design and the use of a statistical analysis that includes potential confounders, are essential. The objective of this article was to describe the most frequently used designs in the evaluation of public health interventions (policies, programs or campaigns). The characteristics, strengths and weaknesses of each of these evaluative designs are described. Additionally, a brief explanation of the most commonly used statistical analysis in each of these designs is provided. Copyright © 2011 Sociedad Española de Salud Pública y Administración Sanitaria. Published by Elsevier Espana. All rights reserved.

RooStatsCms: A tool for analysis modelling, combination and statistical studies

NASA Astrophysics Data System (ADS)

Piparo, D.; Schott, G.; Quast, G.

2010-04-01

RooStatsCms is an object oriented statistical framework based on the RooFit technology. Its scope is to allow the modelling, statistical analysis and combination of multiple search channels for new phenomena in High Energy Physics. It provides a variety of methods described in literature implemented as classes, whose design is oriented to the execution of multiple CPU intensive jobs on batch systems or on the Grid.

[The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

PubMed

Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

2017-01-01

The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

Software for the Integration of Multiomics Experiments in Bioconductor.

PubMed

Ramos, Marcel; Schiffer, Lucas; Re, Angela; Azhar, Rimsha; Basunia, Azfar; Rodriguez, Carmen; Chan, Tiffany; Chapman, Phil; Davis, Sean R; Gomez-Cabrero, David; Culhane, Aedin C; Haibe-Kains, Benjamin; Hansen, Kasper D; Kodali, Hanish; Louis, Marie S; Mer, Arvind S; Riester, Markus; Morgan, Martin; Carey, Vince; Waldron, Levi

2017-11-01

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR . ©2017 American Association for Cancer Research.

Improving Student Understanding of Spatial Ecology Statistics

ERIC Educational Resources Information Center

Hopkins, Robert, II; Alberts, Halley

2015-01-01

This activity is designed as a primer to teaching population dispersion analysis. The aim is to help improve students' spatial thinking and their understanding of how spatial statistic equations work. Students use simulated data to develop their own statistic and apply that equation to experimental behavioral data for Gambusia affinis (western…

A comparison of two experimental design approaches in applying conjoint analysis in patient-centered outcomes research: a randomized trial.

PubMed

Kinter, Elizabeth T; Prior, Thomas J; Carswell, Christopher I; Bridges, John F P

2012-01-01

While the application of conjoint analysis and discrete-choice experiments in health are now widely accepted, a healthy debate exists around competing approaches to experimental design. There remains, however, a paucity of experimental evidence comparing competing design approaches and their impact on the application of these methods in patient-centered outcomes research. Our objectives were to directly compare the choice-model parameters and predictions of an orthogonal and a D-efficient experimental design using a randomized trial (i.e., an experiment on experiments) within an application of conjoint analysis studying patient-centered outcomes among outpatients diagnosed with schizophrenia in Germany. Outpatients diagnosed with schizophrenia were surveyed and randomized to receive choice tasks developed using either an orthogonal or a D-efficient experimental design. The choice tasks elicited judgments from the respondents as to which of two patient profiles (varying across seven outcomes and process attributes) was preferable from their own perspective. The results from the two survey designs were analyzed using the multinomial logit model, and the resulting parameter estimates and their robust standard errors were compared across the two arms of the study (i.e., the orthogonal and D-efficient designs). The predictive performances of the two resulting models were also compared by computing their percentage of survey responses classified correctly, and the potential for variation in scale between the two designs of the experiments was tested statistically and explored graphically. The results of the two models were statistically identical. No difference was found using an overall chi-squared test of equality for the seven parameters (p = 0.69) or via uncorrected pairwise comparisons of the parameter estimates (p-values ranged from 0.30 to 0.98). The D-efficient design resulted in directionally smaller standard errors for six of the seven parameters, of which only two were statistically significant, and no differences were found in the observed D-efficiencies of their standard errors (p = 0.62). The D-efficient design resulted in poorer predictive performance, but this was not significant (p = 0.73); there was some evidence that the parameters of the D-efficient design were biased marginally towards the null. While no statistical difference in scale was detected between the two designs (p = 0.74), the D-efficient design had a higher relative scale (1.06). This could be observed when the parameters were explored graphically, as the D-efficient parameters were lower. Our results indicate that orthogonal and D-efficient experimental designs have produced results that are statistically equivalent. This said, we have identified several qualitative findings that speak to the potential differences in these results that may have been statistically identified in a larger sample. While more comparative studies focused on the statistical efficiency of competing design strategies are needed, a more pressing research problem is to document the impact the experimental design has on respondent efficiency.

Experimental design in chemistry: A tutorial.

PubMed

Leardi, Riccardo

2009-10-12

In this tutorial the main concepts and applications of experimental design in chemistry will be explained. Unfortunately, nowadays experimental design is not as known and applied as it should be, and many papers can be found in which the "optimization" of a procedure is performed one variable at a time. Goal of this paper is to show the real advantages in terms of reduced experimental effort and of increased quality of information that can be obtained if this approach is followed. To do that, three real examples will be shown. Rather than on the mathematical aspects, this paper will focus on the mental attitude required by experimental design. The readers being interested to deepen their knowledge of the mathematical and algorithmical part can find very good books and tutorials in the references [G.E.P. Box, W.G. Hunter, J.S. Hunter, Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, John Wiley & Sons, New York, 1978; R. Brereton, Chemometrics: Data Analysis for the Laboratory and Chemical Plant, John Wiley & Sons, New York, 1978; R. Carlson, J.E. Carlson, Design and Optimization in Organic Synthesis: Second Revised and Enlarged Edition, in: Data Handling in Science and Technology, vol. 24, Elsevier, Amsterdam, 2005; J.A. Cornell, Experiments with Mixtures: Designs, Models and the Analysis of Mixture Data, in: Series in Probability and Statistics, John Wiley & Sons, New York, 1991; R.E. Bruns, I.S. Scarminio, B. de Barros Neto, Statistical Design-Chemometrics, in: Data Handling in Science and Technology, vol. 25, Elsevier, Amsterdam, 2006; D.C. Montgomery, Design and Analysis of Experiments, 7th edition, John Wiley & Sons, Inc., 2009; T. Lundstedt, E. Seifert, L. Abramo, B. Thelin, A. Nyström, J. Pettersen, R. Bergman, Chemolab 42 (1998) 3; Y. Vander Heyden, LC-GC Europe 19 (9) (2006) 469].

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

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

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

2008-05-03

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

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

Modeling Longitudinal Data with Generalized Additive Models: Applications to Single-Case Designs

ERIC Educational Resources Information Center

Sullivan, Kristynn J.; Shadish, William R.

2013-01-01

Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…

The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods.

PubMed

Görgen, Kai; Hebart, Martin N; Allefeld, Carsten; Haynes, John-Dylan

2017-12-27

Standard neuroimaging data analysis based on traditional principles of experimental design, modelling, and statistical inference is increasingly complemented by novel analysis methods, driven e.g. by machine learning methods. While these novel approaches provide new insights into neuroimaging data, they often have unexpected properties, generating a growing literature on possible pitfalls. We propose to meet this challenge by adopting a habit of systematic testing of experimental design, analysis procedures, and statistical inference. Specifically, we suggest to apply the analysis method used for experimental data also to aspects of the experimental design, simulated confounds, simulated null data, and control data. We stress the importance of keeping the analysis method the same in main and test analyses, because only this way possible confounds and unexpected properties can be reliably detected and avoided. We describe and discuss this Same Analysis Approach in detail, and demonstrate it in two worked examples using multivariate decoding. With these examples, we reveal two sources of error: A mismatch between counterbalancing (crossover designs) and cross-validation which leads to systematic below-chance accuracies, and linear decoding of a nonlinear effect, a difference in variance. Copyright © 2017 Elsevier Inc. All rights reserved.

Accounting for variation in designing greenhouse experiments with special reference to greenhouses containing plants on conveyor systems

PubMed Central

2013-01-01

Background There are a number of unresolved issues in the design of experiments in greenhouses. They include whether statistical designs should be used and, if so, which designs should be used. Also, are there thigmomorphogenic or other effects arising from the movement of plants on conveyor belts within a greenhouse? A two-phase, single-line wheat experiment involving four tactics was conducted in a conventional greenhouse and a fully-automated phenotyping greenhouse (Smarthouse) to investigate these issues. Results and discussion Analyses of our experiment show that there was a small east–west trend in total area of the plants in the Smarthouse. Analyses of the data from three multiline experiments reveal a large north–south trend. In the single-line experiment, there was no evidence of differences between trios of lanes, nor of movement effects. Swapping plant positions during the trial was found to decrease the east–west trend, but at the cost of increased error variance. The movement of plants in a north–south direction, through a shaded area for an equal amount of time, nullified the north–south trend. An investigation of alternative experimental designs for equally-replicated experiments revealed that generally designs with smaller blocks performed best, but that (nearly) trend-free designs can be effective when blocks are larger. Conclusions To account for variation in microclimate in a greenhouse, using statistical design and analysis is better than rearranging the position of plants during the experiment. For the relocation of plants to be successful requires that plants spend an equal amount of time in each microclimate, preferably during comparable growth stages. Even then, there is no evidence that this will be any more precise than statistical design and analysis of the experiment, and the risk is that it will not be successful at all. As for statistical design and analysis, it is best to use either (i) smaller blocks, (ii) (nearly) trend-free arrangement of treatments with a linear trend term included in the analysis, or, as a last resort, (iii) blocks of several complete rows with trend terms in the analysis. Also, we recommend that the greenhouse arrangement parallel that in the Smarthouse, but with randomization where appropriate. PMID:23391282

WEC Design Response Toolbox v. 1.0

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

Coe, Ryan; Michelen, Carlos; Eckert-Gallup, Aubrey

2016-03-30

The WEC Design Response Toolbox (WDRT) is a numerical toolbox for design-response analysis of wave energy converters (WECs). The WDRT was developed during a series of efforts to better understand WEC survival design. The WDRT has been designed as a tool for researchers and developers, enabling the straightforward application of statistical and engineering methods. The toolbox includes methods for short-term extreme response, environmental characterization, long-term extreme response and risk analysis, fatigue, and design wave composition.

Implementation of quality by design principles in the development of microsponges as drug delivery carriers: Identification and optimization of critical factors using multivariate statistical analyses and design of experiments studies.

PubMed

Simonoska Crcarevska, Maja; Dimitrovska, Aneta; Sibinovska, Nadica; Mladenovska, Kristina; Slavevska Raicki, Renata; Glavas Dodov, Marija

2015-07-15

Microsponges drug delivery system (MDDC) was prepared by double emulsion-solvent-diffusion technique using rotor-stator homogenization. Quality by design (QbD) concept was implemented for the development of MDDC with potential to be incorporated into semisolid dosage form (gel). Quality target product profile (QTPP) and critical quality attributes (CQA) were defined and identified, accordingly. Critical material attributes (CMA) and Critical process parameters (CPP) were identified using quality risk management (QRM) tool, failure mode, effects and criticality analysis (FMECA). CMA and CPP were identified based on results obtained from principal component analysis (PCA-X&Y) and partial least squares (PLS) statistical analysis along with literature data, product and process knowledge and understanding. FMECA identified amount of ethylcellulose, chitosan, acetone, dichloromethane, span 80, tween 80 and water ratio in primary/multiple emulsions as CMA and rotation speed and stirrer type used for organic solvent removal as CPP. The relationship between identified CPP and particle size as CQA was described in the design space using design of experiments - one-factor response surface method. Obtained results from statistically designed experiments enabled establishment of mathematical models and equations that were used for detailed characterization of influence of identified CPP upon MDDC particle size and particle size distribution and their subsequent optimization. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2002-06-01

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

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

PubMed

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

2018-03-01

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

The Australasian Resuscitation in Sepsis Evaluation (ARISE) trial statistical analysis plan.

PubMed

Delaney, Anthony P; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

2013-09-01

The Australasian Resuscitation in Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the emergency department with severe sepsis. In keeping with current practice, and considering aspects of trial design and reporting specific to non-pharmacological interventions, our plan outlines the principles and methods for analysing and reporting the trial results. The document is prepared before completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and before completion of the two related international studies. Our statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. We reviewed the data collected by the research team as specified in the study protocol and detailed in the study case report form. We describe information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation, other related therapies and other relevant data with appropriate comparisons between groups. We define the primary, secondary and tertiary outcomes for the study, with description of the planned statistical analyses. We have developed a statistical analysis plan with a trial profile, mock-up tables and figures. We describe a plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies and adverse events. We describe the primary, secondary and tertiary outcomes with identification of subgroups to be analysed. We have developed a statistical analysis plan for the ARISE study, available in the public domain, before the completion of recruitment into the study. This will minimise analytical bias and conforms to current best practice in conducting clinical trials.

Sb2Te3 and Its Superlattices: Optimization by Statistical Design.

PubMed

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

2018-05-02

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

Interpolative modeling of GaAs FET S-parameter data bases for use in Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Campbell, L.; Purviance, J.

1992-01-01

A statistical interpolation technique is presented for modeling GaAs FET S-parameter measurements for use in the statistical analysis and design of circuits. This is accomplished by interpolating among the measurements in a GaAs FET S-parameter data base in a statistically valid manner.

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

PubMed

Su, Yu-Xuan; Tu, Yu-Kang

2018-05-22

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

MAGMA: analysis of two-channel microarrays made easy.

PubMed

Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

2007-07-01

The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Clinical Trials.

PubMed

Zink, Richard C; Marchenko, Olga; Sanchez-Kam, Matilde; Ma, Haijun; Jiang, Qi

2018-03-01

There has been an increased emphasis on the proactive and comprehensive evaluation of safety endpoints to ensure patient well-being throughout the medical product life cycle. In fact, depending on the severity of the underlying disease, it is important to plan for a comprehensive safety evaluation at the start of any development program. Statisticians should be intimately involved in this process and contribute their expertise to study design, safety data collection, analysis, reporting (including data visualization), and interpretation. In this manuscript, we review the challenges associated with the analysis of safety endpoints and describe the safety data that are available to influence the design and analysis of premarket clinical trials. We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from clinical trials compared to other sources. Clinical trials are an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. This work is a result of the efforts of the American Statistical Association Biopharmaceutical Section Safety Working Group.

A bibliometric analysis of statistical terms used in American Physical Therapy Association journals (2011-2012): evidence for educating physical therapists.

PubMed

Tilson, Julie K; Marshall, Katie; Tam, Jodi J; Fetters, Linda

2016-04-22

A primary barrier to the implementation of evidence based practice (EBP) in physical therapy is therapists' limited ability to understand and interpret statistics. Physical therapists demonstrate limited skills and report low self-efficacy for interpreting results of statistical procedures. While standards for physical therapist education include statistics, little empirical evidence is available to inform what should constitute such curricula. The purpose of this study was to conduct a census of the statistical terms and study designs used in physical therapy literature and to use the results to make recommendations for curricular development in physical therapist education. We conducted a bibliometric analysis of 14 peer-reviewed journals associated with the American Physical Therapy Association over 12 months (Oct 2011-Sept 2012). Trained raters recorded every statistical term appearing in identified systematic reviews, primary research reports, and case series and case reports. Investigator-reported study design was also recorded. Terms representing the same statistical test or concept were combined into a single, representative term. Cumulative percentage was used to identify the most common representative statistical terms. Common representative terms were organized into eight categories to inform curricular design. Of 485 articles reviewed, 391 met the inclusion criteria. These 391 articles used 532 different terms which were combined into 321 representative terms; 13.1 (sd = 8.0) terms per article. Eighty-one representative terms constituted 90% of all representative term occurrences. Of the remaining 240 representative terms, 105 (44%) were used in only one article. The most common study design was prospective cohort (32.5%). Physical therapy literature contains a large number of statistical terms and concepts for readers to navigate. However, in the year sampled, 81 representative terms accounted for 90% of all occurrences. These "common representative terms" can be used to inform curricula to promote physical therapists' skills, competency, and confidence in interpreting statistics in their professional literature. We make specific recommendations for curriculum development informed by our findings.

16 CFR 1000.26 - Directorate for Epidemiology.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... In addition, staff in the Hazard Analysis Division design special studies, design and analyze data from experiments for testing of consumer products, and provide statistical expertise and advice to...

16 CFR 1000.26 - Directorate for Epidemiology.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... In addition, staff in the Hazard Analysis Division design special studies, design and analyze data from experiments for testing of consumer products, and provide statistical expertise and advice to...

16 CFR 1000.26 - Directorate for Epidemiology.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... In addition, staff in the Hazard Analysis Division design special studies, design and analyze data from experiments for testing of consumer products, and provide statistical expertise and advice to...

The High Cost of Complexity in Experimental Design and Data Analysis: Type I and Type II Error Rates in Multiway ANOVA.

ERIC Educational Resources Information Center

Smith, Rachel A.; Levine, Timothy R.; Lachlan, Kenneth A.; Fediuk, Thomas A.

2002-01-01

Notes that the availability of statistical software packages has led to a sharp increase in use of complex research designs and complex statistical analyses in communication research. Reports a series of Monte Carlo simulations which demonstrate that this complexity may come at a heavier cost than many communication researchers realize. Warns…

GLIMMPSE Lite: Calculating Power and Sample Size on Smartphone Devices

PubMed Central

Munjal, Aarti; Sakhadeo, Uttara R.; Muller, Keith E.; Glueck, Deborah H.; Kreidler, Sarah M.

2014-01-01

Researchers seeking to develop complex statistical applications for mobile devices face a common set of difficult implementation issues. In this work, we discuss general solutions to the design challenges. We demonstrate the utility of the solutions for a free mobile application designed to provide power and sample size calculations for univariate, one-way analysis of variance (ANOVA), GLIMMPSE Lite. Our design decisions provide a guide for other scientists seeking to produce statistical software for mobile platforms. PMID:25541688

Statistical issues in the design, conduct and analysis of two large safety studies.

PubMed

Gaffney, Michael

2016-10-01

The emergence, post approval, of serious medical events, which may be associated with the use of a particular drug or class of drugs, is an important public health and regulatory issue. The best method to address this issue is through a large, rigorously designed safety study. Therefore, it is important to elucidate the statistical issues involved in these large safety studies. Two such studies are PRECISION and EAGLES. PRECISION is the primary focus of this article. PRECISION is a non-inferiority design with a clinically relevant non-inferiority margin. Statistical issues in the design, conduct and analysis of PRECISION are discussed. Quantitative and clinical aspects of the selection of the composite primary endpoint, the determination and role of the non-inferiority margin in a large safety study and the intent-to-treat and modified intent-to-treat analyses in a non-inferiority safety study are shown. Protocol changes that were necessary during the conduct of PRECISION are discussed from a statistical perspective. Issues regarding the complex analysis and interpretation of the results of PRECISION are outlined. EAGLES is presented as a large, rigorously designed safety study when a non-inferiority margin was not able to be determined by a strong clinical/scientific method. In general, when a non-inferiority margin is not able to be determined, the width of the 95% confidence interval is a way to size the study and to assess the cost-benefit of relative trial size. A non-inferiority margin, when able to be determined by a strong scientific method, should be included in a large safety study. Although these studies could not be called "pragmatic," they are examples of best real-world designs to address safety and regulatory concerns. © The Author(s) 2016.

Use of check lists in assessing the statistical content of medical studies.

PubMed Central

Gardner, M J; Machin, D; Campbell, M J

1986-01-01

Two check lists are used routinely in the statistical assessment of manuscripts submitted to the "BMJ." One is for papers of a general nature and the other specifically for reports on clinical trials. Each check list includes questions on the design, conduct, analysis, and presentation of studies, and answers to these contribute to the overall statistical evaluation. Only a small proportion of submitted papers are assessed statistically, and these are selected at the refereeing or editorial stage. Examination of the use of the check lists showed that most papers contained statistical failings, many of which could easily be remedied. It is recommended that the check lists should be used by statistical referees, editorial staff, and authors and also during the design stage of studies. PMID:3082452

16 CFR § 1000.26 - Directorate for Epidemiology.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... In addition, staff in the Hazard Analysis Division design special studies, design and analyze data from experiments for testing of consumer products, and provide statistical expertise and advice to...

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Exploration of the Maximum Entropy/Optimal Projection Approach to Control Design Synthesis for Large Space Structures.

DTIC Science & Technology

1985-02-01

Energy Analysis , a branch of dynamic modal analysis developed for analyzing acoustic vibration problems, its present stage of development embodies a...Maximum Entropy Stochastic Modelling and Reduced-Order Design Synthesis is a rigorous new approach to this class of problems. Inspired by Statistical

Monitoring and Evaluation: Statistical Support for Life-cycle Studies, Annual Report 2003.

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

Skalski, John

2003-11-01

The ongoing mission of this project is the development of statistical tools for analyzing fisheries tagging data in the most precise and appropriate manner possible. This mission also includes providing statistical guidance on the best ways to design large-scale tagging studies. This mission continues because the technologies for conducting fish tagging studies continuously evolve. In just the last decade, fisheries biologists have seen the evolution from freeze-brands and coded wire tags (CWT) to passive integrated transponder (PIT) tags, balloon-tags, radiotelemetry, and now, acoustic-tags. With each advance, the technology holds the promise of more detailed and precise information. However, the technologymore » for analyzing and interpreting the data also becomes more complex as the tagging techniques become more sophisticated. The goal of the project is to develop the analytical tools in parallel with the technical advances in tagging studies, so that maximum information can be extracted on a timely basis. Associated with this mission is the transfer of these analytical capabilities to the field investigators to assure consistency and the highest levels of design and analysis throughout the fisheries community. Consequently, this project provides detailed technical assistance on the design and analysis of tagging studies to groups requesting assistance throughout the fisheries community. Ideally, each project and each investigator would invest in the statistical support needed for the successful completion of their study. However, this is an ideal that is rarely if every attained. Furthermore, there is only a small pool of highly trained scientists in this specialized area of tag analysis here in the Northwest. Project 198910700 provides the financial support to sustain this local expertise on the statistical theory of tag analysis at the University of Washington and make it available to the fisheries community. Piecemeal and fragmented support from various agencies and organizations would be incapable of maintaining a center of expertise. The mission of the project is to help assure tagging studies are designed and analyzed from the onset to extract the best available information using state-of-the-art statistical methods. The overarching goals of the project is to assure statistically sound survival studies so that fish managers can focus on the management implications of their findings and not be distracted by concerns whether the studies are statistically reliable or not. Specific goals and objectives of the study include the following: (1) Provide consistent application of statistical methodologies for survival estimation across all salmon life cycle stages to assure comparable performance measures and assessment of results through time, to maximize learning and adaptive management opportunities, and to improve and maintain the ability to responsibly evaluate the success of implemented Columbia River FWP salmonid mitigation programs and identify future mitigation options. (2) Improve analytical capabilities to conduct research on survival processes of wild and hatchery chinook and steelhead during smolt outmigration, to improve monitoring and evaluation capabilities and assist in-season river management to optimize operational and fish passage strategies to maximize survival. (3) Extend statistical support to estimate ocean survival and in-river survival of returning adults. Provide statistical guidance in implementing a river-wide adult PIT-tag detection capability. (4) Develop statistical methods for survival estimation for all potential users and make this information available through peer-reviewed publications, statistical software, and technology transfers to organizations such as NOAA Fisheries, the Fish Passage Center, US Fish and Wildlife Service, US Geological Survey (USGS), US Army Corps of Engineers (USACE), Public Utility Districts (PUDs), the Independent Scientific Advisory Board (ISAB), and other members of the Northwest fisheries community. (5) Provide and maintain statistical software for tag analysis and user support. (6) Provide improvements in statistical theory and software as requested by user groups. These improvements include extending software capabilities to address new research issues, adapting tagging techniques to new study designs, and extending the analysis capabilities to new technologies such as radio-tags and acoustic-tags.« less

Statistical Analyses of Femur Parameters for Designing Anatomical Plates.

PubMed

Wang, Lin; He, Kunjin; Chen, Zhengming

2016-01-01

Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study. The specific steps were as follows. First, taking eight anatomical femur parameters as variables, 100 femur samples were classified into three classes with factor analysis and Q-type cluster analysis. Second, based on the mean parameter values of the three classes of femurs, three sizes of average anatomical plates corresponding to the three classes of femurs were designed. Finally, based on Bayes discriminant analysis, a new femur could be assigned to the proper class. Thereafter, the average anatomical plate suitable for that new femur was selected from the three available sizes of plates. Experimental results showed that the classification of femurs was quite reasonable based on the anatomical aspects of the femurs. For instance, three sizes of condylar buttress plates were designed. Meanwhile, 20 new femurs are judged to which classes the femurs belong. Thereafter, suitable condylar buttress plates were determined and selected.

Math Academy: Play Ball! Explorations in Data Analysis & Statistics. Book 3: Supplemental Math Materials for Grades 3-8

ERIC Educational Resources Information Center

Rimbey, Kimberly

2008-01-01

Created by teachers for teachers, the Math Academy tools and activities included in this booklet were designed to create hands-on activities and a fun learning environment for the teaching of mathematics to the students. This booklet contains the "Math Academy--Play Ball! Explorations in Data Analysis & Statistics," which teachers can use to…

Statistical flaws in design and analysis of fertility treatment studies on cryopreservation raise doubts on the conclusions

PubMed Central

van Gelder, P.H.A.J.M.; Nijs, M.

2011-01-01

Decisions about pharmacotherapy are being taken by medical doctors and authorities based on comparative studies on the use of medications. In studies on fertility treatments in particular, the methodological quality is of utmost importance in the application of evidence-based medicine and systematic reviews. Nevertheless, flaws and omissions appear quite regularly in these types of studies. Current study aims to present an overview of some of the typical statistical flaws, illustrated by a number of example studies which have been published in peer reviewed journals. Based on an investigation of eleven studies at random selected on fertility treatments with cryopreservation, it appeared that the methodological quality of these studies often did not fulfil the required statistical criteria. The following statistical flaws were identified: flaws in study design, patient selection, and units of analysis or in the definition of the primary endpoints. Other errors could be found in p-value and power calculations or in critical p-value definitions. Proper interpretation of the results and/or use of these study results in a meta analysis should therefore be conducted with care. PMID:24753877

Statistical flaws in design and analysis of fertility treatment -studies on cryopreservation raise doubts on the conclusions.

PubMed

van Gelder, P H A J M; Nijs, M

2011-01-01

Decisions about pharmacotherapy are being taken by medical doctors and authorities based on comparative studies on the use of medications. In studies on fertility treatments in particular, the methodological quality is of utmost -importance in the application of evidence-based medicine and systematic reviews. Nevertheless, flaws and omissions appear quite regularly in these types of studies. Current study aims to present an overview of some of the typical statistical flaws, illustrated by a number of example studies which have been published in peer reviewed journals. Based on an investigation of eleven studies at random selected on fertility treatments with cryopreservation, it appeared that the methodological quality of these studies often did not fulfil the -required statistical criteria. The following statistical flaws were identified: flaws in study design, patient selection, and units of analysis or in the definition of the primary endpoints. Other errors could be found in p-value and power calculations or in critical p-value definitions. Proper -interpretation of the results and/or use of these study results in a meta analysis should therefore be conducted with care.

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

PubMed

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

2015-03-01

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

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

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

PubMed

Kanda, Yoshinobu

2015-10-01

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

SOCR: Statistics Online Computational Resource

PubMed Central

Dinov, Ivo D.

2011-01-01

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

SSD for R: A Comprehensive Statistical Package to Analyze Single-System Data

ERIC Educational Resources Information Center

Auerbach, Charles; Schudrich, Wendy Zeitlin

2013-01-01

The need for statistical analysis in single-subject designs presents a challenge, as analytical methods that are applied to group comparison studies are often not appropriate in single-subject research. "SSD for R" is a robust set of statistical functions with wide applicability to single-subject research. It is a comprehensive package…

A Systems Analysis of the Library and Information Science Statistical Data System: The Preliminary Study. Interim Report.

ERIC Educational Resources Information Center

Hamburg, Morris; And Others

The long-term goal of this investigation is to design and establish a national model for a system of library statistical data. This is a report on The Preliminary Study which was carried out over an 11-month period ending May, 1969. The objective of The Preliminary Study was to design and delimit The Research Investigation in the most efficient…

Spatial Statistical Models and Optimal Survey Design for Rapid Geophysical characterization of UXO Sites

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

G. Ostrouchov; W.E.Doll; D.A.Wolf

2003-07-01

Unexploded ordnance(UXO)surveys encompass large areas, and the cost of surveying these areas can be high. Enactment of earlier protocols for sampling UXO sites have shown the shortcomings of these procedures and led to a call for development of scientifically defensible statistical procedures for survey design and analysis. This project is one of three funded by SERDP to address this need.

Public and patient involvement in quantitative health research: A statistical perspective.

PubMed

Hannigan, Ailish

2018-06-19

The majority of studies included in recent reviews of impact for public and patient involvement (PPI) in health research had a qualitative design. PPI in solely quantitative designs is underexplored, particularly its impact on statistical analysis. Statisticians in practice have a long history of working in both consultative (indirect) and collaborative (direct) roles in health research, yet their perspective on PPI in quantitative health research has never been explicitly examined. To explore the potential and challenges of PPI from a statistical perspective at distinct stages of quantitative research, that is sampling, measurement and statistical analysis, distinguishing between indirect and direct PPI. Statistical analysis is underpinned by having a representative sample, and a collaborative or direct approach to PPI may help achieve that by supporting access to and increasing participation of under-represented groups in the population. Acknowledging and valuing the role of lay knowledge of the context in statistical analysis and in deciding what variables to measure may support collective learning and advance scientific understanding, as evidenced by the use of participatory modelling in other disciplines. A recurring issue for quantitative researchers, which reflects quantitative sampling methods, is the selection and required number of PPI contributors, and this requires further methodological development. Direct approaches to PPI in quantitative health research may potentially increase its impact, but the facilitation and partnership skills required may require further training for all stakeholders, including statisticians. © 2018 The Authors Health Expectations published by John Wiley & Sons Ltd.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Statistical design of quantitative mass spectrometry-based proteomic experiments.

PubMed

Oberg, Ann L; Vitek, Olga

2009-05-01

We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

Common statistical and research design problems in manuscripts submitted to high-impact psychiatry journals: what editors and reviewers want authors to know.

PubMed

Harris, Alex H S; Reeder, Rachelle; Hyun, Jenny K

2009-10-01

Journal editors and statistical reviewers are often in the difficult position of catching serious problems in submitted manuscripts after the research is conducted and data have been analyzed. We sought to learn from editors and reviewers of major psychiatry journals what common statistical and design problems they most often find in submitted manuscripts and what they wished to communicate to authors regarding these issues. Our primary goal was to facilitate communication between journal editors/reviewers and researchers/authors and thereby improve the scientific and statistical quality of research and submitted manuscripts. Editors and statistical reviewers of 54 high-impact psychiatry journals were surveyed to learn what statistical or design problems they encounter most often in submitted manuscripts. Respondents completed the survey online. The authors analyzed survey text responses using content analysis procedures to identify major themes related to commonly encountered statistical or research design problems. Editors and reviewers (n=15) who handle manuscripts from 39 different high-impact psychiatry journals responded to the survey. The most commonly cited problems regarded failure to map statistical models onto research questions, improper handling of missing data, not controlling for multiple comparisons, not understanding the difference between equivalence and difference trials, and poor controls in quasi-experimental designs. The scientific quality of psychiatry research and submitted reports could be greatly improved if researchers became sensitive to, or sought consultation on frequently encountered methodological and analytic issues.

Effect Size Measure and Analysis of Single Subject Designs

ERIC Educational Resources Information Center

Swaminathan, Hariharan; Horner, Robert H.; Rogers, H. Jane; Sugai, George

2012-01-01

This study is aimed at addressing the criticisms that have been leveled at the currently available statistical procedures for analyzing single subject designs (SSD). One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been…

Factorial analysis of trihalomethanes formation in drinking water.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2010-06-01

Disinfection of drinking water reduces pathogenic infection, but may pose risks to human health through the formation of disinfection byproducts. The effects of different factors on the formation of trihalomethanes were investigated using a statistically designed experimental program, and a predictive model for trihalomethanes formation was developed. Synthetic water samples with different factor levels were produced, and trihalomethanes concentrations were measured. A replicated fractional factorial design with center points was performed, and significant factors were identified through statistical analysis. A second-order trihalomethanes formation model was developed from 92 experiments, and the statistical adequacy was assessed through appropriate diagnostics. This model was validated using additional data from the Drinking Water Surveillance Program database and was applied to the Smiths Falls water supply system in Ontario, Canada. The model predictions were correlated strongly to the measured trihalomethanes, with correlations of 0.95 and 0.91, respectively. The resulting model can assist in analyzing risk-cost tradeoffs in the design and operation of water supply systems.

Interactive design and analysis of future large spacecraft concepts

NASA Technical Reports Server (NTRS)

Garrett, L. B.

1981-01-01

An interactive computer aided design program used to perform systems level design and analysis of large spacecraft concepts is presented. Emphasis is on rapid design, analysis of integrated spacecraft, and automatic spacecraft modeling for lattice structures. Capabilities and performance of multidiscipline applications modules, the executive and data management software, and graphics display features are reviewed. A single user at an interactive terminal create, design, analyze, and conduct parametric studies of Earth orbiting spacecraft with relative ease. Data generated in the design, analysis, and performance evaluation of an Earth-orbiting large diameter antenna satellite are used to illustrate current capabilities. Computer run time statistics for the individual modules quantify the speed at which modeling, analysis, and design evaluation of integrated spacecraft concepts is accomplished in a user interactive computing environment.

Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design.

PubMed

Selvarasu, Suresh; Kim, Do Yun; Karimi, Iftekhar A; Lee, Dong-Yup

2010-10-01

We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in the feed medium can be inferred, potentially leading to an increase in cell viability and productivity, as well as a decrease in toxic waste production. The study demonstrated how the current methodological framework using multivariate statistical analysis techniques can serve as a potential tool for deriving rational medium design strategies. Copyright © 2010 Elsevier B.V. All rights reserved.

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Statistical evaluation of metal fill widths for emulated metal fill in parasitic extraction methodology

NASA Astrophysics Data System (ADS)

J-Me, Teh; Noh, Norlaili Mohd.; Aziz, Zalina Abdul

2015-05-01

In the chip industry today, the key goal of a chip development organization is to develop and market chips within a short time frame to gain foothold on market share. This paper proposes a design flow around the area of parasitic extraction to improve the design cycle time. The proposed design flow utilizes the usage of metal fill emulation as opposed to the current flow which performs metal fill insertion directly. By replacing metal fill structures with an emulation methodology in earlier iterations of the design flow, this is targeted to help reduce runtime in fill insertion stage. Statistical design of experiments methodology utilizing the randomized complete block design was used to select an appropriate emulated metal fill width to improve emulation accuracy. The experiment was conducted on test cases of different sizes, ranging from 1000 gates to 21000 gates. The metal width was varied from 1 x minimum metal width to 6 x minimum metal width. Two-way analysis of variance and Fisher's least significant difference test were used to analyze the interconnect net capacitance values of the different test cases. This paper presents the results of the statistical analysis for the 45 nm process technology. The recommended emulated metal fill width was found to be 4 x the minimum metal width.

Evaluation Using Sequential Trials Methods.

ERIC Educational Resources Information Center

Cohen, Mark E.; Ralls, Stephen A.

1986-01-01

Although dental school faculty as well as practitioners are interested in evaluating products and procedures used in clinical practice, research design and statistical analysis can sometimes pose problems. Sequential trials methods provide an analytical structure that is both easy to use and statistically valid. (Author/MLW)

Crop identification technology assessment for remote sensing. (CITARS) Volume 9: Statistical analysis of results

NASA Technical Reports Server (NTRS)

Davis, B. J.; Feiveson, A. H.

1975-01-01

Results are presented of CITARS data processing in raw form. Tables of descriptive statistics are given along with descriptions and results of inferential analyses. The inferential results are organized by questions which CITARS was designed to answer.

MSUSTAT.

ERIC Educational Resources Information Center

Mauriello, David

1984-01-01

Reviews an interactive statistical analysis package (designed to run on 8- and 16-bit machines that utilize CP/M 80 and MS-DOS operating systems), considering its features and uses, documentation, operation, and performance. The package consists of 40 general purpose statistical procedures derived from the classic textbook "Statistical…

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

PubMed

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

2007-12-01

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

Primer of statistics in dental research: part I.

PubMed

Shintani, Ayumi

2014-01-01

Statistics play essential roles in evidence-based dentistry (EBD) practice and research. It ranges widely from formulating scientific questions, designing studies, collecting and analyzing data to interpreting, reporting, and presenting study findings. Mastering statistical concepts appears to be an unreachable goal among many dental researchers in part due to statistical authorities' limitations of explaining statistical principles to health researchers without elaborating complex mathematical concepts. This series of 2 articles aim to introduce dental researchers to 9 essential topics in statistics to conduct EBD with intuitive examples. The part I of the series includes the first 5 topics (1) statistical graph, (2) how to deal with outliers, (3) p-value and confidence interval, (4) testing equivalence, and (5) multiplicity adjustment. Part II will follow to cover the remaining topics including (6) selecting the proper statistical tests, (7) repeated measures analysis, (8) epidemiological consideration for causal association, and (9) analysis of agreement. Copyright © 2014. Published by Elsevier Ltd.

Testing and Evaluating C3I Systems That Employ AI. Volume 1. Handbook for Testing Expert Systems

DTIC Science & Technology

1991-01-31

Designs ....... ............. .. 6-29 Nonequivalent Control Group Design ...does not receive the system; and (c) nonequivalent (and nonrandomized) control group designs that rely on statistical techniques like analysis of...implementation); (b) multiple time-series designs using a control group ; and (c) nonequivalent control group designs that obtain pretest and

DCL System Research Using Advanced Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2012-09-30

recognition. Algorithm design and statistical analysis and feature analysis. Post -Doctoral Associate, Cornell University, Bioacoustics Research...short. The HPC-ADA was designed based on fielded systems [1-4, 6] that offer a variety of desirable attributes, specifically dynamic resource...The software package was designed to utilize parallel and distributed processing for running recognition and other advanced algorithms. DeLMA

The Practicality of Statistical Physics Handout Based on KKNI and the Constructivist Approach

NASA Astrophysics Data System (ADS)

Sari, S. Y.; Afrizon, R.

2018-04-01

Statistical physics lecture shows that: 1) the performance of lecturers, social climate, students’ competence and soft skills needed at work are in enough category, 2) students feel difficulties in following the lectures of statistical physics because it is abstract, 3) 40.72% of students needs more understanding in the form of repetition, practice questions and structured tasks, and 4) the depth of statistical physics material needs to be improved gradually and structured. This indicates that learning materials in accordance of The Indonesian National Qualification Framework or Kerangka Kualifikasi Nasional Indonesia (KKNI) with the appropriate learning approach are needed to help lecturers and students in lectures. The author has designed statistical physics handouts which have very valid criteria (90.89%) according to expert judgment. In addition, the practical level of handouts designed also needs to be considered in order to be easy to use, interesting and efficient in lectures. The purpose of this research is to know the practical level of statistical physics handout based on KKNI and a constructivist approach. This research is a part of research and development with 4-D model developed by Thiagarajan. This research activity has reached part of development test at Development stage. Data collection took place by using a questionnaire distributed to lecturers and students. Data analysis using descriptive data analysis techniques in the form of percentage. The analysis of the questionnaire shows that the handout of statistical physics has very practical criteria. The conclusion of this study is statistical physics handouts based on the KKNI and constructivist approach have been practically used in lectures.

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

STATWIZ - AN ELECTRONIC STATISTICAL TOOL (ABSTRACT)

EPA Science Inventory

StatWiz is a web-based, interactive, and dynamic statistical tool for researchers. It will allow researchers to input information and/or data and then receive experimental design options, or outputs from data analysis. StatWiz is envisioned as an expert system that will walk rese...

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.

Profile Of 'Original Articles' Published In 2016 By The Journal Of Ayub Medical College, Pakistan.

PubMed

Shaikh, Masood Ali

2018-01-01

Journal of Ayub Medical College (JAMC) is the only Medline indexed biomedical journal of Pakistan that is edited and published by a medical college. Assessing the trends of study designs employed, statistical methods used, and statistical analysis software used in the articles of medical journals help understand the sophistication of research published. The objectives of this descriptive study were to assess all original articles published by JAMC in the year 2016. JAMC published 147 original articles in the year 2016. The most commonly used study design was crosssectional studies, with 64 (43.5%) articles reporting its use. Statistical tests involving bivariate analysis were most common and reported by 73 (49.6%) articles. Use of SPSS software was reported by 109 (74.1%) of articles. Most 138 (93.9%) of the original articles published were based on studies conducted in Pakistan. The number and sophistication of analysis reported in JAMC increased from year 2014 to 2016.

Systematic survey of the design, statistical analysis, and reporting of studies published in the 2008 volume of the Journal of Cerebral Blood Flow and Metabolism.

PubMed

Vesterinen, Hanna M; Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich

2011-04-01

Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication.

Systematic survey of the design, statistical analysis, and reporting of studies published in the 2008 volume of the Journal of Cerebral Blood Flow and Metabolism

PubMed Central

Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich

2011-01-01

Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication. PMID:21157472

A statistical design for testing apomictic diversification through linkage analysis.

PubMed

Zeng, Yanru; Hou, Wei; Song, Shuang; Feng, Sisi; Shen, Lin; Xia, Guohua; Wu, Rongling

2014-03-01

The capacity of apomixis to generate maternal clones through seed reproduction has made it a useful characteristic for the fixation of heterosis in plant breeding. It has been observed that apomixis displays pronounced intra- and interspecific diversification, but the genetic mechanisms underlying this diversification remains elusive, obstructing the exploitation of this phenomenon in practical breeding programs. By capitalizing on molecular information in mapping populations, we describe and assess a statistical design that deploys linkage analysis to estimate and test the pattern and extent of apomictic differences at various levels from genotypes to species. The design is based on two reciprocal crosses between two individuals each chosen from a hermaphrodite or monoecious species. A multinomial distribution likelihood is constructed by combining marker information from two crosses. The EM algorithm is implemented to estimate the rate of apomixis and test its difference between two plant populations or species as the parents. The design is validated by computer simulation. A real data analysis of two reciprocal crosses between hickory (Carya cathayensis) and pecan (C. illinoensis) demonstrates the utilization and usefulness of the design in practice. The design provides a tool to address fundamental and applied questions related to the evolution and breeding of apomixis.

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.

Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

ERIC Educational Resources Information Center

Wiens, Stefan; Nilsson, Mats E.

2017-01-01

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…

A method for developing design diagrams for ceramic and glass materials using fatigue data

NASA Technical Reports Server (NTRS)

Heslin, T. M.; Magida, M. B.; Forrest, K. A.

1986-01-01

The service lifetime of glass and ceramic materials can be expressed as a plot of time-to-failure versus applied stress whose plot is parametric in percent probability of failure. This type of plot is called a design diagram. Confidence interval estimates for such plots depend on the type of test that is used to generate the data, on assumptions made concerning the statistical distribution of the test results, and on the type of analysis used. This report outlines the development of design diagrams for glass and ceramic materials in engineering terms using static or dynamic fatigue tests, assuming either no particular statistical distribution of test results or a Weibull distribution and using either median value or homologous ratio analysis of the test results.

Modified Bayesian Kriging for Noisy Response Problems for Reliability Analysis

DTIC Science & Technology

2015-01-01

52242, USA nicholas-gaul@uiowa.edu Mary Kathryn Cowles Department of Statistics & Actuarial Science College of Liberal Arts and Sciences , The...Forrester, A. I. J., & Keane, A. J. (2009). Recent advances in surrogate-based optimization. Progress in Aerospace Sciences , 45(1–3), 50-79. doi...Wiley. [27] Sacks, J., Welch, W. J., Toby J. Mitchell, & Wynn, H. P. (1989). Design and analysis of computer experiments. Statistical Science , 4

Analysis of design attributes and crashes on the Oregon highway system : final report.

DOT National Transportation Integrated Search

2001-08-01

This report has investigated the statistical relationship between crash activity and roadway design attributes on the Oregon state : highway system. Crash models were estimated from highway segments distinguished by functional classification (freeway...

An Automated System for Chromosome Analysis

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.

PubMed

Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

2013-10-01

The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the study. This will minimise analytic bias and conforms to current best practice in conducting clinical trials. © 2013 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Analysis of Developmental Data: Comparison Among Alternative Methods

ERIC Educational Resources Information Center

Wilson, Ronald S.

1975-01-01

To examine the ability of the correction factor epsilon to counteract statistical bias in univariate analysis, an analysis of variance (adjusted by epsilon) and a multivariate analysis of variance were performed on the same data. The results indicated that univariate analysis is a fully protected design when used with epsilon. (JMB)

Statistics 101 for Radiologists.

PubMed

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

2015-10-01

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

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

NASA Technical Reports Server (NTRS)

He, Yuning; Davies, Misty Dawn

2013-01-01

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Sampling and Data Analysis for Environmental Microbiology

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

Murray, Christopher J.

2001-06-01

A brief review of the literature indicates the importance of statistical analysis in applied and environmental microbiology. Sampling designs are particularly important for successful studies, and it is highly recommended that researchers review their sampling design before heading to the laboratory or the field. Most statisticians have numerous stories of scientists who approached them after their study was complete only to have to tell them that the data they gathered could not be used to test the hypothesis they wanted to address. Once the data are gathered, a large and complex body of statistical techniques are available for analysis ofmore » the data. Those methods include both numerical and graphical techniques for exploratory characterization of the data. Hypothesis testing and analysis of variance (ANOVA) are techniques that can be used to compare the mean and variance of two or more groups of samples. Regression can be used to examine the relationships between sets of variables and is often used to examine the dependence of microbiological populations on microbiological parameters. Multivariate statistics provides several methods that can be used for interpretation of datasets with a large number of variables and to partition samples into similar groups, a task that is very common in taxonomy, but also has applications in other fields of microbiology. Geostatistics and other techniques have been used to examine the spatial distribution of microorganisms. The objectives of this chapter are to provide a brief survey of some of the statistical techniques that can be used for sample design and data analysis of microbiological data in environmental studies, and to provide some examples of their use from the literature.« less

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

NASA Technical Reports Server (NTRS)

Stefanski, Philip L.

2015-01-01

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

Joint QTL linkage mapping for multiple-cross mating design sharing one common parent

USDA-ARS?s Scientific Manuscript database

Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present th...

Sensitivity analysis of navy aviation readiness based sparing model

DTIC Science & Technology

2017-09-01

variability. (See Figure 4.) Figure 4. Research design flowchart 18 Figure 4 lays out the four steps of the methodology , starting in the upper left-hand...as a function of changes in key inputs. We develop NAVARM Experimental Designs (NED), a computational tool created by applying a state-of-the-art...experimental design to the NAVARM model. Statistical analysis of the resulting data identifies the most influential cost factors. Those are, in order of

The Health Services Mobility Study Method of Task Analysis and Curriculum Design. Research Report No. 11. Volume 3: Using the Computer to Develop Job Ladders.

ERIC Educational Resources Information Center

Gilpatrick, Eleanor

This document is volume 3 of a four-volume report which describes the components of the Health Services Mobility Study (HSMS) method of task analysis, job ladder design, and curriculum development. Divided into four chapters, volume 3 is a manual for using HSMS computer based statistical procedures to design job structures and job ladders. Chapter…

Analysis of in vivo corrosion of 316L stainless steel posterior thoracolumbar plate systems: a retrieval study.

PubMed

Majid, Kamran; Crowder, Terence; Baker, Erin; Baker, Kevin; Koueiter, Denise; Shields, Edward; Herkowitz, Harry N

2011-12-01

One hundred eighteen patients retrieved 316L stainless steel thoracolumbar plates, of 3 different designs, used for fusion in 60 patients were examined for evidence of corrosion. A medical record review and statistical analysis were also carried out. This study aims to identify types of corrosion and examine preferential metal ion release and the possibility of statistical correlation to clinical effects. Earlier studies have found that stainless steel spine devices showed evidence of mild-to-severe corrosion; fretting and crevice corrosion were the most commonly reported types. Studies have also shown the toxicity of metal ions released from stainless steel corrosion and how the ions may adversely affect bone formation and/or induce granulomatous foreign body responses. The retrieved plates were visually inspected and graded based on the degree of corrosion. The plates were then analyzed with optical microscopy, scanning electron microscopy, and energy dispersive x-ray spectroscopy. A retrospective medical record review was performed and statistical analysis was carried out to determine any correlations between experimental findings and patient data. More than 70% of the plates exhibited some degree of corrosion. Both fretting and crevice corrosion mechanisms were observed, primarily at the screw plate interface. Energy dispersive x-ray spectroscopy analysis indicated reductions in nickel content in corroded areas, suggestive of nickel ion release to the surrounding biological environment. The incidence and severity of corrosion was significantly correlated with the design of the implant. Stainless steel thoracolumbar plates show a high incidence of corrosion, with statistical dependence on device design.

LADES: a software for constructing and analyzing longitudinal designs in biomedical research.

PubMed

Vázquez-Alcocer, Alan; Garzón-Cortes, Daniel Ladislao; Sánchez-Casas, Rosa María

2014-01-01

One of the most important steps in biomedical longitudinal studies is choosing a good experimental design that can provide high accuracy in the analysis of results with a minimum sample size. Several methods for constructing efficient longitudinal designs have been developed based on power analysis and the statistical model used for analyzing the final results. However, development of this technology is not available to practitioners through user-friendly software. In this paper we introduce LADES (Longitudinal Analysis and Design of Experiments Software) as an alternative and easy-to-use tool for conducting longitudinal analysis and constructing efficient longitudinal designs. LADES incorporates methods for creating cost-efficient longitudinal designs, unequal longitudinal designs, and simple longitudinal designs. In addition, LADES includes different methods for analyzing longitudinal data such as linear mixed models, generalized estimating equations, among others. A study of European eels is reanalyzed in order to show LADES capabilities. Three treatments contained in three aquariums with five eels each were analyzed. Data were collected from 0 up to the 12th week post treatment for all the eels (complete design). The response under evaluation is sperm volume. A linear mixed model was fitted to the results using LADES. The complete design had a power of 88.7% using 15 eels. With LADES we propose the use of an unequal design with only 14 eels and 89.5% efficiency. LADES was developed as a powerful and simple tool to promote the use of statistical methods for analyzing and creating longitudinal experiments in biomedical research.

Statistical analysis plan for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). A randomized controlled trial

PubMed Central

Damiani, Lucas Petri; Berwanger, Otavio; Paisani, Denise; Laranjeira, Ligia Nasi; Suzumura, Erica Aranha; Amato, Marcelo Britto Passos; Carvalho, Carlos Roberto Ribeiro; Cavalcanti, Alexandre Biasi

2017-01-01

Background The Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) is an international multicenter randomized pragmatic controlled trial with allocation concealment involving 120 intensive care units in Brazil, Argentina, Colombia, Italy, Poland, Portugal, Malaysia, Spain, and Uruguay. The primary objective of ART is to determine whether maximum stepwise alveolar recruitment associated with PEEP titration, adjusted according to the static compliance of the respiratory system (ART strategy), is able to increase 28-day survival in patients with acute respiratory distress syndrome compared to conventional treatment (ARDSNet strategy). Objective To describe the data management process and statistical analysis plan. Methods The statistical analysis plan was designed by the trial executive committee and reviewed and approved by the trial steering committee. We provide an overview of the trial design with a special focus on describing the primary (28-day survival) and secondary outcomes. We describe our data management process, data monitoring committee, interim analyses, and sample size calculation. We describe our planned statistical analyses for primary and secondary outcomes as well as pre-specified subgroup analyses. We also provide details for presenting results, including mock tables for baseline characteristics, adherence to the protocol and effect on clinical outcomes. Conclusion According to best trial practice, we report our statistical analysis plan and data management plan prior to locking the database and beginning analyses. We anticipate that this document will prevent analysis bias and enhance the utility of the reported results. Trial registration ClinicalTrials.gov number, NCT01374022. PMID:28977255

Statistical power in parallel group point exposure studies with time-to-event outcomes: an empirical comparison of the performance of randomized controlled trials and the inverse probability of treatment weighting (IPTW) approach.

PubMed

Austin, Peter C; Schuster, Tibor; Platt, Robert W

2015-10-15

Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods. We used an extensive series of Monte Carlo simulations to compare the statistical power of an IPTW analysis of an observational study with time-to-event outcomes with that of an analysis of a similarly-structured RCT. We examined the impact of four factors on the statistical power function: number of observed events, prevalence of treatment, the marginal hazard ratio, and the strength of the treatment-selection process. We found that, on average, an IPTW analysis had lower statistical power compared to an analysis of a similarly-structured RCT. The difference in statistical power increased as the magnitude of the treatment-selection model increased. The statistical power of an IPTW analysis tended to be lower than the statistical power of a similarly-structured RCT.

Stochastic Analysis and Design of Heterogeneous Microstructural Materials System

NASA Astrophysics Data System (ADS)

Xu, Hongyi

Advanced materials system refers to new materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to superior properties over the conventional materials. To accelerate the development of new advanced materials system, the objective of this dissertation is to develop a computational design framework and the associated techniques for design automation of microstructure materials systems, with an emphasis on addressing the uncertainties associated with the heterogeneity of microstructural materials. Five key research tasks are identified: design representation, design evaluation, design synthesis, material informatics and uncertainty quantification. Design representation of microstructure includes statistical characterization and stochastic reconstruction. This dissertation develops a new descriptor-based methodology, which characterizes 2D microstructures using descriptors of composition, dispersion and geometry. Statistics of 3D descriptors are predicted based on 2D information to enable 2D-to-3D reconstruction. An efficient sequential reconstruction algorithm is developed to reconstruct statistically equivalent random 3D digital microstructures. In design evaluation, a stochastic decomposition and reassembly strategy is developed to deal with the high computational costs and uncertainties induced by material heterogeneity. The properties of Representative Volume Elements (RVE) are predicted by stochastically reassembling SVE elements with stochastic properties into a coarse representation of the RVE. In design synthesis, a new descriptor-based design framework is developed, which integrates computational methods of microstructure characterization and reconstruction, sensitivity analysis, Design of Experiments (DOE), metamodeling and optimization the enable parametric optimization of the microstructure for achieving the desired material properties. Material informatics is studied to efficiently reduce the dimension of microstructure design space. This dissertation develops a machine learning-based methodology to identify the key microstructure descriptors that highly impact properties of interest. In uncertainty quantification, a comparative study on data-driven random process models is conducted to provide guidance for choosing the most accurate model in statistical uncertainty quantification. Two new goodness-of-fit metrics are developed to provide quantitative measurements of random process models' accuracy. The benefits of the proposed methods are demonstrated by the example of designing the microstructure of polymer nanocomposites. This dissertation provides material-generic, intelligent modeling/design methodologies and techniques to accelerate the process of analyzing and designing new microstructural materials system.

Fully Bayesian Estimation of Data from Single Case Designs

ERIC Educational Resources Information Center

Rindskopf, David

2013-01-01

Single case designs (SCDs) generally consist of a small number of short time series in two or more phases. The analysis of SCDs statistically fits in the framework of a multilevel model, or hierarchical model. The usual analysis does not take into account the uncertainty in the estimation of the random effects. This not only has an effect on the…

Scientific, statistical, practical, and regulatory considerations in design space development.

PubMed

Debevec, Veronika; Srčič, Stanko; Horvat, Matej

2018-03-01

The quality by design (QbD) paradigm guides the pharmaceutical industry towards improved understanding of products and processes, and at the same time facilitates a high degree of manufacturing and regulatory flexibility throughout the establishment of the design space. This review article presents scientific, statistical and regulatory considerations in design space development. All key development milestones, starting with planning, selection of factors, experimental execution, data analysis, model development and assessment, verification, and validation, and ending with design space submission, are presented and discussed. The focus is especially on frequently ignored topics, like management of factors and CQAs that will not be included in experimental design, evaluation of risk of failure on design space edges, or modeling scale-up strategy. Moreover, development of a design space that is independent of manufacturing scale is proposed as the preferred approach.

Informal Statistics Help Desk

NASA Technical Reports Server (NTRS)

Young, M.; Koslovsky, M.; Schaefer, Caroline M.; Feiveson, A. H.

2017-01-01

Back by popular demand, the JSC Biostatistics Laboratory and LSAH statisticians are offering an opportunity to discuss your statistical challenges and needs. Take the opportunity to meet the individuals offering expert statistical support to the JSC community. Join us for an informal conversation about any questions you may have encountered with issues of experimental design, analysis, or data visualization. Get answers to common questions about sample size, repeated measures, statistical assumptions, missing data, multiple testing, time-to-event data, and when to trust the results of your analyses.

A Guerilla Guide to Common Problems in ‘Neurostatistics’: Essential Statistical Topics in Neuroscience

PubMed Central

Smith, Paul F.

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins. PMID:29371855

A Guerilla Guide to Common Problems in 'Neurostatistics': Essential Statistical Topics in Neuroscience.

PubMed

Smith, Paul F

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins.

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

USGS Publications Warehouse

Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

2018-03-07

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

NASA Astrophysics Data System (ADS)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

Statistical summaries of fatigue data for design purposes

NASA Technical Reports Server (NTRS)

Wirsching, P. H.

1983-01-01

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

Preparing and Presenting Effective Research Posters

PubMed Central

Miller, Jane E

2007-01-01

Objectives Posters are a common way to present results of a statistical analysis, program evaluation, or other project at professional conferences. Often, researchers fail to recognize the unique nature of the format, which is a hybrid of a published paper and an oral presentation. This methods note demonstrates how to design research posters to convey study objectives, methods, findings, and implications effectively to varied professional audiences. Methods A review of existing literature on research communication and poster design is used to identify and demonstrate important considerations for poster content and layout. Guidelines on how to write about statistical methods, results, and statistical significance are illustrated with samples of ineffective writing annotated to point out weaknesses, accompanied by concrete examples and explanations of improved presentation. A comparison of the content and format of papers, speeches, and posters is also provided. Findings Each component of a research poster about a quantitative analysis should be adapted to the audience and format, with complex statistical results translated into simplified charts, tables, and bulleted text to convey findings as part of a clear, focused story line. Conclusions Effective research posters should be designed around two or three key findings with accompanying handouts and narrative description to supply additional technical detail and encourage dialog with poster viewers. PMID:17355594

Radiomic analysis in prediction of Human Papilloma Virus status.

PubMed

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

2017-12-01

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

Impact of a Single Unusually Large Rainfall Event on the Level of Risk Used for Infrastructure Design

NASA Astrophysics Data System (ADS)

Dhakal, N.; Jain, S.

2013-12-01

Rare and unusually large events (such as hurricanes and floods) can create unusual and interesting trends in statistics. Generalized Extreme Value (GEV) distribution is usually used to statistically describe extreme rainfall events. A number of the recent studies have shown that the frequency of extreme rainfall events has increased over the last century and as a result, there has been change in parameters of GEV distribution with the time (non-stationary). But what impact does a single unusually large rainfall event (e.g., hurricane Irene) have on the GEV parameters and consequently on the level of risks or the return periods used in designing the civil infrastructures? In other words, if such a large event occurs today, how will it influence the level of risks (estimated based on past rainfall records) for the civil infrastructures? To answer these questions, we performed sensitivity analysis of the distribution parameters of GEV as well as the return periods to unusually large outlier events. The long-term precipitation records over the period of 1981-2010 from 12 USHCN stations across the state of Maine were used for analysis. For most of the stations, addition of each outlier event caused an increase in the shape parameter with a huge decrease on the corresponding return period. This is a key consideration for time-varying engineering design. These isolated extreme weather events should simultaneously be considered with traditional statistical methodology related to extreme events while designing civil infrastructures (such as dams, bridges, and culverts). Such analysis is also useful in understanding the statistical uncertainty of projecting extreme events into future.

What Time-Series Designs May Have to Offer Educational Researchers.

ERIC Educational Resources Information Center

Kratochwill, Thomas R.; Levin, Joel R.

1978-01-01

The promise of time-series designs for educational research and evaluation is reviewed. Ten time-series designs are presented and discussed in the context of threats to internal and external validity. The advantages and disadvantages of various visual and statistical data-analysis techniques are presented. A bibliography is appended. (Author/RD)

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...

Students' Initial Knowledge State and Test Design: Towards a Valid and Reliable Test Instrument

ERIC Educational Resources Information Center

CoPo, Antonio Roland I.

2015-01-01

Designing a good test instrument involves specifications, test construction, validation, try-out, analysis and revision. The initial knowledge state of forty (40) tertiary students enrolled in Business Statistics course was determined and the same test instrument undergoes validation. The designed test instrument did not only reveal the baseline…

75 FR 47592 - Final Test Guideline; Product Performance of Skin-applied Insect Repellents of Insect and Other...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-06

... considerations affecting the design and conduct of repellent studies when human subjects are involved. Any... recommendations for the design and execution of studies to evaluate the performance of pesticide products intended... recommends appropriate study designs and methods for selecting subjects, statistical analysis, and reporting...

A statistical approach to optimizing concrete mixture design.

PubMed

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

PubMed Central

Alghamdi, Saeid A.

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m3), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options. PMID:24688405

A study of the feasibility of statistical analysis of airport performance simulation

NASA Technical Reports Server (NTRS)

Myers, R. H.

1982-01-01

The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.

The use of statistical tools in field testing of putative effects of genetically modified plants on nontarget organisms

PubMed Central

Semenov, Alexander V; Elsas, Jan Dirk; Glandorf, Debora C M; Schilthuizen, Menno; Boer, Willem F

2013-01-01

Abstract To fulfill existing guidelines, applicants that aim to place their genetically modified (GM) insect-resistant crop plants on the market are required to provide data from field experiments that address the potential impacts of the GM plants on nontarget organisms (NTO's). Such data may be based on varied experimental designs. The recent EFSA guidance document for environmental risk assessment (2010) does not provide clear and structured suggestions that address the statistics of field trials on effects on NTO's. This review examines existing practices in GM plant field testing such as the way of randomization, replication, and pseudoreplication. Emphasis is placed on the importance of design features used for the field trials in which effects on NTO's are assessed. The importance of statistical power and the positive and negative aspects of various statistical models are discussed. Equivalence and difference testing are compared, and the importance of checking the distribution of experimental data is stressed to decide on the selection of the proper statistical model. While for continuous data (e.g., pH and temperature) classical statistical approaches – for example, analysis of variance (ANOVA) – are appropriate, for discontinuous data (counts) only generalized linear models (GLM) are shown to be efficient. There is no golden rule as to which statistical test is the most appropriate for any experimental situation. In particular, in experiments in which block designs are used and covariates play a role GLMs should be used. Generic advice is offered that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in this testing. The combination of decision trees and a checklist for field trials, which are provided, will help in the interpretation of the statistical analyses of field trials and to assess whether such analyses were correctly applied. We offer generic advice to risk assessors and applicants that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in field testing. PMID:24567836

The use of statistical tools in field testing of putative effects of genetically modified plants on nontarget organisms.

PubMed

Semenov, Alexander V; Elsas, Jan Dirk; Glandorf, Debora C M; Schilthuizen, Menno; Boer, Willem F

2013-08-01

To fulfill existing guidelines, applicants that aim to place their genetically modified (GM) insect-resistant crop plants on the market are required to provide data from field experiments that address the potential impacts of the GM plants on nontarget organisms (NTO's). Such data may be based on varied experimental designs. The recent EFSA guidance document for environmental risk assessment (2010) does not provide clear and structured suggestions that address the statistics of field trials on effects on NTO's. This review examines existing practices in GM plant field testing such as the way of randomization, replication, and pseudoreplication. Emphasis is placed on the importance of design features used for the field trials in which effects on NTO's are assessed. The importance of statistical power and the positive and negative aspects of various statistical models are discussed. Equivalence and difference testing are compared, and the importance of checking the distribution of experimental data is stressed to decide on the selection of the proper statistical model. While for continuous data (e.g., pH and temperature) classical statistical approaches - for example, analysis of variance (ANOVA) - are appropriate, for discontinuous data (counts) only generalized linear models (GLM) are shown to be efficient. There is no golden rule as to which statistical test is the most appropriate for any experimental situation. In particular, in experiments in which block designs are used and covariates play a role GLMs should be used. Generic advice is offered that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in this testing. The combination of decision trees and a checklist for field trials, which are provided, will help in the interpretation of the statistical analyses of field trials and to assess whether such analyses were correctly applied. We offer generic advice to risk assessors and applicants that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in field testing.

Obtaining mathematical models for assessing efficiency of dust collectors using integrated system of analysis and data management STATISTICA Design of Experiments

NASA Astrophysics Data System (ADS)

Azarov, A. V.; Zhukova, N. S.; Kozlovtseva, E. Yu; Dobrinsky, D. R.

2018-05-01

The article considers obtaining mathematical models to assess the efficiency of the dust collectors using an integrated system of analysis and data management STATISTICA Design of Experiments. The procedure for obtaining mathematical models and data processing is considered by the example of laboratory studies on a mounted installation containing a dust collector in counter-swirling flows (CSF) using gypsum dust of various fractions. Planning of experimental studies has been carried out in order to reduce the number of experiments and reduce the cost of experimental research. A second-order non-position plan (Box-Bencken plan) was used, which reduced the number of trials from 81 to 27. The order of statistical data research of Box-Benken plan using standard tools of integrated system for analysis and data management STATISTICA Design of Experiments is considered. Results of statistical data processing with significance estimation of coefficients and adequacy of mathematical models are presented.

Statistical sensitivity analysis of a simple nuclear waste repository model

NASA Astrophysics Data System (ADS)

Ronen, Y.; Lucius, J. L.; Blow, E. M.

1980-06-01

A preliminary step in a comprehensive sensitivity analysis of the modeling of a nuclear waste repository. The purpose of the complete analysis is to determine which modeling parameters and physical data are most important in determining key design performance criteria and then to obtain the uncertainty in the design for safety considerations. The theory for a statistical screening design methodology is developed for later use in the overall program. The theory was applied to the test case of determining the relative importance of the sensitivity of near field temperature distribution in a single level salt repository to modeling parameters. The exact values of the sensitivities to these physical and modeling parameters were then obtained using direct methods of recalculation. The sensitivity coefficients found to be important for the sample problem were thermal loading, distance between the spent fuel canisters and their radius. Other important parameters were those related to salt properties at a point of interest in the repository.

Clinical study of the Erlanger silver catheter--data management and biometry.

PubMed

Martus, P; Geis, C; Lugauer, S; Böswald, M; Guggenbichler, J P

1999-01-01

The clinical evaluation of venous catheters for catheter-induced infections must conform to a strict biometric methodology. The statistical planning of the study (target population, design, degree of blinding), data management (database design, definition of variables, coding), quality assurance (data inspection at several levels) and the biometric evaluation of the Erlanger silver catheter project are described. The three-step data flow included: 1) primary data from the hospital, 2) relational database, 3) files accessible for statistical evaluation. Two different statistical models were compared: analyzing the first catheter only of a patient in the analysis (independent data) and analyzing several catheters from the same patient (dependent data) by means of the generalized estimating equations (GEE) method. The main result of the study was based on the comparison of both statistical models.

Towards evidence-based computational statistics: lessons from clinical research on the role and design of real-data benchmark studies.

PubMed

Boulesteix, Anne-Laure; Wilson, Rory; Hapfelmeier, Alexander

2017-09-09

The goal of medical research is to develop interventions that are in some sense superior, with respect to patient outcome, to interventions currently in use. Similarly, the goal of research in methodological computational statistics is to develop data analysis tools that are themselves superior to the existing tools. The methodology of the evaluation of medical interventions continues to be discussed extensively in the literature and it is now well accepted that medicine should be at least partly "evidence-based". Although we statisticians are convinced of the importance of unbiased, well-thought-out study designs and evidence-based approaches in the context of clinical research, we tend to ignore these principles when designing our own studies for evaluating statistical methods in the context of our methodological research. In this paper, we draw an analogy between clinical trials and real-data-based benchmarking experiments in methodological statistical science, with datasets playing the role of patients and methods playing the role of medical interventions. Through this analogy, we suggest directions for improvement in the design and interpretation of studies which use real data to evaluate statistical methods, in particular with respect to dataset inclusion criteria and the reduction of various forms of bias. More generally, we discuss the concept of "evidence-based" statistical research, its limitations and its impact on the design and interpretation of real-data-based benchmark experiments. We suggest that benchmark studies-a method of assessment of statistical methods using real-world datasets-might benefit from adopting (some) concepts from evidence-based medicine towards the goal of more evidence-based statistical research.

STRengthening analytical thinking for observational studies: the STRATOS initiative.

PubMed

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-12-30

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Space biology initiative program definition review. Trade study 4: Design modularity and commonality

NASA Technical Reports Server (NTRS)

Jackson, L. Neal; Crenshaw, John, Sr.; Davidson, William L.; Herbert, Frank J.; Bilodeau, James W.; Stoval, J. Michael; Sutton, Terry

1989-01-01

The relative cost impacts (up or down) of developing Space Biology hardware using design modularity and commonality is studied. Recommendations for how the hardware development should be accomplished to meet optimum design modularity requirements for Life Science investigation hardware will be provided. In addition, the relative cost impacts of implementing commonality of hardware for all Space Biology hardware are defined. Cost analysis and supporting recommendations for levels of modularity and commonality are presented. A mathematical or statistical cost analysis method with the capability to support development of production design modularity and commonality impacts to parametric cost analysis is provided.

Comparative efficacy of two battery-powered toothbrushes on dental plaque removal.

PubMed

Ruhlman, C Douglas; Bartizek, Robert D; Biesbrock, Aaron R

2002-01-01

A number of clinical studies have consistently demonstrated that power toothbrushes deliver superior plaque removal compared to manual toothbrushes. Recently, a new power toothbrush (Crest SpinBrush) has been marketed with a design that fundamentally differs from other marketed power toothbrushes. Other power toothbrushes feature a small, round head designed to oscillate for enhanced cleaning between the teeth and below the gumline. The new power toothbrush incorporates a similar round oscillating head in conjunction with fixed bristles, which allows the user to brush with optimal manual brushing technique. The objective of this randomized, examiner-blind, parallel design study was to compare the plaque removal efficacy of a positive control power toothbrush (Colgate Actibrush) to an experimental toothbrush (Crest SpinBrush) following a single use among 59 subjects. Baseline plaque scores were 1.64 and 1.40 for the experimental toothbrush and control toothbrush treatment groups, respectively. With regard to all surfaces examined, the experimental toothbrush delivered an adjusted (via analysis of covariance) mean difference between baseline and post-brushing plaque scores of 0.47, while the control toothbrush delivered an adjusted mean difference of 0.33. On average, the difference between toothbrushes was statistically significant (p = 0.013). Because the covariate slope for the experimental group was statistically significantly greater (p = 0.001) than the slope for the control group, a separate slope model was used. Further analysis demonstrated that the experimental group had statistically significantly greater plaque removal than the control group for baseline plaque scores above 1.43. With respect to buccal surfaces, using a separate slope analysis of covariance, the experimental toothbrush delivered an adjusted mean difference between baseline and post-brushing plaque scores of 0.61, while the control toothbrush delivered an adjusted mean difference of 0.39. This difference between toothbrushes was also statistically significant (p = 0.002). On average, the results on lingual surfaces demonstrated similar directional scores favoring the experimental toothbrush; however these results did not achieve statistical significance. In conclusion, the experimental Crest SpinBrush, with its novel fixed and oscillating bristle design, was found to be more effective than the positive control Colgate Actibrush, which is designed with a small round oscillating cluster of bristles.

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

PubMed

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

2017-12-16

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

Older and Younger Workers: The Equalling Effects of Health

ERIC Educational Resources Information Center

Beck, Vanessa; Quinn, Martin

2012-01-01

Purpose: The purpose of this paper is to consider the statistical evidence on the effects that ill health has on labour market participation and opportunities for younger and older workers in the East Midlands (UK). Design/methodology/approach: A statistical analysis of Labour Force Survey data was undertaken to demonstrate that health issues…

Remedial Education at Degree-Granting Postsecondary Institutions in Fall 2000. Statistical Analysis Report.

ERIC Educational Resources Information Center

Parsad, Basmat; Lewis, Laurie

This study, conducted through the Postsecondary Quick Information System (PEQIS) of the National Center for Education Statistics, was designed to provide current national estimates of the prevalence and characteristics of remedial courses and enrollments in degree-granting 2-year and 4-year postsecondary institutions that enrolled freshmen in fall…

Spatial Statistical Model and Optimal Survey Design for Rapid Geophysical Characterization of UXO Sites

DTIC Science & Technology

2003-07-01

4, Gnanadesikan , 1977). An entity whose measured features fall into one of the regions is classified accordingly. For the approaches we discuss here... Gnanadesikan , R. 1977. Methods for Statistical Data Analysis of Multivariate Observations. John Wiley & Sons, New York. Hassig, N. L., O’Brien, R. F

Statistical description of tectonic motions

NASA Technical Reports Server (NTRS)

Agnew, Duncan Carr

1993-01-01

This report summarizes investigations regarding tectonic motions. The topics discussed include statistics of crustal deformation, Earth rotation studies, using multitaper spectrum analysis techniques applied to both space-geodetic data and conventional astrometric estimates of the Earth's polar motion, and the development, design, and installation of high-stability geodetic monuments for use with the global positioning system.

An On-Line Virtual Environment for Teaching Statistical Sampling and Analysis

ERIC Educational Resources Information Center

Marsh, Michael T.

2009-01-01

Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and…

Recommendations for the Design and Analysis of Treatment Trials for Alcohol Use Disorders

PubMed Central

Witkiewitz, Katie; Finney, John W.; Harris, Alex H.S; Kivlahan, Daniel R.; Kranzler, Henry R.

2015-01-01

Background Over the past 60 years the view that “alcoholism” is a disease for which the only acceptable goal of treatment is abstinence has given way to the recognition that alcohol use disorders (AUDs) occur on a continuum of severity, for which a variety of treatment options are appropriate. However, because the available treatments for AUDs are not effective for everyone, more research is needed to develop novel and more efficacious treatments to address the range of AUD severity in diverse populations. Here we offer recommendations for the design and analysis of alcohol treatment trials, with a specific focus on the careful conduct of randomized clinical trials of medications and non-pharmacological interventions for AUDs. Methods Narrative review of the quality of published clinical trials and recommendations for the optimal design and analysis of treatment trials for AUDs. Results Despite considerable improvements in the design of alcohol clinical trials over the past two decades, many studies of AUD treatments have used faulty design features and statistical methods that are known to produce biased estimates of treatment efficacy. Conclusions The published statistical and methodological literatures provide clear guidance on methods to improve clinical trial design and analysis. Consistent use of state-of-the-art design features and analytic approaches will enhance the internal and external validity of treatment trials for AUDs across the spectrum of severity. The ultimate result of this attention to methodological rigor is that better treatment options will be identified for patients with an AUD. PMID:26250333

Evaluation of Next-Generation Vision Testers for Aeromedical Certification of Aviation Personnel

DTIC Science & Technology

2009-07-01

measure distant, intermediate, and near acuity. The slides are essentially abbreviated versions of the Early Treatment for Diabetic Retinopathy Study...over, requiring intermediate vision testing and 12 were color deficient. Analysis was designed to detect statistically significant differences between...Vertical Phoria (Right & Left Hyperphoria) Test scores from each of the vision testers were collated and analyzed. Analysis was designed to detect

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

Good experimental design and statistics can save animals, but how can it be promoted?

PubMed

Festing, Michael F W

2004-06-01

Surveys of published papers show that there are many errors both in the design of the experiments and in the statistical analysis of the resulting data. This must result in a waste of animals and scientific resources, and it is surely unethical. Scientific quality might be improved, to some extent, by journal editors, but they are constrained by lack of statistical referees and inadequate statistical training of those referees that they do use. Other parties, such as welfare regulators, ethical review committees and individual scientists also have an interest in scientific quality, but they do not seem to be well placed to make the required changes. However, those who fund research would have the power to do something if they could be convinced that it is in their best interests to do so. More examples of the way in which better experimental design has led to improved experiments would be helpful in persuading these funding organisations to take further action.

The Development of Statistics Textbook Supported with ICT and Portfolio-Based Assessment

NASA Astrophysics Data System (ADS)

Hendikawati, Putriaji; Yuni Arini, Florentina

2016-02-01

This research was development research that aimed to develop and produce a Statistics textbook model that supported with information and communication technology (ICT) and Portfolio-Based Assessment. This book was designed for students of mathematics at the college to improve students’ ability in mathematical connection and communication. There were three stages in this research i.e. define, design, and develop. The textbooks consisted of 10 chapters which each chapter contains introduction, core materials and include examples and exercises. The textbook developed phase begins with the early stages of designed the book (draft 1) which then validated by experts. Revision of draft 1 produced draft 2 which then limited test for readability test book. Furthermore, revision of draft 2 produced textbook draft 3 which simulated on a small sample to produce a valid model textbook. The data were analysed with descriptive statistics. The analysis showed that the Statistics textbook model that supported with ICT and Portfolio-Based Assessment valid and fill up the criteria of practicality.

Computational Analysis for Rocket-Based Combined-Cycle Systems During Rocket-Only Operation

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.; Smith, T. D.; Yungster, S.; Keller, D. J.

2000-01-01

A series of Reynolds-averaged Navier-Stokes calculations were employed to study the performance of rocket-based combined-cycle systems operating in an all-rocket mode. This parametric series of calculations were executed within a statistical framework, commonly known as design of experiments. The parametric design space included four geometric and two flowfield variables set at three levels each, for a total of 729 possible combinations. A D-optimal design strategy was selected. It required that only 36 separate computational fluid dynamics (CFD) solutions be performed to develop a full response surface model, which quantified the linear, bilinear, and curvilinear effects of the six experimental variables. The axisymmetric, Reynolds-averaged Navier-Stokes simulations were executed with the NPARC v3.0 code. The response used in the statistical analysis was created from Isp efficiency data integrated from the 36 CFD simulations. The influence of turbulence modeling was analyzed by using both one- and two-equation models. Careful attention was also given to quantify the influence of mesh dependence, iterative convergence, and artificial viscosity upon the resulting statistical model. Thirteen statistically significant effects were observed to have an influence on rocket-based combined-cycle nozzle performance. It was apparent that the free-expansion process, directly downstream of the rocket nozzle, can influence the Isp efficiency. Numerical schlieren images and particle traces have been used to further understand the physical phenomena behind several of the statistically significant results.

STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative

PubMed Central

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-01-01

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. PMID:25074480

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

Data Model Performance in Data Warehousing

NASA Astrophysics Data System (ADS)

Rorimpandey, G. C.; Sangkop, F. I.; Rantung, V. P.; Zwart, J. P.; Liando, O. E. S.; Mewengkang, A.

2018-02-01

Data Warehouses have increasingly become important in organizations that have large amount of data. It is not a product but a part of a solution for the decision support system in those organizations. Data model is the starting point for designing and developing of data warehouses architectures. Thus, the data model needs stable interfaces and consistent for a longer period of time. The aim of this research is to know which data model in data warehousing has the best performance. The research method is descriptive analysis, which has 3 main tasks, such as data collection and organization, analysis of data and interpretation of data. The result of this research is discussed in a statistic analysis method, represents that there is no statistical difference among data models used in data warehousing. The organization can utilize four data model proposed when designing and developing data warehouse.

The effect of berberine on insulin resistance in women with polycystic ovary syndrome: detailed statistical analysis plan (SAP) for a multicenter randomized controlled trial.

PubMed

Zhang, Ying; Sun, Jin; Zhang, Yun-Jiao; Chai, Qian-Yun; Zhang, Kang; Ma, Hong-Li; Wu, Xiao-Ke; Liu, Jian-Ping

2016-10-21

Although Traditional Chinese Medicine (TCM) has been widely used in clinical settings, a major challenge that remains in TCM is to evaluate its efficacy scientifically. This randomized controlled trial aims to evaluate the efficacy and safety of berberine in the treatment of patients with polycystic ovary syndrome. In order to improve the transparency and research quality of this clinical trial, we prepared this statistical analysis plan (SAP). The trial design, primary and secondary outcomes, and safety outcomes were declared to reduce selection biases in data analysis and result reporting. We specified detailed methods for data management and statistical analyses. Statistics in corresponding tables, listings, and graphs were outlined. The SAP provided more detailed information than trial protocol on data management and statistical analysis methods. Any post hoc analyses could be identified via referring to this SAP, and the possible selection bias and performance bias will be reduced in the trial. This study is registered at ClinicalTrials.gov, NCT01138930 , registered on 7 June 2010.

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

PubMed

Chapman, Phillip L; Seidel, George E

2008-01-01

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

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis.

PubMed

Althuis, Michelle D; Weed, Douglas L; Frankenfeld, Cara L

2014-07-23

Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called 'evidence mapping' can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis

PubMed Central

2014-01-01

Background Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. Methods In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called ‘evidence mapping’ can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Results Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Conclusions Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates. PMID:25055879

A new feedback image encryption scheme based on perturbation with dynamical compound chaotic sequence cipher generator

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Cui, Minggen; Wang, Zhu

2009-07-01

The design of the new compound two-dimensional chaotic function is presented by exploiting two one-dimensional chaotic functions which switch randomly, and the design is used as a chaotic sequence generator which is proved by Devaney's definition proof of chaos. The properties of compound chaotic functions are also proved rigorously. In order to improve the robustness against difference cryptanalysis and produce avalanche effect, a new feedback image encryption scheme is proposed using the new compound chaos by selecting one of the two one-dimensional chaotic functions randomly and a new image pixels method of permutation and substitution is designed in detail by array row and column random controlling based on the compound chaos. The results from entropy analysis, difference analysis, statistical analysis, sequence randomness analysis, cipher sensitivity analysis depending on key and plaintext have proven that the compound chaotic sequence cipher can resist cryptanalytic, statistical and brute-force attacks, and especially it accelerates encryption speed, and achieves higher level of security. By the dynamical compound chaos and perturbation technology, the paper solves the problem of computer low precision of one-dimensional chaotic function.

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

NASA Astrophysics Data System (ADS)

Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

2015-03-01

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

Practicality of Elementary Statistics Module Based on CTL Completed by Instructions on Using Software R

NASA Astrophysics Data System (ADS)

Delyana, H.; Rismen, S.; Handayani, S.

2018-04-01

This research is a development research using 4-D design model (define, design, develop, and disseminate). The results of the define stage are analyzed for the needs of the following; Syllabus analysis, textbook analysis, student characteristics analysis and literature analysis. The results of textbook analysis obtained the description that of the two textbooks that must be owned by students also still difficulty in understanding it, the form of presentation also has not facilitated students to be independent in learning to find the concept, textbooks are also not equipped with data processing referrals by using software R. The developed module is considered valid by the experts. Further field trials are conducted to determine the practicality and effectiveness. The trial was conducted to the students of Mathematics Education Study Program of STKIP PGRI which was taken randomly which has not taken Basic Statistics Course that is as many as 4 people. Practical aspects of attention are easy, time efficient, easy to interpret, and equivalence. The practical value in each aspect is 3.7; 3.79, 3.7 and 3.78. Based on the results of the test students considered that the module has been very practical use in learning. This means that the module developed can be used by students in Elementary Statistics learning.

A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry

NASA Astrophysics Data System (ADS)

Yepes-Calderon, Fernando; Brun, Caroline; Sant, Nishita; Thompson, Paul; Lepore, Natasha

2015-01-01

Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA's multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.

Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis

ERIC Educational Resources Information Center

Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A.

2011-01-01

In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…

Trial Sequential Methods for Meta-Analysis

ERIC Educational Resources Information Center

Kulinskaya, Elena; Wood, John

2014-01-01

Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…

An Intuitive Graphical Approach to Understanding the Split-Plot Experiment

ERIC Educational Resources Information Center

Robinson, Timothy J.; Brenneman, William A.; Myers, William R.

2009-01-01

While split-plot designs have received considerable attention in the literature over the past decade, there seems to be a general lack of intuitive understanding of the error structure of these designs and the resulting statistical analysis. Typically, students learn the proper error terms for testing factors of a split-plot design via "expected…

Color Charts, Esthetics, and Subjective Randomness

ERIC Educational Resources Information Center

Sanderson, Yasmine B.

2012-01-01

Color charts, or grids of evenly spaced multicolored dots or squares, appear in the work of modern artists and designers. Often the artist/designer distributes the many colors in a way that could be described as "random," that is, without an obvious pattern. We conduct a statistical analysis of 125 "random-looking" art and design color charts and…

[New design of the Health Survey of Catalonia (Spain, 2010-2014): a step forward in health planning and evaluation].

PubMed

Alcañiz-Zanón, Manuela; Mompart-Penina, Anna; Guillén-Estany, Montserrat; Medina-Bustos, Antonia; Aragay-Barbany, Josep M; Brugulat-Guiteras, Pilar; Tresserras-Gaju, Ricard

2014-01-01

This article presents the genesis of the Health Survey of Catalonia (Spain, 2010-2014) with its semiannual subsamples and explains the basic characteristics of its multistage sampling design. In comparison with previous surveys, the organizational advantages of this new statistical operation include rapid data availability and the ability to continuously monitor the population. The main benefits are timeliness in the production of indicators and the possibility of introducing new topics through the supplemental questionnaire as a function of needs. Limitations consist of the complexity of the sample design and the lack of longitudinal follow-up of the sample. Suitable sampling weights for each specific subsample are necessary for any statistical analysis of micro-data. Accuracy in the analysis of territorial disaggregation or population subgroups increases if annual samples are accumulated. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

SimHap GUI: an intuitive graphical user interface for genetic association analysis.

PubMed

Carter, Kim W; McCaskie, Pamela A; Palmer, Lyle J

2008-12-25

Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.

Treated cabin acoustic prediction using statistical energy analysis

NASA Technical Reports Server (NTRS)

Yoerkie, Charles A.; Ingraham, Steven T.; Moore, James A.

1987-01-01

The application of statistical energy analysis (SEA) to the modeling and design of helicopter cabin interior noise control treatment is demonstrated. The information presented here is obtained from work sponsored at NASA Langley for the development of analytic modeling techniques and the basic understanding of cabin noise. Utility and executive interior models are developed directly from existing S-76 aircraft designs. The relative importance of panel transmission loss (TL), acoustic leakage, and absorption to the control of cabin noise is shown using the SEA modeling parameters. It is shown that the major cabin noise improvement below 1000 Hz comes from increased panel TL, while above 1000 Hz it comes from reduced acoustic leakage and increased absorption in the cabin and overhead cavities.

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Holland, R. L.

1981-01-01

Spacecraft acceleration resulting from firings of vernier control system thrusters is an important consideration in the design, planning, execution and post-flight analysis of laboratory experiments in space. In particular, scientists and technologists involved with the development of experiments to be performed in space in many instances required statistical information on the magnitude and rate of occurrence of spacecraft accelerations. Typically, these accelerations are stochastic in nature, so that it is useful to characterize these accelerations in statistical terms. Statistics of spacecraft accelerations are summarized.

The 1985 Army Experience Survey. Data Sourcebook and User’s Manual

DTIC Science & Technology

1986-01-01

on the survey data file produced for the 1985 AES.- 4 The survey data are available in Operating System (OS) as well as Statistical Analysis System ...version of the survey data files was produced using the Statistical Analysis System (SASJ. The survey data were also produced in Operating System (OS...impacts upon future enlistments. In order iThe OS data file was designed to make the survey data accessible on any IBM-compatible computer system . 3 N’ to

EBSCO's Usage Consolidation Attempts to Streamline Gathering, Storage, and Reporting of Usage Statistics

ERIC Educational Resources Information Center

Remy, Charlie

2012-01-01

This paper provides an overview of EBSCO's new Usage Consolidation product designed to streamline the harvesting, storage, and analysis of usage statistics from electronic resources. Strengths and weaknesses of the product are discussed as well as an early beta partner's experience. In the current atmosphere of flat or declining budgets, libraries…

An Automated Statistical Process Control Study of Inline Mixing Using Spectrophotometric Detection

ERIC Educational Resources Information Center

Dickey, Michael D.; Stewart, Michael D.; Willson, C. Grant

2006-01-01

An experiment is described, which is designed for a junior-level chemical engineering "fundamentals of measurements and data analysis" course, where students are introduced to the concept of statistical process control (SPC) through a simple inline mixing experiment. The students learn how to create and analyze control charts in an effort to…

Three Dimensional CFD Analysis of the GTX Combustor

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.; Bond, R. B.; Edwards, J. R.

2002-01-01

The annular combustor geometry of a combined-cycle engine has been analyzed with three-dimensional computational fluid dynamics. Both subsonic combustion and supersonic combustion flowfields have been simulated. The subsonic combustion analysis was executed in conjunction with a direct-connect test rig. Two cold-flow and one hot-flow results are presented. The simulations compare favorably with the test data for the two cold flow calculations; the hot-flow data was not yet available. The hot-flow simulation indicates that the conventional ejector-ramjet cycle would not provide adequate mixing at the conditions tested. The supersonic combustion ramjet flowfield was simulated with frozen chemistry model. A five-parameter test matrix was specified, according to statistical design-of-experiments theory. Twenty-seven separate simulations were used to assemble surrogate models for combustor mixing efficiency and total pressure recovery. ScramJet injector design parameters (injector angle, location, and fuel split) as well as mission variables (total fuel massflow and freestream Mach number) were included in the analysis. A promising injector design has been identified that provides good mixing characteristics with low total pressure losses. The surrogate models can be used to develop performance maps of different injector designs. Several complex three-way variable interactions appear within the dataset that are not adequately resolved with the current statistical analysis.

A Course Model for Teaching Research Evaluation in Colleges of Pharmacy.

ERIC Educational Resources Information Center

Draugalis, JoLaine R.; Slack, Marion K.

1992-01-01

A University of Arizona undergraduate pharmacy course designed to develop student skills in evaluation of research has five parts: introduction to the scientific method; statistical techniques/data analysis review; research design; fundamentals of clinical studies; and practical applications. Prerequisites include biostatistics and drug…

A statistical model of operational impacts on the framework of the bridge crane

NASA Astrophysics Data System (ADS)

Antsev, V. Yu; Tolokonnikov, A. S.; Gorynin, A. D.; Reutov, A. A.

2017-02-01

The technical regulations of the Customs Union demands implementation of the risk analysis of the bridge cranes operation at their design stage. The statistical model has been developed for performance of random calculations of risks, allowing us to model possible operational influences on the bridge crane metal structure in their various combination. The statistical model is practically actualized in the software product automated calculation of risks of failure occurrence of bridge cranes.

Nonindependence and sensitivity analyses in ecological and evolutionary meta-analyses.

PubMed

Noble, Daniel W A; Lagisz, Malgorzata; O'dea, Rose E; Nakagawa, Shinichi

2017-05-01

Meta-analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta-analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta-analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta-analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta-analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta-analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta-analyses, leading to greater transparency and more robust conclusions. © 2017 John Wiley & Sons Ltd.

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)

Regulatory considerations in the design of comparative observational studies using propensity scores.

PubMed

Yue, Lilly Q

2012-01-01

In the evaluation of medical products, including drugs, biological products, and medical devices, comparative observational studies could play an important role when properly conducted randomized, well-controlled clinical trials are infeasible due to ethical or practical reasons. However, various biases could be introduced at every stage and into every aspect of the observational study, and consequently the interpretation of the resulting statistical inference would be of concern. While there do exist statistical techniques for addressing some of the challenging issues, often based on propensity score methodology, these statistical tools probably have not been as widely employed in prospectively designing observational studies as they should be. There are also times when they are implemented in an unscientific manner, such as performing propensity score model selection for a dataset involving outcome data in the same dataset, so that the integrity of observational study design and the interpretability of outcome analysis results could be compromised. In this paper, regulatory considerations on prospective study design using propensity scores are shared and illustrated with hypothetical examples.

On-Line Analysis of Southern FIA Data

Treesearch

Michael P. Spinney; Paul C. Van Deusen; Francis A. Roesch

2006-01-01

The Southern On-Line Estimator (SOLE) is a web-based FIA database analysis tool designed with an emphasis on modularity. The Java-based user interface is simple and intuitive to use and the R-based analysis engine is fast and stable. Each component of the program (data retrieval, statistical analysis and output) can be individually modified to accommodate major...

Statistical process management: An essential element of quality improvement

NASA Astrophysics Data System (ADS)

Buckner, M. R.

Successful quality improvement requires a balanced program involving the three elements that control quality: organization, people and technology. The focus of the SPC/SPM User's Group is to advance the technology component of Total Quality by networking within the Group and by providing an outreach within Westinghouse to foster the appropriate use of statistic techniques to achieve Total Quality. SPM encompasses the disciplines by which a process is measured against its intrinsic design capability, in the face of measurement noise and other obscuring variability. SPM tools facilitate decisions about the process that generated the data. SPM deals typically with manufacturing processes, but with some flexibility of definition and technique it accommodates many administrative processes as well. The techniques of SPM are those of Statistical Process Control, Statistical Quality Control, Measurement Control, and Experimental Design. In addition, techniques such as job and task analysis, and concurrent engineering are important elements of systematic planning and analysis that are needed early in the design process to ensure success. The SPC/SPM User's Group is endeavoring to achieve its objectives by sharing successes that have occurred within the member's own Westinghouse department as well as within other US and foreign industry. In addition, failures are reviewed to establish lessons learned in order to improve future applications. In broader terms, the Group is interested in making SPM the accepted way of doing business within Westinghouse.

Computer experimental analysis of the CHP performance of a 100 kW e SOFC Field Unit by a factorial design

NASA Astrophysics Data System (ADS)

Calì, M.; Santarelli, M. G. L.; Leone, P.

Gas Turbine Technologies (GTT) and Politecnico di Torino, both located in Torino (Italy), have been involved in the design and installation of a SOFC laboratory in order to analyse the operation, in cogenerative configuration, of the CHP 100 kW e SOFC Field Unit, built by Siemens-Westinghouse Power Corporation (SWPC), which is at present (May 2005) starting its operation and which will supply electric and thermal power to the GTT factory. In order to take the better advantage from the analysis of the on-site operation, and especially to correctly design the scheduled experimental tests on the system, we developed a mathematical model and run a simulated experimental campaign, applying a rigorous statistical approach to the analysis of the results. The aim of this work is the computer experimental analysis, through a statistical methodology (2 k factorial experiments), of the CHP 100 performance. First, the mathematical model has been calibrated with the results acquired during the first CHP100 demonstration at EDB/ELSAM in Westerwoort. After, the simulated tests have been performed in the form of computer experimental session, and the measurement uncertainties have been simulated with perturbation imposed to the model independent variables. The statistical methodology used for the computer experimental analysis is the factorial design (Yates' Technique): using the ANOVA technique the effect of the main independent variables (air utilization factor U ox, fuel utilization factor U F, internal fuel and air preheating and anodic recycling flow rate) has been investigated in a rigorous manner. Analysis accounts for the effects of parameters on stack electric power, thermal recovered power, single cell voltage, cell operative temperature, consumed fuel flow and steam to carbon ratio. Each main effect and interaction effect of parameters is shown with particular attention on generated electric power and stack heat recovered.

rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

PubMed

Shen, Shihao; Park, Juw Won; Lu, Zhi-xiang; Lin, Lan; Henry, Michael D; Wu, Ying Nian; Zhou, Qing; Xing, Yi

2014-12-23

Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.

Guidelines for Genome-Scale Analysis of Biological Rhythms.

PubMed

Hughes, Michael E; Abruzzi, Katherine C; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M Fernanda; Chen, Zheng; Chiu, Joanna C; Cox, Juergen; Crowell, Alexander M; DeBruyne, Jason P; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J; Duffield, Giles E; Dunlap, Jay C; Eckel-Mahan, Kristin; Esser, Karyn A; FitzGerald, Garret A; Forger, Daniel B; Francey, Lauren J; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H; Herzel, Hanspeter; Herzog, Erik D; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J; Hurley, Jennifer M; de la Iglesia, Horacio O; Johnson, Carl; Kay, Steve A; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A; Li, Jiajia; Li, Xiaodong; Liu, Andrew C; Loros, Jennifer J; Martino, Tami A; Menet, Jerome S; Merrow, Martha; Millar, Andrew J; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N; Olmedo, Maria; Nusinow, Dmitri A; Ptáček, Louis J; Rand, David; Reddy, Akhilesh B; Robles, Maria S; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D; Rund, Samuel S C; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J; Storch, Kai-Florian; Takahashi, Joseph S; Ueda, Hiroki R; Wang, Han; Weitz, Charles; Westermark, Pål O; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B

2017-10-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Guidelines for Genome-Scale Analysis of Biological Rhythms

PubMed Central

Hughes, Michael E.; Abruzzi, Katherine C.; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M. Fernanda; Chen, Zheng; Chiu, Joanna C.; Cox, Juergen; Crowell, Alexander M.; DeBruyne, Jason P.; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J.; Duffield, Giles E.; Dunlap, Jay C.; Eckel-Mahan, Kristin; Esser, Karyn A.; FitzGerald, Garret A.; Forger, Daniel B.; Francey, Lauren J.; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S.; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H.; Herzel, Hanspeter; Herzog, Erik D.; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J.; Hurley, Jennifer M.; de la Iglesia, Horacio O.; Johnson, Carl; Kay, Steve A.; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A.; Li, Jiajia; Li, Xiaodong; Liu, Andrew C.; Loros, Jennifer J.; Martino, Tami A.; Menet, Jerome S.; Merrow, Martha; Millar, Andrew J.; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N.; Olmedo, Maria; Nusinow, Dmitri A.; Ptáček, Louis J.; Rand, David; Reddy, Akhilesh B.; Robles, Maria S.; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D.; Rund, Samuel S.C.; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J.; Storch, Kai-Florian; Takahashi, Joseph S.; Ueda, Hiroki R.; Wang, Han; Weitz, Charles; Westermark, Pål O.; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B.

2017-01-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them. PMID:29098954

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

PubMed Central

Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-01-01

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

Design of off-statistics axial-flow fans by means of vortex law optimization

NASA Astrophysics Data System (ADS)

Lazari, Andrea; Cattanei, Andrea

2014-12-01

Off-statistics input data sets are common in axial-flow fans design and may easily result in some violation of the requirements of a good aerodynamic blade design. In order to circumvent this problem, in the present paper, a solution to the radial equilibrium equation is found which minimizes the outlet kinetic energy and fulfills the aerodynamic constraints, thus ensuring that the resulting blade has acceptable aerodynamic performance. The presented method is based on the optimization of a three-parameters vortex law and of the meridional channel size. The aerodynamic quantities to be employed as constraints are individuated and their suitable ranges of variation are proposed. The method is validated by means of a design with critical input data values and CFD analysis. Then, by means of systematic computations with different input data sets, some correlations and charts are obtained which are analogous to classic correlations based on statistical investigations on existing machines. Such new correlations help size a fan of given characteristics as well as study the feasibility of a given design.

Recommendations for the Design and Analysis of Treatment Trials for Alcohol Use Disorders.

PubMed

Witkiewitz, Katie; Finney, John W; Harris, Alex H S; Kivlahan, Daniel R; Kranzler, Henry R

2015-09-01

Over the past 60 years, the view that "alcoholism" is a disease for which the only acceptable goal of treatment is abstinence has given way to the recognition that alcohol use disorders (AUDs) occur on a continuum of severity, for which a variety of treatment options are appropriate. However, because the available treatments for AUDs are not effective for everyone, more research is needed to develop novel and more efficacious treatments to address the range of AUD severity in diverse populations. Here we offer recommendations for the design and analysis of alcohol treatment trials, with a specific focus on the careful conduct of randomized clinical trials of medications and nonpharmacological interventions for AUDs. This paper provides a narrative review of the quality of published clinical trials and recommendations for the optimal design and analysis of treatment trials for AUDs. Despite considerable improvements in the design of alcohol clinical trials over the past 2 decades, many studies of AUD treatments have used faulty design features and statistical methods that are known to produce biased estimates of treatment efficacy. The published statistical and methodological literatures provide clear guidance on methods to improve clinical trial design and analysis. Consistent use of state-of-the-art design features and analytic approaches will enhance the internal and external validity of treatment trials for AUDs across the spectrum of severity. The ultimate result of this attention to methodological rigor is that better treatment options will be identified for patients with an AUD. Copyright © 2015 by the Research Society on Alcoholism.

78 FR 45194 - General Electric Company; Analysis of Proposed Agreement Containing Consent Order To Aid Public...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-26

... industries throughout the globe. GE's aviation segment, among other things, designs and manufactures jet... anticompetitive effects of the proposed transaction. The design and production of an aircraft engine, along with... information such as costs, sales statistics, inventories, formulas, patterns, devices, manufacturing processes...

Television broadcast relay system, volume 2

NASA Technical Reports Server (NTRS)

Graf, E. R.

1972-01-01

A statistical analysis of propagation characteristics at 12 GHz for the design of a worldwide communication satellite system is reported. High power spaceborne TV transmitter design and the development of a low cost, low noise ground receiver for domestic reception are considered most important for implementation of a TVBS system.

Statistical competencies for medical research learners: What is fundamental?

PubMed

Enders, Felicity T; Lindsell, Christopher J; Welty, Leah J; Benn, Emma K T; Perkins, Susan M; Mayo, Matthew S; Rahbar, Mohammad H; Kidwell, Kelley M; Thurston, Sally W; Spratt, Heidi; Grambow, Steven C; Larson, Joseph; Carter, Rickey E; Pollock, Brad H; Oster, Robert A

2017-06-01

It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from 'fundamental' (necessary for all) to 'specialized' (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized. We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by 'fundamental' and 'specialized.' There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one's own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%). We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.

Design Oriented Structural Modeling for Airplane Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Livne, Eli

1999-01-01

The main goal for research conducted with the support of this grant was to develop design oriented structural optimization methods for the conceptual design of airplanes. Traditionally in conceptual design airframe weight is estimated based on statistical equations developed over years of fitting airplane weight data in data bases of similar existing air- planes. Utilization of such regression equations for the design of new airplanes can be justified only if the new air-planes use structural technology similar to the technology on the airplanes in those weight data bases. If any new structural technology is to be pursued or any new unconventional configurations designed the statistical weight equations cannot be used. In such cases any structural weight estimation must be based on rigorous "physics based" structural analysis and optimization of the airframes under consideration. Work under this grant progressed to explore airframe design-oriented structural optimization techniques along two lines of research: methods based on "fast" design oriented finite element technology and methods based on equivalent plate / equivalent shell models of airframes, in which the vehicle is modelled as an assembly of plate and shell components, each simulating a lifting surface or nacelle / fuselage pieces. Since response to changes in geometry are essential in conceptual design of airplanes, as well as the capability to optimize the shape itself, research supported by this grant sought to develop efficient techniques for parametrization of airplane shape and sensitivity analysis with respect to shape design variables. Towards the end of the grant period a prototype automated structural analysis code designed to work with the NASA Aircraft Synthesis conceptual design code ACS= was delivered to NASA Ames.

Raising the bar for reproducible science at the U.S. Environmental Protection Agency Office of Research and Development.

PubMed

George, Barbara Jane; Sobus, Jon R; Phelps, Lara P; Rashleigh, Brenda; Simmons, Jane Ellen; Hines, Ronald N

2015-05-01

Considerable concern has been raised regarding research reproducibility both within and outside the scientific community. Several factors possibly contribute to a lack of reproducibility, including a failure to adequately employ statistical considerations during study design, bias in sample selection or subject recruitment, errors in developing data inclusion/exclusion criteria, and flawed statistical analysis. To address some of these issues, several publishers have developed checklists that authors must complete. Others have either enhanced statistical expertise on existing editorial boards, or formed distinct statistics editorial boards. Although the U.S. Environmental Protection Agency, Office of Research and Development, already has a strong Quality Assurance Program, an initiative was undertaken to further strengthen statistics consideration and other factors in study design and also to ensure these same factors are evaluated during the review and approval of study protocols. To raise awareness of the importance of statistical issues and provide a forum for robust discussion, a Community of Practice for Statistics was formed in January 2014. In addition, three working groups were established to develop a series of questions or criteria that should be considered when designing or reviewing experimental, observational, or modeling focused research. This article describes the process used to develop these study design guidance documents, their contents, how they are being employed by the Agency's research enterprise, and expected benefits to Agency science. The process and guidance documents presented here may be of utility for any research enterprise interested in enhancing the reproducibility of its science. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.

Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation

NASA Technical Reports Server (NTRS)

DePriest, Douglas; Morgan, Carolyn

2003-01-01

The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.

Improved Statistics for Genome-Wide Interaction Analysis

PubMed Central

Ueki, Masao; Cordell, Heather J.

2012-01-01

Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new “joint effects” statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al.'s originally-proposed statistics, on account of the inflated error rate that can result. PMID:22496670

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

PubMed Central

Calcagno, Cristina; Coppo, Mario

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed. PMID:25050327

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

PubMed

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

Statistical analysis of nonmonotonic dose-response relationships: research design and analysis of nasal cell proliferation in rats exposed to formaldehyde.

PubMed

Gaylor, David W; Lutz, Werner K; Conolly, Rory B

2004-01-01

Statistical analyses of nonmonotonic dose-response curves are proposed, experimental designs to detect low-dose effects of J-shaped curves are suggested, and sample sizes are provided. For quantal data such as cancer incidence rates, much larger numbers of animals are required than for continuous data such as biomarker measurements. For example, 155 animals per dose group are required to have at least an 80% chance of detecting a decrease from a 20% incidence in controls to an incidence of 10% at a low dose. For a continuous measurement, only 14 animals per group are required to have at least an 80% chance of detecting a change of the mean by one standard deviation of the control group. Experimental designs based on three dose groups plus controls are discussed to detect nonmonotonicity or to estimate the zero equivalent dose (ZED), i.e., the dose that produces a response equal to the average response in the controls. Cell proliferation data in the nasal respiratory epithelium of rats exposed to formaldehyde by inhalation are used to illustrate the statistical procedures. Statistically significant departures from a monotonic dose response were obtained for time-weighted average labeling indices with an estimated ZED at a formaldehyde dose of 5.4 ppm, with a lower 95% confidence limit of 2.7 ppm. It is concluded that demonstration of a statistically significant bi-phasic dose-response curve, together with estimation of the resulting ZED, could serve as a point-of departure in establishing a reference dose for low-dose risk assessment.

Computational tools for multi-linked flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.; Brubaker, Thomas A.; Shults, James R.

1990-01-01

A software module which designs and tests controllers and filters in Kalman Estimator form, based on a polynomial state-space model is discussed. The user-friendly program employs an interactive graphics approach to simplify the design process. A variety of input methods are provided to test the effectiveness of the estimator. Utilities are provided which address important issues in filter design such as graphical analysis, statistical analysis, and calculation time. The program also provides the user with the ability to save filter parameters, inputs, and outputs for future use.

Comparative Evaluation of Stress Distribution in Experimentally Designed Nickel-titanium Rotary Files with Varying Cross Sections: A Finite Element Analysis.

PubMed

Basheer Ahamed, Shadir Bughari; Vanajassun, Purushothaman Pranav; Rajkumar, Kothandaraman; Mahalaxmi, Sekar

2018-04-01

Single cross-sectional nickel-titanium (NiTi) rotary instruments during continuous rotations are subjected to constant and variable stresses depending on the canal anatomy. This study was intended to create 2 new experimental, theoretic single-file designs with combinations of triple U (TU), triangle (TR), and convex triangle (CT) cross sections and to compare their bending stresses in simulated root canals with a single cross-sectional instrument using finite element analysis. A 3-dimensional model of the simulated root canal with 45° curvature and NiTi files with 5 cross-sectional designs were created using Pro/ENGINEER Wildfire 4.0 software (PTC Inc, Needham, MA) and ANSYS software (version 17; ANSYS, Inc, Canonsburg, PA) for finite element analysis. The NiTi files of 3 groups had single cross-sectional shapes of CT, TR, and TU designs, and 2 experimental groups had a CT, TR, and TU (CTU) design and a TU, TR, and CT (UTC) design. The file was rotated in simulated root canals to analyze the bending stress, and the von Mises stress value for every file was recorded in MPa. Statistical analysis was performed using the Kruskal-Wallis test and the Bonferroni-adjusted Mann-Whitney test for multiple pair-wise comparison with a P value <.05 (95 %). The maximum bending stress of the rotary file was observed in the apical third of the CT design, whereas comparatively less stress was recorded in the CTU design. The TU and TR designs showed a similar stress pattern at the curvature, whereas the UTC design showed greater stress in the apical and middle thirds of the file in curved canals. All the file designs showed a statistically significant difference. The CTU designed instruments showed the least bending stress on a 45° angulated simulated root canal when compared with all the other tested designs. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

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

Person Fit Analysis in Computerized Adaptive Testing Using Tests for a Change Point

ERIC Educational Resources Information Center

Sinharay, Sandip

2016-01-01

Meijer and van Krimpen-Stoop noted that the number of person-fit statistics (PFSs) that have been designed for computerized adaptive tests (CATs) is relatively modest. This article partially addresses that concern by suggesting three new PFSs for CATs. The statistics are based on tests for a change point and can be used to detect an abrupt change…

Astrophysics

Science.gov Websites

, microquasars, neutron stars, pulsars, black holes astro-ph.IM - Instrumentation and Methods for Astrophysics Astrophysics. Methods for data analysis, statistical methods. Software, database design astro-ph.SR - Solar and

Efficacy and Physicochemical Evaluation of an Optimized Semisolid Formulation of Povidone Iodine Proposed by Extreme Vertices Statistical Design; a Practical Approach

PubMed Central

Lotfipour, Farzaneh; Valizadeh, Hadi; Shademan, Shahin; Monajjemzadeh, Farnaz

2015-01-01

One of the most significant issues in pharmaceutical industries, prior to commercialization of a pharmaceutical preparation is the "preformulation" stage. However, far too attention has been paid to verification of the software assisted statistical designs in preformulation studies. The main aim of this study was to report a step by step preformulation approach for a semisolid preparation based on a statistical mixture design and to verify the predictions made by the software with an in-vitro efficacy bioassay test. Extreme vertices mixture design (4 factors, 4 levels) was applied for preformulation of a semisolid Povidone Iodine preparation as Water removable ointment using different PolyEthylenGlycoles. Software Assisted (Minitab) analysis was then performed using four practically assessed response values including; Available iodine, viscosity (N index and yield value) and water absorption capacity. Subsequently mixture analysis was performed and finally, an optimized formulation was proposed. The efficacy of this formulation was bio-assayed using microbial tests in-vitro and MIC values were calculated for Escherichia coli, pseudomonaaeruginosa, staphylococcus aureus and Candida albicans. Results indicated the acceptable conformity of the measured responses. Thus, it can be concluded that the proposed design had an adequate power to predict the responses in practice. Stability studies, proved no significant change during the one year study for the optimized formulation. Efficacy was eligible on all tested species and in the case of staphylococcus aureus; the prepared semisolid formulation was even more effective. PMID:26664368

Evaluating the quality of a cell counting measurement process via a dilution series experimental design.

PubMed

Sarkar, Sumona; Lund, Steven P; Vyzasatya, Ravi; Vanguri, Padmavathy; Elliott, John T; Plant, Anne L; Lin-Gibson, Sheng

2017-12-01

Cell counting measurements are critical in the research, development and manufacturing of cell-based products, yet determining cell quantity with accuracy and precision remains a challenge. Validating and evaluating a cell counting measurement process can be difficult because of the lack of appropriate reference material. Here we describe an experimental design and statistical analysis approach to evaluate the quality of a cell counting measurement process in the absence of appropriate reference materials or reference methods. The experimental design is based on a dilution series study with replicate samples and observations as well as measurement process controls. The statistical analysis evaluates the precision and proportionality of the cell counting measurement process and can be used to compare the quality of two or more counting methods. As an illustration of this approach, cell counting measurement processes (automated and manual methods) were compared for a human mesenchymal stromal cell (hMSC) preparation. For the hMSC preparation investigated, results indicated that the automated method performed better than the manual counting methods in terms of precision and proportionality. By conducting well controlled dilution series experimental designs coupled with appropriate statistical analysis, quantitative indicators of repeatability and proportionality can be calculated to provide an assessment of cell counting measurement quality. This approach does not rely on the use of a reference material or comparison to "gold standard" methods known to have limited assurance of accuracy and precision. The approach presented here may help the selection, optimization, and/or validation of a cell counting measurement process. Published by Elsevier Inc.

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

PubMed

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

2009-03-01

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

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Holland, R. L.

1983-01-01

Spacecraft acceleration resulting from firings of vernier control system thrusters is an important consideration in the design, planning, execution and post-flight analysis of laboratory experiments in space. In particular, scientists and technologists involved with the development of experiments to be performed in space in many instances required statistical information on the magnitude and rate of occurrence of spacecraft accelerations. Typically, these accelerations are stochastic in nature, so that it is useful to characterize these accelerations in statistical terms. Statistics of spacecraft accelerations are summarized. Previously announced in STAR as N82-12127

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2013-12-06

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

Cognition, comprehension and application of biostatistics in research by Indian postgraduate students in periodontics.

PubMed

Swetha, Jonnalagadda Laxmi; Arpita, Ramisetti; Srikanth, Chintalapani; Nutalapati, Rajasekhar

2014-01-01

Biostatistics is an integral part of research protocols. In any field of inquiry or investigation, data obtained is subsequently classified, analyzed and tested for accuracy by statistical methods. Statistical analysis of collected data, thus, forms the basis for all evidence-based conclusions. The aim of this study is to evaluate the cognition, comprehension and application of biostatistics in research among post graduate students in Periodontics, in India. A total of 391 post graduate students registered for a master's course in periodontics at various dental colleges across India were included in the survey. Data regarding the level of knowledge, understanding and its application in design and conduct of the research protocol was collected using a dichotomous questionnaire. A descriptive statistics was used for data analysis. Nearly 79.2% students were aware of the importance of biostatistics in research, 55-65% were familiar with MS-EXCEL spreadsheet for graphical representation of data and with the statistical softwares available on the internet, 26.0% had biostatistics as mandatory subject in their curriculum, 9.5% tried to perform statistical analysis on their own while 3.0% were successful in performing statistical analysis of their studies on their own. Biostatistics should play a central role in planning, conduct, interim analysis, final analysis and reporting of periodontal research especially by the postgraduate students. Indian postgraduate students in periodontics are aware of the importance of biostatistics in research but the level of understanding and application is still basic and needs to be addressed.

SimHap GUI: An intuitive graphical user interface for genetic association analysis

PubMed Central

Carter, Kim W; McCaskie, Pamela A; Palmer, Lyle J

2008-01-01

Background Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. Results We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. Conclusion SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis. PMID:19109877

Probabilistic/Fracture-Mechanics Model For Service Life

NASA Technical Reports Server (NTRS)

Watkins, T., Jr.; Annis, C. G., Jr.

1991-01-01

Computer program makes probabilistic estimates of lifetime of engine and components thereof. Developed to fill need for more accurate life-assessment technique that avoids errors in estimated lives and provides for statistical assessment of levels of risk created by engineering decisions in designing system. Implements mathematical model combining techniques of statistics, fatigue, fracture mechanics, nondestructive analysis, life-cycle cost analysis, and management of engine parts. Used to investigate effects of such engine-component life-controlling parameters as return-to-service intervals, stresses, capabilities for nondestructive evaluation, and qualities of materials.

Index of Selected Publications Through December 1983,

DTIC Science & Technology

1984-03-01

substantiating methodology , and is designed mainly for * readers with a professional interest in the subject but do * not have a primary responsibility in that...Navy in postwar American security policy -- computer subroutines - CRC 20 H 1052 experimental design techniques, computer North Atlantic-Norwegian...statistical tion and Congestion, With an Example from Southern experimental design technique aids the analysis California, 27 pp., Jan 1971, AD 719 906 of

Engineering Design Handbook. Army Weapon Systems Analysis. Part 2

DTIC Science & Technology

1979-10-01

EXPERIMENTAL DESIGN ............................... ............ 41-3 41-5 RESULTS OF THE ASARS lIX SIMULATIONS ........................... 41-4 41-6 LATIN...sciences and human factors engineering fields utilizing experimental methodology and multi-variable statistical techniques drawn from experimental ...randomly to grenades for the test design . The nine experimental types of hand grenades (first’ nine in Table 33-2) had a "pip" on their spherical

Modeling and Recovery of Iron (Fe) from Red Mud by Coal Reduction

NASA Astrophysics Data System (ADS)

Zhao, Xiancong; Li, Hongxu; Wang, Lei; Zhang, Lifeng

Recovery of Fe from red mud has been studied using statistically designed experiments. The effects of three factors, namely: reduction temperature, reduction time and proportion of additive on recovery of Fe have been investigated. Experiments have been carried out using orthogonal central composite design and factorial design methods. A model has been obtained through variance analysis at 92.5% confidence level.

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

PubMed

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

2018-01-16

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

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

PubMed Central

Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

PubMed

Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

Return to Our Roots: Raising Radishes to Teach Experimental Design. Methods and Techniques.

ERIC Educational Resources Information Center

Stallings, William M.

1993-01-01

Reviews research in teaching applied statistics. Concludes that students should analyze data from studies they have designed and conducted. Describes an activity in which students study germination and growth of radish seeds. Includes a table providing student instructions for both the experimental procedure and data analysis. (CFR)

Toward User Interfaces and Data Visualization Criteria for Learning Design of Digital Textbooks

ERIC Educational Resources Information Center

Railean, Elena

2014-01-01

User interface and data visualisation criteria are central issues in digital textbooks design. However, when applying mathematical modelling of learning process to the analysis of the possible solutions, it could be observed that results differ. Mathematical learning views cognition in on the base on statistics and probability theory, graph…

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

ERIC Educational Resources Information Center

Hancock, Gregory R.; McNeish, Daniel M.

2017-01-01

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

Understanding the behavioral linkages needed for designing effective interventions to increase fruit and vegetable intake in diverse populations

USDA-ARS?s Scientific Manuscript database

The design of interventions to increase fruit and vegetable consumption in a population (e.g. all men, all elementary school students) requires an underlying model that organizes the relevant literatures and provides an audience. The mediating-moderating variable model is a statistical analysis tech...

The Hard but Necessary Task of Gathering Order-One Effect Size Indices in Meta-Analysis

ERIC Educational Resources Information Center

Ortego, Carmen; Botella, Juan

2010-01-01

Meta-analysis of studies with two groups and two measurement occasions must employ order-one effect size indices to represent study outcomes. Especially with non-random assignment, non-equivalent control group designs, a statistical analysis restricted to post-treatment scores can lead to severely biased conclusions. The 109 primary studies…

Family Early Literacy Practices Questionnaire: A Validation Study for a Spanish-Speaking Population

ERIC Educational Resources Information Center

Lewis, Kandia

2012-01-01

The purpose of the current study was to evaluate the psychometric validity of a Spanish translated version of a family involvement questionnaire (the FELP) using a mixed-methods design. Thus, statistical analyses (i.e., factor analysis, reliability analysis, and item analysis) and qualitative analyses (i.e., focus group data) were assessed.…

Statistical metrology—measurement and modeling of variation for advanced process development and design rule generation

NASA Astrophysics Data System (ADS)

Boning, Duane S.; Chung, James E.

1998-11-01

Advanced process technology will require more detailed understanding and tighter control of variation in devices and interconnects. The purpose of statistical metrology is to provide methods to measure and characterize variation, to model systematic and random components of that variation, and to understand the impact of variation on both yield and performance of advanced circuits. Of particular concern are spatial or pattern-dependencies within individual chips; such systematic variation within the chip can have a much larger impact on performance than wafer-level random variation. Statistical metrology methods will play an important role in the creation of design rules for advanced technologies. For example, a key issue in multilayer interconnect is the uniformity of interlevel dielectric (ILD) thickness within the chip. For the case of ILD thickness, we describe phases of statistical metrology development and application to understanding and modeling thickness variation arising from chemical-mechanical polishing (CMP). These phases include screening experiments including design of test structures and test masks to gather electrical or optical data, techniques for statistical decomposition and analysis of the data, and approaches to calibrating empirical and physical variation models. These models can be integrated with circuit CAD tools to evaluate different process integration or design rule strategies. One focus for the generation of interconnect design rules are guidelines for the use of "dummy fill" or "metal fill" to improve the uniformity of underlying metal density and thus improve the uniformity of oxide thickness within the die. Trade-offs that can be evaluated via statistical metrology include the improvements to uniformity possible versus the effect of increased capacitance due to additional metal.

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.

Statistical Analysis of CFD Solutions from the Fourth AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.

2010-01-01

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from the U.S., Europe, Asia, and Russia using a variety of grid systems and turbulence models for the June 2009 4th Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was a new subsonic transport model, the Common Research Model, designed using a modern approach for the wing and included a horizontal tail. The fourth workshop focused on the prediction of both absolute and incremental drag levels for wing-body and wing-body-horizontal tail configurations. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with earlier workshops using the statistical framework.

No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.

PubMed

Li, Xuelong; Guo, Qun; Lu, Xiaoqiang

2016-05-13

It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.

Characteristics of At-Risk Students in NELS:88. National Education Longitudinal Study of 1988. Statistical Analysis Report. Contractor Report. NCES 92-042

ERIC Educational Resources Information Center

Kaufman, Phillip; Bradbury, Denise

1992-01-01

The National Education Longitudinal Study of 1988 (NELS:88) is a large-scale, national longitudinal study designed and sponsored by the National Center for Education Statistics (NCES), with support from other government agencies. Beginning in the spring of 1988 with a cohort of eighth graders (25,000) attending public and private schools across…

Content Analysis of Chemistry Curricula in Germany Case Study: Chemical Reactions

ERIC Educational Resources Information Center

Timofte, Roxana S.

2015-01-01

Curriculum-assessment alignment is a well known foundation for good practice in educational assessment, for items' curricular validity purposes. Nowadays instruments are designed to measure pupils' competencies in one or more areas of competence. Sub-competence areas could be defined theoretically and statistical analysis of empirical data by…

A Comparison of Conjoint Analysis Response Formats

Treesearch

Kevin J. Boyle; Thomas P. Holmes; Mario F. Teisl; Brian Roe

2001-01-01

A split-sample design is used to evaluate the convergent validity of three response formats used in conjoint analysis experiments. WC investigate whether recoding rating data to rankings and choose-one formats, and recoding ranking data to choose one. result in structural models and welfare estimates that are statistically indistinguishable from...

DNA Fingerprinting in a Forensic Teaching Experiment

ERIC Educational Resources Information Center

Wagoner, Stacy A.; Carlson, Kimberly A.

2008-01-01

This article presents an experiment designed to provide students, in a classroom laboratory setting, a hands-on demonstration of the steps used in DNA forensic analysis by performing DNA extraction, DNA fingerprinting, and statistical analysis of the data. This experiment demonstrates how DNA fingerprinting is performed and how long it takes. It…

Cellular Consequences of Telomere Shortening in Histologically Normal Breast Tissues

DTIC Science & Technology

2013-09-01

using the open source, JAVA -based image analysis software package ImageJ (http://rsb.info.nih.gov/ij/) and a custom designed plugin (“Telometer...Tabulated data were stored in a MySQL (http://www.mysql.com) database and viewed through Microsoft Access (Microsoft Corp.). Statistical Analysis For

RANDOMIZATION PROCEDURES FOR THE ANALYSIS OF EDUCATIONAL EXPERIMENTS.

ERIC Educational Resources Information Center

COLLIER, RAYMOND O.

CERTAIN SPECIFIC ASPECTS OF HYPOTHESIS TESTS USED FOR ANALYSIS OF RESULTS IN RANDOMIZED EXPERIMENTS WERE STUDIED--(1) THE DEVELOPMENT OF THE THEORETICAL FACTOR, THAT OF PROVIDING INFORMATION ON STATISTICAL TESTS FOR CERTAIN EXPERIMENTAL DESIGNS AND (2) THE DEVELOPMENT OF THE APPLIED ELEMENT, THAT OF SUPPLYING THE EXPERIMENTER WITH MACHINERY FOR…

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

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

PubMed

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

2012-05-01

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

Analysis and interpretation of cost data in randomised controlled trials: review of published studies

PubMed Central

Barber, Julie A; Thompson, Simon G

1998-01-01

Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study. Design Survey of published randomised trials including an economic evaluation with cost values suitable for statistical analysis; 45 such trials published in 1995 were identified from Medline. Main outcome measures The use of statistical methods for cost data was assessed in terms of the descriptive statistics reported, use of statistical inference, and whether the reported conclusions were justified. Results Although all 45 trials reviewed apparently had cost data for each patient, only 9 (20%) reported adequate measures of variability for these data and only 25 (56%) gave results of statistical tests or a measure of precision for the comparison of costs between the randomised groups. Only 16 (36%) of the articles gave conclusions which were justified on the basis of results presented in the paper. No paper reported sample size calculations for costs. Conclusions The analysis and interpretation of cost data from published trials reveal a lack of statistical awareness. Strong and potentially misleading conclusions about the relative costs of alternative therapies have often been reported in the absence of supporting statistical evidence. Improvements in the analysis and reporting of health economic assessments are urgently required. Health economic guidelines need to be revised to incorporate more detailed statistical advice. Key messagesHealth economic evaluations required for important healthcare policy decisions are often carried out in randomised controlled trialsA review of such published economic evaluations assessed whether statistical methods for cost outcomes have been appropriately used and interpretedFew publications presented adequate descriptive information for costs or performed appropriate statistical analysesIn at least two thirds of the papers, the main conclusions regarding costs were not justifiedThe analysis and reporting of health economic assessments within randomised controlled trials urgently need improving PMID:9794854

fMRI reliability: influences of task and experimental design.

PubMed

Bennett, Craig M; Miller, Michael B

2013-12-01

As scientists, it is imperative that we understand not only the power of our research tools to yield results, but also their ability to obtain similar results over time. This study is an investigation into how common decisions made during the design and analysis of a functional magnetic resonance imaging (fMRI) study can influence the reliability of the statistical results. To that end, we gathered back-to-back test-retest fMRI data during an experiment involving multiple cognitive tasks (episodic recognition and two-back working memory) and multiple fMRI experimental designs (block, event-related genetic sequence, and event-related m-sequence). Using these data, we were able to investigate the relative influences of task, design, statistical contrast (task vs. rest, target vs. nontarget), and statistical thresholding (unthresholded, thresholded) on fMRI reliability, as measured by the intraclass correlation (ICC) coefficient. We also utilized data from a second study to investigate test-retest reliability after an extended, six-month interval. We found that all of the factors above were statistically significant, but that they had varying levels of influence on the observed ICC values. We also found that these factors could interact, increasing or decreasing the relative reliability of certain Task × Design combinations. The results suggest that fMRI reliability is a complex construct whose value may be increased or decreased by specific combinations of factors.

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

Bennett, Janine Camille; Thompson, David; Pebay, Philippe Pierre

Statistical analysis is typically used to reduce the dimensionality of and infer meaning from data. A key challenge of any statistical analysis package aimed at large-scale, distributed data is to address the orthogonal issues of parallel scalability and numerical stability. Many statistical techniques, e.g., descriptive statistics or principal component analysis, are based on moments and co-moments and, using robust online update formulas, can be computed in an embarrassingly parallel manner, amenable to a map-reduce style implementation. In this paper we focus on contingency tables, through which numerous derived statistics such as joint and marginal probability, point-wise mutual information, information entropy,more » and {chi}{sup 2} independence statistics can be directly obtained. However, contingency tables can become large as data size increases, requiring a correspondingly large amount of communication between processors. This potential increase in communication prevents optimal parallel speedup and is the main difference with moment-based statistics (which we discussed in [1]) where the amount of inter-processor communication is independent of data size. Here we present the design trade-offs which we made to implement the computation of contingency tables in parallel. We also study the parallel speedup and scalability properties of our open source implementation. In particular, we observe optimal speed-up and scalability when the contingency statistics are used in their appropriate context, namely, when the data input is not quasi-diffuse.« less

A Systematic Review of Clinical Functional Outcomes After Medial Stabilized Versus Non-Medial Stabilized Total Knee Joint Replacement

PubMed Central

Young, Tony; Dowsey, Michelle M.; Pandy, Marcus; Choong, Peter F.

2018-01-01

Background Medial stabilized total knee joint replacement (TKJR) construct is designed to closely replicate the kinematics of the knee. Little is known regarding comparison of clinical functional outcomes of patients utilising validated patient reported outcome measures (PROM) after medial stabilized TKJR and other construct designs. Purpose To perform a systematic review of the available literature related to the assessment of clinical functional outcomes following a TKJR employing a medial stabilized construct design. Methods The review was performed with a Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) algorithm. The literature search was performed using variouscombinations of keywords. The statistical analysis was completed using Review Manager (RevMan), Version 5.3. Results In the nineteen unique studies identified, there were 2,448 medial stabilized TKJRs implanted in 2,195 participants, there were 1,777 TKJRs with non-medial stabilized design constructs implanted in 1,734 subjects. The final mean Knee Society Score (KSS) value in the medial stabilized group was 89.92 compared to 90.76 in the non-medial stabilized group, with the final KSS mean value difference between the two groups was statistically significant and favored the non-medial stabilized group (SMD 0.21; 95% CI: 0.01 to 0.41; p = 004). The mean difference in the final WOMAC values between the two groups was also statistically significant and favored the medial stabilized group (SMD: −0.27; 95% CI: −0.47 to −0.07; p = 0.009). Moderate to high values (I2) of heterogeneity were observed during the statistical comparison of these functional outcomes. Conclusion Based on the small number of studies with appropriate statistical analysis, we are unable to reach a clear conclusion in the clinical performance of medial stabilized knee replacement construct. Level of Evidence Level II PMID:29696144

A Systematic Review of Clinical Functional Outcomes After Medial Stabilized Versus Non-Medial Stabilized Total Knee Joint Replacement.

PubMed

Young, Tony; Dowsey, Michelle M; Pandy, Marcus; Choong, Peter F

2018-01-01

Medial stabilized total knee joint replacement (TKJR) construct is designed to closely replicate the kinematics of the knee. Little is known regarding comparison of clinical functional outcomes of patients utilising validated patient reported outcome measures (PROM) after medial stabilized TKJR and other construct designs. To perform a systematic review of the available literature related to the assessment of clinical functional outcomes following a TKJR employing a medial stabilized construct design. The review was performed with a Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) algorithm. The literature search was performed using variouscombinations of keywords. The statistical analysis was completed using Review Manager (RevMan), Version 5.3. In the nineteen unique studies identified, there were 2,448 medial stabilized TKJRs implanted in 2,195 participants, there were 1,777 TKJRs with non-medial stabilized design constructs implanted in 1,734 subjects. The final mean Knee Society Score (KSS) value in the medial stabilized group was 89.92 compared to 90.76 in the non-medial stabilized group, with the final KSS mean value difference between the two groups was statistically significant and favored the non-medial stabilized group (SMD 0.21; 95% CI: 0.01 to 0.41; p = 004). The mean difference in the final WOMAC values between the two groups was also statistically significant and favored the medial stabilized group (SMD: -0.27; 95% CI: -0.47 to -0.07; p = 0.009). Moderate to high values ( I 2 ) of heterogeneity were observed during the statistical comparison of these functional outcomes. Based on the small number of studies with appropriate statistical analysis, we are unable to reach a clear conclusion in the clinical performance of medial stabilized knee replacement construct. Level II.

An application of principal component analysis to the clavicle and clavicle fixation devices.

PubMed

Daruwalla, Zubin J; Courtis, Patrick; Fitzpatrick, Clare; Fitzpatrick, David; Mullett, Hannan

2010-03-26

Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories. Twenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation. The first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups. This unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

Methodological quality of behavioural weight loss studies: a systematic review

PubMed Central

Lemon, S. C.; Wang, M. L.; Haughton, C. F.; Estabrook, D. P.; Frisard, C. F.; Pagoto, S. L.

2018-01-01

Summary This systematic review assessed the methodological quality of behavioural weight loss intervention studies conducted among adults and associations between quality and statistically significant weight loss outcome, strength of intervention effectiveness and sample size. Searches for trials published between January, 2009 and December, 2014 were conducted using PUBMED, MEDLINE and PSYCINFO and identified ninety studies. Methodological quality indicators included study design, anthropometric measurement approach, sample size calculations, intent-to-treat (ITT) analysis, loss to follow-up rate, missing data strategy, sampling strategy, report of treatment receipt and report of intervention fidelity (mean = 6.3). Indicators most commonly utilized included randomized design (100%), objectively measured anthropometrics (96.7%), ITT analysis (86.7%) and reporting treatment adherence (76.7%). Most studies (62.2%) had a follow-up rate >75% and reported a loss to follow-up analytic strategy or minimal missing data (69.9%). Describing intervention fidelity (34.4%) and sampling from a known population (41.1%) were least common. Methodological quality was not associated with reporting a statistically significant result, effect size or sample size. This review found the published literature of behavioural weight loss trials to be of high quality for specific indicators, including study design and measurement. Identified for improvement include utilization of more rigorous statistical approaches to loss to follow up and better fidelity reporting. PMID:27071775

Optimization of fermentation medium for the production of atrazine degrading strain Acinetobacter sp. DNS(32) by statistical analysis system.

PubMed

Zhang, Ying; Wang, Yang; Wang, Zhi-Gang; Wang, Xi; Guo, Huo-Sheng; Meng, Dong-Fang; Wong, Po-Keung

2012-01-01

Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS(32) in shake-flask cultures. A "Plackett-Burman Design" was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K(2)HPO(4) were found to significantly influence Acinetobacter sp. DNS(32) production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of "response surface methodology." The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO(3) 3, K(2)HPO(4) 3.27, MgSO(4)·7H(2)O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079 × 10(8) CFU/mL and 7.194 × 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS(32).

Design of Neural Networks for Fast Convergence and Accuracy

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1998-01-01

A novel procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed to provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component spacecraft design changes and measures of its performance. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The design algorithm attempts to avoid the local minima phenomenon that hampers the traditional network training. A numerical example is performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

The Ontology of Biological and Clinical Statistics (OBCS) for standardized and reproducible statistical analysis.

PubMed

Zheng, Jie; Harris, Marcelline R; Masci, Anna Maria; Lin, Yu; Hero, Alfred; Smith, Barry; He, Yongqun

2016-09-14

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. The terms in OBCS including 'data collection', 'data transformation in statistics', 'data visualization', 'statistical data analysis', and 'drawing a conclusion based on data', cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. Currently, OBCS comprehends 878 terms, representing 20 BFO classes, 403 OBI classes, 229 OBCS specific classes, and 122 classes imported from ten other OBO ontologies. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. Other ongoing projects using OBCS for statistical data processing are also discussed. The OBCS source code and documentation are available at: https://github.com/obcs/obcs . The Ontology of Biological and Clinical Statistics (OBCS) is a community-based open source ontology in the domain of biological and clinical statistics. OBCS is a timely ontology that represents statistics-related terms and their relations in a rigorous fashion, facilitates standard data analysis and integration, and supports reproducible biological and clinical research.

Implementation of the medical research curriculum in graduate medical school.

PubMed

Park, Kwi Hwa; Kim, Tae-Hee; Chung, Wook-Jin

2011-06-01

The purpose of this study was to analyze the effect of the medical research curriculum on the students' satisfaction and the research self-efficacy. The curriculum was implemented to 79 graduate medical school students who entered in 2007 and 2008. This curriculum is implemented through 3 years consisting of 5 different sub-courses: Research design, Research ethics, Medical statistics, Writing medical paper, and Presentation. The effect of this program was measured with 2 self-administered surveys to students: the course satisfaction survey and the self-efficacy inventories. The Research Self-Efficacy Scale consisted of 18 items from 4 categories: Research design, Research ethics, Data analysis, and Result presentation. The descriptive statistics, paired t-test, and analysis of covariance (ANCOVA) were implemented. The average point of satisfaction of the course was 2.74 out of 4, which told us that students generally satisfied with the course. The frequencies of tutoring for research course were 2 or 3 times on average and each session of tutorial lasted 1.5 to 2 hours. The research self-efficacy in three categories (Research design, Research ethics, and Result presentation) increased significantly (p<0.1). The self-efficacy of the male students was higher than females' one. The self-efficacy was not significantly different by the experience of research paper writing at undergraduate level. The curriculum showed positive results in cultivating research self-efficacy of students. There is a need for improvement of the class of Statistical analysis as students reported that it was difficult.

Designing for auto safety

NASA Technical Reports Server (NTRS)

Driver, E. T.

1971-01-01

Safety design features in the motor vehicle and highway construction fields result from systems analysis approach to prevent or lessen death, injury, and property damage results. Systems analysis considers the prevention of crashes, increased survivability in crashes, and prompt medical attention to injuries as well as other postcrash salvage measures. The interface of these system elements with the driver, the vehicle, and the environment shows that action on the vehicle system produces the greatest safety payoff through design modifications. New and amended safety standards developed through hazard analysis technique improved accident statistics in the 70'; these regulations include driver qualifications and countermeasures to identify the chronic drunken driver who is involved in more than two-thirds of all auto deaths.

Use of Statistical Analyses in the Ophthalmic Literature

PubMed Central

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

2014-01-01

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

Computer Programs for Obtaining and Analyzing Daily Mean Steamflow Data from the U.S. Geological Survey National Water Information System Web Site

USGS Publications Warehouse

Granato, Gregory E.

2009-01-01

Streamflow information is important for many planning and design activities including water-supply analysis, habitat protection, bridge and culvert design, calibration of surface and ground-water models, and water-quality assessments. Streamflow information is especially critical for water-quality assessments (Warn and Brew, 1980; Di Toro, 1984; Driscoll and others, 1989; Driscoll and others, 1990, a,b). Calculation of streamflow statistics for receiving waters is necessary to estimate the potential effects of point sources such as wastewater-treatment plants and nonpoint sources such as highway and urban-runoff discharges on receiving water. Streamflow statistics indicate the amount of flow that may be available for dilution and transport of contaminants (U.S. Environmental Protection Agency, 1986; Driscoll and others, 1990, a,b). Streamflow statistics also may be used to indicate receiving-water quality because concentrations of water-quality constituents commonly vary naturally with streamflow. For example, concentrations of suspended sediment and sediment-associated constituents (such as nutrients, trace elements, and many organic compounds) commonly increase with increasing flows, and concentrations of many dissolved constituents commonly decrease with increasing flows in streams and rivers (O'Connor, 1976; Glysson, 1987; Vogel and others, 2003, 2005). Reliable, efficient and repeatable methods are needed to access and process streamflow information and data. For example, the Nation's highway infrastructure includes an innumerable number of stream crossings and stormwater-outfall points for which estimates of stream-discharge statistics may be needed. The U.S. Geological Survey (USGS) streamflow data-collection program is designed to provide streamflow data at gaged sites and to provide information that can be used to estimate streamflows at almost any point along any stream in the United States (Benson and Carter, 1973; Wahl and others, 1995; National Research Council, 2004). The USGS maintains the National Water Information System (NWIS), a distributed network of computers and file servers used to store and retrieve hydrologic data (Mathey, 1998; U.S. Geological Survey, 2008). NWISWeb is an online version of this database that includes water data from more than 24,000 streamflow-gaging stations throughout the United States (U.S. Geological Survey, 2002, 2008). Information from NWISWeb is commonly used to characterize streamflows at gaged sites and to help predict streamflows at ungaged sites. Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model. The programs were developed because reliable, efficient, and repeatable methods are needed to access and process streamflow information and data. The first program is designed to facilitate the downloading and reformatting of NWISWeb streamflow data. The second program is designed to facilitate graphical analysis of streamflow data. The third program is designed to facilitate streamflow-record extension and augmentation to help develop long-term statistical estimates for sites with limited data. The fourth program is designed to facilitate statistical analysis of streamflow data. The fifth program is a preprocessor to create batch input files for the U.S. Environmental Protection Agency DFLOW3 program for calculating low-flow statistics. These computer programs were developed to facilitate the analysis of daily mean streamflow data for planning-level water-quality analyses but also are useful for many other applications pertaining to streamflow data and statistics. These programs and the associated documentation are included on the CD-ROM accompanying this report. This report and the appendixes on the

An Analysis of Operational Suitability for Test and Evaluation of Highly Reliable Systems

DTIC Science & Technology

1994-03-04

Exposition," Journal of the American Statistical A iation-59: 353-375 (June 1964). 17. SYS 229, Test and Evaluation Management Coursebook , School of Systems...in hours, 0 is 2-5 the desired MTBCF in hours, R is the number of critical failures, and a is the P[type-I error] of the X2 statistic with 2*R+2...design of experiments (DOE) tables and the use of Bayesian statistics to increase the confidence level of the test results that will be obtained from

Failure Mode Identification Through Clustering Analysis

NASA Technical Reports Server (NTRS)

Arunajadai, Srikesh G.; Stone, Robert B.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)

2002-01-01

Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently, failure identification procedures (such as FMEA (Failure Modes and Effects Analysis), FMECA (Failure Modes, Effects and Criticality Analysis) and FTA (Fault Tree Analysis)) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.

NASA DOE POD NDE Capabilities Data Book

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2015-01-01

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

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

PubMed

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Fatigue Countermeasures in Support of CF CC130 Air Transport Operations; from the Operation to the Laboratory and Back to the Operation

DTIC Science & Technology

2003-10-01

Toujours comparativement au placebo, les sujets ayant pris du zopiclone avaient eu moins de difficulté à s’endormir (p < 0,001), s’étaient réveillés...5 Multitask (MT)........................................................................... 6 Experimental Design Considerations...Experimental Design ............................................................................ 19 Statistical Analysis

HAZARDS SUMMARY REPORT FOR A TWO WATT PROMETHIUM-147 FUELED THERMOELECTRIC GENERATOR

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

None

1959-06-01

Discussions are included of the APU design, vehicle integration, Pm/sup 147/ properties, shielding requirements, hazards design criteria, statistical analysis for impact, and radiation protection. The use of Pm/sup 147/ makes possible the fabrication of an auxiliary power unit which has applications for low power space missions of <10 watts (electrical). (B.O.G.)

Design and statistical problems in prevention.

PubMed

Gullberg, B

1996-01-01

Clinical and epidemiological research in osteoporosis can benefit from using the methods and techniques established in the area of chronic disease epidemiology. However, attention has to be given to the special characteristics such as the multifactorial nature and the fact that the subjects usually are of high ages. In order to evaluate prevention it is of course first necessary to detect and confirm reversible risk factors. The advantage and disadvantage of different design (cross-sectional, cohort and case-control) are well known. The effects of avoidable biases, e.g. selection, observation and confounding have to be balanced against practical conveniences like time, expenses, recruitment etc. The translation of relative risks into population attributable risks (etiologic fractions, prevented fractions) are complex and are usually performed under unrealistic, simplified assumptions. The consequences of interactions (synergy) between risk factors are often neglected. The multifactorial structure requires application of more advanced multi-level statistical techniques. The common strategy in prevention to target a cluster of risk factors in order to avoid the multifactorial nature implies that in the end it is impossible to separate each unique factor. Experimental designs for evaluating prevention like clinical trials and intervention have to take into account the distinction between explanatory and pragmatic studies. An explanatory approach is similar to an idealized laboratory trial while the pragmatic design is more realistic, practical and has a general public health perspective. The statistical techniques to be used in osteoporosis research are implemented in easy available computer-packages like SAS, SPSS, BMDP and GLIM. In addition to the traditional logistic regression methods like Cox analysis and Poisson regression also analysis of repeated measurement and cluster analysis are relevant.

Cognition, comprehension and application of biostatistics in research by Indian postgraduate students in periodontics

PubMed Central

Swetha, Jonnalagadda Laxmi; Arpita, Ramisetti; Srikanth, Chintalapani; Nutalapati, Rajasekhar

2014-01-01

Background: Biostatistics is an integral part of research protocols. In any field of inquiry or investigation, data obtained is subsequently classified, analyzed and tested for accuracy by statistical methods. Statistical analysis of collected data, thus, forms the basis for all evidence-based conclusions. Aim: The aim of this study is to evaluate the cognition, comprehension and application of biostatistics in research among post graduate students in Periodontics, in India. Materials and Methods: A total of 391 post graduate students registered for a master's course in periodontics at various dental colleges across India were included in the survey. Data regarding the level of knowledge, understanding and its application in design and conduct of the research protocol was collected using a dichotomous questionnaire. A descriptive statistics was used for data analysis. Results: Nearly 79.2% students were aware of the importance of biostatistics in research, 55-65% were familiar with MS-EXCEL spreadsheet for graphical representation of data and with the statistical softwares available on the internet, 26.0% had biostatistics as mandatory subject in their curriculum, 9.5% tried to perform statistical analysis on their own while 3.0% were successful in performing statistical analysis of their studies on their own. Conclusion: Biostatistics should play a central role in planning, conduct, interim analysis, final analysis and reporting of periodontal research especially by the postgraduate students. Indian postgraduate students in periodontics are aware of the importance of biostatistics in research but the level of understanding and application is still basic and needs to be addressed. PMID:24744547

Selecting the best design for nonstandard toxicology experiments.

PubMed

Webb, Jennifer M; Smucker, Byran J; Bailer, A John

2014-10-01

Although many experiments in environmental toxicology use standard statistical experimental designs, there are situations that arise where no such standard design is natural or applicable because of logistical constraints. For example, the layout of a laboratory may suggest that each shelf serve as a block, with the number of experimental units per shelf either greater than or less than the number of treatments in a way that precludes the use of a typical block design. In such cases, an effective and powerful alternative is to employ optimal experimental design principles, a strategy that produces designs with precise statistical estimates. Here, a D-optimal design was generated for an experiment in environmental toxicology that has 2 factors, 16 treatments, and constraints similar to those described above. After initial consideration of a randomized complete block design and an intuitive cyclic design, it was decided to compare a D-optimal design and a slightly more complicated version of the cyclic design. Simulations were conducted generating random responses under a variety of scenarios that reflect conditions motivated by a similar toxicology study, and the designs were evaluated via D-efficiency as well as by a power analysis. The cyclic design performed well compared to the D-optimal design. © 2014 SETAC.

Modelling short time series in metabolomics: a functional data analysis approach.

PubMed

Montana, Giovanni; Berk, Maurice; Ebbels, Tim

2011-01-01

Metabolomics is the study of the complement of small molecule metabolites in cells, biofluids and tissues. Many metabolomic experiments are designed to compare changes observed over time under two or more experimental conditions (e.g. a control and drug-treated group), thus producing time course data. Models from traditional time series analysis are often unsuitable because, by design, only very few time points are available and there are a high number of missing values. We propose a functional data analysis approach for modelling short time series arising in metabolomic studies which overcomes these obstacles. Our model assumes that each observed time series is a smooth random curve, and we propose a statistical approach for inferring this curve from repeated measurements taken on the experimental units. A test statistic for detecting differences between temporal profiles associated with two experimental conditions is then presented. The methodology has been applied to NMR spectroscopy data collected in a pre-clinical toxicology study.

Vibration Response Models of a Stiffened Aluminum Plate Excited by a Shaker

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.

2008-01-01

Numerical models of structural-acoustic interactions are of interest to aircraft designers and the space program. This paper describes a comparison between two energy finite element codes, a statistical energy analysis code, a structural finite element code, and the experimentally measured response of a stiffened aluminum plate excited by a shaker. Different methods for modeling the stiffeners and the power input from the shaker are discussed. The results show that the energy codes (energy finite element and statistical energy analysis) accurately predicted the measured mean square velocity of the plate. In addition, predictions from an energy finite element code had the best spatial correlation with measured velocities. However, predictions from a considerably simpler, single subsystem, statistical energy analysis model also correlated well with the spatial velocity distribution. The results highlight a need for further work to understand the relationship between modeling assumptions and the prediction results.

Statistical Analysis of Adaptive Beam-Forming Methods

DTIC Science & Technology

1988-05-01

minimum amount of computing resources? * What are the tradeoffs being made when a system design selects block averaging over exponential averaging? Will...understood by many signal processing practitioners, however, is how system parameters and the number of sensors effect the distribution of the... system performance improve and if so by how much? b " It is well known that the noise sampled at adjacent sensors is not statistically independent

Composite Material Aircraft Electromagnetic Properties and Design Guidelines

DTIC Science & Technology

1981-01-01

Diode Characteristics for IN914 Diode at 220 MHz 7-6 7.5 Characteristics of a 2N2369A Transitor With and Without RF Interference on the Collector Lead...Analylsi Miser Reiponse Model Adjacent Channel Interference Summary 7. STATISTICAL AND NUMERICAL I. PROPAGATION MODELS ANALYSIS MASTER PROPAGATION SYSTEM...Propagation System lIPS) Simsulationst Smorothe Curve Smooth Earth (SCSIS) Oemtralltzd File Statistics Analyzer (Q63) flislance Free Space Spherical Raflectiot

Measuring Circulation Desk Activities Using a Random Alarm Mechanism.

ERIC Educational Resources Information Center

Mosborg, Stella Frank

1980-01-01

Reports a job analysis methodology to gather meaningful data related to circulation desk activity. The technique is designed to give librarians statistical data on actual time expenditures for complex and varying activities. (Author/RAA)

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

DTIC Science & Technology

2017-05-25

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

An Educational Program of Mathematical Creativity

ERIC Educational Resources Information Center

Petrovici, Constantin; Havârneanu, Geanina

2015-01-01

In this article we intend to analyze the effectiveness of an educational program of mathematical creativity, designed for learners aged 10 to 12 years, which has been implemented in an urban school of Iasi, Romania. This analysis has both a psycho-educational dimension and a statistical analysis one. The psycho-educational dimension refers to the…

A Meta-Analysis of Referential Communication Studies: A Computer Readable Literature Review.

ERIC Educational Resources Information Center

Dickson, W. Patrick; Moskoff, Mary

A computer-assisted analysis of studies on referential communication (giving directions/explanations) located 66 reports involving 80 experiments, 114 referential tasks, and over 6,200 individuals. The studies were entered into a statistical software package system (SPSS) and analyzed for characteristics of the subjects and experimental designs,…

Analysis Tools (AT)

Treesearch

Larry J. Gangi

2006-01-01

The FIREMON Analysis Tools program is designed to let the user perform grouped or ungrouped summary calculations of single measurement plot data, or statistical comparisons of grouped or ungrouped plot data taken at different sampling periods. The program allows the user to create reports and graphs, save and print them, or cut and paste them into a word processor....

An Analysis of Variance Framework for Matrix Sampling.

ERIC Educational Resources Information Center

Sirotnik, Kenneth

Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Mixed-Methods Research in the Discipline of Nursing.

PubMed

Beck, Cheryl Tatano; Harrison, Lisa

2016-01-01

In this review article, we examined the prevalence and characteristics of 294 mixed-methods studies in the discipline of nursing. Creswell and Plano Clark's typology was most frequently used along with concurrent timing. Bivariate statistics was most often the highest level of statistics reported in the results. As for qualitative data analysis, content analysis was most frequently used. The majority of nurse researchers did not specifically address the purpose, paradigm, typology, priority, timing, interaction, or integration of their mixed-methods studies. Strategies are suggested for improving the design, conduct, and reporting of mixed-methods studies in the discipline of nursing.

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.

Experimental Design and Data Analysis Issues Contribute to Inconsistent Results of C-Bouton Changes in Amyotrophic Lateral Sclerosis.

PubMed

Dukkipati, S Shekar; Chihi, Aouatef; Wang, Yiwen; Elbasiouny, Sherif M

2017-01-01

The possible presence of pathological changes in cholinergic synaptic inputs [cholinergic boutons (C-boutons)] is a contentious topic within the ALS field. Conflicting data reported on this issue makes it difficult to assess the roles of these synaptic inputs in ALS. Our objective was to determine whether the reported changes are truly statistically and biologically significant and why replication is problematic. This is an urgent question, as C-boutons are an important regulator of spinal motoneuron excitability, and pathological changes in motoneuron excitability are present throughout disease progression. Using male mice of the SOD1-G93A high-expresser transgenic ( G93A ) mouse model of ALS, we examined C-boutons on spinal motoneurons. We performed histological analysis at high statistical power, which showed no difference in C-bouton size in G93A versus wild-type motoneurons throughout disease progression. In an attempt to examine the underlying reasons for our failure to replicate reported changes, we performed further histological analyses using several variations on experimental design and data analysis that were reported in the ALS literature. This analysis showed that factors related to experimental design, such as grouping unit, sampling strategy, and blinding status, potentially contribute to the discrepancy in published data on C-bouton size changes. Next, we systematically analyzed the impact of study design variability and potential bias on reported results from experimental and preclinical studies of ALS. Strikingly, we found that practices such as blinding and power analysis are not systematically reported in the ALS field. Protocols to standardize experimental design and minimize bias are thus critical to advancing the ALS field.

Technical Note: The Initial Stages of Statistical Data Analysis

PubMed Central

Tandy, Richard D.

1998-01-01

Objective: To provide an overview of several important data-related considerations in the design stage of a research project and to review the levels of measurement and their relationship to the statistical technique chosen for the data analysis. Background: When planning a study, the researcher must clearly define the research problem and narrow it down to specific, testable questions. The next steps are to identify the variables in the study, decide how to group and treat subjects, and determine how to measure, and the underlying level of measurement of, the dependent variables. Then the appropriate statistical technique can be selected for data analysis. Description: The four levels of measurement in increasing complexity are nominal, ordinal, interval, and ratio. Nominal data are categorical or “count” data, and the numbers are treated as labels. Ordinal data can be ranked in a meaningful order by magnitude. Interval data possess the characteristics of ordinal data and also have equal distances between levels. Ratio data have a natural zero point. Nominal and ordinal data are analyzed with nonparametric statistical techniques and interval and ratio data with parametric statistical techniques. Advantages: Understanding the four levels of measurement and when it is appropriate to use each is important in determining which statistical technique to use when analyzing data. PMID:16558489

A Content Analysis of Quantitative Research in Journal of Marital and Family Therapy: A 10-Year Review.

PubMed

Parker, Elizabeth O; Chang, Jennifer; Thomas, Volker

2016-01-01

We examined the trends of quantitative research over the past 10 years in the Journal of Marital and Family Therapy (JMFT). Specifically, within the JMFT, we investigated the types and trends of research design and statistical analysis within the quantitative research that was published in JMFT from 2005 to 2014. We found that while the amount of peer-reviewed articles have increased over time, the percentage of quantitative research has remained constant. We discussed the types and trends of statistical analysis and the implications for clinical work and training programs in the field of marriage and family therapy. © 2016 American Association for Marriage and Family Therapy.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu

2013-08-08

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Application of a quality by design approach to the cell culture process of monoclonal antibody production, resulting in the establishment of a design space.

PubMed

Nagashima, Hiroaki; Watari, Akiko; Shinoda, Yasuharu; Okamoto, Hiroshi; Takuma, Shinya

2013-12-01

This case study describes the application of Quality by Design elements to the process of culturing Chinese hamster ovary cells in the production of a monoclonal antibody. All steps in the cell culture process and all process parameters in each step were identified by using a cause-and-effect diagram. Prospective risk assessment using failure mode and effects analysis identified the following four potential critical process parameters in the production culture step: initial viable cell density, culture duration, pH, and temperature. These parameters and lot-to-lot variability in raw material were then evaluated by process characterization utilizing a design of experiments approach consisting of a face-centered central composite design integrated with a full factorial design. Process characterization was conducted using a scaled down model that had been qualified by comparison with large-scale production data. Multivariate regression analysis was used to establish statistical prediction models for performance indicators and quality attributes; with these, we constructed contour plots and conducted Monte Carlo simulation to clarify the design space. The statistical analyses, especially for raw materials, identified set point values, which were most robust with respect to the lot-to-lot variability of raw materials while keeping the product quality within the acceptance criteria. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Statistical validation and an empirical model of hydrogen production enhancement found by utilizing passive flow disturbance in the steam-reformation process

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

Erickson, Paul A.; Liao, Chang-hsien

2007-11-15

A passive flow disturbance has been proven to enhance the conversion of fuel in a methanol-steam reformer. This study presents a statistical validation of the experiment based on a standard 2{sup k} factorial experiment design and the resulting empirical model of the enhanced hydrogen producing process. A factorial experiment design was used to statistically analyze the effects and interactions of various input factors in the experiment. Three input factors, including the number of flow disturbers, catalyst size, and reactant flow rate were investigated for their effects on the fuel conversion in the steam-reformation process. Based on the experimental results, anmore » empirical model was developed and further evaluated with an uncertainty analysis and interior point data. (author)« less

Statistical mixture design and multivariate analysis of inkjet printed a-WO3/TiO2/WOX electrochromic films.

PubMed

Wojcik, Pawel Jerzy; Pereira, Luís; Martins, Rodrigo; Fortunato, Elvira

2014-01-13

An efficient mathematical strategy in the field of solution processed electrochromic (EC) films is outlined as a combination of an experimental work, modeling, and information extraction from massive computational data via statistical software. Design of Experiment (DOE) was used for statistical multivariate analysis and prediction of mixtures through a multiple regression model, as well as the optimization of a five-component sol-gel precursor subjected to complex constraints. This approach significantly reduces the number of experiments to be realized, from 162 in the full factorial (L=3) and 72 in the extreme vertices (D=2) approach down to only 30 runs, while still maintaining a high accuracy of the analysis. By carrying out a finite number of experiments, the empirical modeling in this study shows reasonably good prediction ability in terms of the overall EC performance. An optimized ink formulation was employed in a prototype of a passive EC matrix fabricated in order to test and trial this optically active material system together with a solid-state electrolyte for the prospective application in EC displays. Coupling of DOE with chromogenic material formulation shows the potential to maximize the capabilities of these systems and ensures increased productivity in many potential solution-processed electrochemical applications.

Design optimization of a prescribed vibration system using conjoint value analysis

NASA Astrophysics Data System (ADS)

Malinga, Bongani; Buckner, Gregory D.

2016-12-01

This article details a novel design optimization strategy for a prescribed vibration system (PVS) used to mechanically filter solids from fluids in oil and gas drilling operations. A dynamic model of the PVS is developed, and the effects of disturbance torques are detailed. This model is used to predict the effects of design parameters on system performance and efficiency, as quantified by system attributes. Conjoint value analysis, a statistical technique commonly used in marketing science, is utilized to incorporate designer preferences. This approach effectively quantifies and optimizes preference-based trade-offs in the design process. The effects of designer preferences on system performance and efficiency are simulated. This novel optimization strategy yields improvements in all system attributes across all simulated vibration profiles, and is applicable to other industrial electromechanical systems.

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

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

2015-01-01

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

Statistical Optics

NASA Astrophysics Data System (ADS)

Goodman, Joseph W.

2000-07-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research

Metrological traceability in education: A practical online system for measuring and managing middle school mathematics instruction

NASA Astrophysics Data System (ADS)

Torres Irribarra, D.; Freund, R.; Fisher, W.; Wilson, M.

2015-02-01

Computer-based, online assessments modelled, designed, and evaluated for adaptively administered invariant measurement are uniquely suited to defining and maintaining traceability to standardized units in education. An assessment of this kind is embedded in the Assessing Data Modeling and Statistical Reasoning (ADM) middle school mathematics curriculum. Diagnostic information about middle school students' learning of statistics and modeling is provided via computer-based formative assessments for seven constructs that comprise a learning progression for statistics and modeling from late elementary through the middle school grades. The seven constructs are: Data Display, Meta-Representational Competence, Conceptions of Statistics, Chance, Modeling Variability, Theory of Measurement, and Informal Inference. The end product is a web-delivered system built with Ruby on Rails for use by curriculum development teams working with classroom teachers in designing, developing, and delivering formative assessments. The online accessible system allows teachers to accurately diagnose students' unique comprehension and learning needs in a common language of real-time assessment, logging, analysis, feedback, and reporting.

Comparative efficacy of golimumab, infliximab, and adalimumab for moderately to severely active ulcerative colitis: a network meta-analysis accounting for differences in trial designs.

PubMed

Thorlund, Kristian; Druyts, Eric; Toor, Kabirraaj; Mills, Edward J

2015-05-01

To conduct a network meta-analysis (NMA) to establish the comparative efficacy of infliximab, adalimumab and golimumab for the treatment of moderately to severely active ulcerative colitis (UC). A systematic literature search identified five randomized controlled trials for inclusion in the NMA. One trial assessed golimumab, two assessed infliximab and two assessed adalimumab. Outcomes included clinical response, clinical remission, mucosal healing, sustained clinical response and sustained clinical remission. Innovative methods were used to allow inclusion of the golimumab trial data given the alternative design of this trial (i.e., two-stage re-randomization). After induction, no statistically significant differences were found between golimumab and adalimumab or between golimumab and infliximab. Infliximab was statistically superior to adalimumab after induction for all outcomes and treatment ranking suggested infliximab as the superior treatment for induction. Golimumab and infliximab were associated with similar efficacy for achieving maintained clinical remission and sustained clinical remission, whereas adalimumab was not significantly better than placebo for sustained clinical remission. Golimumab and infliximab were also associated with similar efficacy for achieving maintained clinical response, sustained clinical response and mucosal healing. Finally, golimumab 50 and 100 mg was statistically superior to adalimumab for clinical response and sustained clinical response, and golimumab 100 mg was also statistically superior to adalimumab for mucosal healing. The results of our NMA suggest that infliximab was statistically superior to adalimumab after induction, and that golimumab was statistically superior to adalimumab for sustained outcomes. Golimumab and infliximab appeared comparable in efficacy.

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

PubMed

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

2015-08-01

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

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

PubMed

Varekar, Vikas; Karmakar, Subhankar; Jha, Ramakar

2016-02-01

The design of surface water quality sampling location is a crucial decision-making process for rationalization of monitoring network. The quantity, quality, and types of available dataset (watershed characteristics and water quality data) may affect the selection of appropriate design methodology. The modified Sanders approach and multivariate statistical techniques [particularly factor analysis (FA)/principal component analysis (PCA)] are well-accepted and widely used techniques for design of sampling locations. However, their performance may vary significantly with quantity, quality, and types of available dataset. In this paper, an attempt has been made to evaluate performance of these techniques by accounting the effect of seasonal variation, under a situation of limited water quality data but extensive watershed characteristics information, as continuous and consistent river water quality data is usually difficult to obtain, whereas watershed information may be made available through application of geospatial techniques. A case study of Kali River, Western Uttar Pradesh, India, is selected for the analysis. The monitoring was carried out at 16 sampling locations. The discrete and diffuse pollution loads at different sampling sites were estimated and accounted using modified Sanders approach, whereas the monitored physical and chemical water quality parameters were utilized as inputs for FA/PCA. The designed optimum number of sampling locations for monsoon and non-monsoon seasons by modified Sanders approach are eight and seven while that for FA/PCA are eleven and nine, respectively. Less variation in the number and locations of designed sampling sites were obtained by both techniques, which shows stability of results. A geospatial analysis has also been carried out to check the significance of designed sampling location with respect to river basin characteristics and land use of the study area. Both methods are equally efficient; however, modified Sanders approach outperforms FA/PCA when limited water quality and extensive watershed information is available. The available water quality dataset is limited and FA/PCA-based approach fails to identify monitoring locations with higher variation, as these multivariate statistical approaches are data-driven. The priority/hierarchy and number of sampling sites designed by modified Sanders approach are well justified by the land use practices and observed river basin characteristics of the study area.

The Role of Margin in Link Design and Optimization

NASA Technical Reports Server (NTRS)

Cheung, K.

2015-01-01

Link analysis is a system engineering process in the design, development, and operation of communication systems and networks. Link models that are mathematical abstractions representing the useful signal power and the undesirable noise and attenuation effects (including weather effects if the signal path transverses through the atmosphere) that are integrated into the link budget calculation that provides the estimates of signal power and noise power at the receiver. Then the link margin is applied which attempts to counteract the fluctuations of the signal and noise power to ensure reliable data delivery from transmitter to receiver. (Link margin is dictated by the link margin policy or requirements.) A simple link budgeting approach assumes link parameters to be deterministic values typically adopted a rule-of-thumb policy of 3 dB link margin. This policy works for most S- and X-band links due to their insensitivity to weather effects. But for higher frequency links like Ka-band, Ku-band, and optical communication links, it is unclear if a 3 dB link margin would guarantee link closure. Statistical link analysis that adopted the 2-sigma or 3-sigma link margin incorporates link uncertainties in the sigma calculation. (The Deep Space Network (DSN) link margin policies are 2-sigma for downlink and 3-sigma for uplink.) The link reliability can therefore be quantified statistically even for higher frequency links. However in the current statistical link analysis approach, link reliability is only expressed as the likelihood of exceeding the signal-to-noise ratio (SNR) threshold that corresponds to a given bit-error-rate (BER) or frame-error-rate (FER) requirement. The method does not provide the true BER or FER estimate of the link with margin, or the required signalto-noise ratio (SNR) that would meet the BER or FER requirement in the statistical sense. In this paper, we perform in-depth analysis on the relationship between BER/FER requirement, operating SNR, and coding performance curve, in the case when the channel coherence time of link fluctuation is comparable or larger than the time duration of a codeword. We compute the "true" SNR design point that would meet the BER/FER requirement by taking into account the fluctuation of signal power and noise power at the receiver, and the shape of the coding performance curve. This analysis yields a number of valuable insights on the design choices of coding scheme and link margin for the reliable data delivery of a communication system - space and ground. We illustrate the aforementioned analysis using a number of standard NASA error-correcting codes.

Statistical mixture design selective extraction of compounds with antioxidant activity and total polyphenol content from Trichilia catigua.

PubMed

Lonni, Audrey Alesandra Stinghen Garcia; Longhini, Renata; Lopes, Gisely Cristiny; de Mello, João Carlos Palazzo; Scarminio, Ieda Spacino

2012-03-16

Statistical design mixtures of water, methanol, acetone and ethanol were used to extract material from Trichilia catigua (Meliaceae) barks to study the effects of different solvents and their mixtures on its yield, total polyphenol content and antioxidant activity. The experimental results and their response surface models showed that quaternary mixtures with approximately equal proportions of all four solvents provided the highest yields, total polyphenol contents and antioxidant activities of the crude extracts followed by ternary design mixtures. Principal component and hierarchical clustering analysis of the HPLC-DAD spectra of the chromatographic peaks of 1:1:1:1 water-methanol-acetone-ethanol mixture extracts indicate the presence of cinchonains, gallic acid derivatives, natural polyphenols, flavanoids, catechins, and epicatechins. Copyright © 2011 Elsevier B.V. All rights reserved.

Analysis of Pulsed Flow Modification Alternatives, Lower Missouri River, 2005

USGS Publications Warehouse

Jacobson, Robert B.

2008-01-01

The graphical, tabular, and statistical data presented in this report resulted from analysis of alternative flow regime designs considered by a group of Missouri River managers, stakeholders, and scientists during the summer of 2005. This plenary group was charged with designing a flow regime with increased spring flow pulses to support reproduction and survival of the endangered pallid sturgeon. Environmental flow components extracted from the reference natural flow regime were used to design and assess performance of alternative flow regimes. The analysis is based on modeled flow releases from Gavins Point Dam (near Yankton, South Dakota) for nine design alternatives and two reference scenarios; the reference scenarios are the run-of-the-river and the water-control plan implemented in 2004. The alternative designs were developed by the plenary group with the goal of providing pulsed spring flows, while retaining traditional social and economic uses of the river.

Analysis of Variance in Statistical Image Processing

NASA Astrophysics Data System (ADS)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Collaboration and Synergy among Government, Industry and Academia in M&S Domain: Turkey’s Approach

DTIC Science & Technology

2009-10-01

Analysis, Decision Support System Design and Implementation, Simulation Output Analysis, Statistical Data Analysis, Virtual Reality , Artificial... virtual and constructive visual simulation systems as well as integrated advanced analytical models. Collaboration and Synergy among Government...simulation systems that are ready to use, credible, integrated with C4ISR systems.  Creating synthetic environments and/or virtual prototypes of concepts

Statistical analysis of the limitation of half integer resonances on the available momentum acceptance of the High Energy Photon Source

NASA Astrophysics Data System (ADS)

Jiao, Yi; Duan, Zhe

2017-01-01

In a diffraction-limited storage ring, half integer resonances can have strong effects on the beam dynamics, associated with the large detuning terms from the strong focusing and strong sextupoles as required for an ultralow emittance. In this study, the limitation of half integer resonances on the available momentum acceptance (MA) was statistically analyzed based on one design of the High Energy Photon Source (HEPS). It was found that the probability of MA reduction due to crossing of half integer resonances is closely correlated with the level of beta beats at the nominal tunes, but independent of the error sources. The analysis indicated that for the presented HEPS lattice design, the rms amplitude of beta beats should be kept below 1.5% horizontally and 2.5% vertically to reach a small MA reduction probability of about 1%.

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

PubMed

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

2008-03-01

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

Optimization of Dissolution Compartments in a Biorelevant Dissolution Apparatus Golem v2, Supported by Multivariate Analysis.

PubMed

Stupák, Ivan; Pavloková, Sylvie; Vysloužil, Jakub; Dohnal, Jiří; Čulen, Martin

2017-11-23

Biorelevant dissolution instruments represent an important tool for pharmaceutical research and development. These instruments are designed to simulate the dissolution of drug formulations in conditions most closely mimicking the gastrointestinal tract. In this work, we focused on the optimization of dissolution compartments/vessels for an updated version of the biorelevant dissolution apparatus-Golem v2. We designed eight compartments of uniform size but different inner geometry. The dissolution performance of the compartments was tested using immediate release caffeine tablets and evaluated by standard statistical methods and principal component analysis. Based on two phases of dissolution testing (using 250 and 100 mL of dissolution medium), we selected two compartment types yielding the highest measurement reproducibility. We also confirmed a statistically ssignificant effect of agitation rate and dissolution volume on the extent of drug dissolved and measurement reproducibility.

A polynomial-chaos-expansion-based building block approach for stochastic analysis of photonic circuits

NASA Astrophysics Data System (ADS)

Waqas, Abi; Melati, Daniele; Manfredi, Paolo; Grassi, Flavia; Melloni, Andrea

2018-02-01

The Building Block (BB) approach has recently emerged in photonic as a suitable strategy for the analysis and design of complex circuits. Each BB can be foundry related and contains a mathematical macro-model of its functionality. As well known, statistical variations in fabrication processes can have a strong effect on their functionality and ultimately affect the yield. In order to predict the statistical behavior of the circuit, proper analysis of the uncertainties effects is crucial. This paper presents a method to build a novel class of Stochastic Process Design Kits for the analysis of photonic circuits. The proposed design kits directly store the information on the stochastic behavior of each building block in the form of a generalized-polynomial-chaos-based augmented macro-model obtained by properly exploiting stochastic collocation and Galerkin methods. Using this approach, we demonstrate that the augmented macro-models of the BBs can be calculated once and stored in a BB (foundry dependent) library and then used for the analysis of any desired circuit. The main advantage of this approach, shown here for the first time in photonics, is that the stochastic moments of an arbitrary photonic circuit can be evaluated by a single simulation only, without the need for repeated simulations. The accuracy and the significant speed-up with respect to the classical Monte Carlo analysis are verified by means of classical photonic circuit example with multiple uncertain variables.

Wall finish selection in hospital design: a survey of facility managers.

PubMed

Lavy, Sarel; Dixit, Manish K

2012-01-01

This paper seeks to analyze healthcare facility managers' perceptions regarding the materials used for interior wall finishes and the criteria used to select them. It also examines differences in wall finish materials and the selection process in three major hospital spaces: emergency, surgery, and in-patient units. These findings are compared with healthcare designers' perceptions on similar issues, as currently documented in the literature. Hospital design and the materials used for hospital construction have a considerable effect on the environment and health of patients. A 2002 survey revealed which characteristics healthcare facility designers consider when selecting materials for healthcare facilities; however, no similar study has examined the views of facility managers on building finish selection. A 22-question survey questionnaire was distributed to 210 facility managers of metropolitan, for-profit hospitals in Texas; IRB approval was obtained. Respondents were asked to rank 10 interior wall finish materials and 11 selection criteria for wall finishes. Data from 48 complete questionnaires were analyzed using descriptive statistics and nonparametric statistical analysis methods. The study found no statistically significant differences in terms of wall finish materials or the characteristics for material selection in the three major spaces studied. It identified facility managers' four most-preferred wall finish materials and the five-most preferred characteristics, with a statistical confidence level of greater than 95%. The paper underscores the importance of incorporating all perspectives: facility designers and facility managers should work together toward achieving common organizational goals.

Generalized linear models and point count data: statistical considerations for the design and analysis of monitoring studies

Treesearch

Nathaniel E. Seavy; Suhel Quader; John D. Alexander; C. John Ralph

2005-01-01

The success of avian monitoring programs to effectively guide management decisions requires that studies be efficiently designed and data be properly analyzed. A complicating factor is that point count surveys often generate data with non-normal distributional properties. In this paper we review methods of dealing with deviations from normal assumptions, and we focus...

Accounting for measurement error: a critical but often overlooked process.

PubMed

Harris, Edward F; Smith, Richard N

2009-12-01

Due to instrument imprecision and human inconsistencies, measurements are not free of error. Technical error of measurement (TEM) is the variability encountered between dimensions when the same specimens are measured at multiple sessions. A goal of a data collection regimen is to minimise TEM. The few studies that actually quantify TEM, regardless of discipline, report that it is substantial and can affect results and inferences. This paper reviews some statistical approaches for identifying and controlling TEM. Statistically, TEM is part of the residual ('unexplained') variance in a statistical test, so accounting for TEM, which requires repeated measurements, enhances the chances of finding a statistically significant difference if one exists. The aim of this paper was to review and discuss common statistical designs relating to types of error and statistical approaches to error accountability. This paper addresses issues of landmark location, validity, technical and systematic error, analysis of variance, scaled measures and correlation coefficients in order to guide the reader towards correct identification of true experimental differences. Researchers commonly infer characteristics about populations from comparatively restricted study samples. Most inferences are statistical and, aside from concerns about adequate accounting for known sources of variation with the research design, an important source of variability is measurement error. Variability in locating landmarks that define variables is obvious in odontometrics, cephalometrics and anthropometry, but the same concerns about measurement accuracy and precision extend to all disciplines. With increasing accessibility to computer-assisted methods of data collection, the ease of incorporating repeated measures into statistical designs has improved. Accounting for this technical source of variation increases the chance of finding biologically true differences when they exist.

Interim analyses in 2 x 2 crossover trials.

PubMed

Cook, R J

1995-09-01

A method is presented for performing interim analyses in long term 2 x 2 crossover trials with serial patient entry. The analyses are based on a linear statistic that combines data from individuals observed for one treatment period with data from individuals observed for both periods. The coefficients in this linear combination can be chosen quite arbitrarily, but we focus on variance-based weights to maximize power for tests regarding direct treatment effects. The type I error rate of this procedure is controlled by utilizing the joint distribution of the linear statistics over analysis stages. Methods for performing power and sample size calculations are indicated. A two-stage sequential design involving simultaneous patient entry and a single between-period interim analysis is considered in detail. The power and average number of measurements required for this design are compared to those of the usual crossover trial. The results indicate that, while there is minimal loss in power relative to the usual crossover design in the absence of differential carry-over effects, the proposed design can have substantially greater power when differential carry-over effects are present. The two-stage crossover design can also lead to more economical studies in terms of the expected number of measurements required, due to the potential for early stopping. Attention is directed toward normally distributed responses.

A Non-Intrusive Algorithm for Sensitivity Analysis of Chaotic Flow Simulations

NASA Technical Reports Server (NTRS)

Blonigan, Patrick J.; Wang, Qiqi; Nielsen, Eric J.; Diskin, Boris

2017-01-01

We demonstrate a novel algorithm for computing the sensitivity of statistics in chaotic flow simulations to parameter perturbations. The algorithm is non-intrusive but requires exposing an interface. Based on the principle of shadowing in dynamical systems, this algorithm is designed to reduce the effect of the sampling error in computing sensitivity of statistics in chaotic simulations. We compare the effectiveness of this method to that of the conventional finite difference method.

Measuring Efficiency and Tradeoffs in Attainment of EEO Goals.

DTIC Science & Technology

1982-02-01

in FY78 and FY79. i.e., T9tese goals Are based on undifferentiated Civilian Labor Force (CLF) ratios required for reporting by the Equal Employment...Lewis and R.J. Niehaus, "Design and Development of Equal Employment Opportunity Human Resources Planning Models," NPDRC TR79--141 (San Diego: Navy...Approach to Analysis of Tradeoffs Among Household Ptoduction Outputs," American Statistical Association 1979 Proceedings of the Social Statistics Section

Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

PubMed

Giambartolomei, Claudia; Vukcevic, Damjan; Schadt, Eric E; Franke, Lude; Hingorani, Aroon D; Wallace, Chris; Plagnol, Vincent

2014-05-01

Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of the approach by re-analysing a gene expression dataset in 966 liver samples with a published meta-analysis of lipid traits including >100,000 individuals of European ancestry. Combining all lipid biomarkers, our re-analysis supported 26 out of 38 reported colocalisation results with eQTLs and identified 14 new colocalisation results, hence highlighting the value of a formal statistical test. In three cases of reported eQTL-lipid pairs (SYPL2, IFT172, TBKBP1) for which our analysis suggests that the eQTL pattern is not consistent with the lipid association, we identify alternative colocalisation results with SORT1, GCKR, and KPNB1, indicating that these genes are more likely to be causal in these genomic intervals. A key feature of the method is the ability to derive the output statistics from single SNP summary statistics, hence making it possible to perform systematic meta-analysis type comparisons across multiple GWAS datasets (implemented online at http://coloc.cs.ucl.ac.uk/coloc/). Our methodology provides information about candidate causal genes in associated intervals and has direct implications for the understanding of complex diseases as well as the design of drugs to target disease pathways.

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

Sample size re-estimation and other midcourse adjustments with sequential parallel comparison design.

PubMed

Silverman, Rachel K; Ivanova, Anastasia

2017-01-01

Sequential parallel comparison design (SPCD) was proposed to reduce placebo response in a randomized trial with placebo comparator. Subjects are randomized between placebo and drug in stage 1 of the trial, and then, placebo non-responders are re-randomized in stage 2. Efficacy analysis includes all data from stage 1 and all placebo non-responding subjects from stage 2. This article investigates the possibility to re-estimate the sample size and adjust the design parameters, allocation proportion to placebo in stage 1 of SPCD, and weight of stage 1 data in the overall efficacy test statistic during an interim analysis.

An overview of engineering concepts and current design algorithms for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Duffy, S. F.; Hu, J.; Hopkins, D. A.

1995-01-01

The article begins by examining the fundamentals of traditional deterministic design philosophy. The initial section outlines the concepts of failure criteria and limit state functions two traditional notions that are embedded in deterministic design philosophy. This is followed by a discussion regarding safety factors (a possible limit state function) and the common utilization of statistical concepts in deterministic engineering design approaches. Next the fundamental aspects of a probabilistic failure analysis are explored and it is shown that deterministic design concepts mentioned in the initial portion of the article are embedded in probabilistic design methods. For components fabricated from ceramic materials (and other similarly brittle materials) the probabilistic design approach yields the widely used Weibull analysis after suitable assumptions are incorporated. The authors point out that Weibull analysis provides the rare instance where closed form solutions are available for a probabilistic failure analysis. Since numerical methods are usually required to evaluate component reliabilities, a section on Monte Carlo methods is included to introduce the concept. The article concludes with a presentation of the technical aspects that support the numerical method known as fast probability integration (FPI). This includes a discussion of the Hasofer-Lind and Rackwitz-Fiessler approximations.

Classification Techniques for Multivariate Data Analysis.

DTIC Science & Technology

1980-03-28

analysis among biologists, botanists, and ecologists, while some social scientists may refer "typology". Other frequently encountered terms are pattern...the determinantal equation: lB -XW 0 (42) 49 The solutions X. are the eigenvalues of the matrix W-1 B 1 as in discriminant analysis. There are t non...Statistical Package for Social Sciences (SPSS) (14) subprogram FACTOR was used for the principal components analysis. It is designed both for the factor

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

PubMed Central

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

Precision, Reliability, and Effect Size of Slope Variance in Latent Growth Curve Models: Implications for Statistical Power Analysis

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; Ghisletta, Paolo; Lindenberger, Ulman; Hertzog, Christopher

2018-01-01

Latent Growth Curve Models (LGCM) have become a standard technique to model change over time. Prediction and explanation of inter-individual differences in change are major goals in lifespan research. The major determinants of statistical power to detect individual differences in change are the magnitude of true inter-individual differences in linear change (LGCM slope variance), design precision, alpha level, and sample size. Here, we show that design precision can be expressed as the inverse of effective error. Effective error is determined by instrument reliability and the temporal arrangement of measurement occasions. However, it also depends on another central LGCM component, the variance of the latent intercept and its covariance with the latent slope. We derive a new reliability index for LGCM slope variance—effective curve reliability (ECR)—by scaling slope variance against effective error. ECR is interpretable as a standardized effect size index. We demonstrate how effective error, ECR, and statistical power for a likelihood ratio test of zero slope variance formally relate to each other and how they function as indices of statistical power. We also provide a computational approach to derive ECR for arbitrary intercept-slope covariance. With practical use cases, we argue for the complementary utility of the proposed indices of a study's sensitivity to detect slope variance when making a priori longitudinal design decisions or communicating study designs. PMID:29755377

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

PubMed Central

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

2011-01-01

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

Protocol Analysis of Man-Computer Languages: Design and Preliminary Findings

DTIC Science & Technology

1975-07-01

describes a statistical moael o propot of the exercise. It is one particular model used for analysis of variance which allows us to test the significance of... Body : Congressman Blake will be visiting Camp Smith to confer with J6, J612, and Col. Smith with regard to operation of the pilot project on

SIMREL: Software for Coefficient Alpha and Its Confidence Intervals with Monte Carlo Studies

ERIC Educational Resources Information Center

Yurdugul, Halil

2009-01-01

This article describes SIMREL, a software program designed for the simulation of alpha coefficients and the estimation of its confidence intervals. SIMREL runs on two alternatives. In the first one, if SIMREL is run for a single data file, it performs descriptive statistics, principal components analysis, and variance analysis of the item scores…

Comparing the Effectiveness of SPSS and EduG Using Different Designs for Generalizability Theory

ERIC Educational Resources Information Center

Teker, Gulsen Tasdelen; Guler, Nese; Uyanik, Gulden Kaya

2015-01-01

Generalizability theory (G theory) provides a broad conceptual framework for social sciences such as psychology and education, and a comprehensive construct for numerous measurement events by using analysis of variance, a strong statistical method. G theory, as an extension of both classical test theory and analysis of variance, is a model which…

Implementation of Head Start Planned Variation: 1970-1971. Part II.

ERIC Educational Resources Information Center

Lukas, Carol Van Deusen; Wohlleb, Cynthia

This volume of appendices is Part II of a study of program implementation in 12 models of Head Start Planned Variation. It presents details of the data analysis, copies of data collection instruments, and additional analyses and statistics. The appendices are: (A) Analysis of Variance Designs, (B) Copies of Instruments, (C) Additional Analyses,…

A Content Analysis of Dissertations in the Field of Educational Technology: The Case of Turkey

ERIC Educational Resources Information Center

Durak, Gurhan; Cankaya, Serkan; Yunkul, Eyup; Misirli, Zeynel Abidin

2018-01-01

The present study aimed at conducting content analysis on dissertations carried out so far in the field of Educational Technology in Turkey. A total of 137 dissertations were examined to determine the key words, academic discipline, research areas, theoretical frameworks, research designs and models, statistical analyses, data collection tools,…

Some challenges with statistical inference in adaptive designs.

PubMed

Hung, H M James; Wang, Sue-Jane; Yang, Peiling

2014-01-01

Adaptive designs have generated a great deal of attention to clinical trial communities. The literature contains many statistical methods to deal with added statistical uncertainties concerning the adaptations. Increasingly encountered in regulatory applications are adaptive statistical information designs that allow modification of sample size or related statistical information and adaptive selection designs that allow selection of doses or patient populations during the course of a clinical trial. For adaptive statistical information designs, a few statistical testing methods are mathematically equivalent, as a number of articles have stipulated, but arguably there are large differences in their practical ramifications. We pinpoint some undesirable features of these methods in this work. For adaptive selection designs, the selection based on biomarker data for testing the correlated clinical endpoints may increase statistical uncertainty in terms of type I error probability, and most importantly the increased statistical uncertainty may be impossible to assess.

Models of dyadic social interaction.

PubMed Central

Griffin, Dale; Gonzalez, Richard

2003-01-01

We discuss the logic of research designs for dyadic interaction and present statistical models with parameters that are tied to psychologically relevant constructs. Building on Karl Pearson's classic nineteenth-century statistical analysis of within-organism similarity, we describe several approaches to indexing dyadic interdependence and provide graphical methods for visualizing dyadic data. We also describe several statistical and conceptual solutions to the 'levels of analytic' problem in analysing dyadic data. These analytic strategies allow the researcher to examine and measure psychological questions of interdependence and social influence. We provide illustrative data from casually interacting and romantic dyads. PMID:12689382

Statistical assessment of normal mitral annular geometry using automated three-dimensional echocardiographic analysis.

PubMed

Pouch, Alison M; Vergnat, Mathieu; McGarvey, Jeremy R; Ferrari, Giovanni; Jackson, Benjamin M; Sehgal, Chandra M; Yushkevich, Paul A; Gorman, Robert C; Gorman, Joseph H

2014-01-01

The basis of mitral annuloplasty ring design has progressed from qualitative surgical intuition to experimental and theoretical analysis of annular geometry with quantitative imaging techniques. In this work, we present an automated three-dimensional (3D) echocardiographic image analysis method that can be used to statistically assess variability in normal mitral annular geometry to support advancement in annuloplasty ring design. Three-dimensional patient-specific models of the mitral annulus were automatically generated from 3D echocardiographic images acquired from subjects with normal mitral valve structure and function. Geometric annular measurements including annular circumference, annular height, septolateral diameter, intercommissural width, and the annular height to intercommissural width ratio were automatically calculated. A mean 3D annular contour was computed, and principal component analysis was used to evaluate variability in normal annular shape. The following mean ± standard deviations were obtained from 3D echocardiographic image analysis: annular circumference, 107.0 ± 14.6 mm; annular height, 7.6 ± 2.8 mm; septolateral diameter, 28.5 ± 3.7 mm; intercommissural width, 33.0 ± 5.3 mm; and annular height to intercommissural width ratio, 22.7% ± 6.9%. Principal component analysis indicated that shape variability was primarily related to overall annular size, with more subtle variation in the skewness and height of the anterior annular peak, independent of annular diameter. Patient-specific 3D echocardiographic-based modeling of the human mitral valve enables statistical analysis of physiologically normal mitral annular geometry. The tool can potentially lead to the development of a new generation of annuloplasty rings that restore the diseased mitral valve annulus back to a truly normal geometry. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Fitting and Modeling in the ASC Data Analysis Environment

NASA Astrophysics Data System (ADS)

Doe, S.; Siemiginowska, A.; Joye, W.; McDowell, J.

As part of the AXAF Science Center (ASC) Data Analysis Environment, we will provide to the astronomical community a Fitting Application. We present a design of the application in this paper. Our design goal is to give the user the flexibility to use a variety of optimization techniques (Levenberg-Marquardt, maximum entropy, Monte Carlo, Powell, downhill simplex, CERN-Minuit, and simulated annealing) and fit statistics (chi (2) , Cash, variance, and maximum likelihood); our modular design allows the user easily to add their own optimization techniques and/or fit statistics. We also present a comparison of the optimization techniques to be provided by the Application. The high spatial and spectral resolutions that will be obtained with AXAF instruments require a sophisticated data modeling capability. We will provide not only a suite of astronomical spatial and spectral source models, but also the capability of combining these models into source models of up to four data dimensions (i.e., into source functions f(E,x,y,t)). We will also provide tools to create instrument response models appropriate for each observation.

Validation of the measure automobile emissions model : a statistical analysis

DOT National Transportation Integrated Search

2000-09-01

The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized e...

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

Code of Federal Regulations, 2010 CFR

2010-07-01

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

Application of probabilistic analysis/design methods in space programs - The approaches, the status, and the needs

NASA Technical Reports Server (NTRS)

Ryan, Robert S.; Townsend, John S.

1993-01-01

The prospective improvement of probabilistic methods for space program analysis/design entails the further development of theories, codes, and tools which match specific areas of application, the drawing of lessons from previous uses of probability and statistics data bases, the enlargement of data bases (especially in the field of structural failures), and the education of engineers and managers on the advantages of these methods. An evaluation is presently made of the current limitations of probabilistic engineering methods. Recommendations are made for specific applications.

Advanced support systems development and supporting technologies for Controlled Ecological Life Support Systems (CELSS)

NASA Technical Reports Server (NTRS)

Simon, William E.; Li, Ku-Yen; Yaws, Carl L.; Mei, Harry T.; Nguyen, Vinh D.; Chu, Hsing-Wei

1994-01-01

A methyl acetate reactor was developed to perform a subscale kinetic investigation in the design and optimization of a full-scale metabolic simulator for long term testing of life support systems. Other tasks in support of the closed ecological life support system test program included: (1) heating, ventilation and air conditioning analysis of a variable pressure growth chamber, (2) experimental design for statistical analysis of plant crops, (3) resource recovery for closed life support systems, and (4) development of data acquisition software for automating an environmental growth chamber.

Utah Virtual Lab: JAVA interactivity for teaching science and statistics on line.

PubMed

Malloy, T E; Jensen, G C

2001-05-01

The Utah on-line Virtual Lab is a JAVA program run dynamically off a database. It is embedded in StatCenter (www.psych.utah.edu/learn/statsampler.html), an on-line collection of tools and text for teaching and learning statistics. Instructors author a statistical virtual reality that simulates theories and data in a specific research focus area by defining independent, predictor, and dependent variables and the relations among them. Students work in an on-line virtual environment to discover the principles of this simulated reality: They go to a library, read theoretical overviews and scientific puzzles, and then go to a lab, design a study, collect and analyze data, and write a report. Each student's design and data analysis decisions are computer-graded and recorded in a database; the written research report can be read by the instructor or by other students in peer groups simulating scientific conventions.

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

PubMed Central

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

2009-01-01

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

Statistical analysis of tiny SXR flares observed by SphinX

NASA Astrophysics Data System (ADS)

Gryciuk, Magdalena; Siarkowski, Marek; Sylwester, Janusz; Kepa, Anna; Gburek, Szymon; Mrozek, Tomasz; Podgórski, Piotr

2015-08-01

The Solar Photometer in X-rays (SphinX) was designed to observe soft X-ray solar emission in the energy range between ~1 keV and 15 keV with the resolution better than 0.5 keV. The instrument operated from February until November 2009 aboard CORONAS-Photon satellite, during the phase of exceptionally low minimum of solar activity. Here we use SphinX data for analysis of micro-flares and brightenings. Despite a very low activity more than a thousand small X-ray events have been recognized by semi-automatic inspection of SphinX light curves. A catalogue of temporal and physical characteristics of these events is shown and discussed and results of the statistical analysis of the catalogue data are presented.

MWASTools: an R/bioconductor package for metabolome-wide association studies.

PubMed

Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel

2018-03-01

MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version  > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Clinical and Radiographic Mid-Term Outcomes After Total Shoulder Replacement: A Retrospective Study Protocol Including 400 Anatomical and Reverse Prosthetic Implants

PubMed Central

Merolla, Giovanni; Tartarone, Antonio; Porcellini, Giuseppe

2016-01-01

Objectives: To obtain outcomes data on anatomical and reverse total shoulder arthroplasty by analysis of clinical scores and standard radiographs. Subject selection and enrollment: 400 consecutive series of patients replaced with anatomical and reverse total shoulder arthroplasty (minimum 3 years follow-up). Study Design: retrospective monocenter. Preoperative assessment: Demographics, clinical scores (Constant-Murley) as available, shoulder X-ray (AP, outlet and axillary views) . Last follow-up: Postoperative radiographhs and clinical scores. Adverse events and complications to be reported as occurred since implantation. Statistical analysis: Data collected will be summarized and analyzed for statistical significance. PMID:27326389

Integrating statistical and clinical research elements in intervention-related grant applications: summary from an NIMH workshop.

PubMed

Sherrill, Joel T; Sommers, David I; Nierenberg, Andrew A; Leon, Andrew C; Arndt, Stephan; Bandeen-Roche, Karen; Greenhouse, Joel; Guthrie, Donald; Normand, Sharon-Lise; Phillips, Katharine A; Shear, M Katherine; Woolson, Robert

2009-01-01

The authors summarize points for consideration generated in a National Institute of Mental Health (NIMH) workshop convened to provide an opportunity for reviewers from different disciplines-specifically clinical researchers and statisticians-to discuss how their differing and complementary expertise can be well integrated in the review of intervention-related grant applications. A 1-day workshop was convened in October, 2004. The workshop featured panel presentations on key topics followed by interactive discussion. This article summarizes the workshop and subsequent discussions, which centered on topics including weighting the statistics/data analysis elements of an application in the assessment of the application's overall merit; the level of statistical sophistication appropriate to different stages of research and for different funding mechanisms; some key considerations in the design and analysis portions of applications; appropriate statistical methods for addressing essential questions posed by an application; and the role of the statistician in the application's development, study conduct, and interpretation and dissemination of results. A number of key elements crucial to the construction and review of grant applications were identified. It was acknowledged that intervention-related studies unavoidably involve trade-offs. Reviewers are helped when applications acknowledge such trade-offs and provide good rationale for their choices. Clear linkage among the design, aims, hypotheses, and data analysis plan and avoidance of disconnections among these elements also strengthens applications. The authors identify multiple points to consider when constructing intervention-related grant applications. The points are presented here as questions and do not reflect institute policy or comprise a list of best practices, but rather represent points for consideration.

Phenolic Analysis and Theoretic Design for Chinese Commercial Wines' Authentication.

PubMed

Li, Si-Yu; Zhu, Bao-Qing; Reeves, Malcolm J; Duan, Chang-Qing

2018-01-01

To develop a robust tool for Chinese commercial wines' varietal, regional, and vintage authentication, phenolic compounds in 121 Chinese commercial dry red wines were detected and quantified by using high-performance liquid chromatography triple-quadrupole mass spectrometry (HPLC-QqQ-MS/MS), and differentiation abilities of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were compared. Better than PCA and PLS-DA, OPLS-DA models used to differentiate wines according to their varieties (Cabernet Sauvignon or other varieties), regions (east or west Cabernet Sauvignon wines), and vintages (young or old Cabernet Sauvignon wines) were ideally established. The S-plot provided in OPLS-DA models showed the key phenolic compounds which were both statistically and biochemically significant in sample differentiation. Besides, the potential of the OPLS-DA models in deeper sample differentiating of more detailed regional and vintage information of wines was proved optimistic. On the basis of our results, a promising theoretic design for wine authentication was further proposed for the first time, which might be helpful in practical authentication of more commercial wines. The phenolic data of 121 Chinese commercial dry red wines was processed with different statistical tools for varietal, regional, and vintage differentiation. A promising theoretical design was summarized, which might be helpful for wine authentication in practical situation. © 2017 Institute of Food Technologists®.

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Sparks, Dean W., Jr.

1997-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Design of neural networks for fast convergence and accuracy: dynamics and control.

PubMed

Maghami, P G; Sparks, D R

2000-01-01

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

An optimal stratified Simon two-stage design.

PubMed

Parashar, Deepak; Bowden, Jack; Starr, Colin; Wernisch, Lorenz; Mander, Adrian

2016-07-01

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants' molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: 'An adaptive Simon two-stage design for phase 2 studies of targeted therapies', Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Methodological considerations, such as directed acyclic graphs, for studying "acute on chronic" disease epidemiology: chronic obstructive pulmonary disease example.

PubMed

Tsai, Chu-Lin; Camargo, Carlos A

2009-09-01

Acute exacerbations of chronic disease are ubiquitous in clinical medicine, and thus far, there has been a paucity of integrated methodological discussion on this phenomenon. We use acute exacerbations of chronic obstructive pulmonary disease as an example to emphasize key epidemiological and statistical issues for this understudied field in clinical epidemiology. Directed acyclic graphs are a useful epidemiological tool to explain the differential effects of risk factor on health outcomes in studies of acute and chronic phases of disease. To study the pathogenesis of acute exacerbations of chronic disease, case-crossover design and time-series analysis are well-suited study designs to differentiate acute and chronic effect. Modeling changes over time and setting appropriate thresholds are important steps to separate acute from chronic phases of disease in serial measurements. In statistical analysis, acute exacerbations are recurrent events, and some individuals are more prone to recurrences than others. Therefore, appropriate statistical modeling should take into account intraindividual dependence. Finally, we recommend the use of "event-based" number needed to treat (NNT) to prevent a single exacerbation instead of traditional patient-based NNT. Addressing these methodological challenges will advance research quality in acute on chronic disease epidemiology.

Machine learning patterns for neuroimaging-genetic studies in the cloud.

PubMed

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Targeting change: Assessing a faculty learning community focused on increasing statistics content in life science curricula.

PubMed

Parker, Loran Carleton; Gleichsner, Alyssa M; Adedokun, Omolola A; Forney, James

2016-11-12

Transformation of research in all biological fields necessitates the design, analysis and, interpretation of large data sets. Preparing students with the requisite skills in experimental design, statistical analysis, and interpretation, and mathematical reasoning will require both curricular reform and faculty who are willing and able to integrate mathematical and statistical concepts into their life science courses. A new Faculty Learning Community (FLC) was constituted each year for four years to assist in the transformation of the life sciences curriculum and faculty at a large, Midwestern research university. Participants were interviewed after participation and surveyed before and after participation to assess the impact of the FLC on their attitudes toward teaching, perceived pedagogical skills, and planned teaching practice. Overall, the FLC had a meaningful positive impact on participants' attitudes toward teaching, knowledge about teaching, and perceived pedagogical skills. Interestingly, confidence for viewing the classroom as a site for research about teaching declined. Implications for the creation and development of FLCs for science faculty are discussed. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(6):517-525, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

40 CFR Appendix C to Part 136 - Determination of Metals and Trace Elements in Water and Wastes by Inductively Coupled Plasma...

Code of Federal Regulations, 2014 CFR

2014-07-01

... comparative data to other methods and SRM materials are presented in Reference 23 of Section 16.0. 13... Plasma, Anal. Chem. 52:1965, 1980. 20. Deming, S.N. and S.L. Morgan. Experimental Design for Quality and... Statistical Designs, 9941 Rowlett, Suite 6, Houston, TX 77075, 1989. 21. Winefordner, J.D., Trace Analysis...

40 CFR Appendix C to Part 136 - Determination of Metals and Trace Elements in Water and Wastes by Inductively Coupled Plasma...

Code of Federal Regulations, 2013 CFR

2013-07-01

... comparative data to other methods and SRM materials are presented in Reference 23 of Section 16.0. 13... Plasma, Anal. Chem. 52:1965, 1980. 20. Deming, S.N. and S.L. Morgan. Experimental Design for Quality and... Statistical Designs, 9941 Rowlett, Suite 6, Houston, TX 77075, 1989. 21. Winefordner, J.D., Trace Analysis...

40 CFR Appendix C to Part 136 - Determination of Metals and Trace Elements in Water and Wastes by Inductively Coupled Plasma...

Code of Federal Regulations, 2012 CFR

2012-07-01

... comparative data to other methods and SRM materials are presented in Reference 23 of Section 16.0. 13... Plasma, Anal. Chem. 52:1965, 1980. 20. Deming, S.N. and S.L. Morgan. Experimental Design for Quality and... Statistical Designs, 9941 Rowlett, Suite 6, Houston, TX 77075, 1989. 21. Winefordner, J.D., Trace Analysis...

The Design and Development of a Context-Rich, Photo-Based Online Testing to Assess Students' Science Learning

ERIC Educational Resources Information Center

Lin, Min-Jin; Guo, Chorng-Jee; Hsu, Chia-Er

2011-01-01

This study designed and developed a CP-MCT (content-rich, photo-based multiple choice online test) to assess whether college students can apply the basic light concept to interpret daily light phenomena. One hundred college students volunteered to take the CP-MCT, and the results were statistically analyzed by applying t-test or ANOVA (Analysis of…

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

USGS Publications Warehouse

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

1998-01-01

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

SRS 2010 Vegetation Inventory GeoStatistical Mapping Results for Custom Reaction Intensity and Total Dead Fuels.

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

Edwards, Lloyd A.; Paresol, Bernard

This report of the geostatistical analysis results of the fire fuels response variables, custom reaction intensity and total dead fuels is but a part of an SRS 2010 vegetation inventory project. For detailed description of project, theory and background including sample design, methods, and results please refer to USDA Forest Service Savannah River Site internal report “SRS 2010 Vegetation Inventory GeoStatistical Mapping Report”, (Edwards & Parresol 2013).

A review of statistical issues with progression-free survival as an interval-censored time-to-event endpoint.

PubMed

Sun, Xing; Li, Xiaoyun; Chen, Cong; Song, Yang

2013-01-01

Frequent rise of interval-censored time-to-event data in randomized clinical trials (e.g., progression-free survival [PFS] in oncology) challenges statistical researchers in the pharmaceutical industry in various ways. These challenges exist in both trial design and data analysis. Conventional statistical methods treating intervals as fixed points, which are generally practiced by pharmaceutical industry, sometimes yield inferior or even flawed analysis results in extreme cases for interval-censored data. In this article, we examine the limitation of these standard methods under typical clinical trial settings and further review and compare several existing nonparametric likelihood-based methods for interval-censored data, methods that are more sophisticated but robust. Trial design issues involved with interval-censored data comprise another topic to be explored in this article. Unlike right-censored survival data, expected sample size or power for a trial with interval-censored data relies heavily on the parametric distribution of the baseline survival function as well as the frequency of assessments. There can be substantial power loss in trials with interval-censored data if the assessments are very infrequent. Such an additional dependency controverts many fundamental assumptions and principles in conventional survival trial designs, especially the group sequential design (e.g., the concept of information fraction). In this article, we discuss these fundamental changes and available tools to work around their impacts. Although progression-free survival is often used as a discussion point in the article, the general conclusions are equally applicable to other interval-censored time-to-event endpoints.

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

Gilbert, Richard O.

The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Somemore » statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.« less

Meta-analysis of neutropenia or leukopenia as a prognostic factor in patients with malignant disease undergoing chemotherapy.

PubMed

Shitara, Kohei; Matsuo, Keitaro; Oze, Isao; Mizota, Ayako; Kondo, Chihiro; Nomura, Motoo; Yokota, Tomoya; Takahari, Daisuke; Ura, Takashi; Muro, Kei

2011-08-01

We performed a systematic review and meta-analysis to determine the impact of neutropenia or leukopenia experienced during chemotherapy on survival. Eligible studies included prospective or retrospective analyses that evaluated neutropenia or leukopenia as a prognostic factor for overall survival or disease-free survival. Statistical analyses were conducted to calculate a summary hazard ratio and 95% confidence interval (CI) using random-effects or fixed-effects models based on the heterogeneity of the included studies. Thirteen trials were selected for the meta-analysis, with a total of 9,528 patients. The hazard ratio of death was 0.69 (95% CI, 0.64-0.75) for patients with higher-grade neutropenia or leukopenia compared to patients with lower-grade or lack of cytopenia. Our analysis was also stratified by statistical method (any statistical method to decrease lead-time bias; time-varying analysis or landmark analysis), but no differences were observed. Our results indicate that neutropenia or leukopenia experienced during chemotherapy is associated with improved survival in patients with advanced cancer or hematological malignancies undergoing chemotherapy. Future prospective analyses designed to investigate the potential impact of chemotherapy dose adjustment coupled with monitoring of neutropenia or leukopenia on survival are warranted.

Anima: Modular Workflow System for Comprehensive Image Data Analysis

PubMed Central

Rantanen, Ville; Valori, Miko; Hautaniemi, Sampsa

2014-01-01

Modern microscopes produce vast amounts of image data, and computational methods are needed to analyze and interpret these data. Furthermore, a single image analysis project may require tens or hundreds of analysis steps starting from data import and pre-processing to segmentation and statistical analysis; and ending with visualization and reporting. To manage such large-scale image data analysis projects, we present here a modular workflow system called Anima. Anima is designed for comprehensive and efficient image data analysis development, and it contains several features that are crucial in high-throughput image data analysis: programing language independence, batch processing, easily customized data processing, interoperability with other software via application programing interfaces, and advanced multivariate statistical analysis. The utility of Anima is shown with two case studies focusing on testing different algorithms developed in different imaging platforms and an automated prediction of alive/dead C. elegans worms by integrating several analysis environments. Anima is a fully open source and available with documentation at www.anduril.org/anima. PMID:25126541

PCR evaluation : considering transition from manual to semi-automated pavement distress collection and analysis.

DOT National Transportation Integrated Search

2013-07-01

This study is designed to assist the Ohio Department of Transportation (ODOT) in determining : whether transitioning from manual to state-of the-practice semi-automated pavement distress : data collection is feasible and recommended. Statistical and ...

Analysis of spectrum utilization and message length statistics for the railroad land mobile radio service

DOT National Transportation Integrated Search

1997-11-01

In support of the Federal Railroad Administration of the United States Department of Transportation, the Institute for Telecommunication Sciences (ITS) has completed a field spectrum uitilization survey designed to examine individual channel utilizat...

Black Male Labor Force Participation.

ERIC Educational Resources Information Center

Baer, Roger K.

This study attempts to test (via multiple regression analysis) hypothesized relationships between designated independent variables and age specific incidences of labor force participation for black male subpopulations in 54 Standard Metropolitan Statistical Areas. Leading independent variables tested include net migration, earnings, unemployment,…

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

Spatially referenced crash data system for application to commercial motor vehicle crashes.

DOT National Transportation Integrated Search

2003-05-01

The Maryland Spatial Analysis of Crashes (MSAC) project involves the design of a : prototype of a geographic information system (GIS) for the State of Maryland that has : the capability of providing online crash information and statistical informatio...

Statistical analysis of spectral data: a methodology for designing an intelligent monitoring system for the diabetic foot

NASA Astrophysics Data System (ADS)

Liu, Chanjuan; van Netten, Jaap J.; Klein, Marvin E.; van Baal, Jeff G.; Bus, Sicco A.; van der Heijden, Ferdi

2013-12-01

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

An ANOVA approach for statistical comparisons of brain networks.

PubMed

Fraiman, Daniel; Fraiman, Ricardo

2018-03-16

The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.

Visual Sample Plan Version 7.0 User's Guide

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

Matzke, Brett D.; Newburn, Lisa LN; Hathaway, John E.

2014-03-01

User's guide for VSP 7.0 This user's guide describes Visual Sample Plan (VSP) Version 7.0 and provides instructions for using the software. VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 7.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination.more » The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (XP, Vista, Windows 7, and Windows 8). Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem/rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for unexploded ordnance (UXO) identification.« less

Statistical Approaches to Interpretation of Local, Regional, and National Highway-Runoff and Urban-Stormwater Data

USGS Publications Warehouse

Tasker, Gary D.; Granato, Gregory E.

2000-01-01

Decision makers need viable methods for the interpretation of local, regional, and national-highway runoff and urban-stormwater data including flows, concentrations and loads of chemical constituents and sediment, potential effects on receiving waters, and the potential effectiveness of various best management practices (BMPs). Valid (useful for intended purposes), current, and technically defensible stormwater-runoff models are needed to interpret data collected in field studies, to support existing highway and urban-runoffplanning processes, to meet National Pollutant Discharge Elimination System (NPDES) requirements, and to provide methods for computation of Total Maximum Daily Loads (TMDLs) systematically and economically. Historically, conceptual, simulation, empirical, and statistical models of varying levels of detail, complexity, and uncertainty have been used to meet various data-quality objectives in the decision-making processes necessary for the planning, design, construction, and maintenance of highways and for other land-use applications. Water-quality simulation models attempt a detailed representation of the physical processes and mechanisms at a given site. Empirical and statistical regional water-quality assessment models provide a more general picture of water quality or changes in water quality over a region. All these modeling techniques share one common aspect-their predictive ability is poor without suitable site-specific data for calibration. To properly apply the correct model, one must understand the classification of variables, the unique characteristics of water-resources data, and the concept of population structure and analysis. Classifying variables being used to analyze data may determine which statistical methods are appropriate for data analysis. An understanding of the characteristics of water-resources data is necessary to evaluate the applicability of different statistical methods, to interpret the results of these techniques, and to use tools and techniques that account for the unique nature of water-resources data sets. Populations of data on stormwater-runoff quantity and quality are often best modeled as logarithmic transformations. Therefore, these factors need to be considered to form valid, current, and technically defensible stormwater-runoff models. Regression analysis is an accepted method for interpretation of water-resources data and for prediction of current or future conditions at sites that fit the input data model. Regression analysis is designed to provide an estimate of the average response of a system as it relates to variation in one or more known variables. To produce valid models, however, regression analysis should include visual analysis of scatterplots, an examination of the regression equation, evaluation of the method design assumptions, and regression diagnostics. A number of statistical techniques are described in the text and in the appendixes to provide information necessary to interpret data by use of appropriate methods. Uncertainty is an important part of any decisionmaking process. In order to deal with uncertainty problems, the analyst needs to know the severity of the statistical uncertainty of the methods used to predict water quality. Statistical models need to be based on information that is meaningful, representative, complete, precise, accurate, and comparable to be deemed valid, up to date, and technically supportable. To assess uncertainty in the analytical tools, the modeling methods, and the underlying data set, all of these components need be documented and communicated in an accessible format within project publications.

Evaluating the efficiency of environmental monitoring programs

USGS Publications Warehouse

Levine, Carrie R.; Yanai, Ruth D.; Lampman, Gregory G.; Burns, Douglas A.; Driscoll, Charles T.; Lawrence, Gregory B.; Lynch, Jason; Schoch, Nina

2014-01-01

Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.

Trajectory Design for a Single-String Impactor Concept

NASA Technical Reports Server (NTRS)

Dono Perez, Andres; Burton, Roland; Stupl, Jan; Mauro, David

2017-01-01

This paper introduces a trajectory design for a secondary spacecraft concept to augment science return in interplanetary missions. The concept consist of a single-string probe with a kinetic impactor on board that generates an artificial plume to perform in-situ sampling. The trajectory design was applied to a particular case study that samples ejecta particles from the Jovian moon Europa. Results were validated using statistical analysis. Details regarding the navigation, targeting and disposal challenges related to this concept are presented herein.

A design methodology for nonlinear systems containing parameter uncertainty

NASA Technical Reports Server (NTRS)

Young, G. E.; Auslander, D. M.

1983-01-01

In the present design methodology for nonlinear systems containing parameter uncertainty, a generalized sensitivity analysis is incorporated which employs parameter space sampling and statistical inference. For the case of a system with j adjustable and k nonadjustable parameters, this methodology (which includes an adaptive random search strategy) is used to determine the combination of j adjustable parameter values which maximize the probability of those performance indices which simultaneously satisfy design criteria in spite of the uncertainty due to k nonadjustable parameters.

Response to Comments on "Ducklings imprint on the relational concept of 'same or different'".

PubMed

Martinho, Antone; Kacelnik, Alex

2017-02-24

Two Comments by Hupé and by Langbein and Puppe address our choice of statistical analysis in assigning preference between sets of stimuli to individual ducklings in our paper. We believe that our analysis remains the most appropriate approach for our data and experimental design. Copyright © 2017, American Association for the Advancement of Science.

A Secondary Analysis of the Impact of School Management Practices on School Performance

ERIC Educational Resources Information Center

Talbert, Dale A.

2009-01-01

The purpose of this study was to conduct a secondary analysis of the impact of school management practices on school performance utilizing a survey design of School and Staffing (SASS) data collected by the National Center for Education Statistics (NCES) of the U.S. Department of Education, 1999-2000. The study identifies those school management…

Highly Efficient Design-of-Experiments Methods for Combining CFD Analysis and Experimental Data

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Haller, Harold S.

2009-01-01

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different.

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

PubMed

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

2017-06-01

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

A powerful approach for association analysis incorporating imprinting effects

PubMed Central

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

2011-01-01

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

A powerful approach for association analysis incorporating imprinting effects.

PubMed

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

2011-09-15

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

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

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

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

NASA Technical Reports Server (NTRS)

Hailperin, Max

1993-01-01

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

PubMed

Yue Xu, Selene; Nelson, Sandahl; Kerr, Jacqueline; Godbole, Suneeta; Patterson, Ruth; Merchant, Gina; Abramson, Ian; Staudenmayer, John; Natarajan, Loki

2018-04-01

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis.

PubMed

Amlung, M; Petker, T; Jackson, J; Balodis, I; MacKillop, J

2016-08-01

An increasing number of studies have investigated delay discounting (DD) in relation to obesity, but with mixed findings. This meta-analysis synthesized the literature on the relationship between monetary and food DD and obesity, with three objectives: (1) to characterize the relationship between DD and obesity in both case-control comparisons and continuous designs; (2) to examine potential moderators, including case-control v. continuous design, money v. food rewards, sample sex distribution, and sample age (18 years); and (3) to evaluate publication bias. From 134 candidate articles, 39 independent investigations yielded 29 case-control and 30 continuous comparisons (total n = 10 278). Random-effects meta-analysis was conducted using Cohen's d as the effect size. Publication bias was evaluated using fail-safe N, Begg-Mazumdar and Egger tests, meta-regression of publication year and effect size, and imputation of missing studies. The primary analysis revealed a medium effect size across studies that was highly statistically significant (d = 0.43, p < 10-14). None of the moderators examined yielded statistically significant differences, although notably larger effect sizes were found for studies with case-control designs, food rewards and child/adolescent samples. Limited evidence of publication bias was present, although the Begg-Mazumdar test and meta-regression suggested a slightly diminishing effect size over time. Steep DD of food and money appears to be a robust feature of obesity that is relatively consistent across the DD assessment methodologies and study designs examined. These findings are discussed in the context of research on DD in drug addiction, the neural bases of DD in obesity, and potential clinical applications.

Statistical Methodologies to Integrate Experimental and Computational Research

NASA Technical Reports Server (NTRS)

Parker, P. A.; Johnson, R. T.; Montgomery, D. C.

2008-01-01

Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.

CRACK GROWTH ANALYSIS OF SOLID OXIDE FUEL CELL ELECTROLYTES

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

S. Bandopadhyay; N. Nagabhushana

2003-10-01

Defects and Flaws control the structural and functional property of ceramics. In determining the reliability and lifetime of ceramics structures it is very important to quantify the crack growth behavior of the ceramics. In addition, because of the high variability of the strength and the relatively low toughness of ceramics, a statistical design approach is necessary. The statistical nature of the strength of ceramics is currently well recognized, and is usually accounted for by utilizing Weibull or similar statistical distributions. Design tools such as CARES using a combination of strength measurements, stress analysis, and statistics are available and reasonably wellmore » developed. These design codes also incorporate material data such as elastic constants as well as flaw distributions and time-dependent properties. The fast fracture reliability for ceramics is often different from their time-dependent reliability. Further confounding the design complexity, the time-dependent reliability varies with the environment/temperature/stress combination. Therefore, it becomes important to be able to accurately determine the behavior of ceramics under simulated application conditions to provide a better prediction of the lifetime and reliability for a given component. In the present study, Yttria stabilized Zirconia (YSZ) of 9.6 mol% Yttria composition was procured in the form of tubes of length 100 mm. The composition is of interest as tubular electrolytes for Solid Oxide Fuel Cells. Rings cut from the tubes were characterized for microstructure, phase stability, mechanical strength (Weibull modulus) and fracture mechanisms. The strength at operating condition of SOFCs (1000 C) decreased to 95 MPa as compared to room temperature strength of 230 MPa. However, the Weibull modulus remains relatively unchanged. Slow crack growth (SCG) parameter, n = 17 evaluated at room temperature in air was representative of well studied brittle materials. Based on the results, further work was planned to evaluate the strength degradation, modulus and failure in more representative environment of the SOFCs.« less

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

NASA Technical Reports Server (NTRS)

Hailperin, M.

1993-01-01

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

Exploring the statistical and clinical impact of two interim analyses on the Phase II design with option for direct assignment.

PubMed

An, Ming-Wen; Mandrekar, Sumithra J; Edelman, Martin J; Sargent, Daniel J

2014-07-01

The primary goal of Phase II clinical trials is to understand better a treatment's safety and efficacy to inform a Phase III go/no-go decision. Many Phase II designs have been proposed, incorporating randomization, interim analyses, adaptation, and patient selection. The Phase II design with an option for direct assignment (i.e. stop randomization and assign all patients to the experimental arm based on a single interim analysis (IA) at 50% accrual) was recently proposed [An et al., 2012]. We discuss this design in the context of existing designs, and extend it from a single-IA to a two-IA design. We compared the statistical properties and clinical relevance of the direct assignment design with two IA (DAD-2) versus a balanced randomized design with two IA (BRD-2) and a direct assignment design with one IA (DAD-1), over a range of response rate ratios (2.0-3.0). The DAD-2 has minimal loss in power (<2.2%) and minimal increase in T1ER (<1.6%) compared to a BRD-2. As many as 80% more patients were treated with experimental vs. control in the DAD-2 than with the BRD-2 (experimental vs. control ratio: 1.8 vs. 1.0), and as many as 64% more in the DAD-2 than with the DAD-1 (1.8 vs. 1.1). We illustrate the DAD-2 using a case study in lung cancer. In the spectrum of Phase II designs, the direct assignment design, especially with two IA, provides a middle ground with desirable statistical properties and likely appeal to both clinicians and patients. Copyright © 2014 Elsevier Inc. All rights reserved.

CRAX. Cassandra Exoskeleton

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

Robinson, D.G.; Eubanks, L.

1998-03-01

This software assists the engineering designer in characterizing the statistical uncertainty in the performance of complex systems as a result of variations in manufacturing processes, material properties, system geometry or operating environment. The software is composed of a graphical user interface that provides the user with easy access to Cassandra uncertainty analysis routines. Together this interface and the Cassandra routines are referred to as CRAX (CassandRA eXoskeleton). The software is flexible enough, that with minor modification, it is able to interface with large modeling and analysis codes such as heat transfer or finite element analysis software. The current version permitsmore » the user to manually input a performance function, the number of random variables and their associated statistical characteristics: density function, mean, coefficients of variation. Additional uncertainity analysis modules are continuously being added to the Cassandra core.« less

Cassandra Exoskeleton

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

Robiinson, David G.

1999-02-20

This software assists the engineering designer in characterizing the statistical uncertainty in the performance of complex systems as a result of variations in manufacturing processes, material properties, system geometry or operating environment. The software is composed of a graphical user interface that provides the user with easy access to Cassandra uncertainty analysis routines. Together this interface and the Cassandra routines are referred to as CRAX (CassandRA eXoskeleton). The software is flexible enough, that with minor modification, it is able to interface with large modeling and analysis codes such as heat transfer or finite element analysis software. The current version permitsmore » the user to manually input a performance function, the number of random variables and their associated statistical characteristics: density function, mean, coefficients of variation. Additional uncertainity analysis modules are continuously being added to the Cassandra core.« less

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.

PubMed

Oberg, Ann L; Mahoney, Douglas W

2012-01-01

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

Interpretation of statistical results.

PubMed

García Garmendia, J L; Maroto Monserrat, F

2018-02-21

The appropriate interpretation of the statistical results is crucial to understand the advances in medical science. The statistical tools allow us to transform the uncertainty and apparent chaos in nature to measurable parameters which are applicable to our clinical practice. The importance of understanding the meaning and actual extent of these instruments is essential for researchers, the funders of research and for professionals who require a permanent update based on good evidence and supports to decision making. Various aspects of the designs, results and statistical analysis are reviewed, trying to facilitate his comprehension from the basics to what is most common but no better understood, and bringing a constructive, non-exhaustive but realistic look. Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

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.

DESIGNA ND ANALYSIS FOR THEMATIC MAP ACCURACY ASSESSMENT: FUNDAMENTAL PRINCIPLES

EPA Science Inventory

Before being used in scientific investigations and policy decisions, thematic maps constructed from remotely sensed data should be subjected to a statistically rigorous accuracy assessment. The three basic components of an accuracy assessment are: 1) the sampling design used to s...

Evaluation of bearing capacity of piles from cone penetration test data.

DOT National Transportation Integrated Search

2007-12-01

A statistical analysis and ranking criteria were used to compare the CPT methods and the conventional alpha design method. Based on the results, the de Ruiter/Beringen and LCPC methods showed the best capability in predicting the measured load carryi...

Prostate Cancer Disparities in an Incarcerated Community

DTIC Science & Technology

2013-09-01

Based Medicine & Health Outcomes Research 12901 Bruce B Downs Blvd. MDC 02 Tampa, Florida 33612-4799 (Study Design and Interpretation) Task 1...Clinical Research 12901 Bruce B. Downs Blvd. MDC 2 Tampa, Florida 33612-4799 (Statistical Analysis) University of South Florida Center for Evidence

The use and misuse of statistical methodologies in pharmacology research.

PubMed

Marino, Michael J

2014-01-01

Descriptive, exploratory, and inferential statistics are necessary components of hypothesis-driven biomedical research. Despite the ubiquitous need for these tools, the emphasis on statistical methods in pharmacology has become dominated by inferential methods often chosen more by the availability of user-friendly software than by any understanding of the data set or the critical assumptions of the statistical tests. Such frank misuse of statistical methodology and the quest to reach the mystical α<0.05 criteria has hampered research via the publication of incorrect analysis driven by rudimentary statistical training. Perhaps more critically, a poor understanding of statistical tools limits the conclusions that may be drawn from a study by divorcing the investigator from their own data. The net result is a decrease in quality and confidence in research findings, fueling recent controversies over the reproducibility of high profile findings and effects that appear to diminish over time. The recent development of "omics" approaches leading to the production of massive higher dimensional data sets has amplified these issues making it clear that new approaches are needed to appropriately and effectively mine this type of data. Unfortunately, statistical education in the field has not kept pace. This commentary provides a foundation for an intuitive understanding of statistics that fosters an exploratory approach and an appreciation for the assumptions of various statistical tests that hopefully will increase the correct use of statistics, the application of exploratory data analysis, and the use of statistical study design, with the goal of increasing reproducibility and confidence in the literature. Copyright © 2013. Published by Elsevier Inc.

Mapping remote and multidisciplinary learning barriers: lessons from challenge-based innovation at CERN

NASA Astrophysics Data System (ADS)

Jensen, Matilde Bisballe; Utriainen, Tuuli Maria; Steinert, Martin

2018-01-01

This paper presents the experienced difficulties of students participating in the multidisciplinary, remote collaborating engineering design course challenge-based innovation at CERN. This is with the aim to identify learning barriers and improve future learning experiences. We statistically analyse the rated differences between distinct design activities, educational background and remote vs. co-located collaboration. The analysis is based on a quantitative and qualitative questionnaire (N = 37). Our analysis found significant ranking differences between remote and co-located activities. This questions whether the remote factor might be a barrier for the originally intended learning goals. Further a correlation between analytical and converging design phases was identified. Hence, future facilitators are suggested to help students in the transition from one design phase to the next rather than only teaching methods in the individual design phases. Finally, we discuss how educators address the identified learning barriers when designing future courses including multidisciplinary or remote collaboration.

Parameters optimization defined by statistical analysis for cysteine-dextran radiolabeling with technetium tricarbonyl core.

PubMed

Núñez, Eutimio Gustavo Fernández; Faintuch, Bluma Linkowski; Teodoro, Rodrigo; Wiecek, Danielle Pereira; da Silva, Natanael Gomes; Papadopoulos, Minas; Pelecanou, Maria; Pirmettis, Ioannis; de Oliveira Filho, Renato Santos; Duatti, Adriano; Pasqualini, Roberto

2011-04-01

The objective of this study was the development of a statistical approach for radiolabeling optimization of cysteine-dextran conjugates with Tc-99m tricarbonyl core. This strategy has been applied to the labeling of 2-propylene-S-cysteine-dextran in the attempt to prepare a new class of tracers for sentinel lymph node detection, and can be extended to other radiopharmaceuticals for different targets. The statistical routine was based on three-level factorial design. Best labeling conditions were achieved. The specific activity reached was 5 MBq/μg. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Surface flaw reliability analysis of ceramic components with the SCARE finite element postprocessor program

NASA Technical Reports Server (NTRS)

Gyekenyesi, John P.; Nemeth, Noel N.

1987-01-01

The SCARE (Structural Ceramics Analysis and Reliability Evaluation) computer program on statistical fast fracture reliability analysis with quadratic elements for volume distributed imperfections is enhanced to include the use of linear finite elements and the capability of designing against concurrent surface flaw induced ceramic component failure. The SCARE code is presently coupled as a postprocessor to the MSC/NASTRAN general purpose, finite element analysis program. The improved version now includes the Weibull and Batdorf statistical failure theories for both surface and volume flaw based reliability analysis. The program uses the two-parameter Weibull fracture strength cumulative failure probability distribution model with the principle of independent action for poly-axial stress states, and Batdorf's shear-sensitive as well as shear-insensitive statistical theories. The shear-sensitive surface crack configurations include the Griffith crack and Griffith notch geometries, using the total critical coplanar strain energy release rate criterion to predict mixed-mode fracture. Weibull material parameters based on both surface and volume flaw induced fracture can also be calculated from modulus of rupture bar tests, using the least squares method with known specimen geometry and grouped fracture data. The statistical fast fracture theories for surface flaw induced failure, along with selected input and output formats and options, are summarized. An example problem to demonstrate various features of the program is included.

National Indian Education Study Part I: The Performance of American Indian and Alaska Native Fourth-and Eighth-Grade Students on NAEP 2005 Reading and Mathematics Assessments Statistical Analysis Report. NCES 2006-463

ERIC Educational Resources Information Center

Rampey, B.D.; Lutkus, Anthony D.; Weiner, Arlene W.; Rahman, Taslima

2006-01-01

The National Indian Education Study is a two-part study designed to describe the condition of education for American Indian/Alaska Native students in the United States. The study was conducted by the National Center for Education Statistics for the U.S. Department of Education, with the support of the Office of Indian Education. This report, Part…

Statistics, Uncertainty, and Transmitted Variation

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

Wendelberger, Joanne Roth

2014-11-05

The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.

Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.

1998-01-01

The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.

Analysis of Nonequivalent Assessments across Different Linguistic Groups Using a Mixed Methods Approach: Understanding the Causes of Differential Item Functioning by Cognitive Interviewing

ERIC Educational Resources Information Center

Benítez, Isabel; Padilla, José-Luis

2014-01-01

Differential item functioning (DIF) can undermine the validity of cross-lingual comparisons. While a lot of efficient statistics for detecting DIF are available, few general findings have been found to explain DIF results. The objective of the article was to study DIF sources by using a mixed method design. The design involves a quantitative phase…

Statistical Models and Inference Procedures for Structural and Materials Reliability

DTIC Science & Technology

1990-12-01

as an official Department of the Army positio~n, policy, or decision, unless sD designated by other documentazion. 12a. DISTRIBUTION /AVAILABILITY...Some general stress-strength models were also developed and applied to the failure of systems subject to cyclic loading. Involved in the failure of...process control ideas and sequential design and analysis methods. Finally, smooth nonparametric quantile .wJ function estimators were studied. All of

Fulfilling the law of a single independent variable and improving the result of mathematical educational research

NASA Astrophysics Data System (ADS)

Pardimin, H.; Arcana, N.

2018-01-01

Many types of research in the field of mathematics education apply the Quasi-Experimental method and statistical analysis use t-test. Quasi-experiment has a weakness that is difficult to fulfil “the law of a single independent variable”. T-test also has a weakness that is a generalization of the conclusions obtained is less powerful. This research aimed to find ways to reduce the weaknesses of the Quasi-experimental method and improved the generalization of the research results. The method applied in the research was a non-interactive qualitative method, and the type was concept analysis. Concepts analysed are the concept of statistics, research methods of education, and research reports. The result represented a way to overcome the weaknesses of quasi-Experiments and T-test. In addition, the way was to apply a combination of Factorial Design and Balanced Design, which the authors refer to as Factorial-Balanced Design. The advantages of this design are: (1) almost fulfilling “the low of single independent variable” so no need to test the similarity of the academic ability, (2) the sample size of the experimental group and the control group became larger and equal; so it becomes robust to deal with violations of the assumptions of the ANOVA test.

Gain optimization with non-linear controls

NASA Technical Reports Server (NTRS)

Slater, G. L.; Kandadai, R. D.

1984-01-01

An algorithm has been developed for the analysis and design of controls for non-linear systems. The technical approach is to use statistical linearization to model the non-linear dynamics of a system by a quasi-Gaussian model. A covariance analysis is performed to determine the behavior of the dynamical system and a quadratic cost function. Expressions for the cost function and its derivatives are determined so that numerical optimization techniques can be applied to determine optimal feedback laws. The primary application for this paper is centered about the design of controls for nominally linear systems but where the controls are saturated or limited by fixed constraints. The analysis is general, however, and numerical computation requires only that the specific non-linearity be considered in the analysis.

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-30

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-01

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Seven Pervasive Statistical Flaws in Cognitive Training Interventions

PubMed Central

Moreau, David; Kirk, Ian J.; Waldie, Karen E.

2016-01-01

The prospect of enhancing cognition is undoubtedly among the most exciting research questions currently bridging psychology, neuroscience, and evidence-based medicine. Yet, convincing claims in this line of work stem from designs that are prone to several shortcomings, thus threatening the credibility of training-induced cognitive enhancement. Here, we present seven pervasive statistical flaws in intervention designs: (i) lack of power; (ii) sampling error; (iii) continuous variable splits; (iv) erroneous interpretations of correlated gain scores; (v) single transfer assessments; (vi) multiple comparisons; and (vii) publication bias. Each flaw is illustrated with a Monte Carlo simulation to present its underlying mechanisms, gauge its magnitude, and discuss potential remedies. Although not restricted to training studies, these flaws are typically exacerbated in such designs, due to ubiquitous practices in data collection or data analysis. The article reviews these practices, so as to avoid common pitfalls when designing or analyzing an intervention. More generally, it is also intended as a reference for anyone interested in evaluating claims of cognitive enhancement. PMID:27148010

fMRI paradigm designing and post-processing tools

PubMed Central

James, Jija S; Rajesh, PG; Chandran, Anuvitha VS; Kesavadas, Chandrasekharan

2014-01-01

In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result. PMID:24851001

Experimental Design in Clinical 'Omics Biomarker Discovery.

PubMed

Forshed, Jenny

2017-11-03

This tutorial highlights some issues in the experimental design of clinical 'omics biomarker discovery, how to avoid bias and get as true quantities as possible from biochemical analyses, and how to select samples to improve the chance of answering the clinical question at issue. This includes the importance of defining clinical aim and end point, knowing the variability in the results, randomization of samples, sample size, statistical power, and how to avoid confounding factors by including clinical data in the sample selection, that is, how to avoid unpleasant surprises at the point of statistical analysis. The aim of this Tutorial is to help translational clinical and preclinical biomarker candidate research and to improve the validity and potential of future biomarker candidate findings.

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

PubMed Central

2010-01-01

Background The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Methods/Design Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Discussion Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis. PMID:20950449

Evolutionary computing for the design search and optimization of space vehicle power subsystems

NASA Technical Reports Server (NTRS)

Kordon, Mark; Klimeck, Gerhard; Hanks, David; Hua, Hook

2004-01-01

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

A note about high blood pressure in childhood

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Simão, Carla

2017-06-01

In medical, behavioral and social sciences it is usual to get a binary outcome. In the present work is collected information where some of the outcomes are binary variables (1='yes'/ 0='no'). In [14] a preliminary study about the caregivers perception of pediatric hypertension was introduced. An experimental questionnaire was designed to be answered by the caregivers of routine pediatric consultation attendees in the Santa Maria's hospital (HSM). The collected data was statistically analyzed, where a descriptive analysis and a predictive model were performed. Significant relations between some socio-demographic variables and the assessed knowledge were obtained. In [14] can be found a statistical data analysis using partial questionnaire's information. The present article completes the statistical approach estimating a model for relevant remaining questions of questionnaire by Generalized Linear Models (GLM). Exploring the binary outcome issue, we intend to extend this approach using Generalized Linear Mixed Models (GLMM), but the process is still ongoing.

In vivo Comet assay--statistical analysis and power calculations of mice testicular cells.

PubMed

Hansen, Merete Kjær; Sharma, Anoop Kumar; Dybdahl, Marianne; Boberg, Julie; Kulahci, Murat

2014-11-01

The in vivo Comet assay is a sensitive method for evaluating DNA damage. A recurrent concern is how to analyze the data appropriately and efficiently. A popular approach is to summarize the raw data into a summary statistic prior to the statistical analysis. However, consensus on which summary statistic to use has yet to be reached. Another important consideration concerns the assessment of proper sample sizes in the design of Comet assay studies. This study aims to identify a statistic suitably summarizing the % tail DNA of mice testicular samples in Comet assay studies. A second aim is to provide curves for this statistic outlining the number of animals and gels to use. The current study was based on 11 compounds administered via oral gavage in three doses to male mice: CAS no. 110-26-9, CAS no. 512-56-1, CAS no. 111873-33-7, CAS no. 79-94-7, CAS no. 115-96-8, CAS no. 598-55-0, CAS no. 636-97-5, CAS no. 85-28-9, CAS no. 13674-87-8, CAS no. 43100-38-5 and CAS no. 60965-26-6. Testicular cells were examined using the alkaline version of the Comet assay and the DNA damage was quantified as % tail DNA using a fully automatic scoring system. From the raw data 23 summary statistics were examined. A linear mixed-effects model was fitted to the summarized data and the estimated variance components were used to generate power curves as a function of sample size. The statistic that most appropriately summarized the within-sample distributions was the median of the log-transformed data, as it most consistently conformed to the assumptions of the statistical model. Power curves for 1.5-, 2-, and 2.5-fold changes of the highest dose group compared to the control group when 50 and 100 cells were scored per gel are provided to aid in the design of future Comet assay studies on testicular cells. Copyright © 2014 Elsevier B.V. All rights reserved.

Getting the big picture in community science: methods that capture context.

PubMed

Luke, Douglas A

2005-06-01

Community science has a rich tradition of using theories and research designs that are consistent with its core value of contextualism. However, a survey of empirical articles published in the American Journal of Community Psychology shows that community scientists utilize a narrow range of statistical tools that are not well suited to assess contextual data. Multilevel modeling, geographic information systems (GIS), social network analysis, and cluster analysis are recommended as useful tools to address contextual questions in community science. An argument for increased methodological consilience is presented, where community scientists are encouraged to adopt statistical methodology that is capable of modeling a greater proportion of the data than is typical with traditional methods.