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

Reliability approach to rotating-component design. [fatigue life and stress concentration

NASA Technical Reports Server (NTRS)

Kececioglu, D. B.; Lalli, V. R.

1975-01-01

A probabilistic methodology for designing rotating mechanical components using reliability to relate stress to strength is explained. The experimental test machines and data obtained for steel to verify this methodology are described. A sample mechanical rotating component design problem is solved by comparing a deterministic design method with the new design-by reliability approach. The new method shows that a smaller size and weight can be obtained for specified rotating shaft life and reliability, and uses the statistical distortion-energy theory with statistical fatigue diagrams for optimum shaft design. Statistical methods are presented for (1) determining strength distributions for steel experimentally, (2) determining a failure theory for stress variations in a rotating shaft subjected to reversed bending and steady torque, and (3) relating strength to stress by reliability.

76 FR 17107 - Fisheries of the Exclusive Economic Zone Off Alaska; Application for an Exempted Fishing Permit

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-28

... experimental design requires this quantity of salmon to ensure statistically valid results. The applicant also... encounters sufficient concentrations of salmon and pollock for meeting the experimental design. Groundfish... of the groundfish harvested is expected to be pollock. The experimental design requires this quantity...

77 FR 69796 - Fisheries of the Exclusive Economic Zone Off Alaska; Application for an Exempted Fishing Permit

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-21

...-year EFP. The experimental design requires this quantity of salmon to ensure statistically valid... of the groundfish harvested each year from the EFP is expected to be pollock. The experimental design... concentrations of salmon and pollock for addressing experimental design criteria. The activities under the EFP...

Statistical process control in nursing research.

PubMed

Polit, Denise F; Chaboyer, Wendy

2012-02-01

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

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

78 FR 18710 - Applications for New Awards; Investing in Innovation Fund, Development Grants

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-27

... statistical controls for selection bias; (2) Quasi-experimental study (as defined in this notice) that meets... Act of 1965, as amended. Quasi-experimental design study means a study using a design that attempts to approximate an experimental design by identifying a comparison group that is similar to the treatment group in...

78 FR 25977 - Applications for New Awards; Investing in Innovation Fund, Scale-up Grants

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-03

... statistical controls for selection bias; (2) Quasi-experimental study (as defined in this notice) that meets... Act of 1965, as amended. Quasi-experimental design study means a study using a design that attempts to approximate an experimental design by identifying a comparison group that is similar to the treatment group in...

Learning Compositional Simulation Models

DTIC Science & Technology

2010-01-01

techniques developed by social scientists, economists, and medical researchers over the past four decades. Quasi-experimental designs (QEDs) are...statistical techniques from the social sciences known as quasi- experimental design (QED). QEDs allow a researcher to exploit unique characteristics...can be grouped under the rubric “quasi-experimental design ” (QED), and they attempt to exploit inherent characteristics of observational data sets

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.

Instruction of Statistics via Computer-Based Tools: Effects on Statistics' Anxiety, Attitude, and Achievement

ERIC Educational Resources Information Center

Ciftci, S. Koza; Karadag, Engin; Akdal, Pinar

2014-01-01

The purpose of this study was to determine the effect of statistics instruction using computer-based tools, on statistics anxiety, attitude, and achievement. This study was designed as quasi-experimental research and the pattern used was a matched pre-test/post-test with control group design. Data was collected using three scales: a Statistics…

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].

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

Heaney, Mike

Statistically designed experiments can save researchers time and money by reducing the number of necessary experimental trials, while resulting in more conclusive experimental results. Surprisingly, many researchers are still not aware of this efficient and effective experimental methodology. As reported in a 2013 article from Chemical & Engineering News, there has been a resurgence of this methodology in recent years (http://cen.acs.org/articles/91/i13/Design-Experiments-Makes-Comeback.html?h=2027056365). This presentation will provide a brief introduction to statistically designed experiments. The main advantages will be reviewed along with the some basic concepts such as factorial and fractional factorial designs. The recommended sequential approach to experiments will be introducedmore » and finally a case study will be presented to demonstrate this methodology.« less

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…

Proceedings of the Symposium on Psychology in the Department of Defense (8th) Held in Colorado Springs, Colorado on 21-23 April 1982

DTIC Science & Technology

1982-12-01

readily visible but still represent low level flight. 33 Experimental Design and Pc,cedures. The experimental design used in this study was a 3 X 2...October 1979. Winer, B.J. Statistical principles in experimental design . New York: McGraw-Hill, 1971. 47 NONTRADITIONAL ADMISSIONS FACTORS: THE SPECIAL...Quasi- Experimental Designs for Research. Chicago: Rand McNally, 1963. R.C. Carter and H. Sbisa. Human Performance tests for repeated measurements

[Review of research design and statistical methods in Chinese Journal of Cardiology].

PubMed

Zhang, Li-jun; Yu, Jin-ming

2009-07-01

To evaluate the research design and the use of statistical methods in Chinese Journal of Cardiology. Peer through the research design and statistical methods in all of the original papers in Chinese Journal of Cardiology from December 2007 to November 2008. The most frequently used research designs are cross-sectional design (34%), prospective design (21%) and experimental design (25%). In all of the articles, 49 (25%) use wrong statistical methods, 29 (15%) lack some sort of statistic analysis, 23 (12%) have inconsistencies in description of methods. There are significant differences between different statistical methods (P < 0.001). The correction rates of multifactor analysis were low and repeated measurement datas were not used repeated measurement analysis. Many problems exist in Chinese Journal of Cardiology. Better research design and correct use of statistical methods are still needed. More strict review by statistician and epidemiologist is also required to improve the literature qualities.

D-OPTIMAL EXPERIMENTAL DESIGNS TO TEST FOR DEPARTURE FROM ADDITIVITY IN A FIXED-RATIO MIXTURE RAY.

EPA Science Inventory

Traditional factorial designs for evaluating interactions among chemicals in a mixture are prohibitive when the number of chemicals is large. However, recent advances in statistically-based experimental design have made it easier to evaluate interactions involving many chemicals...

A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.

The Effect of Multispectral Image Fusion Enhancement on Human Efficiency

DTIC Science & Technology

2017-03-20

performance of the ideal observer is indicative of the relative amount of informa- tion across various experimental manipulations. In our experimental design ...registration and fusion processes, and contributed strongly to the statistical analyses. LMB contributed to the experimental design and writing structure. All... designed to be innovative, low-cost, and (relatively) easy-to-implement, and to provide support across the spectrum of possible users including

Return to Our Roots: Raising Radishes To Teach Experimental Design.

ERIC Educational Resources Information Center

Stallings, William M.

To provide practice in making design decisions, collecting and analyzing data, and writing and documenting results, a professor of statistics has his graduate students in statistics and research methodology classes design and perform an experiment on the effects of fertilizers on the growth of radishes. This project has been required of students…

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-01-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-11-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

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

Optimization of cold-adapted lysozyme production from the psychrophilic yeast Debaryomyces hansenii using statistical experimental methods.

PubMed

Wang, Quanfu; Hou, Yanhua; Yan, Peisheng

2012-06-01

Statistical experimental designs were employed to optimize culture conditions for cold-adapted lysozyme production of a psychrophilic yeast Debaryomyces hansenii. In the first step of optimization using Plackett-Burman design (PBD), peptone, glucose, temperature, and NaCl were identified as significant variables that affected lysozyme production, the formula was further optimized using a four factor central composite design (CCD) to understand their interaction and to determine their optimal levels. A quadratic model was developed and validated. Compared to the initial level (18.8 U/mL), the maximum lysozyme production (65.8 U/mL) observed was approximately increased by 3.5-fold under the optimized conditions. Cold-adapted lysozymes production was first optimized using statistical experimental methods. A 3.5-fold enhancement of microbial lysozyme was gained after optimization. Such an improved production will facilitate the application of microbial lysozyme. Thus, D. hansenii lysozyme may be a good and new resource for the industrial production of cold-adapted lysozymes. © 2012 Institute of Food Technologists®

Vitamin B12 production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii: optimization of medium composition through statistical experimental designs.

PubMed

Kośmider, Alicja; Białas, Wojciech; Kubiak, Piotr; Drożdżyńska, Agnieszka; Czaczyk, Katarzyna

2012-02-01

A two-step statistical experimental design was employed to optimize the medium for vitamin B(12) production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii. In the first step, using Plackett-Burman design, five of 13 tested medium components (calcium pantothenate, NaH(2)PO(4)·2H(2)O, casein hydrolysate, glycerol and FeSO(4)·7H(2)O) were identified as factors having significant influence on vitamin production. In the second step, a central composite design was used to optimize levels of medium components selected in the first step. Valid statistical models describing the influence of significant factors on vitamin B(12) production were established for each optimization phase. The optimized medium provided a 93% increase in final vitamin concentration compared to the original medium. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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

PubMed

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

2010-09-01

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

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.

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 search for causal inferences: using propensity scores post hoc to reduce estimation error with nonexperimental research.

PubMed

Tumlinson, Samuel E; Sass, Daniel A; Cano, Stephanie M

2014-03-01

While experimental designs are regarded as the gold standard for establishing causal relationships, such designs are usually impractical owing to common methodological limitations. The objective of this article is to illustrate how propensity score matching (PSM) and using propensity scores (PS) as a covariate are viable alternatives to reduce estimation error when experimental designs cannot be implemented. To mimic common pediatric research practices, data from 140 simulated participants were used to resemble an experimental and nonexperimental design that assessed the effect of treatment status on participant weight loss for diabetes. Pretreatment participant characteristics (age, gender, physical activity, etc.) were then used to generate PS for use in the various statistical approaches. Results demonstrate how PSM and using the PS as a covariate can be used to reduce estimation error and improve statistical inferences. References for issues related to the implementation of these procedures are provided to assist researchers.

Statistical issues in the design and planning of proteomic profiling experiments.

PubMed

Cairns, David A

2015-01-01

The statistical design of a clinical proteomics experiment is a critical part of well-undertaken investigation. Standard concepts from experimental design such as randomization, replication and blocking should be applied in all experiments, and this is possible when the experimental conditions are well understood by the investigator. The large number of proteins simultaneously considered in proteomic discovery experiments means that determining the number of required replicates to perform a powerful experiment is more complicated than in simple experiments. However, by using information about the nature of an experiment and making simple assumptions this is achievable for a variety of experiments useful for biomarker discovery and initial validation.

Stated Choice design comparison in a developing country: recall and attribute nonattendance

PubMed Central

2014-01-01

Background Experimental designs constitute a vital component of all Stated Choice (aka discrete choice experiment) studies. However, there exists limited empirical evaluation of the statistical benefits of Stated Choice (SC) experimental designs that employ non-zero prior estimates in constructing non-orthogonal constrained designs. This paper statistically compares the performance of contrasting SC experimental designs. In so doing, the effect of respondent literacy on patterns of Attribute non-Attendance (ANA) across fractional factorial orthogonal and efficient designs is also evaluated. The study uses a ‘real’ SC design to model consumer choice of primary health care providers in rural north India. A total of 623 respondents were sampled across four villages in Uttar Pradesh, India. Methods Comparison of orthogonal and efficient SC experimental designs is based on several measures. Appropriate comparison of each design’s respective efficiency measure is made using D-error results. Standardised Akaike Information Criteria are compared between designs and across recall periods. Comparisons control for stated and inferred ANA. Coefficient and standard error estimates are also compared. Results The added complexity of the efficient SC design, theorised elsewhere, is reflected in higher estimated amounts of ANA among illiterate respondents. However, controlling for ANA using stated and inferred methods consistently shows that the efficient design performs statistically better. Modelling SC data from the orthogonal and efficient design shows that model-fit of the efficient design outperform the orthogonal design when using a 14-day recall period. The performance of the orthogonal design, with respect to standardised AIC model-fit, is better when longer recall periods of 30-days, 6-months and 12-months are used. Conclusions The effect of the efficient design’s cognitive demand is apparent among literate and illiterate respondents, although, more pronounced among illiterate respondents. This study empirically confirms that relaxing the orthogonality constraint of SC experimental designs increases the information collected in choice tasks, subject to the accuracy of the non-zero priors in the design and the correct specification of a ‘real’ SC recall period. PMID:25386388

Optimal Experimental Design for Model Discrimination

PubMed Central

Myung, Jay I.; Pitt, Mark A.

2009-01-01

Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values, and thereby identify an optimal experimental design. After describing the method, it is demonstrated in two content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method. PMID:19618983

Optimal Experimental Design for Model Discrimination

ERIC Educational Resources Information Center

Myung, Jay I.; Pitt, Mark A.

2009-01-01

Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…

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

PubMed

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

2014-08-01

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

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.

Learning Axes and Bridging Tools in a Technology-Based Design for Statistics

ERIC Educational Resources Information Center

Abrahamson, Dor; Wilensky, Uri

2007-01-01

We introduce a design-based research framework, "learning axes and bridging tools," and demonstrate its application in the preparation and study of an implementation of a middle-school experimental computer-based unit on probability and statistics, "ProbLab" (Probability Laboratory, Abrahamson and Wilensky 2002 [Abrahamson, D., & Wilensky, U.…

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…

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

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.

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

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)

Characterizing Variability in Smestad and Gratzel's Nanocrystalline Solar Cells: A Collaborative Learning Experience in Experimental Design

ERIC Educational Resources Information Center

Lawson, John; Aggarwal, Pankaj; Leininger, Thomas; Fairchild, Kenneth

2011-01-01

This article describes a collaborative learning experience in experimental design that closely approximates what practicing statisticians and researchers in applied science experience during consulting. Statistics majors worked with a teaching assistant from the chemistry department to conduct a series of experiments characterizing the variation…

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

PubMed

Hu, Liang-ping; Liu, Hui-gang

2005-07-20

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

Experimental design data for the biosynthesis of citric acid using Central Composite Design method.

PubMed

Kola, Anand Kishore; Mekala, Mallaiah; Goli, Venkat Reddy

2017-06-01

In the present investigation, we report that statistical design and optimization of significant variables for the microbial production of citric acid from sucrose in presence of filamentous fungi A. niger NCIM 705. Various combinations of experiments were designed with Central Composite Design (CCD) of Response Surface Methodology (RSM) for the production of citric acid as a function of six variables. The variables are; initial sucrose concentration, initial pH of medium, fermentation temperature, incubation time, stirrer rotational speed, and oxygen flow rate. From experimental data, a statistical model for this process has been developed. The optimum conditions reported in the present article are initial concentration of sucrose of 163.6 g/L, initial pH of medium 5.26, stirrer rotational speed of 247.78 rpm, incubation time of 8.18 days, fermentation temperature of 30.06 °C and flow rate of oxygen of 1.35 lpm. Under optimum conditions the predicted maximum citric acid is 86.42 g/L. The experimental validation carried out under the optimal values and reported citric acid to be 82.0 g/L. The model is able to represent the experimental data and the agreement between the model and experimental data is good.

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

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.

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.

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.

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…

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

PubMed

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

2011-10-01

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

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

PubMed Central

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

2011-01-01

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

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

Measurements of experimental precision for trials with cowpea (Vigna unguiculata L. Walp.) genotypes.

PubMed

Teodoro, P E; Torres, F E; Santos, A D; Corrêa, A M; Nascimento, M; Barroso, L M A; Ceccon, G

2016-05-09

The aim of this study was to evaluate the suitability of statistics as experimental precision degree measures for trials with cowpea (Vigna unguiculata L. Walp.) genotypes. Cowpea genotype yields were evaluated in 29 trials conducted in Brazil between 2005 and 2012. The genotypes were evaluated with a randomized block design with four replications. Ten statistics that were estimated for each trial were compared using descriptive statistics, Pearson correlations, and path analysis. According to the class limits established, selective accuracy and F-test values for genotype, heritability, and the coefficient of determination adequately estimated the degree of experimental precision. Using these statistics, 86.21% of the trials had adequate experimental precision. Selective accuracy and the F-test values for genotype, heritability, and the coefficient of determination were directly related to each other, and were more suitable than the coefficient of variation and the least significant difference (by the Tukey test) to evaluate experimental precision in trials with cowpea genotypes.

Experimental Design and Power Calculation for RNA-seq Experiments.

PubMed

Wu, Zhijin; Wu, Hao

2016-01-01

Power calculation is a critical component of RNA-seq experimental design. The flexibility of RNA-seq experiment and the wide dynamic range of transcription it measures make it an attractive technology for whole transcriptome analysis. These features, in addition to the high dimensionality of RNA-seq data, bring complexity in experimental design, making an analytical power calculation no longer realistic. In this chapter we review the major factors that influence the statistical power of detecting differential expression, and give examples of power assessment using the R package PROPER.

Application of a statistical design to the optimization of parameters and culture medium for alpha-amylase production by Aspergillus oryzae CBS 819.72 grown on gruel (wheat grinding by-product).

PubMed

Kammoun, Radhouane; Naili, Belgacem; Bejar, Samir

2008-09-01

The production optimization of alpha-amylase (E.C.3.2.1.1) from Aspergillus oryzae CBS 819.72 fungus, using a by-product of wheat grinding (gruel) as sole carbon source, was performed with statistical methodology based on three experimental designs. The optimisation of temperature, agitation and inoculum size was attempted using a Box-Behnken design under the response surface methodology. The screening of nineteen nutrients for their influence on alpha-amylase production was achieved using a Plackett-Burman design. KH(2)PO(4), urea, glycerol, (NH(4))(2)SO(4), CoCl(2), casein hydrolysate, soybean meal hydrolysate, MgSO(4) were selected based on their positive influence on enzyme formation. The optimized nutrients concentration was obtained using a Taguchi experimental design and the analysis of the data predicts a theoretical increase in the alpha-amylase expression of 73.2% (from 40.1 to 151.1 U/ml). These conditions were validated experimentally and revealed an enhanced alpha-amylase yield of 72.7%.

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.

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.

Comparison between project-based learning and discovery learning toward students' metacognitive strategies on global warming concept

NASA Astrophysics Data System (ADS)

Tumewu, Widya Anjelia; Wulan, Ana Ratna; Sanjaya, Yayan

2017-05-01

The purpose of this study was to know comparing the effectiveness of learning using Project-based learning (PjBL) and Discovery Learning (DL) toward students metacognitive strategies on global warming concept. A quasi-experimental research design with a The Matching-Only Pretest-Posttest Control Group Design was used in this study. The subjects were students of two classes 7th grade of one of junior high school in Bandung City, West Java of 2015/2016 academic year. The study was conducted on two experimental class, that were project-based learning treatment on the experimental class I and discovery learning treatment was done on the experimental class II. The data was collected through questionnaire to know students metacognitive strategies. The statistical analysis showed that there were statistically significant differences in students metacognitive strategies between project-based learning and discovery learning.

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.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-01-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-03-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Threats to the Internal Validity of Experimental and Quasi-Experimental Research in Healthcare.

PubMed

Flannelly, Kevin J; Flannelly, Laura T; Jankowski, Katherine R B

2018-01-01

The article defines, describes, and discusses the seven threats to the internal validity of experiments discussed by Donald T. Campbell in his classic 1957 article: history, maturation, testing, instrument decay, statistical regression, selection, and mortality. These concepts are said to be threats to the internal validity of experiments because they pose alternate explanations for the apparent causal relationship between the independent variable and dependent variable of an experiment if they are not adequately controlled. A series of simple diagrams illustrate three pre-experimental designs and three true experimental designs discussed by Campbell in 1957 and several quasi-experimental designs described in his book written with Julian C. Stanley in 1966. The current article explains why each design controls for or fails to control for these seven threats to internal validity.

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 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.

[Effects on couples' communication, intimacy, conflict and quality of life by foot massage between immigrants].

PubMed

Uhm, Dong-choon

2010-08-01

The purpose of this study was to evaluate the effects on immigrant couples' communication, intimacy, conflict and quality of life when using foot massage. The research design consisted of pre-and-post test consecutive experimental design through a nonequivalent control group. Data were collected July 6, 2009 to February 27, 2010. The 36 couples were divided into two groups, experimental and control with 18 couples in each group. Foot massage was applied twice a week for 6 weeks by the couples in the experimental group. There were statistically significant increases in communication (p=.011), intimacy (p<.001), quality of life (p=.017) between the couples in the experimental group compared to the control group. There was also a statistically significant decrease in conflict (p=.003) between the couples in the experimental group compared to the control group. Foot massage can be applied as a nursing intervention for improvement of marital relationship in immigrant couples.

The influence of the design matrix on treatment effect estimates in the quantitative analyses of single-subject experimental design research.

PubMed

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M; Beretvas, S Natasha; Van den Noortgate, Wim

2014-09-01

The quantitative methods for analyzing single-subject experimental data have expanded during the last decade, including the use of regression models to statistically analyze the data, but still a lot of questions remain. One question is how to specify predictors in a regression model to account for the specifics of the design and estimate the effect size of interest. These quantitative effect sizes are used in retrospective analyses and allow synthesis of single-subject experimental study results which is informative for evidence-based decision making, research and theory building, and policy discussions. We discuss different design matrices that can be used for the most common single-subject experimental designs (SSEDs), namely, the multiple-baseline designs, reversal designs, and alternating treatment designs, and provide empirical illustrations. The purpose of this article is to guide single-subject experimental data analysts interested in analyzing and meta-analyzing SSED data. © The Author(s) 2014.

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…

A Tutorial on Adaptive Design Optimization

PubMed Central

Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

2013-01-01

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

Learning physics: A comparative analysis between instructional design methods

NASA Astrophysics Data System (ADS)

Mathew, Easow

The purpose of this research was to determine if there were differences in academic performance between students who participated in traditional versus collaborative problem-based learning (PBL) instructional design approaches to physics curricula. This study utilized a quantitative quasi-experimental design methodology to determine the significance of differences in pre- and posttest introductory physics exam performance between students who participated in traditional (i.e., control group) versus collaborative problem solving (PBL) instructional design (i.e., experimental group) approaches to physics curricula over a college semester in 2008. There were 42 student participants (N = 42) enrolled in an introductory physics course at the research site in the Spring 2008 semester who agreed to participate in this study after reading and signing informed consent documents. A total of 22 participants were assigned to the experimental group (n = 22) who participated in a PBL based teaching methodology along with traditional lecture methods. The other 20 students were assigned to the control group (n = 20) who participated in the traditional lecture teaching methodology. Both the courses were taught by experienced professors who have qualifications at the doctoral level. The results indicated statistically significant differences (p < .01) in academic performance between students who participated in traditional (i.e., lower physics posttest scores and lower differences between pre- and posttest scores) versus collaborative (i.e., higher physics posttest scores, and higher differences between pre- and posttest scores) instructional design approaches to physics curricula. Despite some slight differences in control group and experimental group demographic characteristics (gender, ethnicity, and age) there were statistically significant (p = .04) differences between female average academic improvement which was much higher than male average academic improvement (˜63%) in the control group which may indicate that traditional teaching methods are more effective in females, whereas there was no significant difference noted in the experimental group between male and female participants. There was a statistically significant and negative relationship (r = -.61, p = .01) between age and physics pretest scores in the control group. No statistical analyses yielded significantly different average academic performance values in either group as delineated by ethnicity.

Assessing effects of a semi-customized experimental cervical pillow on symptomatic adults with chronic neck pain with and without headache

PubMed Central

Erfanian, Parham; Tenzif, Siamak; Guerriero, Rocco C

2004-01-01

Objective To determine the effects of a semi-customized experimental cervical pillow on symptomatic adults with chronic neck pain (with and without headache) during a four week study. Design A randomized controlled trial. Sample size Thirty-six adults were recruited for the trial, and randomly assigned to experimental or non-experimental groups of 17 and 19 participants respectively. Subjects Adults with chronic biomechanical neck pain who were recruited from the Canadian Memorial Chiropractic College (CMCC) Walk-in Clinic. Outcome measures Subjective findings were assessed using a mail-in self-report daily pain diary, and the CMCC Neck Disability Index (NDI). Statistical analysis Using repeated measure analysis of variance weekly NDI scores, average weekly AM and PM pain scores between the experimental and non-experimental groups were compared throughout the study. Results The experimental group had statistically significant lower NDI scores (p < 0.05) than the non-experimental group. The average weekly AM scores were lower and statistically significant (p < 0.05) in the experimental group. The PM scores in the experimental group were lower but not statistically significant than the other group. Conclusions The study results show that compared to conventional pillows, this experimental semi-customized cervical pillow was effective in reducing low-level neck pain intensity, especially in the morning following its use in a 4 week long study. PMID:17549216

Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin.

PubMed

Low, K H; Chong, C W

2010-12-01

In this paper, we aim to study the swimming performance of fish robots by using a statistical approach. A fish robot employing a carangiform swimming mode had been used as an experimental platform for the performance study. The experiments conducted aim to investigate the effect of various design parameters on the thrust capability of the fish robot with a flexible caudal fin. The controllable parameters associated with the fin include frequency, amplitude of oscillation, aspect ratio and the rigidity of the caudal fin. The significance of these parameters was determined in the first set of experiments by using a statistical approach. A more detailed parametric experimental study was then conducted with only those significant parameters. As a result, the parametric study could be completed with a reduced number of experiments and time spent. With the obtained experimental result, we were able to understand the relationship between various parameters and a possible adjustment of parameters to obtain a higher thrust. The proposed statistical method for experimentation provides an objective and thorough analysis of the effects of individual or combinations of parameters on the swimming performance. Such an efficient experimental design helps to optimize the process and determine factors that influence variability.

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.

A Quasi-Experimental Study on Using Short Stories: Statistical and Inferential Analyses on the Non-English Major University Students' Speaking and Writing Achievements

ERIC Educational Resources Information Center

Iman, Jaya Nur

2017-01-01

This research was conducted to find out whether or not using short stories significantly improve the speaking and writing achievements. A quasi-experimental study of non-equivalent pretest-posttest control group design or comparison group design was used in this research. The population of this research was the all first semester undergraduate…

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

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.

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.

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.

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.

Proceedings of the Conference on the Design of Experiments (23rd) S

DTIC Science & Technology

1978-07-01

of Statistics, Carnegie-Mellon University. * [12] Duran , B. S . (1976). A survey of nonparametric tests for scale. Comunications in Statistics A5, 1287...the twenty-third Design of Experiments Conference was the U. S . Army Combat Development Experimentation Command, Fort Ord, California. Excellent...Availability Prof. G. E. P. Box Time Series Modelling University of Wisconsin Dr. Churchill Eisenhart was recipient this year of the Samuel S . Wilks Memorial

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.

Statistical Treatment of Looking-Time Data

ERIC Educational Resources Information Center

Csibra, Gergely; Hernik, Mikolaj; Mascaro, Olivier; Tatone, Denis; Lengyel, Máté

2016-01-01

Looking times (LTs) are frequently measured in empirical research on infant cognition. We analyzed the statistical distribution of LTs across participants to develop recommendations for their treatment in infancy research. Our analyses focused on a common within-subject experimental design, in which longer looking to novel or unexpected stimuli is…

Design of Experiments with Multiple Independent Variables: A Resource Management Perspective on Complete and Reduced Factorial Designs

PubMed Central

Collins, Linda M.; Dziak, John J.; Li, Runze

2009-01-01

An investigator who plans to conduct experiments with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy. Considerations in making design decisions include whether research questions are framed as main effects or simple effects; whether and which effects are aliased (confounded) in a particular design; the number of experimental conditions that must be implemented in a particular design and the number of experimental subjects the design requires to maintain the desired level of statistical power; and the costs associated with implementing experimental conditions and obtaining experimental subjects. In this article four design options are compared: complete factorial, individual experiments, single factor, and fractional factorial designs. Complete and fractional factorial designs and single factor designs are generally more economical than conducting individual experiments on each factor. Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility. PMID:19719358

Replication, lies and lesser-known truths regarding experimental design in environmental microbiology.

PubMed

Lennon, Jay T

2011-06-01

A recent analysis revealed that most environmental microbiologists neglect replication in their science (Prosser, 2010). Of all peer-reviewed papers published during 2009 in the field's leading journals, slightly more than 70% lacked replication when it came to analyzing microbial community data. The paucity of replication is viewed as an 'endemic' and 'embarrassing' problem that amounts to 'bad science', or worse yet, as the title suggests, lying (Prosser, 2010). Although replication is an important component of experimental design, it is possible to do good science without replication. There are various quantitative techniques - some old, some new - that, when used properly, will allow environmental microbiologists to make strong statistical conclusions from experimental and comparative data. Here, I provide examples where unreplicated data can be used to test hypotheses and yield novel information in a statistically robust manner. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

The Dependence of Strength in Plastics upon Polymer Chain Length and Chain Orientation: An Experiment Emphasizing the Statistical Handling and Evaluation of Data.

ERIC Educational Resources Information Center

Spencer, R. Donald

1984-01-01

Describes an experiment (using plastic bags) designed to give students practical understanding on using statistics to evaluate data and how statistical treatment of experimental results can enhance their value in solving scientific problems. Students also gain insight into the orientation and structure of polymers by examining the plastic bags.…

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

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.

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.

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…

Using R to Simulate Permutation Distributions for Some Elementary Experimental Designs

ERIC Educational Resources Information Center

Eudey, T. Lynn; Kerr, Joshua D.; Trumbo, Bruce E.

2010-01-01

Null distributions of permutation tests for two-sample, paired, and block designs are simulated using the R statistical programming language. For each design and type of data, permutation tests are compared with standard normal-theory and nonparametric tests. These examples (often using real data) provide for classroom discussion use of metrics…

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

Application of Statistical Design for the Production of Cellulase by Trichoderma reesei Using Mango Peel.

PubMed

Saravanan, P; Muthuvelayudham, R; Viruthagiri, T

2012-01-01

Optimization of the culture medium for cellulase production using Trichoderma reesei was carried out. The optimization of cellulase production using mango peel as substrate was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence on cellulase production is achieved using Plackett-Burman design. Avicel, soybean cake flour, KH(2)PO(4), and CoCl(2)·6H(2)O were selected based on their positive influence on cellulase production. The composition of the selected components was optimized using Response Surface Methodology (RSM). The optimum conditions are as follows: Avicel: 25.30 g/L, Soybean cake flour: 23.53 g/L, KH(2)PO(4): 4.90 g/L, and CoCl(2)·6H(2)O: 0.95 g/L. These conditions are validated experimentally which revealed an enhanced Cellulase activity of 7.8 IU/mL.

Effect of experimental design on the prediction performance of calibration models based on near-infrared spectroscopy for pharmaceutical applications.

PubMed

Bondi, Robert W; Igne, Benoît; Drennen, James K; Anderson, Carl A

2012-12-01

Near-infrared spectroscopy (NIRS) is a valuable tool in the pharmaceutical industry, presenting opportunities for online analyses to achieve real-time assessment of intermediates and finished dosage forms. The purpose of this work was to investigate the effect of experimental designs on prediction performance of quantitative models based on NIRS using a five-component formulation as a model system. The following experimental designs were evaluated: five-level, full factorial (5-L FF); three-level, full factorial (3-L FF); central composite; I-optimal; and D-optimal. The factors for all designs were acetaminophen content and the ratio of microcrystalline cellulose to lactose monohydrate. Other constituents included croscarmellose sodium and magnesium stearate (content remained constant). Partial least squares-based models were generated using data from individual experimental designs that related acetaminophen content to spectral data. The effect of each experimental design was evaluated by determining the statistical significance of the difference in bias and standard error of the prediction for that model's prediction performance. The calibration model derived from the I-optimal design had similar prediction performance as did the model derived from the 5-L FF design, despite containing 16 fewer design points. It also outperformed all other models estimated from designs with similar or fewer numbers of samples. This suggested that experimental-design selection for calibration-model development is critical, and optimum performance can be achieved with efficient experimental designs (i.e., optimal designs).

Magic Mirror, on the Wall-Which Is the Right Study Design of Them All?-Part I.

PubMed

Vetter, Thomas R

2017-06-01

The assessment of a new or existing treatment or intervention typically answers 1 of 3 research-related questions: (1) "Can it work?" (efficacy); (2) "Does it work?" (effectiveness); and (3) "Is it worth it?" (efficiency or cost-effectiveness). There are a number of study designs that on a situational basis are appropriate to apply in conducting research. These study designs are classified as experimental, quasi-experimental, or observational, with observational studies being further divided into descriptive and analytic categories. This first of a 2-part statistical tutorial reviews these 3 salient research questions and describes a subset of the most common types of experimental and quasi-experimental study design. Attention is focused on the strengths and weaknesses of each study design to assist in choosing which is appropriate for a given study objective and hypothesis as well as the particular study setting and available resources and data. Specific studies and papers are highlighted as examples of a well-chosen, clearly stated, and properly executed study design type.

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…

47 CFR 1.363 - Introduction of statistical data.

Code of Federal Regulations, 2010 CFR

2010-10-01

... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...

47 CFR 1.363 - Introduction of statistical data.

Code of Federal Regulations, 2013 CFR

2013-10-01

... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...

47 CFR 1.363 - Introduction of statistical data.

Code of Federal Regulations, 2014 CFR

2014-10-01

... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...

47 CFR 1.363 - Introduction of statistical data.

Code of Federal Regulations, 2012 CFR

2012-10-01

... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...

47 CFR 1.363 - Introduction of statistical data.

Code of Federal Regulations, 2011 CFR

2011-10-01

... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...

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.

Space-filling designs for computer experiments: A review

DOE PAGES

Joseph, V. Roshan

2016-01-29

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Space-filling designs for computer experiments: A review

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

Joseph, V. Roshan

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

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.

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation.

PubMed

Finnerty, Justin John; Peyser, Alexander; Carloni, Paolo

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.

Experimental statistics for biological sciences.

PubMed

Bang, Heejung; Davidian, Marie

2010-01-01

In this chapter, we cover basic and fundamental principles and methods in statistics - from "What are Data and Statistics?" to "ANOVA and linear regression," which are the basis of any statistical thinking and undertaking. Readers can easily find the selected topics in most introductory statistics textbooks, but we have tried to assemble and structure them in a succinct and reader-friendly manner in a stand-alone chapter. This text has long been used in real classroom settings for both undergraduate and graduate students who do or do not major in statistical sciences. We hope that from this chapter, readers would understand the key statistical concepts and terminologies, how to design a study (experimental or observational), how to analyze the data (e.g., describe the data and/or estimate the parameter(s) and make inference), and how to interpret the results. This text would be most useful if it is used as a supplemental material, while the readers take their own statistical courses or it would serve as a great reference text associated with a manual for any statistical software as a self-teaching guide.

What Is Design-Based Causal Inference for RCTs and Why Should I Use It? NCEE 2017-4025

ERIC Educational Resources Information Center

Schochet, Peter Z.

2017-01-01

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…

A Comparison of Methods to Test for Mediation in Multisite Experiments

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Stapleton, Laura M.

2005-01-01

A Monte Carlo study extended the research of MacKinnon, Lockwood, Hoffman, West, and Sheets (2002) for single-level designs by examining the statistical performance of four methods to test for mediation in a multilevel experimental design. The design studied was a two-group experiment that was replicated across several sites, included a single…

Plaque removal efficacy of a battery-operated toothbrush compared to a manual toothbrush.

PubMed

Ruhlman, C D; Bartizek, R D; Biesbrock, A R

2001-08-01

Recently, a new power toothbrush has been marketed with a design that fundamentally differs from other marketed power toothbrushes, in that it incorporates a round oscillating head, in conjunction with fixed bristles. The objective of this study was to compare the plaque removal efficacy of a control manual toothbrush (Colgate Navigator) to this experimental power toothbrush (Crest SpinBrush) following a single use. This study was a randomized, controlled, examiner-blind, 4-period crossover design which examined plaque removal with the two toothbrushes following a single use in 40 completed subjects. Plaque was scored before and after brushing using the Turesky Modification of the Quigley-Hein Index. Baseline plaque scores were 1.77 for both the experimental toothbrush and control toothbrush treatment groups. With respect to all surfaces examined, the experimental toothbrush delivered an adjusted (via analysis of covariance) mean difference between baseline and post-brushing plaque scores of 0.48 while the control toothbrush delivered an adjusted mean difference of 0.35. The experimental toothbrush removed, on average, 37.6% more plaque than the control toothbrush. These results were statistically significant (P< 0.001). With respect to buccal surfaces, the experimental toothbrush delivered an adjusted mean difference between baseline and post-brushing plaque scores of 0.54 while the control toothbrush delivered an adjusted mean difference of 0.42. This represents 27.8% more plaque removal with the experimental toothbrush compared to the control toothbrush. These results were also statistically significant (P= 0.001). Results on lingual surfaces also demonstrated statistically significantly (P< 0.001) greater plaque removal for the experimental toothbrush with an average of 53.4% more plaque removal.

Canonical Statistical Model for Maximum Expected Immission of Wire Conductor in an Aperture Enclosure

NASA Technical Reports Server (NTRS)

Bremner, Paul G.; Vazquez, Gabriel; Christiano, Daniel J.; Trout, Dawn H.

2016-01-01

Prediction of the maximum expected electromagnetic pick-up of conductors inside a realistic shielding enclosure is an important canonical problem for system-level EMC design of space craft, launch vehicles, aircraft and automobiles. This paper introduces a simple statistical power balance model for prediction of the maximum expected current in a wire conductor inside an aperture enclosure. It calculates both the statistical mean and variance of the immission from the physical design parameters of the problem. Familiar probability density functions can then be used to predict the maximum expected immission for deign purposes. The statistical power balance model requires minimal EMC design information and solves orders of magnitude faster than existing numerical models, making it ultimately viable for scaled-up, full system-level modeling. Both experimental test results and full wave simulation results are used to validate the foundational model.

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.

Beyond existence and aiming outside the laboratory: estimating frequency-dependent and pay-off-biased social learning strategies.

PubMed

McElreath, Richard; Bell, Adrian V; Efferson, Charles; Lubell, Mark; Richerson, Peter J; Waring, Timothy

2008-11-12

The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.

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.

Wet scrubbing of biomass producer gas tars using vegetable oil

NASA Astrophysics Data System (ADS)

Bhoi, Prakashbhai Ramabhai

The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.

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.

Statistical optimization of process parameters for lipase-catalyzed synthesis of triethanolamine-based esterquats using response surface methodology in 2-liter bioreactor.

PubMed

Masoumi, Hamid Reza Fard; Basri, Mahiran; Kassim, Anuar; Abdullah, Dzulkefly Kuang; Abdollahi, Yadollah; Abd Gani, Siti Salwa; Rezaee, Malahat

2013-01-01

Lipase-catalyzed production of triethanolamine-based esterquat by esterification of oleic acid (OA) with triethanolamine (TEA) in n-hexane was performed in 2 L stirred-tank reactor. A set of experiments was designed by central composite design to process modeling and statistically evaluate the findings. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio of OA to TEA, and agitation speed, were studied under the given conditions designed by Design Expert software. Experimental data were examined for normality test before data processing stage and skewness and kurtosis indices were determined. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum conversion of product. Response surface methodology with central composite design gave the best performance in this study, and the methodology as a whole has been proven to be adequate for the design and optimization of the enzymatic process.

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.

Optimization of Xylanase Production from Penicillium sp.WX-Z1 by a Two-Step Statistical Strategy: Plackett-Burman and Box-Behnken Experimental Design

PubMed Central

Cui, Fengjie; Zhao, Liming

2012-01-01

The objective of the study was to optimize the nutrition sources in a culture medium for the production of xylanase from Penicillium sp.WX-Z1 using Plackett-Burman design and Box-Behnken design. The Plackett-Burman multifactorial design was first employed to screen the important nutrient sources in the medium for xylanase production by Penicillium sp.WX-Z1 and subsequent use of the response surface methodology (RSM) was further optimized for xylanase production by Box-Behnken design. The important nutrient sources in the culture medium, identified by the initial screening method of Placket-Burman, were wheat bran, yeast extract, NaNO3, MgSO4, and CaCl2. The optimal amounts (in g/L) for maximum production of xylanase were: wheat bran, 32.8; yeast extract, 1.02; NaNO3, 12.71; MgSO4, 0.96; and CaCl2, 1.04. Using this statistical experimental design, the xylanase production under optimal condition reached 46.50 U/mL and an increase in xylanase activity of 1.34-fold was obtained compared with the original medium for fermentation carried out in a 30-L bioreactor. PMID:22949884

Optimization of Xylanase production from Penicillium sp.WX-Z1 by a two-step statistical strategy: Plackett-Burman and Box-Behnken experimental design.

PubMed

Cui, Fengjie; Zhao, Liming

2012-01-01

The objective of the study was to optimize the nutrition sources in a culture medium for the production of xylanase from Penicillium sp.WX-Z1 using Plackett-Burman design and Box-Behnken design. The Plackett-Burman multifactorial design was first employed to screen the important nutrient sources in the medium for xylanase production by Penicillium sp.WX-Z1 and subsequent use of the response surface methodology (RSM) was further optimized for xylanase production by Box-Behnken design. The important nutrient sources in the culture medium, identified by the initial screening method of Placket-Burman, were wheat bran, yeast extract, NaNO(3), MgSO(4), and CaCl(2). The optimal amounts (in g/L) for maximum production of xylanase were: wheat bran, 32.8; yeast extract, 1.02; NaNO(3), 12.71; MgSO(4), 0.96; and CaCl(2), 1.04. Using this statistical experimental design, the xylanase production under optimal condition reached 46.50 U/mL and an increase in xylanase activity of 1.34-fold was obtained compared with the original medium for fermentation carried out in a 30-L bioreactor.

Synthesis of Single-Case Experimental Data: A Comparison of Alternative Multilevel Approaches

ERIC Educational Resources Information Center

Ferron, John; Van den Noortgate, Wim; Beretvas, Tasha; Moeyaert, Mariola; Ugille, Maaike; Petit-Bois, Merlande; Baek, Eun Kyeng

2013-01-01

Single-case or single-subject experimental designs (SSED) are used to evaluate the effect of one or more treatments on a single case. Although SSED studies are growing in popularity, the results are in theory case-specific. One systematic and statistical approach for combining single-case data within and across studies is multilevel modeling. The…

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation

PubMed Central

Finnerty, Justin John

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores. PMID:26460827

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.

Subband Image Coding with Jointly Optimized Quantizers

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith Mark J. T.

1995-01-01

An iterative design algorithm for the joint design of complexity- and entropy-constrained subband quantizers and associated entropy coders is proposed. Unlike conventional subband design algorithms, the proposed algorithm does not require the use of various bit allocation algorithms. Multistage residual quantizers are employed here because they provide greater control of the complexity-performance tradeoffs, and also because they allow efficient and effective high-order statistical modeling. The resulting subband coder exploits statistical dependencies within subbands, across subbands, and across stages, mainly through complexity-constrained high-order entropy coding. Experimental results demonstrate that the complexity-rate-distortion performance of the new subband coder is exceptional.

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

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

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Econometric Assessment of "One Minute" Paper as a Pedagogic Tool

ERIC Educational Resources Information Center

Das, Amaresh

2010-01-01

This paper makes an econometric testing of one-minute paper used as a tool to manage and assess instruction in my statistics class. One of our findings is that the one minute paper when I have tested it by using an OLS estimate in a controlled Vs experimental design framework is found to statistically significant and effective in enhancing…

Accuracy of Person-Fit Statistics: A Monte Carlo Study of the Influence of Aberrance Rates

ERIC Educational Resources Information Center

St-Onge, Christina; Valois, Pierre; Abdous, Belkacem; Germain, Stephane

2011-01-01

Using a Monte Carlo experimental design, this research examined the relationship between answer patterns' aberrance rates and person-fit statistics (PFS) accuracy. It was observed that as the aberrance rate increased, the detection rates of PFS also increased until, in some situations, a peak was reached and then the detection rates of PFS…

The effect on prospective teachers of the learning environment supported by dynamic statistics software

NASA Astrophysics Data System (ADS)

Koparan, Timur

2016-02-01

In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study was carried out in 2014-2015 academic year fall semester at a university in Turkey. The study, which employed the pre-test-post-test control group design of quasi-experimental research method, was carried out on a group of 80 prospective teachers, 40 in the control group and 40 in the experimental group. Both groups had four-hour classes about descriptive statistics. The classes with the control group were carried out through traditional methods while dynamic statistics software was used in the experimental group. Five prospective teachers from the experimental group were interviewed clinically after the application for a deeper examination of their views about application. Qualitative data gained are presented under various themes. At the end of the study, it was found that there is a significant difference in favour of the experimental group in terms of achievement and attitudes, the prospective teachers have affirmative approach to the use of dynamic software and see it as an effective tool to enrich maths classes. In accordance with the findings of the study, it is suggested that dynamic software, which offers unique opportunities, be used in classes by teachers and students.

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.

75 FR 42087 - Science Advisory Board Staff Office; Request for Nominations of Experts for the SAB Hydraulic...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-20

... regarding trace organics and environmental monitoring; statistics, particularly regarding experimental design of field studies; human health effects and risk assessment; civil and environmental engineering...

Problems of the Randomization Test for AB Designs

ERIC Educational Resources Information Center

Manolov, Rumen; Solanas, Antonio

2009-01-01

N = 1 designs imply repeated registrations of the behaviour of the same experimental unit and the measurements obtained are often few due to time limitations, while they are also likely to be sequentially dependent. The analytical techniques needed to enhance statistical and clinical decision making have to deal with these problems. Different…

Application of Statistical Design for the Production of Cellulase by Trichoderma reesei Using Mango Peel

PubMed Central

Saravanan, P.; Muthuvelayudham, R.; Viruthagiri, T.

2012-01-01

Optimization of the culture medium for cellulase production using Trichoderma reesei was carried out. The optimization of cellulase production using mango peel as substrate was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence on cellulase production is achieved using Plackett-Burman design. Avicel, soybean cake flour, KH2PO4, and CoCl2 ·6H2O were selected based on their positive influence on cellulase production. The composition of the selected components was optimized using Response Surface Methodology (RSM). The optimum conditions are as follows: Avicel: 25.30 g/L, Soybean cake flour: 23.53 g/L, KH2PO4: 4.90 g/L, and CoCl2 ·6H2O: 0.95 g/L. These conditions are validated experimentally which revealed an enhanced Cellulase activity of 7.8 IU/mL. PMID:23304453

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.

The effects of DRIE operational parameters on vertically aligned micropillar arrays

NASA Astrophysics Data System (ADS)

Miller, Kane; Li, Mingxiao; Walsh, Kevin M.; Fu, Xiao-An

2013-03-01

Vertically aligned silicon micropillar arrays have been created by deep reactive ion etching (DRIE) and used for a number of microfabricated devices including microfluidic devices, micropreconcentrators and photovoltaic cells. This paper delineates an experimental design performed on the Bosch process of DRIE of micropillar arrays. The arrays are fabricated with direct-write optical lithography without photomask, and the effects of DRIE process parameters, including etch cycle time, passivation cycle time, platen power and coil power on profile angle, scallop depth and scallop peak-to-peak distance are studied by statistical design of experiments. Scanning electron microscope images are used for measuring the resultant profile angles and characterizing the scalloping effect on the pillar sidewalls. The experimental results indicate the effects of the determining factors, etch cycle time, passivation cycle time and platen power, on the micropillar profile angles and scallop depths. An optimized DRIE process recipe for creating nearly 90° and smooth surface (invisible scalloping) has been obtained as a result of the statistical design of experiments.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

Sequential experimental design based generalised ANOVA

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2016-07-01

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

Sequential experimental design based generalised ANOVA

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

Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover,more » generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.« less

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 modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

R. A. Fisher and his advocacy of randomization.

PubMed

Hall, Nancy S

2007-01-01

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods.

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.

Total Quality Management: Statistics and Graphics III - Experimental Design and Taguchi Methods. AIR 1993 Annual Forum Paper.

ERIC Educational Resources Information Center

Schwabe, Robert A.

Interest in Total Quality Management (TQM) at institutions of higher education has been stressed in recent years as an important area of activity for institutional researchers. Two previous AIR Forum papers have presented some of the statistical and graphical methods used for TQM. This paper, the third in the series, first discusses some of the…

Assessing the applicability of the Taguchi design method to an interrill erosion study

NASA Astrophysics Data System (ADS)

Zhang, F. B.; Wang, Z. L.; Yang, M. Y.

2015-02-01

Full-factorial experimental designs have been used in soil erosion studies, but are time, cost and labor intensive, and sometimes they are impossible to conduct due to the increasing number of factors and their levels to consider. The Taguchi design is a simple, economical and efficient statistical tool that only uses a portion of the total possible factorial combinations to obtain the results of a study. Soil erosion studies that use the Taguchi design are scarce and no comparisons with full-factorial designs have been made. In this paper, a series of simulated rainfall experiments using a full-factorial design of five slope lengths (0.4, 0.8, 1.2, 1.6, and 2 m), five slope gradients (18%, 27%, 36%, 48%, and 58%), and five rainfall intensities (48, 62.4, 102, 149, and 170 mm h-1) were conducted. Validation of the applicability of a Taguchi design to interrill erosion experiments was achieved by extracting data from the full dataset according to a theoretical Taguchi design. The statistical parameters for the mean quasi-steady state erosion and runoff rates of each test, the optimum conditions for producing maximum erosion and runoff, and the main effect and percentage contribution of each factor obtained from the full-factorial and Taguchi designs were compared. Both designs generated almost identical results. Using the experimental data from the Taguchi design, it was possible to accurately predict the erosion and runoff rates under the conditions that had been excluded from the Taguchi design. All of the results obtained from analyzing the experimental data for both designs indicated that the Taguchi design could be applied to interrill erosion studies and could replace full-factorial designs. This would save time, labor and costs by generally reducing the number of tests to be conducted. Further work should test the applicability of the Taguchi design to a wider range of conditions.

Designing Studies That Would Address the Multilayered Nature of Health Care

PubMed Central

Pennell, Michael; Rhoda, Dale; Hade, Erinn M.; Paskett, Electra D.

2010-01-01

We review design and analytic methods available for multilevel interventions in cancer research with particular attention to study design, sample size requirements, and potential to provide statistical evidence for causal inference. The most appropriate methods will depend on the stage of development of the research and whether randomization is possible. Early on, fractional factorial designs may be used to screen intervention components, particularly when randomization of individuals is possible. Quasi-experimental designs, including time-series and multiple baseline designs, can be useful once the intervention is designed because they require few sites and can provide the preliminary evidence to plan efficacy studies. In efficacy and effectiveness studies, group-randomized trials are preferred when randomization is possible and regression discontinuity designs are preferred otherwise if assignment based on a quantitative score is possible. Quasi-experimental designs may be used, especially when combined with recent developments in analytic methods to reduce bias in effect estimates. PMID:20386057

[Diversity and frequency of scientific research design and statistical methods in the "Arquivos Brasileiros de Oftalmologia": a systematic review of the "Arquivos Brasileiros de Oftalmologia"--1993-2002].

PubMed

Crosta, Fernando; Nishiwaki-Dantas, Maria Cristina; Silvino, Wilmar; Dantas, Paulo Elias Correa

2005-01-01

To verify the frequency of study design, applied statistical analysis and approval by institutional review offices (Ethics Committee) of articles published in the "Arquivos Brasileiros de Oftalmologia" during a 10-year interval, with later comparative and critical analysis by some of the main international journals in the field of Ophthalmology. Systematic review without metanalysis was performed. Scientific papers published in the "Arquivos Brasileiros de Oftalmologia" between January 1993 and December 2002 were reviewed by two independent reviewers and classified according to the applied study design, statistical analysis and approval by the institutional review offices. To categorize those variables, a descriptive statistical analysis was used. After applying inclusion and exclusion criteria, 584 articles for evaluation of statistical analysis and, 725 articles for evaluation of study design were reviewed. Contingency table (23.10%) was the most frequently applied statistical method, followed by non-parametric tests (18.19%), Student's t test (12.65%), central tendency measures (10.60%) and analysis of variance (9.81%). Of 584 reviewed articles, 291 (49.82%) presented no statistical analysis. Observational case series (26.48%) was the most frequently used type of study design, followed by interventional case series (18.48%), observational case description (13.37%), non-random clinical study (8.96%) and experimental study (8.55%). We found a higher frequency of observational clinical studies, lack of statistical analysis in almost half of the published papers. Increase in studies with approval by institutional review Ethics Committee was noted since it became mandatory in 1996.

Establishing Interventions via a Theory-Driven Single Case Design Research Cycle

ERIC Educational Resources Information Center

Kilgus, Stephen P.; Riley-Tillman, T. Chris; Kratochwill, Thomas R.

2016-01-01

Recent studies have suggested single case design (SCD) intervention research is subject to publication bias, wherein studies are more likely to be published if they possess large or statistically significant effects and use rigorous experimental methods. The nature of SCD and the purposes for which it might be used could suggest that large effects…

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

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.

Evaluation of General Classes of Reliability Estimators Often Used in Statistical Analyses of Quasi-Experimental Designs

NASA Astrophysics Data System (ADS)

Saini, K. K.; Sehgal, R. K.; Sethi, B. L.

2008-10-01

In this paper major reliability estimators are analyzed and there comparatively result are discussed. There strengths and weaknesses are evaluated in this case study. Each of the reliability estimators has certain advantages and disadvantages. Inter-rater reliability is one of the best ways to estimate reliability when your measure is an observation. However, it requires multiple raters or observers. As an alternative, you could look at the correlation of ratings of the same single observer repeated on two different occasions. Each of the reliability estimators will give a different value for reliability. In general, the test-retest and inter-rater reliability estimates will be lower in value than the parallel forms and internal consistency ones because they involve measuring at different times or with different raters. Since reliability estimates are often used in statistical analyses of quasi-experimental designs.

Use of response surface methodology in a fed-batch process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of canthaxanthin from Dietzia natronolimnaea HS-1.

PubMed

Nasri Nasrabadi, Mohammad Reza; Razavi, Seyed Hadi

2010-04-01

In this work, we applied statistical experimental design to a fed-batch process for optimization of tricarboxylic acid cycle (TCA) intermediates in order to achieve high-level production of canthaxanthin from Dietzia natronolimnaea HS-1 cultured in beet molasses. A fractional factorial design (screening test) was first conducted on five TCA cycle intermediates. Out of the five TCA cycle intermediates investigated via screening tests, alfaketoglutarate, oxaloacetate and succinate were selected based on their statistically significant (P<0.05) and positive effects on canthaxanthin production. These significant factors were optimized by means of response surface methodology (RSM) in order to achieve high-level production of canthaxanthin. The experimental results of the RSM were fitted with a second-order polynomial equation by means of a multiple regression technique to identify the relationship between canthaxanthin production and the three TCA cycle intermediates. By means of this statistical design under a fed-batch process, the optimum conditions required to achieve the highest level of canthaxanthin (13172 + or - 25 microg l(-1)) were determined as follows: alfaketoglutarate, 9.69 mM; oxaloacetate, 8.68 mM; succinate, 8.51 mM. Copyright 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

The effects of reminiscence in promoting mental health of Taiwanese elderly.

PubMed

Wang, Jing-Jy; Hsu, Ya-Chuan; Cheng, Su-Fen

2005-01-01

This study examined the effects of reminiscence on four selected mental health indicators, including depressive symptoms, mood status, self-esteem, and self-health perception of elderly people residing in community care facilities and at home. A longitudinal quasi-experimental design was conducted, using two equivalent groups for pre-post test and purposive sampling with random assignment. Each subject was administered pre- and post- tests at a 4 month interval but subjects in the experimental group underwent weekly intervention. Ninety-four subjects completed the study, with 48 in the control group and 46 in the experimental group. In the experimental group, a statistically significant difference (p = 0.041) was found between the pre-post tests on the dependent variable, depressive symptoms. However, no statistical significance was found in subjects' level of mood status, self-esteem, and self-health perception after the intervention in the experimental group, but slightly improvement was found. Reminiscence not only supports depression of the elderly but also empower nurses to become proactive in their daily nursing care activities.

A Range Finding Protocol to Support Design for Transcriptomics Experimentation: Examples of In-Vitro and In-Vivo Murine UV Exposure

PubMed Central

van Oostrom, Conny T.; Jonker, Martijs J.; de Jong, Mark; Dekker, Rob J.; Rauwerda, Han; Ensink, Wim A.; de Vries, Annemieke; Breit, Timo M.

2014-01-01

In transcriptomics research, design for experimentation by carefully considering biological, technological, practical and statistical aspects is very important, because the experimental design space is essentially limitless. Usually, the ranges of variable biological parameters of the design space are based on common practices and in turn on phenotypic endpoints. However, specific sub-cellular processes might only be partially reflected by phenotypic endpoints or outside the associated parameter range. Here, we provide a generic protocol for range finding in design for transcriptomics experimentation based on small-scale gene-expression experiments to help in the search for the right location in the design space by analyzing the activity of already known genes of relevant molecular mechanisms. Two examples illustrate the applicability: in-vitro UV-C exposure of mouse embryonic fibroblasts and in-vivo UV-B exposure of mouse skin. Our pragmatic approach is based on: framing a specific biological question and associated gene-set, performing a wide-ranged experiment without replication, eliminating potentially non-relevant genes, and determining the experimental ‘sweet spot’ by gene-set enrichment plus dose-response correlation analysis. Examination of many cellular processes that are related to UV response, such as DNA repair and cell-cycle arrest, revealed that basically each cellular (sub-) process is active at its own specific spot(s) in the experimental design space. Hence, the use of range finding, based on an affordable protocol like this, enables researchers to conveniently identify the ‘sweet spot’ for their cellular process of interest in an experimental design space and might have far-reaching implications for experimental standardization. PMID:24823911

Application of statistical experimental design to study the formulation variables influencing the coating process of lidocaine liposomes.

PubMed

González-Rodríguez, M L; Barros, L B; Palma, J; González-Rodríguez, P L; Rabasco, A M

2007-06-07

In this paper, we have used statistical experimental design to investigate the effect of several factors in coating process of lidocaine hydrochloride (LID) liposomes by a biodegradable polymer (chitosan, CH). These variables were the concentration of CH coating solution, the dripping rate of this solution on the liposome colloidal dispersion, the stirring rate, the time since the liposome production to the liposome coating and finally the amount of drug entrapped into liposomes. The selected response variables were drug encapsulation efficiency (EE, %), coating efficiency (CE, %) and zeta potential. Liposomes were obtained by thin-layer evaporation method. They were subsequently coated with CH according the experimental plan provided by a fractional factorial (2(5-1)) screening matrix. We have used spectroscopic methods to determine the zeta potential values. The EE (%) assay was carried out in dialysis bags and the brilliant red probe was used to determine CE (%) due to its property of forming molecular complexes with CH. The graphic analysis of the effects allowed the identification of the main formulation and technological factors by the analysis of the selected responses and permitted the determination of the proper level of these factors for the response improvement. Moreover, fractional design allowed quantifying the interactions between the factors, which will consider in next experiments. The results obtained pointed out that LID amount was the predominant factor that increased the drug entrapment capacity (EE). The CE (%) response was mainly affected by the concentration of the CH solution and the stirring rate, although all the interactions between the main factors have statistical significance.

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.

Experimental design and data analysis of Ago-RIP-Seq experiments for the identification of microRNA targets.

PubMed

Tichy, Diana; Pickl, Julia Maria Anna; Benner, Axel; Sültmann, Holger

2017-03-31

The identification of microRNA (miRNA) target genes is crucial for understanding miRNA function. Many methods for the genome-wide miRNA target identification have been developed in recent years; however, they have several limitations including the dependence on low-confident prediction programs and artificial miRNA manipulations. Ago-RNA immunoprecipitation combined with high-throughput sequencing (Ago-RIP-Seq) is a promising alternative. However, appropriate statistical data analysis algorithms taking into account the experimental design and the inherent noise of such experiments are largely lacking.Here, we investigate the experimental design for Ago-RIP-Seq and examine biostatistical methods to identify de novo miRNA target genes. Statistical approaches considered are either based on a negative binomial model fit to the read count data or applied to transformed data using a normal distribution-based generalized linear model. We compare them by a real data simulation study using plasmode data sets and evaluate the suitability of the approaches to detect true miRNA targets by sensitivity and false discovery rates. Our results suggest that simple approaches like linear regression models on (appropriately) transformed read count data are preferable. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Examining the Stationarity Assumption for Statistically Downscaled Climate Projections of Precipitation

NASA Astrophysics Data System (ADS)

Wootten, A.; Dixon, K. W.; Lanzante, J. R.; Mcpherson, R. A.

2017-12-01

Empirical statistical downscaling (ESD) approaches attempt to refine global climate model (GCM) information via statistical relationships between observations and GCM simulations. The aim of such downscaling efforts is to create added-value climate projections by adding finer spatial detail and reducing biases. The results of statistical downscaling exercises are often used in impact assessments under the assumption that past performance provides an indicator of future results. Given prior research describing the danger of this assumption with regards to temperature, this study expands the perfect model experimental design from previous case studies to test the stationarity assumption with respect to precipitation. Assuming stationarity implies the performance of ESD methods are similar between the future projections and historical training. Case study results from four quantile-mapping based ESD methods demonstrate violations of the stationarity assumption for both central tendency and extremes of precipitation. These violations vary geographically and seasonally. For the four ESD methods tested the greatest challenges for downscaling of daily total precipitation projections occur in regions with limited precipitation and for extremes of precipitation along Southeast coastal regions. We conclude with a discussion of future expansion of the perfect model experimental design and the implications for improving ESD methods and providing guidance on the use of ESD techniques for impact assessments and decision-support.

Application of the experimental design of experiments (DoE) for the determination of organotin compounds in water samples using HS-SPME and GC-MS/MS.

PubMed

Coscollà, Clara; Navarro-Olivares, Santiago; Martí, Pedro; Yusà, Vicent

2014-02-01

When attempting to discover the important factors and then optimise a response by tuning these factors, experimental design (design of experiments, DoE) gives a powerful suite of statistical methodology. DoE identify significant factors and then optimise a response with respect to them in method development. In this work, a headspace-solid-phase micro-extraction (HS-SPME) combined with gas chromatography tandem mass spectrometry (GC-MS/MS) methodology for the simultaneous determination of six important organotin compounds namely monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), monophenyltin (MPhT), diphenyltin (DPhT), triphenyltin (TPhT) has been optimized using a statistical design of experiments (DOE). The analytical method is based on the ethylation with NaBEt4 and simultaneous headspace-solid-phase micro-extraction of the derivative compounds followed by GC-MS/MS analysis. The main experimental parameters influencing the extraction efficiency selected for optimization were pre-incubation time, incubation temperature, agitator speed, extraction time, desorption temperature, buffer (pH, concentration and volume), headspace volume, sample salinity, preparation of standards, ultrasonic time and desorption time in the injector. The main factors (excitation voltage, excitation time, ion source temperature, isolation time and electron energy) affecting the GC-IT-MS/MS response were also optimized using the same statistical design of experiments. The proposed method presented good linearity (coefficient of determination R(2)>0.99) and repeatibilty (1-25%) for all the compounds under study. The accuracy of the method measured as the average percentage recovery of the compounds in spiked surface and marine waters was higher than 70% for all compounds studied. Finally, the optimized methodology was applied to real aqueous samples enabled the simultaneous determination of all compounds under study in surface and marine water samples obtained from Valencia region (Spain). © 2013 Elsevier B.V. All rights reserved.

Application of Plackett-Burman experimental design in the development of muffin using adlay flour

NASA Astrophysics Data System (ADS)

Valmorida, J. S.; Castillo-Israel, K. A. T.

2018-01-01

The application of Plackett-Burman experimental design was made to identify significant formulation and process variables in the development of muffin using adlay flour. Out of the seven screened variables, levels of sugar, levels of butter and baking temperature had the most significant influence on the product model in terms of physicochemical and sensory acceptability. Results of the experiment further demonstrate the effectiveness of Plackett-Burman design in choosing the best adlay variety for muffin production. Hence, the statistical method used in the study permits an efficient selection of important variables needed in the development of muffin from adlay which can be optimized using response surface methodology.

[Effects of Self-directed Feedback Practice using Smartphone Videos on Basic Nursing Skills, Confidence in Performance and Learning Satisfaction].

PubMed

Lee, Seul Gi; Shin, Yun Hee

2016-04-01

This study was done to verify effects of a self-directed feedback practice using smartphone videos on nursing students' basic nursing skills, confidence in performance and learning satisfaction. In this study an experimental study with a post-test only control group design was used. Twenty-nine students were assigned to the experimental group and 29 to the control group. Experimental treatment was exchanging feedback on deficiencies through smartphone recorded videos of nursing practice process taken by peers during self-directed practice. Basic nursing skills scores were higher for all items in the experimental group compared to the control group, and differences were statistically significant ["Measuring vital signs" (t=-2.10, p=.039); "Wearing protective equipment when entering and exiting the quarantine room and the management of waste materials" (t=-4.74, p<.001) "Gavage tube feeding" (t=-2.70, p=.009)]. Confidence in performance was higher in the experimental group compared to the control group, but the differences were not statistically significant. However, after the complete practice, there was a statistically significant difference in overall performance confidence (t=-3.07. p=.003). Learning satisfaction was higher in the experimental group compared to the control group, but the difference was not statistically significant (t=-1.67, p=.100). Results of this study indicate that self-directed feedback practice using smartphone videos can improve basic nursing skills. The significance is that it can help nursing students gain confidence in their nursing skills for the future through improvement of basic nursing skills and performance of quality care, thus providing patients with safer care.

A Comparison of Single Sample and Bootstrap Methods to Assess Mediation in Cluster Randomized Trials

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.; Kang, Joo Youn

2006-01-01

A Monte Carlo study examined the statistical performance of single sample and bootstrap methods that can be used to test and form confidence interval estimates of indirect effects in two cluster randomized experimental designs. The designs were similar in that they featured random assignment of clusters to one of two treatment conditions and…

40 CFR Appendix 6 to Subpart A of... - Reverse Phase Extraction (RPE) Method for Detection of Oil Contamination in Non-Aqueous Drilling...

Code of Federal Regulations, 2012 CFR

2012-07-01

... rigorous statistical experimental design and interpretation (Reference 16.4). 14.0Pollution Prevention 14... fluids. 1.4This method has been designed to show positive contamination for 5% of representative crude....1Sample collection bottles/jars—New, pre-cleaned bottles/jars, lot-certified to be free of artifacts...

40 CFR Appendix 6 to Subpart A of... - Reverse Phase Extraction (RPE) Method for Detection of Oil Contamination in Non-Aqueous Drilling...

Code of Federal Regulations, 2013 CFR

2013-07-01

... rigorous statistical experimental design and interpretation (Reference 16.4). 14.0Pollution Prevention 14... fluids. 1.4This method has been designed to show positive contamination for 5% of representative crude....1Sample collection bottles/jars—New, pre-cleaned bottles/jars, lot-certified to be free of artifacts...

40 CFR Appendix 6 to Subpart A of... - Reverse Phase Extraction (RPE) Method for Detection of Oil Contamination in Non-Aqueous Drilling...

Code of Federal Regulations, 2014 CFR

2014-07-01

... rigorous statistical experimental design and interpretation (Reference 16.4). 14.0Pollution Prevention 14... fluids. 1.4This method has been designed to show positive contamination for 5% of representative crude....1Sample collection bottles/jars—New, pre-cleaned bottles/jars, lot-certified to be free of artifacts...

40 CFR Appendix 6 to Subpart A of... - Reverse Phase Extraction (RPE) Method for Detection of Oil Contamination in Non-Aqueous Drilling...

Code of Federal Regulations, 2011 CFR

2011-07-01

... rigorous statistical experimental design and interpretation (Reference 16.4). 14.0Pollution Prevention 14... oil contamination in drilling fluids. 1.4This method has been designed to show positive contamination....1Sample collection bottles/jars—New, pre-cleaned bottles/jars, lot-certified to be free of artifacts...

[Difference in time of bowel sounds and passing of gas in abdominal hysterectomy patients having San-Yin-Jia (SP-6) acupressure].

PubMed

Chang, Soon Bok; Kim, Young Ran; Yoon, Mi Hee; Shim, Joung Un; Ko, Eun Hui; Kim, Min Ok

2004-12-01

The purpose of this study was to compare differences in the time when bowel sounds were heard and gas was passed in women who had an abdominal hysterectomy and were treated for 5 minutes (experimental group A) or 10 minutes (experimental group B) with San-Yin-Jiao (SP-6) acupressure. The design of this study was a nonequivalent control group non-synchronized post test only design. The participants included 142 women, 39 in experimental group A, 30 in experimental group B, and 73 in the control group. Data was collected using a structured questionnaire which included items on general characteristics and a self report of time when gas was passed. Differences for the three groups as to time when bowel sounds were heard and gas was passed were analyzed using ANOVA. The time when bowel sounds were heard was statistically significantly shorter in both experimental groups compared to the control group(F=10.29, p=.000). The time when gas was passed was statistically significantly shorter in experimental group B(10 min) compared to the control group(F=4.68, p=.011). It could be concluded that SP-6 acupressure of 10 minutes was effective in shortening the time until bowel sounds were heard and gas was passed for women who had had an abdominal hysterectomy. Replication of the study with a larger number of participants is necessary in order to be able to generalize the results.

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...

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments

PubMed Central

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-01-01

Objectives Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. Design and methods A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2–20), alternatives (2–5), attributes (2–20) and attribute levels (2–5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Outcome Relative d-efficiency was used to measure the optimality of each DCE design. Results DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Conclusions Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. PMID:27436671

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

PubMed

Bajard, Agathe; Chabaud, Sylvie; Cornu, Catherine; Castellan, Anne-Charlotte; Malik, Salma; Kurbatova, Polina; Volpert, Vitaly; Eymard, Nathalie; Kassai, Behrouz; Nony, Patrice

2016-01-01

The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations. A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease. According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL). Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

[Effects of Electric Stimulation and Biofeedback for Pelvic Floor Muscle Exercise in Women with Vaginal Rejuvenation Women].

PubMed

Lee, Jung Bok; Choi, So Young

2015-10-01

The purpose of this study was to investigate the effects of pelvic floor muscle exercise using electric stimulation and biofeedback on maximum pressure of vaginal contraction, vaginal contraction duration and sexual function in women who have had vaginal rejuvenation. The research design was a non-equivalent control group non-synchronized design study. Participants in this study were women who had vaginal rejuvenation at C obstetrics and gynecology hospital. The 15 participants in the experimental group were given pelvic floor muscle exercise using electric stimulation and biofeedback and the 15 participants in the control group received self pelvic floor muscle exercise. For maximum pressure of vaginal contraction, the experimental group showed a statistically significant increase compared to than the control group (t=5.96, p<.001). For vaginal contraction duration, the experimental group also showed a statistically significant increase compared to the control group (t=3.23, p=.003). For women's sexual function, the experimental group showed a significant increase when compared to the control group in total sexual function scores (t=3.41, p=.002). The results indicate that pelvic floor muscle exercise with electric stimulation and biofeedback after vaginal rejuvenation is effective in strengthening vaginal contraction pressure, vaginal contraction and that it also positively functions to increase women's sexual function.

A quasi-experimental feasibility study to determine the effect of a systematic treatment programme on the scores of the Nottingham Adjustment Scale of individuals with visual field deficits following stroke.

PubMed

Taylor, Lisa; Poland, Fiona; Harrison, Peter; Stephenson, Richard

2011-01-01

To evaluate a systematic treatment programme developed by the researcher that targeted aspects of visual functioning affected by visual field deficits following stroke. The study design was a non-equivalent control (conventional) group pretest-posttest quasi-experimental feasibility design, using multisite data collection methods at specified stages. The study was undertaken within three acute hospital settings as outpatient follow-up sessions. Individuals who had visual field deficits three months post stroke were studied. A treatment group received routine occupational therapy and an experimental group received, in addition, a systematic treatment programme. The treatment phase of both groups lasted six weeks. The Nottingham Adjustment Scale, a measure developed specifically for visual impairment, was used as the primary outcome measure. The change in Nottingham Adjustment Scale score was compared between the experimental (n = 7) and conventional (n = 8) treatment groups using the Wilcoxon signed ranks test. The result of Z = -2.028 (P = 0.043) showed that there was a statistically significant difference between the change in Nottingham Adjustment Scale score between both groups. The introduction of the systematic treatment programme resulted in a statistically significant change in the scores of the Nottingham Adjustment Scale.

Two-level QSAR network (2L-QSAR) for peptide inhibitor design based on amino acid properties and sequence positions.

PubMed

Du, Q S; Ma, Y; Xie, N Z; Huang, R B

2014-01-01

In the design of peptide inhibitors the huge possible variety of the peptide sequences is of high concern. In collaboration with the fast accumulation of the peptide experimental data and database, a statistical method is suggested for peptide inhibitor design. In the two-level peptide prediction network (2L-QSAR) one level is the physicochemical properties of amino acids and the other level is the peptide sequence position. The activity contributions of amino acids are the functions of physicochemical properties and the sequence positions. In the prediction equation two weight coefficient sets {ak} and {bl} are assigned to the physicochemical properties and to the sequence positions, respectively. After the two coefficient sets are optimized based on the experimental data of known peptide inhibitors using the iterative double least square (IDLS) procedure, the coefficients are used to evaluate the bioactivities of new designed peptide inhibitors. The two-level prediction network can be applied to the peptide inhibitor design that may aim for different target proteins, or different positions of a protein. A notable advantage of the two-level statistical algorithm is that there is no need for host protein structural information. It may also provide useful insight into the amino acid properties and the roles of sequence positions.

Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation

PubMed Central

Khan, Mohammad Jakir Hossain; Hussain, Mohd Azlan; Mujtaba, Iqbal Mohammed

2014-01-01

Propylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75°C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR). PMID:28788576

Recommendations for research design of telehealth studies.

PubMed

Chumbler, Neale R; Kobb, Rita; Brennan, David M; Rabinowitz, Terry

2008-11-01

Properly designed randomized controlled trials (RCTs) are the gold standard to use when examining the effectiveness of telehealth interventions on clinical outcomes. Some published telehealth studies have employed well-designed RCTs. However, such methods are not always feasible and practical in particular settings. This white paper addresses not only the need for properly designed RCTs, but also offers alternative research designs, such as quasi-experimental designs, and statistical techniques that can be employed to rigorously assess the effectiveness of telehealth studies. This paper further offers design and measurement recommendations aimed at and relevant to administrative decision-makers, policymakers, and practicing clinicians.

Critical evaluation of challenges and future use of animals in experimentation for biomedical research.

PubMed

Singh, Vijay Pal; Pratap, Kunal; Sinha, Juhi; Desiraju, Koundinya; Bahal, Devika; Kukreti, Ritushree

2016-12-01

Animal experiments that are conducted worldwide contribute to significant findings and breakthroughs in the understanding of the underlying mechanisms of various diseases, bringing up appropriate clinical interventions. However, their predictive value is often low, leading to translational failure. Problems like translational failure of animal studies and poorly designed animal experiments lead to loss of animal lives and less translatable data which affect research outcomes ethically and economically. Due to increasing complexities in animal usage with changes in public perception and stringent guidelines, it is becoming difficult to use animals for conducting studies. This review deals with challenges like poor experimental design and ethical concerns and discusses key concepts like sample size, statistics in experimental design, humane endpoints, economic assessment, species difference, housing conditions, and systematic reviews and meta-analyses that are often neglected. If practiced, these strategies can refine the procedures effectively and help translate the outcomes efficiently. © The Author(s) 2016.

The Use of Interrupted Case Studies to Enhance Critical Thinking Skills in Biology

PubMed Central

White, Tracy K.; Whitaker, Paul; Gonya, Terri; Hein, Richard; Kroening, Dubear; Lee, Kevin; Lee, Laura; Lukowiak, Andrea; Hayes, Elizabeth

2009-01-01

There has been a dramatic increase in the availability of case studies for use in the biology classroom, and perceptions of the effectiveness of case-study-based learning are overwhelmingly positive. Here we report the results of a study in which we evaluated the ability of interrupted case studies to improve critical thinking in the context of experimental design and the conventions of data interpretation. Students were assessed using further case studies designed to evaluate their ability to recognize and articulate problematic approaches to these elements of experimentation. Our work reveals that case studies have broad utility in the classroom. In addition to demonstrating a small but statistically significant increase in the number of students capable of critically evaluating selected aspects of experimental design, we also observed increased student engagement and documented widespread misconceptions regarding the conventions of data acquisition and analysis. PMID:23653687

Critical evaluation of challenges and future use of animals in experimentation for biomedical research

PubMed Central

Singh, Vijay Pal; Pratap, Kunal; Sinha, Juhi; Desiraju, Koundinya; Bahal, Devika; Kukreti, Ritushree

2016-01-01

Animal experiments that are conducted worldwide contribute to significant findings and breakthroughs in the understanding of the underlying mechanisms of various diseases, bringing up appropriate clinical interventions. However, their predictive value is often low, leading to translational failure. Problems like translational failure of animal studies and poorly designed animal experiments lead to loss of animal lives and less translatable data which affect research outcomes ethically and economically. Due to increasing complexities in animal usage with changes in public perception and stringent guidelines, it is becoming difficult to use animals for conducting studies. This review deals with challenges like poor experimental design and ethical concerns and discusses key concepts like sample size, statistics in experimental design, humane endpoints, economic assessment, species difference, housing conditions, and systematic reviews and meta-analyses that are often neglected. If practiced, these strategies can refine the procedures effectively and help translate the outcomes efficiently. PMID:27694614

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

PubMed

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

2015-03-01

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

Plackett-Burman experimental design to facilitate syntactic foam development

DOE PAGES

Smith, Zachary D.; Keller, Jennie R.; Bello, Mollie; ...

2015-09-14

The use of an eight-experiment Plackett–Burman method can assess six experimental variables and eight responses in a polysiloxane-glass microsphere syntactic foam. The approach aims to decrease the time required to develop a tunable polymer composite by identifying a reduced set of variables and responses suitable for future predictive modeling. The statistical design assesses the main effects of mixing process parameters, polymer matrix composition, microsphere density and volume loading, and the blending of two grades of microspheres, using a dummy factor in statistical calculations. Responses cover rheological, physical, thermal, and mechanical properties. The cure accelerator content of the polymer matrix andmore » the volume loading of the microspheres have the largest effects on foam properties. These factors are the most suitable for controlling the gel point of the curing foam, and the density of the cured foam. The mixing parameters introduce widespread variability and therefore should be fixed at effective levels during follow-up testing. Some responses may require greater contrast in microsphere-related factors. As a result, compared to other possible statistical approaches, the run economy of the Plackett–Burman method makes it a valuable tool for rapidly characterizing new foams.« less

Rational-Emotive Therapy versus Systematic Desensitization: A Comment on Moleski and Tosi.

ERIC Educational Resources Information Center

Atkinson, Leslie

1983-01-01

Questioned the statistical analyses of the Moleski and Tosi investigation of rational-emotive therapy versus systematic desensitization. Suggested means for lowering the error rate through a more efficient experimental design. Recommended a reanalysis of the original data. (LLL)

MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

EPA Science Inventory

Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

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.

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...

Mentors Offering Maternal Support (M.O.M.S.)

DTIC Science & Technology

2011-08-02

at Sessions 1, 5, and 8. Table 1. Pretest - posttest , randomized, controlled, repeated measured design Experimental Intervention Sessions...theoretical mediators of self-esteem and emotional support (0.6 standard deviation change from pretest to posttest ) with reduction of effect to 0.4...always brought back to the designated topic . In order to have statistically significant results for the outcome variables the study sessions must

Developing a "Semi-Systematic" Approach to Using Large-Scale Data-Sets for Small-Scale Interventions: The "Baby Matterz" Initiative as a Case Study

ERIC Educational Resources Information Center

O'Brien, Mark

2011-01-01

The appropriateness of using statistical data to inform the design of any given service development or initiative often depends upon judgements regarding scale. Large-scale data sets, perhaps national in scope, whilst potentially important in informing the design, implementation and roll-out of experimental initiatives, will often remain unused…

An experimental search strategy retrieves more precise results than PubMed and Google for questions about medical interventions

PubMed Central

Dylla, Daniel P.; Megison, Susan D.

2015-01-01

Objective. We compared the precision of a search strategy designed specifically to retrieve randomized controlled trials (RCTs) and systematic reviews of RCTs with search strategies designed for broader purposes. Methods. We designed an experimental search strategy that automatically revised searches up to five times by using increasingly restrictive queries as long at least 50 citations were retrieved. We compared the ability of the experimental and alternative strategies to retrieve studies relevant to 312 test questions. The primary outcome, search precision, was defined for each strategy as the proportion of relevant, high quality citations among the first 50 citations retrieved. Results. The experimental strategy had the highest median precision (5.5%; interquartile range [IQR]: 0%–12%) followed by the narrow strategy of the PubMed Clinical Queries (4.0%; IQR: 0%–10%). The experimental strategy found the most high quality citations (median 2; IQR: 0–6) and was the strategy most likely to find at least one high quality citation (73% of searches; 95% confidence interval 68%–78%). All comparisons were statistically significant. Conclusions. The experimental strategy performed the best in all outcomes although all strategies had low precision. PMID:25922798

Evaluating the decision accuracy and speed of clinical data visualizations.

PubMed

Pieczkiewicz, David S; Finkelstein, Stanley M

2010-01-01

Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.

Observation of non-classical correlations in sequential measurements of photon polarization

NASA Astrophysics Data System (ADS)

Suzuki, Yutaro; Iinuma, Masataka; Hofmann, Holger F.

2016-10-01

A sequential measurement of two non-commuting quantum observables results in a joint probability distribution for all output combinations that can be explained in terms of an initial joint quasi-probability of the non-commuting observables, modified by the resolution errors and back-action of the initial measurement. Here, we show that the error statistics of a sequential measurement of photon polarization performed at different measurement strengths can be described consistently by an imaginary correlation between the statistics of resolution and back-action. The experimental setup was designed to realize variable strength measurements with well-controlled imaginary correlation between the statistical errors caused by the initial measurement of diagonal polarizations, followed by a precise measurement of the horizontal/vertical polarization. We perform the experimental characterization of an elliptically polarized input state and show that the same complex joint probability distribution is obtained at any measurement strength.

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

PubMed

Chow, S L

1998-04-01

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

Statistical Design in Isothermal Aging of Polyimide Resins

NASA Technical Reports Server (NTRS)

Sutter, James K.; Jobe, Marcus; Crane, Elizabeth A.

1995-01-01

Recent developments in research on polyimides for high temperature applications have led to the synthesis of many new polymers. Among the criteria that determines their thermal oxidative stability, isothermal aging is one of the most important. Isothermal aging studies require that many experimental factors are controlled to provide accurate results. In this article we describe a statistical plan that compares the isothermal stability of several polyimide resins, while minimizing the variations inherent in high-temperature aging studies.

Analysis of chemical warfare agents. II. Use of thiols and statistical experimental design for the trace level determination of vesicant compounds in air samples.

PubMed

Muir, Bob; Quick, Suzanne; Slater, Ben J; Cooper, David B; Moran, Mary C; Timperley, Christopher M; Carrick, Wendy A; Burnell, Christopher K

2005-03-18

Thermal desorption with gas chromatography-mass spectrometry (TD-GC-MS) remains the technique of choice for analysis of trace concentrations of analytes in air samples. This paper describes the development and application of a method for analysing the vesicant compounds sulfur mustard and Lewisites I-III. 3,4-Dimercaptotoluene and butanethiol were used to spike sorbent tubes and vesicant vapours sampled; Lewisite I and II reacted with the thiols while sulfur mustard and Lewisite III did not. Statistical experimental design was used to optimise thermal desorption parameters and the optimum method used to determine vesicant compounds in headspace samples taken from a decontamination trial. 3,4-Dimercaptotoluene reacted with Lewisites I and II to give a common derivative with a limit of detection (LOD) of 260 microg m(-3), while the butanethiol gave distinct derivatives with limits of detection around 30 microg m(-3).

Bio hydrogen production from cassava starch by anaerobic mixed cultures: Multivariate statistical modeling

NASA Astrophysics Data System (ADS)

Tien, Hai Minh; Le, Kien Anh; Le, Phung Thi Kim

2017-09-01

Bio hydrogen is a sustainable energy resource due to its potentially higher efficiency of conversion to usable power, high energy efficiency and non-polluting nature resource. In this work, the experiments have been carried out to indicate the possibility of generating bio hydrogen as well as identifying effective factors and the optimum conditions from cassava starch. Experimental design was used to investigate the effect of operating temperature (37-43 °C), pH (6-7), and inoculums ratio (6-10 %) to the yield hydrogen production, the COD reduction and the ratio of volume of hydrogen production to COD reduction. The statistical analysis of the experiment indicated that the significant effects for the fermentation yield were the main effect of temperature, pH and inoculums ratio. The interaction effects between them seem not significant. The central composite design showed that the polynomial regression models were in good agreement with the experimental results. This result will be applied to enhance the process of cassava starch processing wastewater treatment.

Use of simulation-based learning in undergraduate nurse education: An umbrella systematic review.

PubMed

Cant, Robyn P; Cooper, Simon J

2017-02-01

To conduct a systematic review to appraise and review evidence on the impact of simulation-based education for undergraduate/pre-licensure nursing students, using existing reviews of literature. An umbrella review (review of reviews). Cumulative Index of Nursing and Allied Health Literature (CINAHLPlus), PubMed, and Google Scholar. Reviews of literature conducted between 2010 and 2015 regarding simulation-based education for pre-licensure nursing students. The Joanna Briggs Institute methodology for conduct of an umbrella review was used to inform the review process. Twenty-five systematic reviews of literature were included, of which 14 were recent (2013-2015). Most described the level of evidence of component studies as a mix of experimental and quasi-experimental designs. The reviews measured around 14 different main outcome variables, thus limiting the number of primary studies that each individual review could pool to appraise. Many reviews agreed on the key learning outcome of knowledge acquisition, although no overall quantitative effect was derived. Three of four high-quality reviews found that simulation supported psychomotor development; a fourth found too few high quality studies to make a statistical comparison. Simulation statistically improved self-efficacy in pretest-posttest studies, and in experimental designs self-efficacy was superior to that of other teaching methods; lower level research designs limiting further comparison. The reviews commonly reported strong student satisfaction with simulation education and some reported improved confidence and/or critical thinking. This umbrella review took a global view of 25 reviews of simulation research in nursing education, comprising over 700 primary studies. To discern overall outcomes across reviews, statistical comparison of quantitative results (effect size) must be the key comparator. Simulation-based education contributes to students' learning in a number of ways when integrated into pre-licensure nursing curricula. Overall, use of a constellation of instruments and a lack of high quality study designs mean that there are still some gaps in evidence of effects that need to be addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Photocatalytic degradation using design of experiments: a review and example of the Congo red degradation.

PubMed

Sakkas, Vasilios A; Islam, Md Azharul; Stalikas, Constantine; Albanis, Triantafyllos A

2010-03-15

The use of chemometric methods such as response surface methodology (RSM) based on statistical design of experiments (DOEs) is becoming increasingly widespread in several sciences such as analytical chemistry, engineering and environmental chemistry. Applied catalysis, is certainly not the exception. It is clear that photocatalytic processes mated with chemometric experimental design play a crucial role in the ability of reaching the optimum of the catalytic reactions. The present article reviews the major applications of RSM in modern experimental design combined with photocatalytic degradation processes. Moreover, the theoretical principles and designs that enable to obtain a polynomial regression equation, which expresses the influence of process parameters on the response are thoroughly discussed. An original experimental work, the photocatalytic degradation of the dye Congo red (CR) using TiO(2) suspensions and H(2)O(2), in natural surface water (river water) is comprehensively described as a case study, in order to provide sufficient guidelines to deal with this subject, in a rational and integrated way. (c) 2009 Elsevier B.V. All rights reserved.

The Effect of Reflexology Applied to Patients with Chronic Obstructive Pulmonary Disease on Dyspnea and Fatigue.

PubMed

Polat, Hatice; Ergüney, Seher

The purpose of this study was to determine the effect of reflexology on reducing dyspnea and fatigue in patients with chronic obstructive pulmonary disease (COPD). The study was conducted as a pretest-posttest experimental design. The population of the study consisted of 60 patients (30 in experimental group and 30 in control group). Patient Description Form, Baseline Dyspnea Index (BDI) and Visual Analogue Scale-Fatigue (VAS-F) were used to collect the data. The difference between pretest-posttest dyspnea and fatigue mean scores of patients in the experimental group was statistically significant (p < .01). The difference between pretest-posttest dyspnea and fatigue mean scores of patients in the control group was statistically insignificant (p > .05). It was determined that the reflexology reduced dyspnea and fatigue in patients with COPD. Complementary methods such as reflexology should be used with pharmacological methods to reduce dyspnea and fatigue of COPD patients.

Statistical Engineering in Air Traffic Management Research

NASA Technical Reports Server (NTRS)

Wilson, Sara R.

2015-01-01

NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.

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

A randomized evaluation of a computer-based physician's workstation: design considerations and baseline results.

PubMed Central

Rotman, B. L.; Sullivan, A. N.; McDonald, T.; DeSmedt, P.; Goodnature, D.; Higgins, M.; Suermondt, H. J.; Young, C. Y.; Owens, D. K.

1995-01-01

We are performing a randomized, controlled trial of a Physician's Workstation (PWS), an ambulatory care information system, developed for use in the General Medical Clinic (GMC) of the Palo Alto VA. Goals for the project include selecting appropriate outcome variables and developing a statistically powerful experimental design with a limited number of subjects. As PWS provides real-time drug-ordering advice, we retrospectively examined drug costs and drug-drug interactions in order to select outcome variables sensitive to our short-term intervention as well as to estimate the statistical efficiency of alternative design possibilities. Drug cost data revealed the mean daily cost per physician per patient was 99.3 cents +/- 13.4 cents, with a range from 0.77 cent to 1.37 cents. The rate of major interactions per prescription for each physician was 2.9% +/- 1%, with a range from 1.5% to 4.8%. Based on these baseline analyses, we selected a two-period parallel design for the evaluation, which maximized statistical power while minimizing sources of bias. PMID:8563376

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.

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 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.

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.

Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force.

PubMed

Reed Johnson, F; Lancsar, Emily; Marshall, Deborah; Kilambi, Vikram; Mühlbacher, Axel; Regier, Dean A; Bresnahan, Brian W; Kanninen, Barbara; Bridges, John F P

2013-01-01

Stated-preference methods are a class of evaluation techniques for studying the preferences of patients and other stakeholders. While these methods span a variety of techniques, conjoint-analysis methods-and particularly discrete-choice experiments (DCEs)-have become the most frequently applied approach in health care in recent years. Experimental design is an important stage in the development of such methods, but establishing a consensus on standards is hampered by lack of understanding of available techniques and software. This report builds on the previous ISPOR Conjoint Analysis Task Force Report: Conjoint Analysis Applications in Health-A Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. This report aims to assist researchers specifically in evaluating alternative approaches to experimental design, a difficult and important element of successful DCEs. While this report does not endorse any specific approach, it does provide a guide for choosing an approach that is appropriate for a particular study. In particular, it provides an overview of the role of experimental designs for the successful implementation of the DCE approach in health care studies, and it provides researchers with an introduction to constructing experimental designs on the basis of study objectives and the statistical model researchers have selected for the study. The report outlines the theoretical requirements for designs that identify choice-model preference parameters and summarizes and compares a number of available approaches for constructing experimental designs. The task-force leadership group met via bimonthly teleconferences and in person at ISPOR meetings in the United States and Europe. An international group of experimental-design experts was consulted during this process to discuss existing approaches for experimental design and to review the task force's draft reports. In addition, ISPOR members contributed to developing a consensus report by submitting written comments during the review process and oral comments during two forum presentations at the ISPOR 16th and 17th Annual International Meetings held in Baltimore (2011) and Washington, DC (2012). Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments.

PubMed

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-07-19

Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2-20), alternatives (2-5), attributes (2-20) and attribute levels (2-5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Relative d-efficiency was used to measure the optimality of each DCE design. DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Factorial Experiments: Efficient Tools for Evaluation of Intervention Components

PubMed Central

Collins, Linda M.; Dziak, John J.; Kugler, Kari C.; Trail, Jessica B.

2014-01-01

Background An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the randomized controlled trial (RCT); the two designs address different research questions. Purpose This article offers an introduction to factorial experiments aimed at investigators trained primarily in the RCT. Method The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate. Results Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided. Conclusions Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources. PMID:25092122

Social Early Stimulation of Trisomy-21 Babies

ERIC Educational Resources Information Center

Aparicio, Maria Teresa Sanz; Balana, Javier Menendez

2003-01-01

This study was initiated with twenty Down's syndrome babies to verify whether subjects undergoing social early stimulation would benefit from this type of treatment. An experimental study was designed with two training groups: visual or written instructions. The analyses of the results established statistically significant differences in the…

Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates

DTIC Science & Technology

2008-03-01

injector con- figurations for Scramjet applications.” International Journal of Heat and Mass Transfer 49: 3634–3644 (2006). 8. Anderson, C.D...Experimental Attainment of Optimal Conditions,” Journal of the Royal Statistical Society, B(13): 1–38, 1951. 19. Brewer, K.M. Exergy Methods for the Mission...second applies mvps to a new scramjet design in support of the Hypersonic International Flight Re- search Experimentation (hifire). The results

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

NASA Technical Reports Server (NTRS)

Judge, R. A.; Kephart, R.; Leardi, R.; Myles, D. A.; Snell, E. H.; vanderWoerd, M.; Curreri, Peter A. (Technical Monitor)

2002-01-01

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

The Power Prior: Theory and Applications

PubMed Central

Ibrahim, Joseph G.; Chen, Ming-Hui; Gwon, Yeongjin; Chen, Fang

2015-01-01

The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A to Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Prequentist properties of power priors in posterior inference are established and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials. PMID:26346180

Approach toward enhancement of halophilic protease production by Halobacterium sp. strain LBU50301 using statistical design response surface methodology.

PubMed

Chuprom, Julalak; Bovornreungroj, Preeyanuch; Ahmad, Mehraj; Kantachote, Duangporn; Dueramae, Sawitree

2016-06-01

A new potent halophilic protease producer, Halobacterium sp. strain LBU50301 was isolated from salt-fermented fish samples ( budu ) and identified by phenotypic analysis, and 16S rDNA gene sequencing. Thereafter, sequential statistical strategy was used to optimize halophilic protease production from Halobacterium sp. strain LBU50301 by shake-flask fermentation. The classical one-factor-at-a-time (OFAT) approach determined gelatin was the best nitrogen source. Based on Plackett - Burman (PB) experimental design; gelatin, MgSO 4 ·7H 2 O, NaCl and pH significantly influenced the halophilic protease production. Central composite design (CCD) determined the optimum level of medium components. Subsequently, an 8.78-fold increase in corresponding halophilic protease yield (156.22 U/mL) was obtained, compared with that produced in the original medium (17.80 U/mL). Validation experiments proved the adequacy and accuracy of model, and the results showed the predicted value agreed well with the experimental values. An overall 13-fold increase in halophilic protease yield was achieved using a 3 L laboratory fermenter and optimized medium (231.33 U/mL).

Impact of Chemical Proportions on the Acute Neurotoxicity of a Mixture of Seven Carbamates in Preweanling and Adult Rats

EPA Science Inventory

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose-additivity for two mixtures of seven N-methylcarbamates (carbaryl, carb...

Non-Cognitive Factor Relationships to Hybrid Doctoral Course Satisfaction and Self-Efficacy

ERIC Educational Resources Information Center

Egbert, Jessica Dalby

2013-01-01

Through a quantitative, non-experimental design, the studied explored non-cognitive factor relationships to hybrid doctoral course satisfaction and self-efficacy, including the differences between the online and on-campus components of the student-selected hybrid courses. Descriptive, bivariate, and multivariate statistical analyses were used to…

Using Alien Coins to Test Whether Simple Inference Is Bayesian

ERIC Educational Resources Information Center

Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.

2016-01-01

Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

RESEARCH REPORT ON THE RISK ASSESSMENT OF MIXTURES OF DISINFECTION BY-PRODUCTS (DBPS) IN DRINKING WATER

EPA Science Inventory

This report presents a number of manuscripts and progress reports on statistical and biological research pertaining to the health risk assessment of simple DBP mixtures. Research has been conducted to generate efficient experimental designs to test specific mixtures for departu...

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.

Development and validation of LC-MS/MS method for the quantification of oxcarbazepine in human plasma using an experimental design.

PubMed

Srinubabu, Gedela; Ratnam, Bandaru Veera Venkata; Rao, Allam Appa; Rao, Medicherla Narasimha

2008-01-01

A rapid tandem mass spectrometric (MS-MS) method for the quantification of Oxcarbazepine (OXB) in human plasma using imipramine as an internal standard (IS) has been developed and validated. Chromatographic separation was achieved isocratically on a C18 reversed-phase column within 3.0 min, using a mobile phase of acetonitrile-10 mM ammonium formate (90 : 10 v/v) at a flow rate of 0.3 ml/min. Quantitation was achieved using multiple reaction monitoring (MRM) scan at MRM transitions m/z 253>208 and m/z 281>86 for OXB and the IS respectively. Calibration curves were linear over the concentration range of 0.2-16 mug/ml (r>0.999) with a limit of quantification of 0.2 mug/ml. Analytical recoveries of OXB from spiked human plasma were in the range of 74.9 to 76.3%. Plackett-Burman design was applied for screening of chromatographic and mass spectrometric factors; factorial design was applied for optimization of essential factors for the robustness study. A linear model was postulated and a 2(3) full factorial design was employed to estimate the model coefficients for intermediate precision. More specifically, experimental design helps the researcher to verify if changes in factor values produce a statistically significant variation of the observed response. The strategy is most effective if statistical design is used in most or all stages of the screening and optimizing process for future method validation of pharmacokinetic and bioequivalence studies.

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

PubMed

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

2016-01-27

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

Semantically enabled and statistically supported biological hypothesis testing with tissue microarray databases

PubMed Central

2011-01-01

Background Although many biological databases are applying semantic web technologies, meaningful biological hypothesis testing cannot be easily achieved. Database-driven high throughput genomic hypothesis testing requires both of the capabilities of obtaining semantically relevant experimental data and of performing relevant statistical testing for the retrieved data. Tissue Microarray (TMA) data are semantically rich and contains many biologically important hypotheses waiting for high throughput conclusions. Methods An application-specific ontology was developed for managing TMA and DNA microarray databases by semantic web technologies. Data were represented as Resource Description Framework (RDF) according to the framework of the ontology. Applications for hypothesis testing (Xperanto-RDF) for TMA data were designed and implemented by (1) formulating the syntactic and semantic structures of the hypotheses derived from TMA experiments, (2) formulating SPARQLs to reflect the semantic structures of the hypotheses, and (3) performing statistical test with the result sets returned by the SPARQLs. Results When a user designs a hypothesis in Xperanto-RDF and submits it, the hypothesis can be tested against TMA experimental data stored in Xperanto-RDF. When we evaluated four previously validated hypotheses as an illustration, all the hypotheses were supported by Xperanto-RDF. Conclusions We demonstrated the utility of high throughput biological hypothesis testing. We believe that preliminary investigation before performing highly controlled experiment can be benefited. PMID:21342584

A product of independent beta probabilities dose escalation design for dual-agent phase I trials.

PubMed

Mander, Adrian P; Sweeting, Michael J

2015-04-15

Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, where a 3 + 3 rule-based design is often still used. To expedite this process, new dose-escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve-free (nonparametric) design for a dual-agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose-escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

R A Fisher, design theory, and the Indian connection.

PubMed

Rau, A R P

2009-09-01

Design Theory, a branch of mathematics, was born out of the experimental statistics research of the population geneticist R A Fisher and of Indian mathematical statisticians in the 1930s. The field combines elements of combinatorics, finite projective geometries, Latin squares, and a variety of further mathematical structures, brought together in surprising ways. This essay will present these structures and ideas as well as how the field came together, in itself an interesting story.

An Improved Rank Correlation Effect Size Statistic for Single-Case Designs: Baseline Corrected Tau.

PubMed

Tarlow, Kevin R

2017-07-01

Measuring treatment effects when an individual's pretreatment performance is improving poses a challenge for single-case experimental designs. It may be difficult to determine whether improvement is due to the treatment or due to the preexisting baseline trend. Tau- U is a popular single-case effect size statistic that purports to control for baseline trend. However, despite its strengths, Tau- U has substantial limitations: Its values are inflated and not bound between -1 and +1, it cannot be visually graphed, and its relatively weak method of trend control leads to unacceptable levels of Type I error wherein ineffective treatments appear effective. An improved effect size statistic based on rank correlation and robust regression, Baseline Corrected Tau, is proposed and field-tested with both published and simulated single-case time series. A web-based calculator for Baseline Corrected Tau is also introduced for use by single-case investigators.

Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience.

PubMed

Vuorre, Matti; Bolger, Niall

2017-12-15

Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.

Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors.

PubMed Central

Small, J R

1993-01-01

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434

A Test of the Effectiveness of Time Management Training in a Department of the Navy Program Management Office (PMO)

DTIC Science & Technology

1977-05-01

An experiment, designed to introduce time management concepts, was conducted with 33 volunteers from a Department of the Navy PMO -- the experimental...group. The instruments used to conduct the experiment were a Time Management Survey and a Time Management Questionnaire. The survey was used to...data obtained from the experimental group were statistically compared with similar data from a control group. Time management principles and ’tips’ on

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.

The Role of Formal Experiment Design in Hypersonic Flight System Technology Development

NASA Technical Reports Server (NTRS)

McClinton, Charles R.; Ferlemann, Shelly M.; Rock, Ken E.; Ferlemann, Paul G.

2002-01-01

Hypersonic airbreathing engine (scramjet) powered vehicles are being considered to replace conventional rocket-powered launch systems. Effective utilization of scramjet engines requires careful integration with the air vehicle. This integration synergistically combines aerodynamic forces with propulsive cycle functions of the engine. Due to the highly integrated nature of the hypersonic vehicle design problem, the large flight envelope, and the large number of design variables, the use of a statistical design approach in design is effective. Modern Design-of-Experiments (MDOE) has been used throughout the Hyper-X program, for both systems analysis and experimental testing. Application of MDOE fall into four categories: (1) experimental testing; (2) studies of unit phenomena; (3) refining engine design; and (4) full vehicle system optimization. The MDOE process also provides analytical models, which are also used to document lessons learned, supplement low-level design tools, and accelerate future studies. This paper will discuss the design considerations for scramjet-powered vehicles, specifics of MDOE utilized for Hyper-X, and present highlights from the use of these MDOE methods within the Hyper-X Program.

Electrochemical production and use of free chlorine for pollutant removal: an experimental design approach.

PubMed

Antonelli, Raissa; de Araújo, Karla Santos; Pires, Ricardo Francisco; Fornazari, Ana Luiza de Toledo; Granato, Ana Claudia; Malpass, Geoffroy Roger Pointer

2017-10-28

The present paper presents the study of (1) the optimization of electrochemical-free chlorine production using an experimental design approach, and (2) the application of the optimum conditions obtained for the application in photo-assisted electrochemical degradation of simulated textile effluent. In the experimental design the influence of inter-electrode gap, pH, NaCl concentration and current was considered. It was observed that the four variables studied are significant for the process, with NaCl concentration and current being the most significant variables for free chlorine production. The maximum free chlorine production was obtained at a current of 2.33 A and NaCl concentrations in 0.96 mol dm -3 . The application of the optimized conditions with simultaneous UV irradiation resulted in up to 83.1% Total Organic Carbon removal and 100% of colour removal over 180 min of electrolysis. The results indicate that a systematic (statistical) approach to the electrochemical treatment of pollutants can save time and reagents.

Development of a fast, lean and agile direct pelletization process using experimental design techniques.

PubMed

Politis, Stavros N; Rekkas, Dimitrios M

2017-04-01

A novel hot melt direct pelletization method was developed, characterized and optimized, using statistical thinking and experimental design tools. Mixtures of carnauba wax (CW) and HPMC K100M were spheronized using melted gelucire 50-13 as a binding material (BM). Experimentation was performed sequentially; a fractional factorial design was set up initially to screen the factors affecting the process, namely spray rate, quantity of BM, rotor speed, type of rotor disk, lubricant-glidant presence, additional spheronization time, powder feeding rate and quantity. From the eight factors assessed, three were further studied during process optimization (spray rate, quantity of BM and powder feeding rate), at different ratios of the solid mixture of CW and HPMC K100M. The study demonstrated that the novel hot melt process is fast, efficient, reproducible and predictable. Therefore, it can be adopted in a lean and agile manufacturing setting for the production of flexible pellet dosage forms with various release rates easily customized between immediate and modified delivery.

Polyester: simulating RNA-seq datasets with differential transcript expression.

PubMed

Frazee, Alyssa C; Jaffe, Andrew E; Langmead, Ben; Leek, Jeffrey T

2015-09-01

Statistical methods development for differential expression analysis of RNA sequencing (RNA-seq) requires software tools to assess accuracy and error rate control. Since true differential expression status is often unknown in experimental datasets, artificially constructed datasets must be utilized, either by generating costly spike-in experiments or by simulating RNA-seq data. Polyester is an R package designed to simulate RNA-seq data, beginning with an experimental design and ending with collections of RNA-seq reads. Its main advantage is the ability to simulate reads indicating isoform-level differential expression across biological replicates for a variety of experimental designs. Data generated by Polyester is a reasonable approximation to real RNA-seq data and standard differential expression workflows can recover differential expression set in the simulation by the user. Polyester is freely available from Bioconductor (http://bioconductor.org/). jtleek@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Fractional Factorial Design Study on the Performance of GAC-Enhanced Electrocoagulation Process Involved in Color Removal from Dye Solutions.

PubMed

Secula, Marius Sebastian; Cretescu, Igor; Cagnon, Benoit; Manea, Liliana Rozemarie; Stan, Corneliu Sergiu; Breaban, Iuliana Gabriela

2013-07-10

The aim of this study was to determine the effects of main factors and interactions on the color removal performance from dye solutions using the electrocoagulation process enhanced by adsorption on Granular Activated Carbon (GAC). In this study, a mathematical approach was conducted using a two-level fractional factorial design ( FFD ) for a given dye solution. Three textile dyes: Acid Blue 74, Basic Red 1, and Reactive Black 5 were used. Experimental factors used and their respective levels were: current density (2.73 or 27.32 A/m²), initial pH of aqueous dye solution (3 or 9), electrocoagulation time (20 or 180 min), GAC dose (0.1 or 0.5 g/L), support electrolyte (2 or 50 mM), initial dye concentration (0.05 or 0.25 g/L) and current type (Direct Current- DC or Alternative Pulsed Current- APC ). GAC-enhanced electrocoagulation performance was analyzed statistically in terms of removal efficiency, electrical energy, and electrode material consumptions, using modeling polynomial equations. The statistical significance of GAC dose level on the performance of GAC enhanced electrocoagulation and the experimental conditions that favor the process operation of electrocoagulation in APC regime were determined. The local optimal experimental conditions were established using a multi-objective desirability function method.

Fractional Factorial Design Study on the Performance of GAC-Enhanced Electrocoagulation Process Involved in Color Removal from Dye Solutions

PubMed Central

Secula, Marius Sebastian; Cretescu, Igor; Cagnon, Benoit; Manea, Liliana Rozemarie; Stan, Corneliu Sergiu; Breaban, Iuliana Gabriela

2013-01-01

The aim of this study was to determine the effects of main factors and interactions on the color removal performance from dye solutions using the electrocoagulation process enhanced by adsorption on Granular Activated Carbon (GAC). In this study, a mathematical approach was conducted using a two-level fractional factorial design (FFD) for a given dye solution. Three textile dyes: Acid Blue 74, Basic Red 1, and Reactive Black 5 were used. Experimental factors used and their respective levels were: current density (2.73 or 27.32 A/m2), initial pH of aqueous dye solution (3 or 9), electrocoagulation time (20 or 180 min), GAC dose (0.1 or 0.5 g/L), support electrolyte (2 or 50 mM), initial dye concentration (0.05 or 0.25 g/L) and current type (Direct Current—DC or Alternative Pulsed Current—APC). GAC-enhanced electrocoagulation performance was analyzed statistically in terms of removal efficiency, electrical energy, and electrode material consumptions, using modeling polynomial equations. The statistical significance of GAC dose level on the performance of GAC enhanced electrocoagulation and the experimental conditions that favor the process operation of electrocoagulation in APC regime were determined. The local optimal experimental conditions were established using a multi-objective desirability function method. PMID:28811405

Experimental Design for Hanford Low-Activity Waste Glasses with High Waste Loading

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

Piepel, Gregory F.; Cooley, Scott K.; Vienna, John D.

This report discusses the development of an experimental design for the initial phase of the Hanford low-activity waste (LAW) enhanced glass study. This report is based on a manuscript written for an applied statistics journal. Appendices A, B, and E include additional information relevant to the LAW enhanced glass experimental design that is not included in the journal manuscript. The glass composition experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC involving 15 LAW glass components. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directlymore » applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this report. One of the glass components, SO 3, has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO 3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO 3 solubility limit had previously been modeled by a partial quadratic mixture model expressed in the relative proportions of the 14 other components. The partial quadratic mixture model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This report describes how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study. A layered design consists of points on an outer layer, and inner layer, and a center point. There were 18 outer-layer glasses chosen using optimal experimental design software to augment 147 existing glass compositions that were within the LAW glass composition experimental region. Then 13 inner-layer glasses were chosen with the software to augment the existing and outer-layer glasses. The experimental design was completed by a center-point glass, a Vitreous State Laboratory glass, and replicates of the center point and Vitreous State Laboratory glasses.« less

Effect of extended exposure to frequency-altered feedback on stuttering during reading and monologue.

PubMed

Armson, J; Stuart, A

1998-06-01

An ABA time series design was used to examine the effect of extended, continuous exposure to frequency-altered auditory feedback (FAF) during an oral reading and monologue task on stuttering frequency and speech rate. Twelve adults who stutter participated. A statistically significant decrease in number of stuttering events, an increase in number of syllables produced, and a decrease in percent stuttering was observed during the experimental segment relative to baseline segments for the oral reading task. In the monologue task, there were no statistically significant differences for the number of stuttering events, number of syllables produced, or percent stuttering between the experimental and baseline segments. Varying individual patterns of response to FAF were evident during the experimental segment of the reading task: a large consistent reduction in stuttering, an initial reduction followed by fluctuations in amount of stuttering, and essentially no change in stuttering frequency. Ten of 12 participants showed no reduction in stuttering frequency during the experimental segment of the monologue task. These findings have ramifications both for the clinical utilization of FAF and for theoretical explanations of fluency-enhancement.

Laboratory animal science: a resource to improve the quality of science.

PubMed

Forni, M

2007-08-01

The contribution of animal experimentation to biomedical research is of undoubted value, nevertheless the real usefulness of animal models is still being hotly debated. Laboratory Animal Science is a multidisciplinary approach to humane animal experimentation that allows the choice of the correct animal model and the collection of unbiased data. Refinement, Reduction and Replacement, the "3Rs rule", are now widely accepted and have a major influence on animal experimentation procedures. Refinement, namely any decrease in the incidence or severity of inhumane procedures applied to animals, has been today extended to the entire lives of the experimental animals. Reduction of the number of animals used to obtain statistically significant data may be achieved by improving experimental design and statistical analysis of data. Replacement refers to the development of validated alternative methods. A Laboratory Animal Science training program in biomedical degrees can promote the 3Rs and improve the welfare of laboratory animals as well as the quality of science with ethical, scientific and economic advantages complying with the European requirement that "persons who carry out, take part in, or supervise procedures on animals, or take care of animals used in procedures, shall have had appropriate education and training".

Air ions and respiratory function outcomes: a comprehensive review

PubMed Central

2013-01-01

Background From a mechanistic or physical perspective there is no basis to suspect that electric charges on clusters of air molecules (air ions) would have beneficial or deleterious effects on respiratory function. Yet, there is a large lay and scientific literature spanning 80 years that asserts exposure to air ions affects the respiratory system and has other biological effects. Aims This review evaluates the scientific evidence in published human experimental studies regarding the effects of exposure to air ions on respiratory performance and symptoms. Methods We identified 23 studies (published 1933–1993) that met our inclusion criteria. Relevant data pertaining to study population characteristics, study design, experimental methods, statistical techniques, and study results were assessed. Where relevant, random effects meta-analysis models were utilized to quantify similar exposure and outcome groupings. Results The included studies examined the therapeutic benefits of exposure to negative air ions on respiratory outcomes, such as ventilatory function and asthmatic symptoms. Study specific sample sizes ranged between 7 and 23, and studies varied considerably by subject characteristics (e.g., infants with asthma, adults with emphysema), experimental method, outcomes measured (e.g., subjective symptoms, sensitivity, clinical pulmonary function), analytical design, and statistical reporting. Conclusions Despite numerous experimental and analytical differences across studies, the literature does not clearly support a beneficial role in exposure to negative air ions and respiratory function or asthmatic symptom alleviation. Further, collectively, the human experimental studies do not indicate a significant detrimental effect of exposure to positive air ions on respiratory measures. Exposure to negative or positive air ions does not appear to play an appreciable role in respiratory function. PMID:24016271

Evaluation of Trap Designs and Deployment Strategies for Capturing Halyomorpha halys (Hemiptera: Pentatomidae)

PubMed Central

Morrison, William R.; Cullum, John P.; Leskey, Tracy C.

2015-01-01

Halyomorpha halys (Stål) is an invasive pest that attacks numerous crops. For growers to make informed management decisions against H. halys, an effective monitoring tool must be in place. We evaluated various trap designs baited with the two-component aggregation pheromone of H. halys and synergist and deployed in commercial apple orchards. We compared our current experimental standard trap, a black plywood pyramid trap 1.22 m in height deployed between border row apple trees with other trap designs for two growing seasons. These included a black lightweight coroplast pyramid trap of similar dimension, a smaller (29 cm) pyramid trap also ground deployed, a smaller limb-attached pyramid trap, a smaller pyramid trap hanging from a horizontal branch, and a semipyramid design known as the Rescue trap. We found that the coroplast pyramid was the most sensitive, capturing more adults than all other trap designs including our experimental standard. Smaller pyramid traps performed equally in adult captures to our experimental standard, though nymphal captures were statistically lower for the hanging traps. Experimental standard plywood and coroplast pyramid trap correlations were strong, suggesting that standard plywood pyramid traps could be replaced with lighter, cheaper coroplast pyramid traps. Strong correlations with small ground- and limb-deployed pyramid traps also suggest that these designs offer promise as well. Growers may be able to adopt alternative trap designs that are cheaper, lighter, and easier to deploy to monitor H. halys in orchards without a significant loss in sensitivity. PMID:26470309

The power and promise of RNA-seq in ecology and evolution.

PubMed

Todd, Erica V; Black, Michael A; Gemmell, Neil J

2016-03-01

Reference is regularly made to the power of new genomic sequencing approaches. Using powerful technology, however, is not the same as having the necessary power to address a research question with statistical robustness. In the rush to adopt new and improved genomic research methods, limitations of technology and experimental design may be initially neglected. Here, we review these issues with regard to RNA sequencing (RNA-seq). RNA-seq adds large-scale transcriptomics to the toolkit of ecological and evolutionary biologists, enabling differential gene expression (DE) studies in nonmodel species without the need for prior genomic resources. High biological variance is typical of field-based gene expression studies and means that larger sample sizes are often needed to achieve the same degree of statistical power as clinical studies based on data from cell lines or inbred animal models. Sequencing costs have plummeted, yet RNA-seq studies still underutilize biological replication. Finite research budgets force a trade-off between sequencing effort and replication in RNA-seq experimental design. However, clear guidelines for negotiating this trade-off, while taking into account study-specific factors affecting power, are currently lacking. Study designs that prioritize sequencing depth over replication fail to capitalize on the power of RNA-seq technology for DE inference. Significant recent research effort has gone into developing statistical frameworks and software tools for power analysis and sample size calculation in the context of RNA-seq DE analysis. We synthesize progress in this area and derive an accessible rule-of-thumb guide for designing powerful RNA-seq experiments relevant in eco-evolutionary and clinical settings alike. © 2016 John Wiley & Sons Ltd.

Experimental Mathematics and Computational Statistics

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

Bailey, David H.; Borwein, Jonathan M.

2009-04-30

The field of statistics has long been noted for techniques to detect patterns and regularities in numerical data. In this article we explore connections between statistics and the emerging field of 'experimental mathematics'. These includes both applications of experimental mathematics in statistics, as well as statistical methods applied to computational mathematics.

The Problem of Size in Robust Design

NASA Technical Reports Server (NTRS)

Koch, Patrick N.; Allen, Janet K.; Mistree, Farrokh; Mavris, Dimitri

1997-01-01

To facilitate the effective solution of multidisciplinary, multiobjective complex design problems, a departure from the traditional parametric design analysis and single objective optimization approaches is necessary in the preliminary stages of design. A necessary tradeoff becomes one of efficiency vs. accuracy as approximate models are sought to allow fast analysis and effective exploration of a preliminary design space. In this paper we apply a general robust design approach for efficient and comprehensive preliminary design to a large complex system: a high speed civil transport (HSCT) aircraft. Specifically, we investigate the HSCT wing configuration design, incorporating life cycle economic uncertainties to identify economically robust solutions. The approach is built on the foundation of statistical experimentation and modeling techniques and robust design principles, and is specialized through incorporation of the compromise Decision Support Problem for multiobjective design. For large problems however, as in the HSCT example, this robust design approach developed for efficient and comprehensive design breaks down with the problem of size - combinatorial explosion in experimentation and model building with number of variables -and both efficiency and accuracy are sacrificed. Our focus in this paper is on identifying and discussing the implications and open issues associated with the problem of size for the preliminary design of large complex systems.

Factorial experiments: efficient tools for evaluation of intervention components.

PubMed

Collins, Linda M; Dziak, John J; Kugler, Kari C; Trail, Jessica B

2014-10-01

An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the RCT; the two designs address different research questions. To offer an introduction to factorial experiments aimed at investigators trained primarily in the RCT. The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate. Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided. Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Curricular Innovation in an Undergraduate Medical Program: What Is "Appropriate" Assessment?

ERIC Educational Resources Information Center

Ruhe, Valerie; Boudreau, J. Donald

2011-01-01

In post-secondary education, there is a widely-held belief in a "gold standard" for evaluative studies of curricular innovations. In this context, "appropriate" assessment is understood to refer to experimental designs and statistically significant differences in group outcomes. Yet in our evaluative study of a medical undergraduate program, we…

Detecting response of Douglas-fir plantations to urea fertilizer at three locations in the Oregon Coast Range.

Treesearch

Richard E. Miller; Jim Smith; Harry Anderson

2001-01-01

Fertilizer trials in coast Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco) in the Oregon Coast Range usually indicate small and statistically nonsignificant response to nitrogen (N) fertilizers. Inherently weak experimental designs of past trials could make them too insensitive to detect growth differences...

On the Hedges Correction for a "t"-Test

ERIC Educational Resources Information Center

VanHoudnos, Nathan M.; Greenhouse, Joel B.

2016-01-01

When cluster randomized experiments are analyzed as if units were independent, test statistics for treatment effects can be anticonservative. Hedges proposed a correction for such tests by scaling them to control their Type I error rate. This article generalizes the Hedges correction from a posttest-only experimental design to more common designs…

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,…

Edge Detection and Geometric Methods in Computer Vision,

DTIC Science & Technology

1985-02-01

enlightening discussion) Derivations or Eqs. 3.29, 3.31, 3.32 (some statistics) Experimental results (pictures)-- not very informative, extensive or useful. lie... neurophysiology and hardware design. If one views 9 the state space as a free vector space on the labels over the field of weights (which we take to be R), then

Kiss High Blood Pressure Goodbye: The Relationship between Dark Chocolate and Hypertension

ERIC Educational Resources Information Center

Nordmoe, Eric D.

2008-01-01

This article reports on a delicious finding from a recent study claiming a causal link between dark chocolate consumption and blood pressure reductions. In the article, I provide ideas for using this study to whet student appetites for a discussion of statistical ideas, including experimental design, measurement error and inference methods.

EFFECTS OF BURN RATE, WOOD SPECIES, MOISTURE CONTENT AND WEIGHT OF WOOD LOADED ON WOODSTOVE EMISSIONS

EPA Science Inventory

The report gives results of tests of four woodstove operating parameters (burn rate, wood moisture, wood load, and wood species) at two levels each using a half factorial experimental test design to determine statistically significant effects on the emission components CO, CO2, p...

[Effectiveness of the Military Mental Health Promotion Program].

PubMed

Woo, Chung Hee; Kim, Sun Ah

2014-12-01

This study was done to evaluate the Military Mental Health Promotion Program. The program was an email based cognitive behavioral intervention. The research design was a quasi-experimental study with a non-equivalent control group pretest-posttest design. Participants were 32 soldiers who agreed to participate in the program. Data were collected at three different times from January 2012 to March 2012; pre-test, post-test, and a one-month follow-up test. The data were statistically analyzed using SPSS 18.0. The effectiveness of the program was tested by repeated measures ANOVA. The first hypothesis that the level of depression in the experimental group who participated in the program would decrease compared to the control group was not supported in that the difference in group-time interaction was not statistically significant (F=2.19, p=.121). The second and third hypothesis related to anxiety and self-esteem were supported in group-time interaction, respectively (F=7.41, p=.001, F=11.67, p<.001). Results indicate that the program is effective in improving soldiers' mental health status in areas of anxiety and self-esteem.

Use of statistical design of experiments for surface modification of Kapton films by CF4sbnd O2 microwave plasma treatment

NASA Astrophysics Data System (ADS)

Grandoni, Andrea; Mannini, Giacomo; Glisenti, Antonella; Manariti, Antonella; Galli, Giancarlo

2017-10-01

A statistical design of experiments (DoE) was used to evaluate the effects of CF4sbnd O2 plasma on Kapton films in which the duration of treatment, volume ratio of plasma gases, and microwave power were selected as effective experimental factors for systematic investigation of surface modification. Static water contact angle (θW), polar component of surface free energy (γSp) and surface O/C atomic ratio were analyzed as response variables. A significant enhancement in wettability and polarity of the treated films compared to untreated Kapton films was observed; depending on the experimental conditions, θW very significantly decreased, showing full wettability, and γSp rose dramatically, up to ten times. Within the DoE the conditions of plasma treatment were identified that resulted in selected optimal values of θW, γSp and O/C responses. Surface chemical changes were detected by XPS and ATR-IR investigations that evidenced both the introduction of fluorinated groups and the opening of the imide ring in the plasma-treated films.

Bayesian Dose-Response Modeling in Sparse Data

NASA Astrophysics Data System (ADS)

Kim, Steven B.

This book discusses Bayesian dose-response modeling in small samples applied to two different settings. The first setting is early phase clinical trials, and the second setting is toxicology studies in cancer risk assessment. In early phase clinical trials, experimental units are humans who are actual patients. Prior to a clinical trial, opinions from multiple subject area experts are generally more informative than the opinion of a single expert, but we may face a dilemma when they have disagreeing prior opinions. In this regard, we consider compromising the disagreement and compare two different approaches for making a decision. In addition to combining multiple opinions, we also address balancing two levels of ethics in early phase clinical trials. The first level is individual-level ethics which reflects the perspective of trial participants. The second level is population-level ethics which reflects the perspective of future patients. We extensively compare two existing statistical methods which focus on each perspective and propose a new method which balances the two conflicting perspectives. In toxicology studies, experimental units are living animals. Here we focus on a potential non-monotonic dose-response relationship which is known as hormesis. Briefly, hormesis is a phenomenon which can be characterized by a beneficial effect at low doses and a harmful effect at high doses. In cancer risk assessments, the estimation of a parameter, which is known as a benchmark dose, can be highly sensitive to a class of assumptions, monotonicity or hormesis. In this regard, we propose a robust approach which considers both monotonicity and hormesis as a possibility. In addition, We discuss statistical hypothesis testing for hormesis and consider various experimental designs for detecting hormesis based on Bayesian decision theory. Past experiments have not been optimally designed for testing for hormesis, and some Bayesian optimal designs may not be optimal under a wrong parametric assumption. In this regard, we consider a robust experimental design which does not require any parametric assumption.

Time-to-event continual reassessment method incorporating treatment cycle information with application to an oncology phase I trial.

PubMed

Huang, Bo; Kuan, Pei Fen

2014-11-01

Delayed dose limiting toxicities (i.e. beyond first cycle of treatment) is a challenge for phase I trials. The time-to-event continual reassessment method (TITE-CRM) is a Bayesian dose-finding design to address the issue of long observation time and early patient drop-out. It uses a weighted binomial likelihood with weights assigned to observations by the unknown time-to-toxicity distribution, and is open to accrual continually. To avoid dosing at overly toxic levels while retaining accuracy and efficiency for DLT evaluation that involves multiple cycles, we propose an adaptive weight function by incorporating cyclical data of the experimental treatment with parameters updated continually. This provides a reasonable estimate for the time-to-toxicity distribution by accounting for inter-cycle variability and maintains the statistical properties of consistency and coherence. A case study of a First-in-Human trial in cancer for an experimental biologic is presented using the proposed design. Design calibrations for the clinical and statistical parameters are conducted to ensure good operating characteristics. Simulation results show that the proposed TITE-CRM design with adaptive weight function yields significantly shorter trial duration, does not expose patients to additional risk, is competitive against the existing weighting methods, and possesses some desirable properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The effect of extremity strength training on fibromyalgia symptoms and disease impact in an existing multidisciplinary treatment program.

PubMed

Kas, Tamara; Colby, Megan; Case, Maureen; Vaughn, Dan

2016-10-01

The purpose of this study was to examine the effect of upper and lower body extremity strengthening exercise in patients with Fibromyalgia (FM) within an existing multidisciplinary treatment program. Patients between the ages of 18-65 with the medical diagnosis of FM. Comparative study design. The control and experimental group received the same multidisciplinary treatment except that the experimental group performed upper and lower extremity strengthening exercises. The Fibromyalgia Impact Questionnaire (FIQ) was administered at evaluation and discharge from the program in order to measure change in quality of life (QOL). Statistically significant changes in FIQ scores were found for both groups. The addition of extremity strengthening in the experimental group produced an average 4 points greater reduction in FIQ score, however, these results are not considered statistically significant. This study appears to validate the success of a multidisciplinary approach in treating patients with FM, with the possibility for further benefit with the addition of extremity strengthening. Copyright © 2016 Elsevier Ltd. All rights reserved.

GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic.

PubMed

Whitehead, John; Horby, Peter

2017-03-01

Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood.

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.

Prediction/discussion-based learning cycle versus conceptual change text: comparative effects on students' understanding of genetics

NASA Astrophysics Data System (ADS)

khawaldeh, Salem A. Al

2013-07-01

Background and purpose: The purpose of this study was to investigate the comparative effects of a prediction/discussion-based learning cycle (HPD-LC), conceptual change text (CCT) and traditional instruction on 10th grade students' understanding of genetics concepts. Sample: Participants were 112 10th basic grade male students in three classes of the same school located in an urban area. The three classes taught by the same biology teacher were randomly assigned as a prediction/discussion-based learning cycle class (n = 39), conceptual change text class (n = 37) and traditional class (n = 36). Design and method: A quasi-experimental research design of pre-test-post-test non-equivalent control group was adopted. Participants completed the Genetics Concept Test as pre-test-post-test, to examine the effects of instructional strategies on their genetics understanding. Pre-test scores and Test of Logical Thinking scores were used as covariates. Results: The analysis of covariance showed a statistically significant difference between the experimental and control groups in the favor of experimental groups after treatment. However, no statistically significant difference between the experimental groups (HPD-LC versus CCT instruction) was found. Conclusions: Overall, the findings of this study support the use of the prediction/discussion-based learning cycle and conceptual change text in both research and teaching. The findings may be useful for improving classroom practices in teaching science concepts and for the development of suitable materials promoting students' understanding of science.

The problem is not just sample size: the consequences of low base rates in policing experiments in smaller cities.

PubMed

Hinkle, Joshua C; Weisburd, David; Famega, Christine; Ready, Justin

2013-01-01

Hot spots policing is one of the most influential police innovations, with a strong body of experimental research showing it to be effective in reducing crime and disorder. However, most studies have been conducted in major cities, and we thus know little about whether it is effective in smaller cities, which account for a majority of police agencies. The lack of experimental studies in smaller cities is likely in part due to challenges designing statistically powerful tests in such contexts. The current article explores the challenges of statistical power and "noise" resulting from low base rates of crime in smaller cities and provides suggestions for future evaluations to overcome these limitations. Data from a randomized experimental evaluation of broken windows policing in hot spots are used to illustrate the challenges that low base rates present for evaluating hot spots policing programs in smaller cities. Analyses show low base rates make it difficult to detect treatment effects. Very large effect sizes would be required to reach sufficient power, and random fluctuations around low base rates make detecting treatment effects difficult, irrespective of power, by masking differences between treatment and control groups. Low base rates present strong challenges to researchers attempting to evaluate hot spots policing in smaller cities. As such, base rates must be taken directly into account when designing experimental evaluations. The article offers suggestions for researchers attempting to expand the examination of hot spots policing and other microplace-based interventions to smaller jurisdictions.

Testing the Developmental Origins of Health and Disease Hypothesis for Psychopathology Using Family-Based Quasi-Experimental Designs

PubMed Central

D’Onofrio, Brian M.; Class, Quetzal A.; Lahey, Benjamin B.; Larsson, Henrik

2014-01-01

The Developmental Origin of Health and Disease (DOHaD) hypothesis is a broad theoretical framework that emphasizes how early risk factors have a causal influence on psychopathology. Researchers have raised concerns about the causal interpretation of statistical associations between early risk factors and later psychopathology because most existing studies have been unable to rule out the possibility of environmental and genetic confounding. In this paper we illustrate how family-based quasi-experimental designs can test the DOHaD hypothesis by ruling out alternative hypotheses. We review the logic underlying sibling-comparison, co-twin control, offspring of siblings/twins, adoption, and in vitro fertilization designs. We then present results from studies using these designs focused on broad indices of fetal development (low birth weight and gestational age) and a particular teratogen, smoking during pregnancy. The results provide mixed support for the DOHaD hypothesis for psychopathology, illustrating the critical need to use design features that rule out unmeasured confounding. PMID:25364377

Surface laser marking optimization using an experimental design approach

NASA Astrophysics Data System (ADS)

Brihmat-Hamadi, F.; Amara, E. H.; Lavisse, L.; Jouvard, J. M.; Cicala, E.; Kellou, H.

2017-04-01

Laser surface marking is performed on a titanium substrate using a pulsed frequency doubled Nd:YAG laser ( λ= 532 nm, τ pulse=5 ns) to process the substrate surface under normal atmospheric conditions. The aim of the work is to investigate, following experimental and statistical approaches, the correlation between the process parameters and the response variables (output), using a Design of Experiment method (DOE): Taguchi methodology and a response surface methodology (RSM). A design is first created using MINTAB program, and then the laser marking process is performed according to the planned design. The response variables; surface roughness and surface reflectance were measured for each sample, and incorporated into the design matrix. The results are then analyzed and the RSM model is developed and verified for predicting the process output for the given set of process parameters values. The analysis shows that the laser beam scanning speed is the most influential operating factor followed by the laser pumping intensity during marking, while the other factors show complex influences on the objective functions.

Development of a semidefined growth medium for Pedobacter cryoconitis BG5 using statistical experimental design.

PubMed

Ong, Magdalena; Ongkudon, Clarence M; Wong, Clemente Michael Vui Ling

2016-10-02

Pedobacter cryoconitis BG5 are psychrophiles isolated from the cold environment and capable of proliferating and growing well at low temperature regime. Their cellular products have found a broad spectrum of applications, including in food, medicine, and bioremediation. Therefore, it is imperative to develop a high-cell density cultivation strategy coupled with optimized growth medium for P. cryoconitis BG5. To date, there has been no published report on the design and optimization of growth medium for P. cryoconitis, hence the objective of this research project. A preliminary screening of four commercially available media, namely tryptic soy broth, R2A, Luria Bertani broth, and nutrient broth, was conducted to formulate the basal medium. Based on the preliminary screening, tryptone, glucose, NaCl, and K2HPO4 along with three additional nutrients (yeast extract, MgSO4, and NH4Cl) were identified to form the basal medium which was further analyzed by Plackett-Burman experimental design. Central composite experimental design using response surface methodology was adopted to optimize tryptone, yeast extract, and NH4Cl concentrations in the formulated growth medium. Statistical data analysis showed a high regression factor of 0.84 with a predicted optimum optical (600 nm) cell density of 7.5 using 23.7 g/L of tryptone, 8.8 g/L of yeast extract, and 0.7 g/L of NH4Cl. The optimized medium for P. cryoconitis BG5 was tested, and the observed optical density was 7.8. The cost-effectiveness of the optimized medium was determined as 6.25 unit prices per gram of cell produced in a 250-ml Erlenmeyer flask.

Construction of social value or utility-based health indices: the usefulness of factorial experimental design plans.

PubMed

Cadman, D; Goldsmith, C

1986-01-01

Global indices, which aggregate multiple health or function attributes into a single summary indicator, are useful measures in health research. Two key issues must be addressed in the initial stages of index construction from the universe of possible health and function attributes, which ones should be included in a new index? and how simple can the statistical model be to combine attributes into a single numeric index value? Factorial experimental designs were used in the initial stages of developing a function index for evaluating a program for the care of young handicapped children. Beginning with eight attributes judged important to the goals of the program by clinicians, social preference values for different function states were obtained from 32 parents of handicapped children and 32 members of the community. Using category rating methods each rater scored 16 written multi-attribute case descriptions which contained information about a child's status for all eight attributes. Either a good or poor level of each function attribute and age 3 or 5 years were described in each case. Thus, 2(8) = 256 different cases were rated. Two factorial design plans were selected and used to allocate case descriptions to raters. Analysis of variance determined that seven of the eight clinician selected attributes were required in a social value based index for handicapped children. Most importantly, the subsequent steps of index construction could be greatly simplified by the finding that a simple additive statistical model without complex attribute interaction terms was adequate for the index. We conclude that factorial experimental designs are an efficient, feasible and powerful tool for the initial stages of constructing a multi-attribute health index.

Gene Profiling in Experimental Models of Eye Growth: Clues to Myopia Pathogenesis

PubMed Central

Stone, Richard A.; Khurana, Tejvir S.

2010-01-01

To understand the complex regulatory pathways that underlie the development of refractive errors, expression profiling has evaluated gene expression in ocular tissues of well-characterized experimental models that alter postnatal eye growth and induce refractive errors. Derived from a variety of platforms (e.g. differential display, spotted microarrays or Affymetrix GeneChips), gene expression patterns are now being identified in species that include chicken, mouse and primate. Reconciling available results is hindered by varied experimental designs and analytical/statistical features. Continued application of these methods offers promise to provide the much-needed mechanistic framework to develop therapies to normalize refractive development in children. PMID:20363242

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.

Peer counseling in a culturally specific adolescent pregnancy prevention program.

PubMed

Ferguson, S L

1998-08-01

This study evaluated the effects of peer counseling in a culturally specific adolescent pregnancy prevention program for African American females. A random pretest and multiple posttest experimental and comparison group design was used to obtain data on a sample of 63 female African American adolescents, ages 12 to 16, who lived in four public housing developments. Descriptive data and tests of significance revealed that none of the participants who received peer counseling became pregnant within three months of the intervention. Findings revealed a statistically significant increase in reproductive and other self-related knowledge topics among the experimental group when comparing pretest and eight-week posttest scores. Most participants had not had sexual intercourse; the average age of sexual onset was 12 years in the experimental group and 11 years in the controls. Designing and implementing culturally specific adolescent pregnancy prevention programs for adolescents younger than age 11 and/or before sexually active seems appropriate.

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

A new mathematical approach for the estimation of the AUC and its variability under different experimental designs in preclinical studies.

PubMed

Navarro-Fontestad, Carmen; González-Álvarez, Isabel; Fernández-Teruel, Carlos; Bermejo, Marival; Casabó, Vicente Germán

2012-01-01

The aim of the present work was to develop a new mathematical method for estimating the area under the curve (AUC) and its variability that could be applied in different preclinical experimental designs and amenable to be implemented in standard calculation worksheets. In order to assess the usefulness of the new approach, different experimental scenarios were studied and the results were compared with those obtained with commonly used software: WinNonlin® and Phoenix WinNonlin®. The results do not show statistical differences among the AUC values obtained by both procedures, but the new method appears to be a better estimator of the AUC standard error, measured as the coverage of 95% confidence interval. In this way, the new proposed method demonstrates to be as useful as WinNonlin® software when it was applicable. Copyright © 2011 John Wiley & Sons, Ltd.

Exploring the relationship between time management skills and the academic achievement of African engineering students - a case study

NASA Astrophysics Data System (ADS)

Swart, Arthur James; Lombard, Kobus; de Jager, Henk

2010-03-01

Poor academic success by African engineering students is currently experienced in many higher educational institutions, contributing to lower financial subsidies by local governments. One of the contributing factors to this low academic success may be the poor time management skills of these students. This article endeavours to explore this relationship by means of a theoretical literature review and an empirical study. Numerous studies have been conducted in this regard, but with mixed results. The case study of this article involves a design module termed Design Projects III, where the empirical study incorporated an ex post facto study involving a pre-experimental/exploratory design using descriptive statistics. The results of this study were applied to various tests, which indicated no statistically significant relationship between time management skills and the academic achievement of African engineering students.

A comparative study of restricted randomization procedures for multiarm trials with equal or unequal treatment allocation ratios.

PubMed

Ryeznik, Yevgen; Sverdlov, Oleksandr

2018-06-04

Randomization designs for multiarm clinical trials are increasingly used in practice, especially in phase II dose-ranging studies. Many new methods have been proposed in the literature; however, there is lack of systematic, head-to-head comparison of the competing designs. In this paper, we systematically investigate statistical properties of various restricted randomization procedures for multiarm trials with fixed and possibly unequal allocation ratios. The design operating characteristics include measures of allocation balance, randomness of treatment assignments, variations in the allocation ratio, and statistical characteristics such as type I error rate and power. The results from the current paper should help clinical investigators select an appropriate randomization procedure for their clinical trial. We also provide a web-based R shiny application that can be used to reproduce all results in this paper and run simulations under additional user-defined experimental scenarios. Copyright © 2018 John Wiley & Sons, Ltd.

Statistical optimization of lovastatin production by Omphalotus olearius (DC.) singer in submerged fermentation.

PubMed

Atlı, Burcu; Yamaç, Mustafa; Yıldız, Zeki; Isikhuemhen, Omoanghe S

2016-01-01

In this study, culture conditions were optimized to improve lovastatin production by Omphalotus olearius, isolate OBCC 2002, using statistical experimental designs. The Plackett-Burman design was used to select important variables affecting lovastatin production. Accordingly, glucose, peptone, and agitation speed were determined as the variables that have influence on lovastatin production. In a further experiment, these variables were optimized with a Box-Behnken design and applied in a submerged process; this resulted in 12.51 mg/L lovastatin production on a medium containing glucose (10 g/L), peptone (5 g/L), thiamine (1 mg/L), and NaCl (0.4 g/L) under static conditions. This level of lovastatin production is eight times higher than that produced under unoptimized media and growth conditions by Omphalotus olearius. To the best of our knowledge, this is the first attempt to optimize submerged fermentation process for lovastatin production by Omphalotus olearius.

The power prior: theory and applications.

PubMed

Ibrahim, Joseph G; Chen, Ming-Hui; Gwon, Yeongjin; Chen, Fang

2015-12-10

The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A-to-Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Frequentist properties of power priors in posterior inference are established, and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials. Copyright © 2015 John Wiley & Sons, Ltd.

Effectiveness of a Computer-Based Training Program of Attention and Memory in Patients with Acquired Brain Damage

PubMed Central

Fernandez, Elizabeth; Bergado Rosado, Jorge A.; Rodriguez Perez, Daymi; Salazar Santana, Sonia; Torres Aguilar, Maydane; Bringas, Maria Luisa

2017-01-01

Many training programs have been designed using modern software to restore the impaired cognitive functions in patients with acquired brain damage (ABD). The objective of this study was to evaluate the effectiveness of a computer-based training program of attention and memory in patients with ABD, using a two-armed parallel group design, where the experimental group (n = 50) received cognitive stimulation using RehaCom software, and the control group (n = 30) received the standard cognitive stimulation (non-computerized) for eight weeks. In order to assess the possible cognitive changes after the treatment, a post-pre experimental design was employed using the following neuropsychological tests: Wechsler Memory Scale (WMS) and Trail Making test A and B. The effectiveness of the training procedure was statistically significant (p < 0.05) when it established the comparison between the performance in these scales, before and after the training period, in each patient and between the two groups. The training group had statistically significant (p < 0.001) changes in focused attention (Trail A), two subtests (digit span and logical memory), and the overall score of WMS. Finally, we discuss the advantages of computerized training rehabilitation and further directions of this line of work. PMID:29301194

A practical approach for the scale-up of roller compaction process.

PubMed

Shi, Weixian; Sprockel, Omar L

2016-09-01

An alternative approach for the scale-up of ribbon formation during roller compaction was investigated, which required only one batch at the commercial scale to set the operational conditions. The scale-up of ribbon formation was based on a probability method. It was sufficient in describing the mechanism of ribbon formation at both scales. In this method, a statistical relationship between roller compaction parameters and ribbon attributes (thickness and density) was first defined with DoE using a pilot Alexanderwerk WP120 roller compactor. While the milling speed was included in the design, it has no practical effect on granule properties within the study range despite its statistical significance. The statistical relationship was then adapted to a commercial Alexanderwerk WP200 roller compactor with one experimental run. The experimental run served as a calibration of the statistical model parameters. The proposed transfer method was then confirmed by conducting a mapping study on the Alexanderwerk WP200 using a factorial DoE, which showed a match between the predictions and the verification experiments. The study demonstrates the applicability of the roller compaction transfer method using the statistical model from the development scale calibrated with one experiment point at the commercial scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluating the Process of Generating a Clinical Trial Protocol

PubMed Central

Franciosi, Lui G.; Butterfield, Noam N.; MacLeod, Bernard A.

2002-01-01

The research protocol is the principal document in the conduct of a clinical trial. Its generation requires knowledge about the research problem, the potential experimental confounders, and the relevant Good Clinical Practices for conducting the trial. However, such information is not always available to authors during the writing process. A checklist of over 80 items has been developed to better understand the considerations made by authors in generating a protocol. It is based on the most cited requirements for designing and implementing the randomised controlled trial. Items are categorised according to the trial's research question, experimental design, statistics, ethics, and standard operating procedures. This quality assessment tool evaluates the extent that a generated protocol deviates from the best-planned clinical trial.

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

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.

[Quality of clinical studies published in the RBGO over one decade (1999-2009): methodological and ethical aspects and statistical procedures].

PubMed

de Sá, Joceline Cássia Ferezini; Marini, Gabriela; Gelaleti, Rafael Bottaro; da Silva, João Batista; de Azevedo, George Gantas; Rudge, Marilza Vieira Cunha

2013-11-01

To evaluate the methodological and statistical design evolution of the publications in the Brazilian Journal of Gynecology and Obstetrics (RBGO) from resolution 196/96. A review of 133 articles published in 1999 (65) and 2009 (68) was performed by two independent reviewers with training in clinical epidemiology and methodology of scientific research. We included all original clinical articles, case and series reports and excluded editorials, letters to the editor, systematic reviews, experimental studies, opinion articles, besides abstracts of theses and dissertations. Characteristics related to the methodological quality of the studies were analyzed in each article using a checklist that evaluated two criteria: methodological aspects and statistical procedures. We used descriptive statistics and the χ2 test for comparison of the two years. There was a difference between 1999 and 2009 regarding the study and statistical design, with more accuracy in the procedures and the use of more robust tests between 1999 and 2009. In RBGO, we observed an evolution in the methods of published articles and a more in-depth use of the statistical analyses, with more sophisticated tests such as regression and multilevel analyses, which are essential techniques for the knowledge and planning of health interventions, leading to fewer interpretation errors.

Experimental Test of Heisenberg's Measurement Uncertainty Relation Based on Statistical Distances

NASA Astrophysics Data System (ADS)

Ma, Wenchao; Ma, Zhihao; Wang, Hengyan; Chen, Zhihua; Liu, Ying; Kong, Fei; Li, Zhaokai; Peng, Xinhua; Shi, Mingjun; Shi, Fazhan; Fei, Shao-Ming; Du, Jiangfeng

2016-04-01

Incompatible observables can be approximated by compatible observables in joint measurement or measured sequentially, with constrained accuracy as implied by Heisenberg's original formulation of the uncertainty principle. Recently, Busch, Lahti, and Werner proposed inaccuracy trade-off relations based on statistical distances between probability distributions of measurement outcomes [P. Busch et al., Phys. Rev. Lett. 111, 160405 (2013); P. Busch et al., Phys. Rev. A 89, 012129 (2014)]. Here we reformulate their theoretical framework, derive an improved relation for qubit measurement, and perform an experimental test on a spin system. The relation reveals that the worst-case inaccuracy is tightly bounded from below by the incompatibility of target observables, and is verified by the experiment employing joint measurement in which two compatible observables designed to approximate two incompatible observables on one qubit are measured simultaneously.

Predicting the stochastic guiding of kinesin-driven microtubules in microfabricated tracks: a statistical-mechanics-based modeling approach.

PubMed

Lin, Chih-Tin; Meyhofer, Edgar; Kurabayashi, Katsuo

2010-01-01

Directional control of microtubule shuttles via microfabricated tracks is key to the development of controlled nanoscale mass transport by kinesin motor molecules. Here we develop and test a model to quantitatively predict the stochastic behavior of microtubule guiding when they mechanically collide with the sidewalls of lithographically patterned tracks. By taking into account appropriate probability distributions of microscopic states of the microtubule system, the model allows us to theoretically analyze the roles of collision conditions and kinesin surface densities in determining how the motion of microtubule shuttles is controlled. In addition, we experimentally observe the statistics of microtubule collision events and compare our theoretical prediction with experimental data to validate our model. The model will direct the design of future hybrid nanotechnology devices that integrate nanoscale transport systems powered by kinesin-driven molecular shuttles.

Experimental Test of Heisenberg's Measurement Uncertainty Relation Based on Statistical Distances.

PubMed

Ma, Wenchao; Ma, Zhihao; Wang, Hengyan; Chen, Zhihua; Liu, Ying; Kong, Fei; Li, Zhaokai; Peng, Xinhua; Shi, Mingjun; Shi, Fazhan; Fei, Shao-Ming; Du, Jiangfeng

2016-04-22

Incompatible observables can be approximated by compatible observables in joint measurement or measured sequentially, with constrained accuracy as implied by Heisenberg's original formulation of the uncertainty principle. Recently, Busch, Lahti, and Werner proposed inaccuracy trade-off relations based on statistical distances between probability distributions of measurement outcomes [P. Busch et al., Phys. Rev. Lett. 111, 160405 (2013); P. Busch et al., Phys. Rev. A 89, 012129 (2014)]. Here we reformulate their theoretical framework, derive an improved relation for qubit measurement, and perform an experimental test on a spin system. The relation reveals that the worst-case inaccuracy is tightly bounded from below by the incompatibility of target observables, and is verified by the experiment employing joint measurement in which two compatible observables designed to approximate two incompatible observables on one qubit are measured simultaneously.

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

Impact of care pathways for in-hospital management of COPD exacerbation: a systematic review.

PubMed

Lodewijckx, C; Sermeus, W; Panella, M; Deneckere, S; Leigheb, F; Decramer, M; Vanhaecht, K

2011-11-01

In-hospital management of COPD exacerbation is suboptimal, and outcomes are poor. Care pathways are a possible strategy for optimizing care processes and outcomes. The aim of the literature review was to explore characteristics of existing care pathways for in-hospital management of COPD exacerbations and to address their impact on performance of care processes, clinical outcomes, and team functioning. A literature search was conducted for articles published between 1990 and 2010 in the electronic databases of Medline, CINAHL, EMBASE, and Cochrane Library. Main inclusion criteria were (I) patients hospitalized for a COPD exacerbation; (II) implementation and evaluation of a care pathway; (III) report of original research, including experimental and quasi experimental designs, variance analysis, and interviews of professionals and patients about their perception on pathway effectiveness. Four studies with a quasi experimental design were included. Three studies used a pre-post test design; the fourth study was a non randomized controlled trial comparing an experimental group where patients were treated according to a care pathway with a control group where usual care was provided. The four studied care pathways were multidisciplinary structured care plans, outlining time-specific clinical interventions and responsibilities by discipline. Statistic analyses were rarely performed, and the trials used very divergent indicators to evaluate the impact of the care pathways. The studies described positive effects on blood sampling, daily weight measurement, arterial blood gas measurement, referral to rehabilitation, feelings of anxiety, length of stay, readmission, and in-hospital mortality. Research on COPD care pathways is very limited. The studies described few positive effects of the care pathways on diagnostic processes and on clinical outcomes. Though due to limited statistical analysis and weak design of the studies, the internal validity of results is limited. Therefore, based on these studies the impact of care pathways on COPD exacerbation is inconclusive. These findings indicate the need for properly designed research like a cluster randomized controlled trial to evaluate the impact of COPD care pathways on performance of care processes, clinical outcomes, and teamwork. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Understanding reverberating chambers as an alternative facility for EMC testing

NASA Astrophysics Data System (ADS)

Ma, M. T.

A relatively new facility called a reverberating chamber designed for EMC testing is described. The purpose is to create a statistically uniform electric field inside a metal enclosure for testing radiated susceptibility or immunity of equipment. Design criteria in terms of the number of cavity modes, mode density, and composite quality factor are presented in details in order to understand the physical insight and to enhance interpretations of measurement results. Recent experimental data are included to illustrate the underlying principle.

Tailoring the Statistical Experimental Design Process for LVC Experiments

DTIC Science & Technology

2011-03-01

incredibly large test space, it is important to point out that Gray is presenting a simple case to demonstrate the application of an experimental...weapon’s effectiveness. Gray defines k1 = 4 factors in the whole plot and k2 = 3 factors in the sub plot with f1 and f2 as the number of factors...aliased with interaction terms in the whole plot and sub plot respectively. Gray uses the notation 2k1−f1 × 2k2−f2 [?] to represent the fractional

A persuasive concept of research-oriented teaching in Soil Biochemistry

NASA Astrophysics Data System (ADS)

Blagodatskaya, Evgenia; Kuzyakova, Irina

2013-04-01

One of the main problems of existing bachelor programs is disconnection of basic and experimental education: even during practical training the methods learned are not related to characterization of soil field experiments and observed soil processes. We introduce a multi-level research-oriented teaching system involving Bachelor students in four-semesters active study by integration the basic knowledge, experimental techniques, statistical approaches, project design and it's realization.The novelty of research-oriented teaching system is based 1) on linkage of ongoing experiment to the study of statistical methods and 2) on self-responsibility of students for interpretation of soil chemical and biochemical characteristics obtained in the very beginning of their study by analysing the set of soil samples allowing full-factorial data treatment. This experimental data set is related to specific soil stand and is used as a backbone of the teaching system accelerating the student's interest to soil studies and motivating them for application of basic knowledge from lecture courses. The multi-level system includes: 1) basic lecture course on soil biochemistry with analysis of research questions, 2) practical training course on laboratory analytics where small groups of students are responsible for analysis of soil samples related to the specific land-use/forest type/forest age; 3) training course on biotic (e.g. respiration) - abiotic (e.g. temperature, moisture, fire etc.) interactions in the same soil samples; 4) theoretical seminars where students present and make a first attempt to explain soil characteristics of various soil stands as affected by abiotic factors (first semester); 5) lecture and seminar course on soil statistics where students apply newly learned statistical methods to prove their conclusions and to find relationships between soil characteristics obtained during first semester; 6) seminar course on project design where students develop their scientific projects to study the uncertainties revealed in soil responses to abiotic factors (second and third semesters); 7) Lecture, seminar and training courses on estimation of active microbial biomass in soil where students realize their projects applying a new knowledge to the soils from the stands they are responsible for (fourth semester). Thus, during four semesters the students continuously combine the theoretical knowledge from the lectures with their own experimental experience, compare and discuss results of various groups during seminars and obtain the skills in project design. The successful application of research-oriented teaching system in University of Göttingen allowed each student the early-stage revealing knowledge gaps, accelerated their involvement in ongoing research projects, and motivated them to begin own scientific career.

Teaching Efficacy in the Classroom: Skill Based Training for Teachers' Empowerment

ERIC Educational Resources Information Center

Karimzadeh, Mansoureh; Salehi, Hadi; Embi, Mohamed Amin; Nasiri, Mehdi; Shojaee, Mohammad

2014-01-01

This study aims to use an experimental research design to enhance teaching efficacy by social-emotional skills training in teachers. The statistical sample comprised of 68 elementary teachers (grades 4 and 5) with at least 10 years teaching experience and a bachelor's degree who were randomly assigned into control (18 female, 16 male) and…

Conducting Human Research

DTIC Science & Technology

2009-08-05

Socio-cultural data acquisition, extraction, and management.??? First the idea of a theoretical framework will be very briefly discussed as well as...SUBJECT TERMS human behavior, theoretical framework , hypothesis development, experimental design, ethical research, statistical power, human laboratory...who throw rocks? • How can we make them stay too far away to throw rocks? UNCLASSIFIED – Approved for Public Release Theoretical Framework / Conceptual

The Effectiveness of Art Therapy Interventions in Reducing Post Traumatic Stress Disorder (PTSD) Symptoms in Pediatric Trauma Patients.

ERIC Educational Resources Information Center

Chapman, Linda M.; Morabito, Diane; Ladakakos, Chris; Schreier, Herbert; Knudson, M. Margaret

2001-01-01

Chapman Art Therapy Intervention (CATTI), an art therapy research project at an urban trauma center, was designed to reduce Post Traumatic Stress Disorder (PTSD) symptoms in pediatric patients. Early analysis does not indicate statistically significant differences in reduction of PTSD symptoms between experimental and control groups. Children…

Fisher, Sir Ronald Aylmer (1890-1962)

NASA Astrophysics Data System (ADS)

Murdin, P.

2000-11-01

Statistician, born in London, England. After studying astronomy using AIRY's manual on the Theory of Errors he became interested in statistics, and laid the foundation of randomization in experimental design, the analysis of variance and the use of data in estimating the properties of the parent population from which it was drawn. Invented the maximum likelihood method for estimating from random ...

I Remember You: Independence and the Binomial Model

ERIC Educational Resources Information Center

Levine, Douglas W.; Rockhill, Beverly

2006-01-01

We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how…

Techniques of Differentiation and Integration, Mathematics (Experimental): 5297.27.

ERIC Educational Resources Information Center

Forrester, Gary B.

This guidebook on minimum course content was designed for students who have mastered the skills and concepts of analytic geometry. It is a short course in the basic techniques of calculus recommended for the student who has need of these skills in other courses such as beginning physics, economics or statistics. The course does not intend to teach…

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

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.

2008-01-01

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

The Relationship of Diet to the Performance of the Combat Soldier. Minimal Calorie Intake during Combat Patrols in a Hot Humid Environment (Panama)

DTIC Science & Technology

1979-10-01

nutritional status. Human Biology 28:111, 1956. 17. WINER, B.J. Statistical Principles in Experimental Design (Second edition). New York: McGraw-Hill...Bliological Sciences Di)viuion Commander office of Naval Researh Naval Medical Research Institute Arlington, VA 22217 Nationial Naval Medical (:enter

A Bayesian pick-the-winner design in a randomized phase II clinical trial.

PubMed

Chen, Dung-Tsa; Huang, Po-Yu; Lin, Hui-Yi; Chiappori, Alberto A; Gabrilovich, Dmitry I; Haura, Eric B; Antonia, Scott J; Gray, Jhanelle E

2017-10-24

Many phase II clinical trials evaluate unique experimental drugs/combinations through multi-arm design to expedite the screening process (early termination of ineffective drugs) and to identify the most effective drug (pick the winner) to warrant a phase III trial. Various statistical approaches have been developed for the pick-the-winner design but have been criticized for lack of objective comparison among the drug agents. We developed a Bayesian pick-the-winner design by integrating a Bayesian posterior probability with Simon two-stage design in a randomized two-arm clinical trial. The Bayesian posterior probability, as the rule to pick the winner, is defined as probability of the response rate in one arm higher than in the other arm. The posterior probability aims to determine the winner when both arms pass the second stage of the Simon two-stage design. When both arms are competitive (i.e., both passing the second stage), the Bayesian posterior probability performs better to correctly identify the winner compared with the Fisher exact test in the simulation study. In comparison to a standard two-arm randomized design, the Bayesian pick-the-winner design has a higher power to determine a clear winner. In application to two studies, the approach is able to perform statistical comparison of two treatment arms and provides a winner probability (Bayesian posterior probability) to statistically justify the winning arm. We developed an integrated design that utilizes Bayesian posterior probability, Simon two-stage design, and randomization into a unique setting. It gives objective comparisons between the arms to determine the winner.

Procedure for developing experimental designs for accelerated tests for service-life prediction. [for solar cell modules

NASA Technical Reports Server (NTRS)

Thomas, R. E.; Gaines, G. B.

1978-01-01

Recommended design procedures to reduce the complete factorial design by retaining information on anticipated important interaction effects, and by generally giving up information on unconditional main effects are discussed. A hypothetical photovoltaic module used in the test design is presented. Judgments were made of the relative importance of various environmental stresses such as UV radiation, abrasion, chemical attack, temperature, mechanical stress, relative humidity and voltage. Consideration is given to a complete factorial design and its graphical representation, elimination of selected test conditions, examination and improvement of an engineering design, and parametric study. The resulting design consists of a mix of conditional main effects and conditional interactions and represents a compromise between engineering and statistical requirements.

The effect of a Web-based education programme (WBEP) on disease severity, quality of life and mothers' self-efficacy in children with atopic dermatitis.

PubMed

Son, Hae Kyoung; Lim, Jiyoung

2014-10-01

To develop and evaluate the effects of a web-based education programme in early childhood for children with atopic dermatitis. The prevalence rate of atopic dermatitis is highest in early childhood. A holistic approach is urgently needed for young children with respect to disease severity, quality of life and management, particularly parental knowledge about atopic dermatitis and adherence to treatment. A quasi-experimental study design was used. A total of 40 mother-child dyads participated in the study from 1 July-30 November 2011 in Korea. All children were under 3 years of age. The programme was based on the Network-Based Instructional System Design model, which consists of five phases: analysis, design, development, implementation and evaluation. The experimental group participated in the programme for 2 weeks. Participants took part in a learning session during the first week and then conducted the practice session at home during the second week. Participant knowledge and compliance were evaluated through online quizzes and self-checklists. Statistical analyses (chi-square test and t-test) were performed using the Statistical Analysis System, Version 9.13. There was a significant improvement in disease severity, quality of life and mothers' self-efficacy in the experimental group; thus, the web-based education programme was effective. The web-based education programme as an advanced intervention may be useful in providing basic data for future atopic dermatitis-related studies. Moreover, the programme may serve as a nursing educational intervention tool for clinical nursing practices. © 2014 John Wiley & Sons Ltd.

Adaptive Kalman filtering for real-time mapping of the visual field

PubMed Central

Ward, B. Douglas; Janik, John; Mazaheri, Yousef; Ma, Yan; DeYoe, Edgar A.

2013-01-01

This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume. PMID:22100663

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

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.

An experimental study of the temporal statistics of radio signals scattered by rain

NASA Technical Reports Server (NTRS)

Hubbard, R. W.; Hull, J. A.; Rice, P. L.; Wells, P. I.

1973-01-01

A fixed-beam bistatic CW experiment designed to measure the temporal statistics of the volume reflectivity produced by hydrometeors at several selected altitudes, scattering angles, and at two frequencies (3.6 and 7.8 GHz) is described. Surface rain gauge data, local meteorological data, surveillance S-band radar, and great-circle path propagation measurements were also made to describe the general weather and propagation conditions and to distinguish precipitation scatter signals from those caused by ducting and other nonhydrometeor scatter mechanisms. The data analysis procedures were designed to provide an assessment of a one-year sample of data with a time resolution of one minute. The cumulative distributions of the bistatic signals for all of the rainy minutes during this period are presented for the several path geometries.

Statistical Modelling of Temperature and Moisture Uptake of Biochars Exposed to Selected Relative Humidity of Air.

PubMed

Bastistella, Luciane; Rousset, Patrick; Aviz, Antonio; Caldeira-Pires, Armando; Humbert, Gilles; Nogueira, Manoel

2018-02-09

New experimental techniques, as well as modern variants on known methods, have recently been employed to investigate the fundamental reactions underlying the oxidation of biochar. The purpose of this paper was to experimentally and statistically study how the relative humidity of air, mass, and particle size of four biochars influenced the adsorption of water and the increase in temperature. A random factorial design was employed using the intuitive statistical software Xlstat. A simple linear regression model and an analysis of variance with a pairwise comparison were performed. The experimental study was carried out on the wood of Quercus pubescens , Cyclobalanopsis glauca , Trigonostemon huangmosun , and Bambusa vulgaris , and involved five relative humidity conditions (22, 43, 75, 84, and 90%), two mass samples (0.1 and 1 g), and two particle sizes (powder and piece). Two response variables including water adsorption and temperature increase were analyzed and discussed. The temperature did not increase linearly with the adsorption of water. Temperature was modeled by nine explanatory variables, while water adsorption was modeled by eight. Five variables, including factors and their interactions, were found to be common to the two models. Sample mass and relative humidity influenced the two qualitative variables, while particle size and biochar type only influenced the temperature.

A supportive-educative telephone program: impact on knowledge and anxiety after coronary artery bypass graft surgery.

PubMed

Beckie, T

1989-01-01

The purpose of this study was to investigate the impact of a supportive-educative telephone program on the levels of knowledge and anxiety of patients undergoing coronary artery bypass graft surgery during the first 6 weeks after hospital discharge. With a posttest-only control group design, the first 74 patients scheduled, between September 1986 and February 1987, for coronary artery bypass graft surgery in a large, western Canadian teaching hospital were randomly assigned to either an experimental or a control group. The effect of the intervention, which was implemented by a cardiac rehabilitation nurse specialist, was assessed by a knowledge test and a state anxiety inventory. Data were collected without knowledge of the participants' group assignment. As hypothesized, data analysis with independent t tests revealed a statistically significant (p less than 0.05) difference between the knowledge level of the experimental and the control group in the areas of coronary artery disease, diet, medications, physical activity restrictions, exercise, and rest. A statistically significant difference between the state anxiety level of the experimental and the control group was also evident, as was a statistically significant inverse relationship between participants' knowledge and anxiety levels. From these findings, several implications and recommendations for nursing practice and research have been generated.

iCFD: Interpreted Computational Fluid Dynamics - Degeneration of CFD to one-dimensional advection-dispersion models using statistical experimental design - The secondary clarifier.

PubMed

Guyonvarch, Estelle; Ramin, Elham; Kulahci, Murat; Plósz, Benedek Gy

2015-10-15

The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Simple and Robust Method for Partially Matched Samples Using the P-Values Pooling Approach

PubMed Central

Kuan, Pei Fen; Huang, Bo

2013-01-01

This paper focuses on statistical analyses in scenarios where some samples from the matched pairs design are missing, resulting in partially matched samples. Motivated by the idea of meta-analysis, we recast the partially matched samples as coming from two experimental designs, and propose a simple yet robust approach based on the weighted Z-test to integrate the p-values computed from these two designs. We show that the proposed approach achieves better operating characteristics in simulations and a case study, compared to existing methods for partially matched samples. PMID:23417968

Experiment Design for Complex VTOL Aircraft with Distributed Propulsion and Tilt Wing

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Landman, Drew

2015-01-01

Selected experimental results from a wind tunnel study of a subscale VTOL concept with distributed propulsion and tilt lifting surfaces are presented. The vehicle complexity and automated test facility were ideal for use with a randomized designed experiment. Design of Experiments and Response Surface Methods were invoked to produce run efficient, statistically rigorous regression models with minimized prediction error. Static tests were conducted at the NASA Langley 12-Foot Low-Speed Tunnel to model all six aerodynamic coefficients over a large flight envelope. This work supports investigations at NASA Langley in developing advanced configurations, simulations, and advanced control systems.

D-Optimal Experimental Design for Contaminant Source Identification

NASA Astrophysics Data System (ADS)

Sai Baba, A. K.; Alexanderian, A.

2016-12-01

Contaminant source identification seeks to estimate the release history of a conservative solute given point concentration measurements at some time after the release. This can be mathematically expressed as an inverse problem, with a linear observation operator or a parameter-to-observation map, which we tackle using a Bayesian approach. Acquisition of experimental data can be laborious and expensive. The goal is to control the experimental parameters - in our case, the sparsity of the sensors, to maximize the information gain subject to some physical or budget constraints. This is known as optimal experimental design (OED). D-optimal experimental design seeks to maximize the expected information gain, and has long been considered the gold standard in the statistics community. Our goal is to develop scalable methods for D-optimal experimental designs involving large-scale PDE constrained problems with high-dimensional parameter fields. A major challenge for the OED, is that a nonlinear optimization algorithm for the D-optimality criterion requires repeated evaluation of objective function and gradient involving the determinant of large and dense matrices - this cost can be prohibitively expensive for applications of interest. We propose novel randomized matrix techniques that bring down the computational costs of the objective function and gradient evaluations by several orders of magnitude compared to the naive approach. The effect of randomized estimators on the accuracy and the convergence of the optimization solver will be discussed. The features and benefits of our new approach will be demonstrated on a challenging model problem from contaminant source identification involving the inference of the initial condition from spatio-temporal observations in a time-dependent advection-diffusion problem.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Adaptive design optimization: a mutual information-based approach to model discrimination in cognitive science.

PubMed

Cavagnaro, Daniel R; Myung, Jay I; Pitt, Mark A; Kujala, Janne V

2010-04-01

Discriminating among competing statistical models is a pressing issue for many experimentalists in the field of cognitive science. Resolving this issue begins with designing maximally informative experiments. To this end, the problem to be solved in adaptive design optimization is identifying experimental designs under which one can infer the underlying model in the fewest possible steps. When the models under consideration are nonlinear, as is often the case in cognitive science, this problem can be impossible to solve analytically without simplifying assumptions. However, as we show in this letter, a full solution can be found numerically with the help of a Bayesian computational trick derived from the statistics literature, which recasts the problem as a probability density simulation in which the optimal design is the mode of the density. We use a utility function based on mutual information and give three intuitive interpretations of the utility function in terms of Bayesian posterior estimates. As a proof of concept, we offer a simple example application to an experiment on memory retention.

Fast Synthesis of Gibbsite Nanoplates and Process Optimization using Box-Behnken Experimental Design

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

Zhang, Xin; Zhang, Xianwen; Graham, Trent R.

Developing the ability to synthesize compositionally and morphologically well-defined gibbsite particles at the nanoscale with high yield is an ongoing need that has not yet achieved the level of rational design. Here we report optimization of a clean inorganic synthesis route based on statistical experimental design examining the influence of Al(OH)3 gel precursor concentration, pH, and aging time at temperature. At 80 oC, the optimum synthesis conditions of gel concentration at 0.5 M, pH at 9.2, and time at 72 h maximized the reaction yield up to ~87%. The resulting gibbsite product is composed of highly uniform euhedral hexagonal nanoplatesmore » within a basal plane diameter range of 200-400 nm. The independent roles of key system variables in the growth mechanism are considered. On the basis of these optimized experimental conditions, the synthesis procedure, which is both cost-effective and environmentally friendly, has the potential for mass production scale-up of high quality gibbsite material for various fundamental research and industrial applications.« less

Gaussian process based modeling and experimental design for sensor calibration in drifting environments

PubMed Central

Geng, Zongyu; Yang, Feng; Chen, Xi; Wu, Nianqiang

2016-01-01

It remains a challenge to accurately calibrate a sensor subject to environmental drift. The calibration task for such a sensor is to quantify the relationship between the sensor’s response and its exposure condition, which is specified by not only the analyte concentration but also the environmental factors such as temperature and humidity. This work developed a Gaussian Process (GP)-based procedure for the efficient calibration of sensors in drifting environments. Adopted as the calibration model, GP is not only able to capture the possibly nonlinear relationship between the sensor responses and the various exposure-condition factors, but also able to provide valid statistical inference for uncertainty quantification of the target estimates (e.g., the estimated analyte concentration of an unknown environment). Built on GP’s inference ability, an experimental design method was developed to achieve efficient sampling of calibration data in a batch sequential manner. The resulting calibration procedure, which integrates the GP-based modeling and experimental design, was applied on a simulated chemiresistor sensor to demonstrate its effectiveness and its efficiency over the traditional method. PMID:26924894

Optimization of the synthesis process of an iron oxide nanocatalyst supported on activated carbon for the inactivation of Ascaris eggs in water using the heterogeneous Fenton-like reaction.

PubMed

Morales-Pérez, Ariadna A; Maravilla, Pablo; Solís-López, Myriam; Schouwenaars, Rafael; Durán-Moreno, Alfonso; Ramírez-Zamora, Rosa-María

2016-01-01

An experimental design methodology was used to optimize the synthesis of an iron-supported nanocatalyst as well as the inactivation process of Ascaris eggs (Ae) using this material. A factor screening design was used for identifying the significant experimental factors for nanocatalyst support (supported %Fe, (w/w), temperature and time of calcination) and for the inactivation process called the heterogeneous Fenton-like reaction (H2O2 dose, mass ratio Fe/H2O2, pH and reaction time). The optimization of the significant factors was carried out using a face-centered central composite design. The optimal operating conditions for both processes were estimated with a statistical model and implemented experimentally with five replicates. The predicted value of the Ae inactivation rate was close to the laboratory results. At the optimal operating conditions of the nanocatalyst production and Ae inactivation process, the Ascaris ova showed genomic damage to the point that no cell reparation was possible showing that this advanced oxidation process was highly efficient for inactivating this pathogen.

Imaging of neural oscillations with embedded inferential and group prevalence statistics.

PubMed

Donhauser, Peter W; Florin, Esther; Baillet, Sylvain

2018-02-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.

Imaging of neural oscillations with embedded inferential and group prevalence statistics

PubMed Central

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience. PMID:29408902

Using R in experimental design with BIBD: An application in health sciences

NASA Astrophysics Data System (ADS)

Oliveira, Teresa A.; Francisco, Carla; Oliveira, Amílcar; Ferreira, Agostinho

2016-06-01

Considering the implementation of an Experimental Design, in any field, the experimenter must pay particular attention and look for the best strategies in the following steps: planning the design selection, conduct the experiments, collect observed data, proceed to analysis and interpretation of results. The focus is on providing both - a deep understanding of the problem under research and a powerful experimental process at a reduced cost. Mainly thanks to the possibility of allowing to separate variation sources, the importance of Experimental Design in Health Sciences is strongly recommended since long time. Particular attention has been devoted to Block Designs and more precisely to Balanced Incomplete Block Designs - in this case the relevance states from the fact that these designs allow testing simultaneously a number of treatments bigger than the block size. Our example refers to a possible study of inter reliability of the Parkinson disease, taking into account the UPDRS (Unified Parkinson's disease rating scale) in order to test if there are significant differences between the specialists who evaluate the patients performances. Statistical studies on this disease were described for example in Richards et al (1994), where the authors investigate the inter-rater Reliability of the Unified Parkinson's Disease Rating Scale Motor Examination. We consider a simulation of a practical situation in which the patients were observed by different specialists and the UPDRS on assessing the impact of Parkinson's disease in patients was observed. Assigning treatments to the subjects following a particular BIBD(9,24,8,3,2) structure, we illustrate that BIB Designs can be used as a powerful tool to solve emerging problems in this area. Once a structure with repeated blocks allows to have some block contrasts with minimum variance, see Oliveira et al. (2006), the design with cardinality 12 was selected for the example. R software was used for computations.

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

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.

[The effects of foot reflexology on nausea, vomiting and fatigue of breast cancer patients undergoing chemotherapy].

PubMed

Yang, Jin-Hyang

2005-02-01

The purpose of this study was to identify the effects of foot reflexology on nausea, vomiting and fatigue in breast cancer patients undergoing chemotherapy. The research was a quasi-experimental study using a non-equivalent pre-post design and was conducted from Jan. 26, to Mar. 20, 2004. The subjects consisted of 34 patients with 18 in the experimental group and 16 in control group. A pretest and 2 posttests were conducted to measure nausea, vomiting and fatigue. For the experimental group, foot reflexology, which was consisted of 4 phases for 40 minutes, was given by a researcher and 4 research assistants. The collected data were analyzed by repeated measures ANOVA using the SPSS WIN 10.0 program. There was a statistically significant decrease in nausea, and vomiting in the experimental group compared to the control group over two different times. In addition, there was a statistically significant decrease in fatigue in the experimental group compared to the control group over two different times. Foot reflexology was effective on nausea, vomiting and fatigue in breast cancer patients receiving chemotherapy in this study. Therefore, foot reflexology can be usefully utilized as a nursing intervention in the field of cancer nursing for breast cancer patients receiving chemotherapy.

The direct assignment option as a modular design component: an example for the setting of two predefined subgroups.

PubMed

An, Ming-Wen; Lu, Xin; Sargent, Daniel J; Mandrekar, Sumithra J

2015-01-01

A phase II design with an option for direct assignment (stop randomization and assign all patients to experimental treatment based on interim analysis, IA) for a predefined subgroup was previously proposed. Here, we illustrate the modularity of the direct assignment option by applying it to the setting of two predefined subgroups and testing for separate subgroup main effects. We power the 2-subgroup direct assignment option design with 1 IA (DAD-1) to test for separate subgroup main effects, with assessment of power to detect an interaction in a post-hoc test. Simulations assessed the statistical properties of this design compared to the 2-subgroup balanced randomized design with 1 IA, BRD-1. Different response rates for treatment/control in subgroup 1 (0.4/0.2) and in subgroup 2 (0.1/0.2, 0.4/0.2) were considered. The 2-subgroup DAD-1 preserves power and type I error rate compared to the 2-subgroup BRD-1, while exhibiting reasonable power in a post-hoc test for interaction. The direct assignment option is a flexible design component that can be incorporated into broader design frameworks, while maintaining desirable statistical properties, clinical appeal, and logistical simplicity.

[Development and evaluation of a program to promote self management in patients with chronic hepatitis B].

PubMed

Yang, Jin-Hyang

2012-04-01

The purpose of this study was to identify the effects of the program to promote self management for patients with chronic hepatitis B. The research was a quasi-experimental design using a non-equivalent control group pre-post test. The participants were 61 patients, 29 in the experimental group and 32 in the control group. A pretest and 2 posttests were conducted to measure main variables. For the experimental group, the self-management program, consisting of counseling-centered activities in small groups, was given for 6 weeks. Data were analyzed using χ², t-test, and repeated measures ANOVA with PASW statistics program. There were statistically significant increases in knowledge, self-efficacy, active ways of coping, and self-management compliance but not in passive ways of coping in the experimental group compared to the control group over two different times. The results of this study indicate that the self-management program is effective in increasing knowledge, self-efficacy, active ways of coping, and self-management compliance among patients with chronic hepatitis B. Therefore, it can be usefully utilized in the field of nursing for patients with chronic disease as a nursing intervention for people with chronic hepatitis B.

Use of Mixture Designs to Investigate Contribution of Minor Sex Pheromone Components to Trap Catch of the Carpenterworm Moth, Chilecomadia valdiviana.

PubMed

Lapointe, Stephen L; Barros-Parada, Wilson; Fuentes-Contreras, Eduardo; Herrera, Heidy; Kinsho, Takeshi; Miyake, Yuki; Niedz, Randall P; Bergmann, Jan

2017-12-01

Field experiments were carried out to study responses of male moths of the carpenterworm, Chilecomadia valdiviana (Lepidoptera: Cossidae), a pest of tree and fruit crops in Chile, to five compounds previously identified from the pheromone glands of females. Previously, attraction of males to the major component, (7Z,10Z)-7,10-hexadecadienal, was clearly demonstrated while the role of the minor components was uncertain due to the use of an experimental design that left large portions of the design space unexplored. We used mixture designs to study the potential contributions to trap catch of the four minor pheromone components produced by C. valdiviana. After systematically exploring the design space described by the five pheromone components, we concluded that the major pheromone component alone is responsible for attraction of male moths in this species. The need for appropriate experimental designs to address the problem of assessing responses to mixtures of semiochemicals in chemical ecology is described. We present an analysis of mixture designs and response surface modeling and an explanation of why this approach is superior to commonly used, but statistically inappropriate, designs.

Optimal designs for copula models

PubMed Central

Perrone, E.; Müller, W.G.

2016-01-01

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well. PMID:27453616

Measurement of optical intensity fluctuation over an 11.8 km turbulent path.

PubMed

Jiang, Yijun; Ma, Jing; Tan, Liying; Yu, Siyuan; Du, Wenhe

2008-05-12

An 11.8km optical link is established to examine the intensity fluctuation of the laser beam transmission through atmosphere turbulence. Probability density function, fade statistic, and high-frequency spectrum are researched based on the analysis of the experimental data collected in each season of a year, including both weak and strong fluctuation cases. Finally, the daily variation curve of scintillation index is given, compared with the variation of refractive-index structure parameter C(n) (2), which is calculated from the experimental data of angle of arrival. This work provides the experimental results that are helpful to the atmospheric propagation research and the free-space optical communication system design.

Characterisation of the LMS propagation channel at L- and S-bands: Narrowband experimental data and channel modelling

NASA Technical Reports Server (NTRS)

Sforza, Mario; Buonomo, Sergio

1993-01-01

During the period 1983-1992 the European Space Agency (ESA) carried out several experimental campaigns to investigate the propagation impairments of the Land Mobile Satellite (LMS) communication channel. A substantial amount of data covering quite a large range of elevation angles, environments, and frequencies was obtained. Results from the data analyses are currently used for system planning and design applications within the framework of the future ESA LMS projects. This comprehensive experimental data base is presently utilized also for channel modeling purposes and preliminary results are given. Cumulative Distribution Functions (PDF) and Duration of Fades (DoF) statistics at different elevation angles and environments were also included.

Optimizing an experimental design for an electromagnetic experiment

NASA Astrophysics Data System (ADS)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.

Proceedings of the Conference on the Design of Experiments in Army Research Development and Testing (35th) Held in Monterey California, California on 18-20 October 1989

DTIC Science & Technology

1990-08-01

Statistics. John Wiley and Sons , 1980, p. 111. 7. Hanson, D. L. and Koopmans, Lo H.t Tolerance Limits for the Class of Distributions With Increasing...Am. Statis° Assoc., vol. 82, 1987, p. 918. 9. Lehmann, E0 Lot Testing Statistical Hypotheses. John Wiley and Sons , 1959, pp. 274-275. 10. Lemon, G. H...Surfaces," John Wily & Sons , Inc., New York. 3. Box, G. E. P. and Wilson, K. B. (1951), "On the Experimental Attainment of Optimum Conditions," Journal of

Six Guidelines for Interesting Research.

PubMed

Gray, Kurt; Wegner, Daniel M

2013-09-01

There are many guides on proper psychology, but far fewer on interesting psychology. This article presents six guidelines for interesting research. The first three-Phenomena First, Be Surprising, and Grandmothers, Not Scientists-suggest how to choose your research question; the last three-Be The Participant, Simple Statistics, and Powerful Beginnings-suggest how to answer your research question and offer perspectives on experimental design, statistical analysis, and effective communication. These guidelines serve as reminders that replicability is necessary but not sufficient for compelling psychological science. Interesting research considers subjective experience; it listens to the music of the human condition. © The Author(s) 2013.

Statistical reconstruction for cosmic ray muon tomography.

PubMed

Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J

2007-08-01

Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.

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.

[Effects of Kangaroo Care on anxiety, maternal role confidence, and maternal infant attachment of mothers who delivered preterm infants].

PubMed

Lee, Sang Bok; Shin, Hye Sook

2007-10-01

The purpose of this study was to examine the effects of Kangaroo Care(KC) on anxiety, maternal role confidence, and maternal infant attachment of mothers who delivered preterm infants. The research design was a nonequivalent control group pretest-posttest. Data was collected from September 1. 2006 to June 20. 2007. The participants were 22 mothers in the experimental group and 21 in the control group. KC was applied three times per day, for a total of ten times in 4 days to the experimental group. The degree of anxiety was statistically significantly different between the two groups but maternal role confidence and maternal infant attachment was statistically insignificant. This data suggests that KC was effective for mothers anxiety relief but it was not effective for maternal role confidence and maternal infant attachment of mothers. The implications for nursing practice and directions for future research need to be discussed.

Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

PubMed Central

Chen, Yang; Shen, Kuang

2017-01-01

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process. PMID:28943680

Preliminary results from DIMES: Dispersion in the ACC

NASA Astrophysics Data System (ADS)

Balwada, D.; Speer, K.; LaCasce, J. H.; Owens, B.

2012-04-01

The Diapycnal and Isopynal Mixing Experiment in the Southern Ocean (DIMES) is a CLIVAR process study designed to study mixing in the Antarctic Circumpolar Current. The experiment includes tracer release, float, and small-scale turbulence components. This presentation will report on some results of the float component, from floats deployed across the ACC in the Southeast Pacific Ocean. These are the first subsurface Lagrangian trajectories from the ACC. Floats were deployed to follow approximately a constant density surface for a period of 1-3 years. To help aid the experimental results virtual floats were advected using AVISO data and basic statistics were derived from both deployed and virtual float trajectories. Experimental design, initial results, comparison to virtual floats and single particle and relative dispersion calculations will be presented.

Teacher Professional Development to Foster Authentic Student Research Experiences

NASA Astrophysics Data System (ADS)

Conn, K.; Iyengar, E.

2004-12-01

This presentation reports on a new teacher workshop design that encourages teachers to initiate and support long-term student-directed research projects in the classroom setting. Teachers were recruited and engaged in an intensive marine ecology learning experience at Shoals Marine Laboratory, Appledore Island, Maine. Part of the weeklong summer workshop was spent in field work, part in laboratory work, and part in learning experimental design and basic statistical analysis of experimental results. Teachers were presented with strategies to adapt their workshop learnings to formulate plans for initiating and managing authentic student research projects in their classrooms. The authors will report on the different considerations and constraints facing the teachers in their home school settings and teachers' progress in implementing their plans. Suggestions for replicating the workshop will be offered.

Plant growth modeling at the JSC variable pressure growth chamber - An application of experimental design

NASA Technical Reports Server (NTRS)

Miller, Adam M.; Edeen, Marybeth; Sirko, Robert J.

1992-01-01

This paper describes the approach and results of an effort to characterize plant growth under various environmental conditions at the Johnson Space Center variable pressure growth chamber. Using a field of applied mathematics and statistics known as design of experiments (DOE), we developed a test plan for varying environmental parameters during a lettuce growth experiment. The test plan was developed using a Box-Behnken approach to DOE. As a result of the experimental runs, we have developed empirical models of both the transpiration process and carbon dioxide assimilation for Waldman's Green lettuce over specified ranges of environmental parameters including carbon dioxide concentration, light intensity, dew-point temperature, and air velocity. This model also predicts transpiration and carbon dioxide assimilation for different ages of the plant canopy.

Commentary on Sommer et al. 'A randomized experiment of the effects of including alternative medicine in the mandatory benefit package of health insurance.

PubMed

Heusser, P

2000-03-01

The study by Sommer et al. recently reported in Complementary Therapies in Medicine has been heavily criticised in Switzerland since its original publication. Its major problems are an inadequate reflection of real practice, an inadequate study design relative to the central research objective, questionable value of the applied instrument and procedure for health assessment, methodological and statistical problems, and failure to consider literature relevant to the topic. For these reasons, this experimental study does not allow an answer to its central questions as to costs and effectiveness of complementary medicine made available within Switzerland's mandatory basic health insurance provisions. We propose more practice-related, non-experimental prospective study designs to realistically answer these questions.

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 Laboratory Course for Teaching Laboratory Techniques, Experimental Design, Statistical Analysis, and Peer Review Process to Undergraduate Science Students

ERIC Educational Resources Information Center

Gliddon, C. M.; Rosengren, R. J.

2012-01-01

This article describes a 13-week laboratory course called Human Toxicology taught at the University of Otago, New Zealand. This course used a guided inquiry based laboratory coupled with formative assessment and collaborative learning to develop in undergraduate students the skills of problem solving/critical thinking, data interpretation and…

The Influence of Experimental Design on the Detection of Performance Differences

ERIC Educational Resources Information Center

Bates, B. T.; Dufek, J. S.; James, C. R.; Harry, J. R.; Eggleston, J. D.

2016-01-01

We demonstrate the effect of sample and trial size on statistical outcomes for single-subject analyses (SSA) and group analyses (GA) for a frequently studied performance activity and common intervention. Fifty strides of walking data collected in two blocks of 25 trials for two shoe conditions were analyzed for samples of five, eight, 10, and 12…

Experimental research on mathematical modelling and unconventional control of clinker kiln in cement plants

NASA Astrophysics Data System (ADS)

Rusu-Anghel, S.

2017-01-01

Analytical modeling of the flow of manufacturing process of the cement is difficult because of their complexity and has not resulted in sufficiently precise mathematical models. In this paper, based on a statistical model of the process and using the knowledge of human experts, was designed a fuzzy system for automatic control of clinkering process.

Informal Statistics Help Desk

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, R. J.; Feiveson, A. H.

2015-01-01

Back by popular demand, the JSC Biostatistics Lab is offering an opportunity for informal conversation about challenges you may have encountered with issues of experimental design, analysis, data visualization or related topics. Get answers to common questions about sample size, repeated measures, violation of distributional assumptions, missing data, multiple testing, time-to-event data, when to trust the results of your analyses (reproducibility issues) and more.

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.

Sudden death and cervical spine: A new contribution to pathogenesis for sudden death in critical care unit from subarachnoid hemorrhage; first report – An experimental study

PubMed Central

Kazdal, Hizir; Kanat, Ayhan; Aydin, Mehmet Dumlu; Yazar, Ugur; Guvercin, Ali Riza; Calik, Muhammet; Gundogdu, Betul

2017-01-01

Context: Sudden death from subarachnoid hemorrhage (SAH) is not uncommon. Aims: The goal of this study is to elucidate the effect of the cervical spinal roots and the related dorsal root ganglions (DRGs) on cardiorespiratory arrest following SAH. Settings and Design: This was an experimental study conducted on rabbits. Materials and Methods: This study was conducted on 22 rabbits which were randomly divided into three groups: control (n = 5), physiologic serum saline (SS; n = 6), SAH groups (n = 11). Experimental SAH was performed. Seven of 11 rabbits with SAH died within the first 2 weeks. After 20 days, other animals were sacrificed. The anterior spinal arteries, arteriae nervorum of cervical nerve roots (C6–C8), DRGs, and lungs were histopathologically examined and estimated stereologically. Statistical Analysis Used: Statistical analysis was performed using the PASW Statistics 18.0 for Windows (SPSS Inc., Chicago, Illinois, USA). Intergroup differences were assessed using a one-way ANOVA. The statistical significance was set at P < 0.05. Results: In the SAH group, histopathologically, severe anterior spinal artery (ASA) and arteriae nervorum vasospasm, axonal and neuronal degeneration, and neuronal apoptosis were observed. Vasospasm of ASA did not occur in the SS and control groups. There was a statistically significant increase in the degenerated neuron density in the SAH group as compared to the control and SS groups (P < 0.05). Cardiorespiratory disturbances, arrest, and lung edema more commonly developed in animals in the SAH group. Conclusion: We noticed interestingly that C6–C8 DRG degenerations were secondary to the vasospasm of ASA, following SAH. Cardiorespiratory disturbances or arrest can be explained with these mechanisms. PMID:28250634

Packet Randomized Experiments for Eliminating Classes of Confounders

PubMed Central

Pavela, Greg; Wiener, Howard; Fontaine, Kevin R.; Fields, David A.; Voss, Jameson D.; Allison, David B.

2014-01-01

Background Although randomization is considered essential for causal inference, it is often not possible to randomize in nutrition and obesity research. To address this, we develop a framework for an experimental design—packet randomized experiments (PREs), which improves causal inferences when randomization on a single treatment variable is not possible. This situation arises when subjects are randomly assigned to a condition (such as a new roommate) which varies in one characteristic of interest (such as weight), but also varies across many others. There has been no general discussion of this experimental design, including its strengths, limitations, and statistical properties. As such, researchers are left to develop and apply PREs on an ad hoc basis, limiting its potential to improve causal inferences among nutrition and obesity researchers. Methods We introduce PREs as an intermediary design between randomized controlled trials and observational studies. We review previous research that used the PRE design and describe its application in obesity-related research, including random roommate assignments, heterochronic parabiosis, and the quasi-random assignment of subjects to geographic areas. We then provide a statistical framework to control for potential packet-level confounders not accounted for by randomization. Results PREs have successfully been used to improve causal estimates of the effect of roommates, altitude, and breastfeeding on weight outcomes. When certain assumptions are met, PREs can asymptotically control for packet-level characteristics. This has the potential to statistically estimate the effect of a single treatment even when randomization to a single treatment did not occur. Conclusions Applying PREs to obesity-related research will improve decisions about clinical, public health, and policy actions insofar as it offers researchers new insight into cause and effect relationships among variables. PMID:25444088

Statistical inference for extended or shortened phase II studies based on Simon's two-stage designs.

PubMed

Zhao, Junjun; Yu, Menggang; Feng, Xi-Ping

2015-06-07

Simon's two-stage designs are popular choices for conducting phase II clinical trials, especially in the oncology trials to reduce the number of patients placed on ineffective experimental therapies. Recently Koyama and Chen (2008) discussed how to conduct proper inference for such studies because they found that inference procedures used with Simon's designs almost always ignore the actual sampling plan used. In particular, they proposed an inference method for studies when the actual second stage sample sizes differ from planned ones. We consider an alternative inference method based on likelihood ratio. In particular, we order permissible sample paths under Simon's two-stage designs using their corresponding conditional likelihood. In this way, we can calculate p-values using the common definition: the probability of obtaining a test statistic value at least as extreme as that observed under the null hypothesis. In addition to providing inference for a couple of scenarios where Koyama and Chen's method can be difficult to apply, the resulting estimate based on our method appears to have certain advantage in terms of inference properties in many numerical simulations. It generally led to smaller biases and narrower confidence intervals while maintaining similar coverages. We also illustrated the two methods in a real data setting. Inference procedures used with Simon's designs almost always ignore the actual sampling plan. Reported P-values, point estimates and confidence intervals for the response rate are not usually adjusted for the design's adaptiveness. Proper statistical inference procedures should be used.

Identification and statistical optimization of fermentation conditions for a newly isolated extracellular cholesterol oxidase-producing Streptomyces cavourensis strain NEAE-42.

PubMed

El-Naggar, Noura El-Ahmady; El-Shweihy, Nancy M; El-Ewasy, Sara M

2016-09-20

Due to broad range of clinical and industrial applications of cholesterol oxidase, isolation and screening of bacterial strains producing extracellular form of cholesterol oxidase is of great importance. One hundred and thirty actinomycete isolates were screened for their cholesterol oxidase activity. Among them, a potential culture, strain NEAE-42 is displayed the highest extracellular cholesterol oxidase activity. It was selected and identified as Streptomyces cavourensis strain NEAE-42. The optimization of different process parameters for cholesterol oxidase production by Streptomyces cavourensis strain NEAE-42 using Plackett-Burman experimental design and response surface methodology was carried out. Fifteen variables were screened using Plackett-Burman experimental design. Cholesterol, initial pH and (NH4)2SO4 were the most significant positive independent variables affecting cholesterol oxidase production. Central composite design was chosen to elucidate the optimal concentrations of the selected process variables on cholesterol oxidase production. It was found that, cholesterol oxidase production by Streptomyces cavourensis strain NEAE-42 after optimization process was 20.521U/mL which is higher than result obtained from the basal medium before screening process using Plackett-Burman (3.31 U/mL) with a fold of increase 6.19. The cholesterol oxidase level production obtained in this study (20.521U/mL) by the statistical method is higher than many of the reported values.

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH

PubMed Central

2009-01-01

Background Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. Results We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. Conclusion The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies. PMID:19925645

Mechanistic analysis of challenge-response experiments.

PubMed

Shotwell, M S; Drake, K J; Sidorov, V Y; Wikswo, J P

2013-09-01

We present an application of mechanistic modeling and nonlinear longitudinal regression in the context of biomedical response-to-challenge experiments, a field where these methods are underutilized. In this type of experiment, a system is studied by imposing an experimental challenge, and then observing its response. The combination of mechanistic modeling and nonlinear longitudinal regression has brought new insight, and revealed an unexpected opportunity for optimal design. Specifically, the mechanistic aspect of our approach enables the optimal design of experimental challenge characteristics (e.g., intensity, duration). This article lays some groundwork for this approach. We consider a series of experiments wherein an isolated rabbit heart is challenged with intermittent anoxia. The heart responds to the challenge onset, and recovers when the challenge ends. The mean response is modeled by a system of differential equations that describe a candidate mechanism for cardiac response to anoxia challenge. The cardiac system behaves more variably when challenged than when at rest. Hence, observations arising from this experiment exhibit complex heteroscedasticity and sharp changes in central tendency. We present evidence that an asymptotic statistical inference strategy may fail to adequately account for statistical uncertainty. Two alternative methods are critiqued qualitatively (i.e., for utility in the current context), and quantitatively using an innovative Monte-Carlo method. We conclude with a discussion of the exciting opportunities in optimal design of response-to-challenge experiments. © 2013, The International Biometric Society.

Assessment of Cultivation Factors that Affect Biomass and Geraniol Production in Transgenic Tobacco Cell Suspension Cultures

PubMed Central

Vasilev, Nikolay; Schmitz, Christian; Grömping, Ulrike; Fischer, Rainer; Schillberg, Stefan

2014-01-01

A large-scale statistical experimental design was used to determine essential cultivation parameters that affect biomass accumulation and geraniol production in transgenic tobacco (Nicotiana tabacum cv. Samsun NN) cell suspension cultures. The carbohydrate source played a major role in determining the geraniol yield and factors such as filling volume, inoculum size and light were less important. Sucrose, filling volume and inoculum size had a positive effect on geraniol yield by boosting growth of plant cell cultures whereas illumination of the cultures stimulated the geraniol biosynthesis. We also found that the carbohydrates sucrose and mannitol showed polarizing effects on biomass and geraniol accumulation. Factors such as shaking frequency, the presence of conditioned medium and solubilizers had minor influence on both plant cell growth and geraniol content. When cells were cultivated under the screened conditions for all the investigated factors, the cultures produced ∼5.2 mg/l geraniol after 12 days of cultivation in shaking flasks which is comparable to the yield obtained in microbial expression systems. Our data suggest that industrial experimental designs based on orthogonal arrays are suitable for the selection of initial cultivation parameters prior to the essential medium optimization steps. Such designs are particularly beneficial in the early optimization steps when many factors must be screened, increasing the statistical power of the experiments without increasing the demand on time and resources. PMID:25117009

Assessment of cultivation factors that affect biomass and geraniol production in transgenic tobacco cell suspension cultures.

PubMed

Vasilev, Nikolay; Schmitz, Christian; Grömping, Ulrike; Fischer, Rainer; Schillberg, Stefan

2014-01-01

A large-scale statistical experimental design was used to determine essential cultivation parameters that affect biomass accumulation and geraniol production in transgenic tobacco (Nicotiana tabacum cv. Samsun NN) cell suspension cultures. The carbohydrate source played a major role in determining the geraniol yield and factors such as filling volume, inoculum size and light were less important. Sucrose, filling volume and inoculum size had a positive effect on geraniol yield by boosting growth of plant cell cultures whereas illumination of the cultures stimulated the geraniol biosynthesis. We also found that the carbohydrates sucrose and mannitol showed polarizing effects on biomass and geraniol accumulation. Factors such as shaking frequency, the presence of conditioned medium and solubilizers had minor influence on both plant cell growth and geraniol content. When cells were cultivated under the screened conditions for all the investigated factors, the cultures produced ∼ 5.2 mg/l geraniol after 12 days of cultivation in shaking flasks which is comparable to the yield obtained in microbial expression systems. Our data suggest that industrial experimental designs based on orthogonal arrays are suitable for the selection of initial cultivation parameters prior to the essential medium optimization steps. Such designs are particularly beneficial in the early optimization steps when many factors must be screened, increasing the statistical power of the experiments without increasing the demand on time and resources.

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH.

PubMed

Allemeersch, Joke; Van Vooren, Steven; Hannes, Femke; De Moor, Bart; Vermeesch, Joris Robert; Moreau, Yves

2009-11-19

Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies.

A brief understanding of process optimisation in microwave-assisted extraction of botanical materials: options and opportunities with chemometric tools.

PubMed

Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

2014-01-01

Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave-assisted extraction (MAE) of botanical material. A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine-tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision-making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.

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 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.

Parametric design of pressure-relieving foot orthosis using statistics-based finite element method.

PubMed

Cheung, Jason Tak-Man; Zhang, Ming

2008-04-01

Custom-molded foot orthoses are frequently prescribed in routine clinical practice to prevent or treat plantar ulcers in diabetes by reducing the peak plantar pressure. However, the design and fabrication of foot orthosis vary among clinical practitioners and manufacturers. Moreover, little information about the parametric effect of different combinations of design factors is available. As an alternative to the experimental approach, therefore, computational models of the foot and footwear can provide efficient evaluations of different combinations of structural and material design factors on plantar pressure distribution. In this study, a combined finite element and Taguchi method was used to identify the sensitivity of five design factors (arch type, insole and midsole thickness, insole and midsole stiffness) of foot orthosis on peak plantar pressure relief. From the FE predictions, the custom-molded shape was found to be the most important design factor in reducing peak plantar pressure. Besides the use of an arch-conforming foot orthosis, the insole stiffness was found to be the second most important factor for peak pressure reduction. Other design factors, such as insole thickness, midsole stiffness and midsole thickness, contributed to less important roles in peak pressure reduction in the given order. The statistics-based FE method was found to be an effective approach in evaluating and optimizing the design of foot orthosis.

Error floor behavior study of LDPC codes for concatenated codes design

NASA Astrophysics Data System (ADS)

Chen, Weigang; Yin, Liuguo; Lu, Jianhua

2007-11-01

Error floor behavior of low-density parity-check (LDPC) codes using quantized decoding algorithms is statistically studied with experimental results on a hardware evaluation platform. The results present the distribution of the residual errors after decoding failure and reveal that the number of residual error bits in a codeword is usually very small using quantized sum-product (SP) algorithm. Therefore, LDPC code may serve as the inner code in a concatenated coding system with a high code rate outer code and thus an ultra low error floor can be achieved. This conclusion is also verified by the experimental results.

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.

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

PubMed

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

D-Optimal mixture experimental design for stealth biodegradable crosslinked docetaxel-loaded poly-ε-caprolactone nanoparticles manufactured by dispersion polymerization.

PubMed

Ogunwuyi, O; Adesina, S; Akala, E O

2015-03-01

We report here our efforts on the development of stealth biodegradable crosslinked poly-ε-caprolactone nanoparticles by free radical dispersion polymerization suitable for the delivery of bioactive agents. The uniqueness of the dispersion polymerization technique is that it is surfactant free, thereby obviating the problems known to be associated with the use of surfactants in the fabrication of nanoparticles for biomedical applications. Aided by a statistical software for experimental design and analysis, we used D-optimal mixture statistical experimental design to generate thirty batches of nanoparticles prepared by varying the proportion of the components (poly-ε-caprolactone macromonomer, crosslinker, initiators and stabilizer) in acetone/water system. Morphology of the nanoparticles was examined using scanning electron microscopy (SEM). Particle size and zeta potential were measured by dynamic light scattering (DLS). Scheffe polynomial models were generated to predict particle size (nm) and particle surface zeta potential (mV) as functions of the proportion of the components. Solutions were returned from simultaneous optimization of the response variables for component combinations to (a) minimize nanoparticle size (small nanoparticles are internalized into disease organs easily, avoid reticuloendothelial clearance and lung filtration) and (b) maximization of the negative zeta potential values, as it is known that, following injection into the blood stream, nanoparticles with a positive zeta potential pose a threat of causing transient embolism and rapid clearance compared to negatively charged particles. In vitro availability isotherms show that the nanoparticles sustained the release of docetaxel for 72 to 120 hours depending on the formulation. The data show that nanotechnology platforms for controlled delivery of bioactive agents can be developed based on the nanoparticles.

Single-Case Experimental Designs: A Systematic Review of Published Research and Current Standards

PubMed Central

Smith, Justin D.

2013-01-01

This article systematically reviews the research design and methodological characteristics of single-case experimental design (SCED) research published in peer-reviewed journals between 2000 and 2010. SCEDs provide researchers with a flexible and viable alternative to group designs with large sample sizes. However, methodological challenges have precluded widespread implementation and acceptance of the SCED as a viable complementary methodology to the predominant group design. This article includes a description of the research design, measurement, and analysis domains distinctive to the SCED; a discussion of the results within the framework of contemporary standards and guidelines in the field; and a presentation of updated benchmarks for key characteristics (e.g., baseline sampling, method of analysis), and overall, it provides researchers and reviewers with a resource for conducting and evaluating SCED research. The results of the systematic review of 409 studies suggest that recently published SCED research is largely in accordance with contemporary criteria for experimental quality. Analytic method emerged as an area of discord. Comparison of the findings of this review with historical estimates of the use of statistical analysis indicates an upward trend, but visual analysis remains the most common analytic method and also garners the most support amongst those entities providing SCED standards. Although consensus exists along key dimensions of single-case research design and researchers appear to be practicing within these parameters, there remains a need for further evaluation of assessment and sampling techniques and data analytic methods. PMID:22845874

Statistical Metamodeling and Sequential Design of Computer Experiments to Model Glyco-Altered Gating of Sodium Channels in Cardiac Myocytes.

PubMed

Du, Dongping; Yang, Hui; Ednie, Andrew R; Bennett, Eric S

2016-09-01

Glycan structures account for up to 35% of the mass of cardiac sodium ( Nav ) channels. To question whether and how reduced sialylation affects Nav activity and cardiac electrical signaling, we conducted a series of in vitro experiments on ventricular apex myocytes under two different glycosylation conditions, reduced protein sialylation (ST3Gal4(-/-)) and full glycosylation (control). Although aberrant electrical signaling is observed in reduced sialylation, realizing a better understanding of mechanistic details of pathological variations in INa and AP is difficult without performing in silico studies. However, computer model of Nav channels and cardiac myocytes involves greater levels of complexity, e.g., high-dimensional parameter space, nonlinear and nonconvex equations. Traditional linear and nonlinear optimization methods have encountered many difficulties for model calibration. This paper presents a new statistical metamodeling approach for efficient computer experiments and optimization of Nav models. First, we utilize a fractional factorial design to identify control variables from the large set of model parameters, thereby reducing the dimensionality of parametric space. Further, we develop the Gaussian process model as a surrogate of expensive and time-consuming computer models and then identify the next best design point that yields the maximal probability of improvement. This process iterates until convergence, and the performance is evaluated and validated with real-world experimental data. Experimental results show the proposed algorithm achieves superior performance in modeling the kinetics of Nav channels under a variety of glycosylation conditions. As a result, in silico models provide a better understanding of glyco-altered mechanistic details in state transitions and distributions of Nav channels. Notably, ST3Gal4(-/-) myocytes are shown to have higher probabilities accumulated in intermediate inactivation during the repolarization and yield a shorter refractory period than WTs. The proposed statistical design of computer experiments is generally extensible to many other disciplines that involve large-scale and computationally expensive models.

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.

Estimation of sample size and testing power (Part 4).

PubMed

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-01-01

Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.

Receptor arrays optimized for natural odor statistics.

PubMed

Zwicker, David; Murugan, Arvind; Brenner, Michael P

2016-05-17

Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.

Toughness and strength of nanocrystalline graphene

DOE PAGES

Shekhawat, Ashivni; Ritchie, Robert O.

2016-01-28

Pristine monocrystalline graphene is claimed to be the strongest material known with remarkable mechanical and electrical properties. However, graphene made with scalable fabrication techniques is polycrystalline and contains inherent nanoscale line and point defects—grain boundaries and grain-boundary triple junctions—that lead to significant statistical fluctuations in toughness and strength. These fluctuations become particularly pronounced for nanocrystalline graphene where the density of defects is high. Here we use large-scale simulation and continuum modelling to show that the statistical variation in toughness and strength can be understood with ‘weakest-link’ statistics. We develop the first statistical theory of toughness in polycrystalline graphene, and elucidatemore » the nanoscale origins of the grain-size dependence of its strength and toughness. Lastly, our results should lead to more reliable graphene device design, and provide a framework to interpret experimental results in a broad class of two-dimensional materials.« less

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Thermal and Pressure Characterization of a Wind Tunnel Force Balance Using the Single Vector System. Experimental Design and Analysis Approach to Model Pressure and Temperature Effects in Hypersonic Wind Tunnel Research

NASA Technical Reports Server (NTRS)

Lynn, Keith C.; Commo, Sean A.; Johnson, Thomas H.; Parker, Peter A,

2011-01-01

Wind tunnel research at NASA Langley Research Center s 31-inch Mach 10 hypersonic facility utilized a 5-component force balance, which provided a pressurized flow-thru capability to the test article. The goal of the research was to determine the interaction effects between the free-stream flow and the exit flow from the reaction control system on the Mars Science Laboratory aeroshell during planetary entry. In the wind tunnel, the balance was exposed to aerodynamic forces and moments, steady-state and transient thermal gradients, and various internal balance cavity pressures. Historically, these effects on force measurement accuracy have not been fully characterized due to limitations in the calibration apparatus. A statistically designed experiment was developed to adequately characterize the behavior of the balance over the expected wind tunnel operating ranges (forces/moments, temperatures, and pressures). The experimental design was based on a Taylor-series expansion in the seven factors for the mathematical models. Model inversion was required to calculate the aerodynamic forces and moments as a function of the strain-gage readings. Details regarding transducer on-board compensation techniques, experimental design development, mathematical modeling, and wind tunnel data reduction are included in this paper.

Polymeric behavior evaluation of PVP K30-poloxamer binary carrier for solid dispersed nisoldipine by experimental design.

PubMed

Kyaw Oo, May; Mandal, Uttam K; Chatterjee, Bappaditya

2017-02-01

High melting point polymeric carrier without plasticizer is unacceptable for solid dispersion (SD) by melting method. Combined polymer-plasticizer carrier significantly affects drug solubility and tableting property of SD. To evaluate and optimize the combined effect of a binary carrier consisting PVP K30 and poloxamer 188, on nisoldipine solubility and tensile strength of amorphous SD compact (SD compact ) by experimental design. SD of nisoldpine (SD nisol ) was prepared by melt mixing with different PVP K30 and poloxamer amount. A 3 2 factorial design was employed using nisoldipine solubility and tensile strength of SD compact as response variables. Statistical optimization by design expert software, and SD nisol characterization using ATR FTIR, DSC and microscopy were done. PVP K30:poloxamer, at a ratio of 3.73:6.63, was selected as the optimized combination of binary polymeric carrier resulting nisoldipine solubility of 115 μg/mL and tensile strength of 1.19 N/m 2 . PVP K30 had significant positive effect on both responses. Increase in poloxamer concentration after a certain level decreased nisoldipine solubility and tensile strength of SD compact . An optimized PVP K30-poloxamer binary composition for SD carrier was developed. Tensile strength of SD compact can be considered as a response for experimental design to optimize SD.

Performance mapping of the STM4-120 kinematic Stirling engine using a statistical design of experiments method

NASA Astrophysics Data System (ADS)

Powell, M. A.; Rawlinson, K. S.

A kinetic Stirling cycle engine, the Stirling Thermal Motors (STM) STM4-120, was tested at the Sandia National Laboratories Engine Test Facility (ETF) from March 1989-August 1992. Sandia is interested in determining this engine's potential for solar-thermal-electric applications. The last round of testing was conducted from July-August 1992 using Sandia-designed gas-fired heat pipe evaporators as the heat input system to the engine. The STM4-120 was performance mapped over a range of sodium vapor temperatures, cooling water temperatures, and cycle pressures. The resulting shaft power output levels ranged from 5-9 kW. The engine demonstrated high conversion efficiency (24-31%) even though the power output level was less than 40% of the rated output of 25 kW. The engine had been previously derated from 25 kW to 10 kW shaft power due to mechanical limitations that were identified by STM during parallel testing at their facility in Ann Arbor, MI. A statistical method was used to design the experiment, to choose the experimental points, and to generate correlation equations describing the engine performance given the operating parameters. The testing was truncated due to a failure of the heat pipe system caused by entrainment of liquid sodium in the condenser section of the heat pipes. Enough data was gathered to generate the correlations and to demonstrate the experimental technique. The correlation is accurate in the experimental space and is simple enough for use in hand calculations and spreadsheet-based system models. Use of this method can simplify the construction of accurate performance and economic models of systems in which the engine is a component. The purpose of this paper is to present the method used to design the experiments and to analyze the performance data.

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.

Comparative evaluation of guided tissue regeneration with use of collagen-based barrier freeze-dried dura mater allograft for mandibular class 2 furcation defects (a comparative controlled clinical study).

PubMed

Patel, Sandeep; Kubavat, Ajay; Ruparelia, Brijesh; Agarwal, Arvind; Panda, Anup

2012-01-01

The aim of periodontal surgery is complete regeneration. The present study was designed to evaluate and compare clinically soft tissue changes in form of probing pocket depth, gingival shrinkage, attachment level and hard tissue changes in form of horizontal and vertical bone level using resorbable membranes. Twelve subjects with bilateral class 2 furcation defects were selected. After initial phase one treatment, open debridement was performed in control site while freezedried dura mater allograft was used in experimental site. Soft and hard tissue parameters were registered intrasurgically. Nine months reentry ensured better understanding and evaluation of the final outcome of the study. Guided tissue regeneration is a predictable treatment modality for class 2 furcation defect. There was statistically significant reduction in pocket depth as compared to control (p < 0.01). There is statistically significant increase in periodontal attachment level within control and experimental sites showed better results (p < 0.01). For hard tissue parameter, significant defect fill resulted in experimental group, while in control group, less significant defect fill was found in horizontal direction and nonsignificant defect fill was found in vertical direction. The results showed statistically significant improvement in soft and hard tissue parameters and less gingival shrinkage in experimental sites compared to control site. The use of FDDMA in furcation defects helps us to achieve predictable results. This cross-linked collagen membrane has better handling properties and ease of procurement as well as economic viability making it a logical material to be used in regenerative surgeries.

Framework for the rapid optimization of soluble protein expression in Escherichia coli combining microscale experiments and statistical experimental design.

PubMed

Islam, R S; Tisi, D; Levy, M S; Lye, G J

2007-01-01

A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g.L-1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost.

Using experimental design modules for process characterization in manufacturing/materials processes laboratories

NASA Technical Reports Server (NTRS)

Ankenman, Bruce; Ermer, Donald; Clum, James A.

1994-01-01

Modules dealing with statistical experimental design (SED), process modeling and improvement, and response surface methods have been developed and tested in two laboratory courses. One course was a manufacturing processes course in Mechanical Engineering and the other course was a materials processing course in Materials Science and Engineering. Each module is used as an 'experiment' in the course with the intent that subsequent course experiments will use SED methods for analysis and interpretation of data. Evaluation of the modules' effectiveness has been done by both survey questionnaires and inclusion of the module methodology in course examination questions. Results of the evaluation have been very positive. Those evaluation results and details of the modules' content and implementation are presented. The modules represent an important component for updating laboratory instruction and to provide training in quality for improved engineering practice.

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

PubMed Central

Liu, Yiming; Huang, Nai-Lun; Zeng, Fufu; Lin, Fang-Ying

2014-01-01

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment. PMID:25032231

The in vivo wear resistance of 12 composite resins.

PubMed

Lang, B R; Bloem, T J; Powers, J M; Wang, R F

1992-09-01

The in vivo wear resistance of 12 composite resins were compared with an amalgam control using the Latin Square experimental design. Sixteen edentulous patients wearing specially designed complete dentures formed the experimental population. The Michigan Computer Graphics Measurement System was used to digitize the surface of the control and composite resin samples before and after 3-month test periods to obtain wear data. The 12 composite resins selected for this investigation based on their published composite classification types were seven fine particle composites, three blends, and two microfilled composite resins. The Latin Square experimental design was found to be valid with the factor of material being statistically different at the 5% level of significance. Wear was computed as volume loss (mm3/mm2), and all of the composites studied had more wear than the amalgam control (P = .001). After 3 months, the mean (error) of wear of the amalgam was 0.028 (0.006). Means (error) of wear for the 12 composites were ranked from most to least wear by mean wear volume loss. The absence of any relationship between mean wear volume loss and the volume percentage filler was confirmed by the correlation coefficient r = -0.158.

Effect of music care on depression and behavioral problems in elderly people with dementia in Taiwan: a quasi-experimental, longitudinal study.

PubMed

Wang, Su-Chin; Yu, Ching-Len; Chang, Su-Hsien

2017-02-01

The purpose was to examine the effectiveness of music care on cognitive function, depression, and behavioral problems among elderly people with dementia in long-term care facilities in Taiwan. The study had a quasi-experimental, longitudinal research design and used two groups of subjects. Subjects were not randomly assigned to experimental group (n = 90) or comparison group (n = 56). Based on Bandura's social cognition theory, subjects in the experimental group received Kagayashiki music care (KMC) twice per week for 24 weeks. Subjects in the comparison group were provided with activities as usual. Results found, using the control score of the Clifton Assessment Procedures for the Elderly Behavior Rating Scale (baseline) and time of attending KMC activities as a covariate, the two groups of subjects had statistically significant differences in the mini-mental state examination (MMSE). Results also showed that, using the control score of the Cornell Scale for Depression in Dementia (baseline) and MMSE (baseline) as a covariate, the two groups of subjects had statistically significant differences in the Clifton Assessment Procedures for the Elderly Behavior Rating Scale. These findings provide information for staff caregivers in long-term care facilities to develop a non-invasive care model for elderly people with dementia to deal with depression, anxiety, and behavioral problems.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics

NASA Astrophysics Data System (ADS)

El Koussaifi, R.; Tikan, A.; Toffoli, A.; Randoux, S.; Suret, P.; Onorato, M.

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics.

PubMed

El Koussaifi, R; Tikan, A; Toffoli, A; Randoux, S; Suret, P; Onorato, M

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Implementation and outcome evaluation of high-fidelity simulation scenarios to integrate cognitive and psychomotor skills for Korean nursing students.

PubMed

Ahn, Heejung; Kim, Hyun-Young

2015-05-01

This study is involved in designing high-fidelity simulations reflecting the Korean nursing education environment. In addition, it evaluated the simulations by nursing students' learning outcomes and perceptions of the simulation design features. A quantitative design was used in two separate phases. For the first phase, five nursing experts participated in verifying the appropriateness of two simulation scenarios that reflected the intended learning objectives. For the second phase, 69 nursing students in the third year of a bachelor's degree at a nursing school participated in evaluating the simulations and were randomized according to their previous course grades. The first phase verified the two simulation scenarios using a questionnaire. The second phase evaluated students' perceptions of the simulation design, self-confidence, and critical thinking skills using a quasi-experimental post-test design. ANCOVA was used to compare the experimental and control groups, and correlation coefficient analysis was used to determine the correlation among them. We created 2 simulation scenarios to integrate cognitive and psychomotor skills according to the learning objectives and clinical environment in Korea. The experimental group had significantly higher scores on self-confidence in the first scenario. The positive correlations between perceptions of the simulation design features, self-confidence, and critical thinking skill scores were statistically significant. Students with a more positive perception of the design features of the simulations had better learning outcomes. Based on this result, simulations need to be designed and implemented with more differentiation in order to be perceived more appropriately by students. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data Assimilation - Advances and Applications

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

Williams, Brian J.

2014-07-30

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batchmore » sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.« less

Optimization of β-carotene loaded solid lipid nanoparticles preparation using a high shear homogenization technique

NASA Astrophysics Data System (ADS)

Triplett, Michael D.; Rathman, James F.

2009-04-01

Using statistical experimental design methodologies, the solid lipid nanoparticle design space was found to be more robust than previously shown in literature. Formulation and high shear homogenization process effects on solid lipid nanoparticle size distribution, stability, drug loading, and drug release have been investigated. Experimentation indicated stearic acid as the optimal lipid, sodium taurocholate as the optimal cosurfactant, an optimum lecithin to sodium taurocholate ratio of 3:1, and an inverse relationship between mixing time and speed and nanoparticle size and polydispersity. Having defined the base solid lipid nanoparticle system, β-carotene was incorporated into stearic acid nanoparticles to investigate the effects of introducing a drug into the base solid lipid nanoparticle system. The presence of β-carotene produced a significant effect on the optimal formulation and process conditions, but the design space was found to be robust enough to accommodate the drug. β-Carotene entrapment efficiency averaged 40%. β-Carotene was retained in the nanoparticles for 1 month. As demonstrated herein, solid lipid nanoparticle technology can be sufficiently robust from a design standpoint to become commercially viable.

Supplementation with Silk Amino Acids improves physiological parameters defining stamina in elite fin-swimmers.

PubMed

Zubrzycki, Igor Z; Ossowski, Zbigniew; Przybylski, Stanislaw; Wiacek, Magdalena; Clarke, Anna; Trabka, Bartosz

2014-01-01

Previous animal study has shown that supplementation with silk amino acid hydrolysate (SAA) increases stamina in mice. The presented study was the first formal evaluation of the influence of SAA supplementation on parameters defining physiological fitness level in humans. It was a randomized controlled trial with a parallel-group design on elite male fin-swimmers. The experimental group was supplemented with 500 mg of SAA per kg of body mass, dissolved in 250 ml of a Carborade Drink®; the control group with Carborade Drink® alone; 3 times a day, 30 minutes prior to the training session. Changes discerned in the experimental group were more pronounced than those observed in the control group. For example, the change in the serum lactic acid concentration observed in the experimental group was sevenfold less than in the control group [21.8 vs. -3.7 L% for the control and experimental groups, respectively]. An analysis of a lactate profile as a function of a maximal swimming velocity exposed a statistically significant positive shift in the swimming velocity of 0.05 m/s, at the lactate concentration of 4 mmol/L in the experimental group. There was also a positive, although statistically insignificant, increase of 2.6 L% in serum testosterone levels in the experimental group. This study showed that a 12-day SAA supplementation combined with an extensive and rigorous training schedule was sufficient to increase an aerobic stamina. However, this phenomenon was associated with an augmented level of muscular damage (an increased level of creatine phosphokinase in the experimental group).

Robust parameter design for automatically controlled systems and nanostructure synthesis

NASA Astrophysics Data System (ADS)

Dasgupta, Tirthankar

2007-12-01

This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.

Genetics instruction with history of science: Nature of science learning

NASA Astrophysics Data System (ADS)

Kim, Sun Young

2007-12-01

This study explored the effect of history of genetics in teaching genetics and learning the nature of science (NOS). A quasi-experimental control group research design with pretests, posttests, and delayed posttests was used, combining qualitative data and quantitative data. Two classes which consisted of tenth grade biology students participated in this study. The present study involved two instructional interventions, Best Practice Instruction with History of Genetics (BPIw/HG) and Best Practice Instruction (BPI). The experimental group received BPIw/HG utilizing various historical materials from the history of genetics, while the control group was not introduced to historical materials. Scientific Attitude Inventory II, Genetics Terms' Definitions with Concept Mapping (GTDCM), NOS Terms' Definitions with Concept Mapping (NTDCM), and View of Nature of Science (VNOS-C) were used to investigate students' scientific attitude inventory, and their understanding of genetics as well as the NOS. The results showed that students' scientific attitude inventory, and their understanding of genetics and the NOS were not statistically significantly different in the pretest (p>.05). After the intervention, the experimental group of students who received BPIw/HG demonstrated better understanding of the NOS. NTDCM results showed that the experimental group was better in defining the NOS terms and constructing a concept map ( p<.01). In addition, the experimental group retained their understanding of the NOS two-months after the completion of the intervention, showing no statistically significant difference between the posttest and the delayed posttest of NTDCM (p>.05). Further, VNOS-C data indicated that a greater percentage of the experimental group than the control group improved their understanding of the NOS. However, the two groups' understanding of genetics concepts did not show any statistically significant difference in the pretest, the posttest, and the delayed posttest (p>.05). This result implicated that allocating classroom time in introducing history of science neither helped nor hindered learning science content.

Organic biowastes blend selection for composting industrial eggshell by-product: experimental and statistical mixture design.

PubMed

Soares, Micaela A R; Andrade, Sandra R; Martins, Rui C; Quina, Margarida J; Quinta-Ferreira, Rosa M

2012-01-01

Composting is one of the technologies recommended for pre-treating industrial eggshells (ES) before its application in soils, for calcium recycling. However, due to the high inorganic content of ES, a mixture of biodegradable materials is required to assure a successful procedure. In this study, an adequate organic blend composition containing potato peel (PP), grass clippings (GC) and wheat straw (WS) was determined by applying the simplex-centroid mixture design method to achieve a desired moisture content, carbon: nitrogen ratio and free air space for effective composting of ES. A blend of 56% PP, 37% GC and 7% WS was selected and tested in a self heating reactor, where 10% (w/w) of ES was incorporated. After 29 days of reactor operation, a dry matter reduction of 46% was achieved and thermophilic temperatures were maintained during 15 days, indicating that the blend selected by statistical approach was adequate for composting of ES.

Application of Plackett-Burman Experimental Design for Lipase Production by Aspergillus niger Using Shea Butter Cake

PubMed Central

Salihu, Aliyu; Bala, Muntari; Bala, Shuaibu M.

2013-01-01

Plackett-Burman design was used to efficiently select important medium components affecting the lipase production by Aspergillus niger using shea butter cake as the main substrate. Out of the eleven medium components screened, six comprising of sucrose, (NH4)2SO4, Na2HPO4, MgSO4, Tween-80, and olive oil were found to contribute positively to the overall lipase production with a maximum production of 3.35 U/g. Influence of tween-80 on lipase production was investigated, and 1.0% (v/w) of tween-80 resulted in maximum lipase production of 6.10 U/g. Thus, the statistical approach employed in this study allows for rapid identification of important medium parameters affecting the lipase production, and further statistical optimization of medium and process parameters can be explored using response surface methodology. PMID:25937979

Application of Plackett-Burman Experimental Design for Lipase Production by Aspergillus niger Using Shea Butter Cake.

PubMed

Salihu, Aliyu; Bala, Muntari; Bala, Shuaibu M

2013-01-01

Plackett-Burman design was used to efficiently select important medium components affecting the lipase production by Aspergillus niger using shea butter cake as the main substrate. Out of the eleven medium components screened, six comprising of sucrose, (NH4)2SO4, Na2HPO4, MgSO4, Tween-80, and olive oil were found to contribute positively to the overall lipase production with a maximum production of 3.35 U/g. Influence of tween-80 on lipase production was investigated, and 1.0% (v/w) of tween-80 resulted in maximum lipase production of 6.10 U/g. Thus, the statistical approach employed in this study allows for rapid identification of important medium parameters affecting the lipase production, and further statistical optimization of medium and process parameters can be explored using response surface methodology.

Evaluation of undergraduate nursing students' attitudes towards statistics courses, before and after a course in applied statistics.

PubMed

Hagen, Brad; Awosoga, Olu; Kellett, Peter; Dei, Samuel Ofori

2013-09-01

Undergraduate nursing students must often take a course in statistics, yet there is scant research to inform teaching pedagogy. The objectives of this study were to assess nursing students' overall attitudes towards statistics courses - including (among other things) overall fear and anxiety, preferred learning and teaching styles, and the perceived utility and benefit of taking a statistics course - before and after taking a mandatory course in applied statistics. The authors used a pre-experimental research design (a one-group pre-test/post-test research design), by administering a survey to nursing students at the beginning and end of the course. The study was conducted at a University in Western Canada that offers an undergraduate Bachelor of Nursing degree. Participants included 104 nursing students, in the third year of a four-year nursing program, taking a course in statistics. Although students only reported moderate anxiety towards statistics, student anxiety about statistics had dropped by approximately 40% by the end of the course. Students also reported a considerable and positive change in their attitudes towards learning in groups by the end of the course, a potential reflection of the team-based learning that was used. Students identified preferred learning and teaching approaches, including the use of real-life examples, visual teaching aids, clear explanations, timely feedback, and a well-paced course. Students also identified preferred instructor characteristics, such as patience, approachability, in-depth knowledge of statistics, and a sense of humor. Unfortunately, students only indicated moderate agreement with the idea that statistics would be useful and relevant to their careers, even by the end of the course. Our findings validate anecdotal reports on statistics teaching pedagogy, although more research is clearly needed, particularly on how to increase students' perceptions of the benefit and utility of statistics courses for their nursing careers. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Climate Considerations Of The Electricity Supply Systems In Industries

NASA Astrophysics Data System (ADS)

Asset, Khabdullin; Zauresh, Khabdullina

2014-12-01

The study is focused on analysis of climate considerations of electricity supply systems in a pellet industry. The developed analysis model consists of two modules: statistical data of active power losses evaluation module and climate aspects evaluation module. The statistical data module is presented as a universal mathematical model of electrical systems and components of industrial load. It forms a basis for detailed accounting of power loss from the voltage levels. On the basis of the universal model, a set of programs is designed to perform the calculation and experimental research. It helps to obtain the statistical characteristics of the power losses and loads of the electricity supply systems and to define the nature of changes in these characteristics. Within the module, several methods and algorithms for calculating parameters of equivalent circuits of low- and high-voltage ADC and SD with a massive smooth rotor with laminated poles are developed. The climate aspects module includes an analysis of the experimental data of power supply system in pellet production. It allows identification of GHG emission reduction parameters: operation hours, type of electrical motors, values of load factor and deviation of standard value of voltage.

Statistical and sampling issues when using multiple particle tracking

NASA Astrophysics Data System (ADS)

Savin, Thierry; Doyle, Patrick S.

2007-08-01

Video microscopy can be used to simultaneously track several microparticles embedded in a complex material. The trajectories are used to extract a sample of displacements at random locations in the material. From this sample, averaged quantities characterizing the dynamics of the probes are calculated to evaluate structural and/or mechanical properties of the assessed material. However, the sampling of measured displacements in heterogeneous systems is singular because the volume of observation with video microscopy is finite. By carefully characterizing the sampling design in the experimental output of the multiple particle tracking technique, we derive estimators for the mean and variance of the probes’ dynamics that are independent of the peculiar statistical characteristics. We expose stringent tests of these estimators using simulated and experimental complex systems with a known heterogeneous structure. Up to a certain fundamental limitation, which we characterize through a material degree of sampling by the embedded probe tracking, these estimators can be applied to quantify the heterogeneity of a material, providing an original and intelligible kind of information on complex fluid properties. More generally, we show that the precise assessment of the statistics in the multiple particle tracking output sample of observations is essential in order to provide accurate unbiased measurements.

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).

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.

PhenStat | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

PhenStat is a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations from model organisms developed for the International Mouse Phenotyping Consortium (IMPC at www.mousephenotype.org ). The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation and is being adapted for analysis with PDX mouse strains.

Utilizing the Zero-One Linear Programming Constraints to Draw Multiple Sets of Matched Samples from a Non-Treatment Population as Control Groups for the Quasi-Experimental Design

ERIC Educational Resources Information Center

Li, Yuan H.; Yang, Yu N.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

The statistical technique, "Zero-One Linear Programming," that has successfully been used to create multiple tests with similar characteristics (e.g., item difficulties, test information and test specifications) in the area of educational measurement, was deemed to be a suitable method for creating multiple sets of matched samples to be…

Using the Multiple-Matched-Sample and Statistical Controls to Examine the Effects of Magnet School Programs on the Reading and Mathematics Performance of Students

ERIC Educational Resources Information Center

Yang, Yu N.; Li, Yuan H.; Tompkins, Leroy J.; Modarresi, Shahpar

2005-01-01

This summative evaluation of magnet programs employed a quasi-experimental design to investigate whether or not students enrolled in magnet programs gained any achievement advantage over students who were not enrolled in a magnet program. Researchers used Zero-One Linear Programming to draw multiple sets of matched samples from the non-magnet…

Aerial Refueling Simulator Validation Using Operational Experimentation and Response Surface Methods with Time Series Responses

DTIC Science & Technology

2013-03-21

10 2.3 Time Series Response Data ................................................................................. 12 2.4 Comparison of Response...to 12 evaluating the efficiency of the parameter estimates. In the past, the most popular form of response surface design used the D-optimality...as well. A model can refer to almost anything in math , statistics, or computer science. It can be any “physical, mathematical, or logical

Design standards for experimental and field studies to evaluate diagnostic accuracy of tests for infectious diseases in aquatic animals.

PubMed

Laurin, E; Thakur, K K; Gardner, I A; Hick, P; Moody, N J G; Crane, M S J; Ernst, I

2018-05-01

Design and reporting quality of diagnostic accuracy studies (DAS) are important metrics for assessing utility of tests used in animal and human health. Following standards for designing DAS will assist in appropriate test selection for specific testing purposes and minimize the risk of reporting biased sensitivity and specificity estimates. To examine the benefits of recommending standards, design information from published DAS literature was assessed for 10 finfish, seven mollusc, nine crustacean and two amphibian diseases listed in the 2017 OIE Manual of Diagnostic Tests for Aquatic Animals. Of the 56 DAS identified, 41 were based on field testing, eight on experimental challenge studies and seven on both. Also, we adapted human and terrestrial-animal standards and guidelines for DAS structure for use in aquatic animal diagnostic research. Through this process, we identified and addressed important metrics for consideration at the design phase: study purpose, targeted disease state, selection of appropriate samples and specimens, laboratory analytical methods, statistical methods and data interpretation. These recommended design standards for DAS are presented as a checklist including risk-of-failure points and actions to mitigate bias at each critical step. Adherence to standards when designing DAS will also facilitate future systematic review and meta-analyses of DAS research literature. © 2018 John Wiley & Sons Ltd.

Improvement in Saccharification Yield of Mixed Rumen Enzymes by Identification of Recalcitrant Cell Wall Constituents Using Enzyme Fingerprinting.

PubMed

Badhan, Ajay; Wang, Yu-Xi; Gruninger, Robert; Patton, Donald; Powlowski, Justin; Tsang, Adrian; McAllister, Tim A

2015-01-01

Identification of recalcitrant factors that limit digestion of forages and the development of enzymatic approaches that improve hydrolysis could play a key role in improving the efficiency of meat and milk production in ruminants. Enzyme fingerprinting of barley silage fed to heifers and total tract indigestible fibre residue (TIFR) collected from feces was used to identify cell wall components resistant to total tract digestion. Enzyme fingerprinting results identified acetyl xylan esterases as key to the enhanced ruminal digestion. FTIR analysis also suggested cross-link cell wall polymers as principal components of indigested fiber residues in feces. Based on structural information from enzymatic fingerprinting and FTIR, enzyme pretreatment to enhance glucose yield from barley straw and alfalfa hay upon exposure to mixed rumen-enzymes was developed. Prehydrolysis effects of recombinant fungal fibrolytic hydrolases were analyzed using microassay in combination with statistical experimental design. Recombinant hemicellulases and auxiliary enzymes initiated degradation of plant structural polysaccharides upon application and improved the in vitro saccharification of alfalfa and barley straw by mixed rumen enzymes. The validation results showed that microassay in combination with statistical experimental design can be successfully used to predict effective enzyme pretreatments that can enhance plant cell wall digestion by mixed rumen enzymes.

A quasi-experimental study on the effects of instrument assisted soft tissue mobilization on mechanosensitive neurons.

PubMed

Ge, Weiqing; Roth, Emily; Sansone, Alyssa

2017-04-01

[Purpose] Instrument Assisted Soft Tissue Mobilization (IASTM) is a form of manual therapy. Despite its growing popularity and an increasing number of patients receiving IASTM each year, there is a lack of high-level evidence to elucidate its therapeutic mechanisms and to support its clinical applications. The purpose of this research project was to determine the effects of IASTM on activities of mechanosensitive neurons in skin. [Subjects and Methods] Twenty-three subjects, 9 females and 14 males, mean age 25.7 (SD 6.4) years old were recruited through a convenience sampling on the university campus. The study design was a quasi-experimental study using single group pretest-posttest design. The activities of mechanosensitive neurons were measured before and after the application of IASTM. [Results] The mean 2-point discrimination was 40.2 (SD 9.4) mm before IASTM and increased to 44.9 (SD 12.0) mm after IASTM. The increase was statistically significant pre and post IASTM. The mean pain threshold was 18.2 (SD 6.6) lb and increased slightly to 18.7 (SD 6.8) lb after IASTM; however, no statistical significance was found pre and post IASTM. [Conclusion] The data indicates that IASTM changes the neural activities in 2-point discrimination but not in pain threshold.

Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.

PubMed

Metwally, Abdelkader A; Hathout, Rania M

2015-08-03

We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).

Additives and salts for dye-sensitized solar cells electrolytes: what is the best choice?

NASA Astrophysics Data System (ADS)

Bella, Federico; Sacco, Adriano; Pugliese, Diego; Laurenti, Marco; Bianco, Stefano

2014-10-01

A multivariate chemometric approach is proposed for the first time for performance optimization of I-/I3- liquid electrolytes for dye-sensitized solar cells (DSSCs). Over the years the system composed by iodide/triiodide redox shuttle dissolved in organic solvent has been enriched with the addition of different specific cations and chemical compounds to improve the photoelectrochemical behavior of the cell. However, usually such additives act favorably with respect to some of the cell parameters and negatively to others. Moreover, the combined action of different compounds often yields contradictory results, and from the literature it is not possible to identify an optimal recipe. We report here a systematic work, based on a multivariate experimental design, to statistically and quantitatively evaluate the effect of different additives on the photovoltaic performances of the device. The effect of cation size in iodine salts, the iodine/iodide ratio in the electrolyte and the effect of type and concentration of additives are mutually evaluated by means of a Design of Experiment (DoE) approach. Through this statistical method, the optimization of the overall parameters is demonstrated with a limited number of experimental trials. A 25% improvement on the photovoltaic conversion efficiency compared with that obtained with a commercial electrolyte is demonstrated.

Response Surface Modeling of Combined-Cycle Propulsion Components using Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.

2002-01-01

Three examples of response surface modeling with CFD are presented for combined cycle propulsion components. The examples include a mixed-compression-inlet during hypersonic flight, a hydrogen-fueled scramjet combustor during hypersonic flight, and a ducted-rocket nozzle during all-rocket flight. Three different experimental strategies were examined, including full factorial, fractionated central-composite, and D-optimal with embedded Plackett-Burman designs. The response variables have been confined to integral data extracted from multidimensional CFD results. Careful attention to uncertainty assessment and modeling bias has been addressed. The importance of automating experimental setup and effectively communicating statistical results are emphasized.

Ex-situ bioremediation of crude oil in soil, a comparative kinetic analysis.

PubMed

Mohajeri, Leila; Aziz, Hamidi Abdul; Isa, Mohamed Hasnain; Zahed, Mohammad Ali; Mohajeri, Soraya

2010-07-01

Weathered crude oil (WCO) removals in shoreline sediment samples were monitored for 60 days in bioremediation experimentation. Experimental modeling was carried out using statistical design of experiments. At optimum conditions maximum of 83.13, 78.06 and 69.92% WCO removals were observed for 2, 16 and 30 g/kg initial oil concentrations, respectively. Significant variations in the crude oil degradation pattern were observed with respect to oil, nutrient and microorganism contents. Crude oil bioremediation were successfully described by a first-order kinetic model. The study indicated that the rate of hydrocarbon biodegradation increased with decrease of crude oil concentrations.

[Evaluation of a medication self-management education program for elders with hypertension living in the community].

PubMed

Lee, Jong Kyung

2013-04-01

The purpose of this study was to examine the effect of a medication self-management education program on medication awareness, communication with health care provider, medication misuse behavior, and blood pressure in elders with hypertension. The research design for this study was a non-equivalent control group quasi-experimental design. Participants were 23 elders for the control group, and 26 elders for the experimental group. The experimental group participated in the medication self-management education program which included the following, verbal education, 1:1 consultation, practice in medication self-management, and discussion over 5 sessions. Data were analyzed using the SPSS 18.0 program. There were statistically significant differences between the experimental and control group for medication awareness, medication misuse behavior, and communication with health care providers. However, no significant difference was found between the two groups for blood pressure. The results indicate that the education program is effective in improving medication awareness and communication with health care providers and in decreasing medication misuse behavior. Therefore, it is recommended that this education program be used as an effective intervention for improving medication self-management for elders with hypertension.

The Effectiveness of the Harm Reduction Group Therapy Based on Bandura's Self-Efficacy Theory on Risky Behaviors of Drug-Dependent Sex Worker Women.

PubMed

Rabani-Bavojdan, Marjan; Rabani-Bavojdan, Mozhgan; Rajabizadeh, Ghodratollah; Kaviani, Nahid; Bahramnejad, Ali; Ghaffari, Zohreh; Shafiei-Bafti, Mehdi

2017-07-01

The aim of this study was to investigate the effectiveness of the harm reduction group therapy based on Bandura's self-efficacy theory on risky behaviors of sex workers in Kerman, Iran. A quasi-experimental two-group design (a random selection with pre-test and post-test) was used. A risky behaviors questionnaire was used to collect. The sample was selected among sex workers referring to drop-in centers in Kerman. Subjects were allocated to two groups and were randomly classified into two experimental and control groups. The sample group consisted of 56 subjects. The experimental design was carried out during 12 sessions, and the post-test was performed one month and two weeks after the completion of the sessions. The results were analyzed statistically. By reducing harm based on Bandura's self-efficacy theory, the risky behaviors of the experimental group, including injection behavior, sexual behavior, violence, and damage to the skin, were significantly reduced in the pre-test compared to the post-test (P < 0.010). The harm reduction group therapy based on Bandura's self-efficacy theory can reduce the risky behaviors of sex workers.

The use of clinical trials in comparative effectiveness research on mental health

PubMed Central

Blanco, Carlos; Rafful, Claudia; Olfson, Mark

2013-01-01

Objectives A large body of research on comparative effectiveness research (CER) focuses on the use of observational and quasi-experimental approaches. We sought to examine the use of clinical trials as a tool for CER, particularly in mental health. Study Design and Setting Examination of three ongoing randomized clinical trials in psychiatry that address issues which would pose difficulties for non-experimental CER methods. Results Existing statistical approaches to non-experimental data appear insufficient to compensate for biases that may arise when the pattern of missing data cannot be properly modeled such as when there are no standards for treatment, when affected populations have limited access to treatment, or when there are high rates of treatment dropout. Conclusions Clinical trials should retain an important role in CER, particularly in cases of high disorder prevalence, large expected effect sizes, difficult to reach populations or when examining sequential treatments or stepped-care algorithms. Progress in CER in mental health will require careful consideration of appropriate selection between clinical trials and non-experimental designs and on allocation of research resources to optimally inform key treatment decisions for each individual patient. PMID:23849150

The impact of L5 dorsal root ganglion degeneration and Adamkiewicz artery vasospasm on descending colon dilatation following spinal subarachnoid hemorrhage: An experimental study; first report

PubMed Central

Ozturk, Cengiz; Kanat, Ayhan; Aydin, Mehmet Dumlu; Yolas, Coskun; Kabalar, Mehmet Esref; Gundogdu, Betul; Duman, Aslihan; Kanat, Ilyas Ferit; Gundogdu, Cemal

2015-01-01

Context: Somato-sensitive innervation of bowels are maintained by lower segments of spinal cord and the blood supply of the lower spinal cord is heavily dependent on Adamkiewicz artery. Although bowel problems are sometimes seen in subarachnoid hemorrhage neither Adamkiewicz artery spasm nor spinal cord ischemia has not been elucidated as a cause of bowel dilatation so far. Aims: The goal of this study was to study the effects Adamkiewicz artery (AKA) vasospasm in lumbar subarachnoid hemorrhage (SAH) on bowel dilatation severity. Settings and Design: An experimental rabbit study. Materials and Methods: The study was conducted on 25 rabbits, which were randomly divided into three groups: Spinal SAH (N = 13), serum saline (SS) (SS; N = 7) and control (N = 5) groups. Experimental spinal SAH was performed. After 21 days, volume values of descending parts of large bowels and degenerated neuron density of L5DRG were analyzed. Statistical Analysis Used: Statistical analysis was performed using the PASW Statistics 18.0 for Windows (SPSS Inc., Chicago, Illinois). Two-tailed t-test and Mann-Whitney U-tests were used. The statistical significance was set at P < 0.05. Results: The mean volume of imaginary descending colons was estimated as 93 ± 12 cm3 in the control group and 121 ± 26 cm3 in the SS group and 176 ± 49 cm3 in SAH group. Volume augmentations of the descending colons and degenerated neuron density L5DRG were significantly different between the SAH and other two groups (P < 0.05). Conclusion: An inverse relationship between the living neuronal density of the L5DRG and the volume of imaginary descending colon values was occurred. Our findings will aid in the planning of future experimental studies and determining the clinical relevance on such studies. PMID:25972712

A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis.

PubMed

Holgado-Tello, Fco P; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A

2016-01-01

The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity.

A Simulation Study of Threats to Validity in Quasi-Experimental Designs: Interrelationship between Design, Measurement, and Analysis

PubMed Central

Holgado-Tello, Fco. P.; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana; Pérez-Gil, José A.

2016-01-01

The Campbellian tradition provides a conceptual framework to assess threats to validity. On the other hand, different models of causal analysis have been developed to control estimation biases in different research designs. However, the link between design features, measurement issues, and concrete impact estimation analyses is weak. In order to provide an empirical solution to this problem, we use Structural Equation Modeling (SEM) as a first approximation to operationalize the analytical implications of threats to validity in quasi-experimental designs. Based on the analogies established between the Classical Test Theory (CTT) and causal analysis, we describe an empirical study based on SEM in which range restriction and statistical power have been simulated in two different models: (1) A multistate model in the control condition (pre-test); and (2) A single-trait-multistate model in the control condition (post-test), adding a new mediator latent exogenous (independent) variable that represents a threat to validity. Results show, empirically, how the differences between both the models could be partially or totally attributed to these threats. Therefore, SEM provides a useful tool to analyze the influence of potential threats to validity. PMID:27378991

Assessing the performance of sewer rehabilitation on the reduction of infiltration and inflow.

PubMed

Staufer, P; Scheidegger, A; Rieckermann, J

2012-10-15

Inflow and Infiltration (I/I) into sewer systems is generally unwanted, because, among other things, it decreases the performance of wastewater treatment plants and increases combined sewage overflows. As sewer rehabilitation to reduce I/I is very expensive, water managers not only need methods to accurately measure I/I, but also they need sound approaches to assess the actual performance of implemented rehabilitation measures. However, such performance assessment is rarely performed. On the one hand, it is challenging to adequately take into account the variability of influential factors, such as hydro-meteorological conditions. On the other hand, it is currently not clear how experimental data can indeed support robust evidence for reduced I/I. In this paper, we therefore statistically assess the performance of rehabilitation measures to reduce I/I. This is possible by using observations in a suitable reference catchment as a control group and assessing the significance of the observed effect by regression analysis, which is well established in other disciplines. We successfully demonstrate the usefulness of the approach in a case study, where rehabilitation reduced groundwater infiltration by 23.9%. A reduction of stormwater inflow of 35.7%, however, was not statistically significant. Investigations into the experimental design of monitoring campaigns confirmed that the variability of the data as well as the number of observations collected before the rehabilitation impact the detection limit of the effect. This implies that it is difficult to improve the data quality after the rehabilitation has been implemented. Therefore, future practical applications should consider a careful experimental design. Further developments could employ more sophisticated monitoring methods, such as stable environmental isotopes, to directly observe the individual infiltration components. In addition, water managers should develop strategies to effectively communicate statistically not significant I/I reduction ratios to decision makers. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems

PubMed Central

Junker, Astrid; Muraya, Moses M.; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Klukas, Christian; Melchinger, Albrecht E.; Meyer, Rhonda C.; Riewe, David; Altmann, Thomas

2015-01-01

Detailed and standardized protocols for plant cultivation in environmentally controlled conditions are an essential prerequisite to conduct reproducible experiments with precisely defined treatments. Setting up appropriate and well defined experimental procedures is thus crucial for the generation of solid evidence and indispensable for successful plant research. Non-invasive and high throughput (HT) phenotyping technologies offer the opportunity to monitor and quantify performance dynamics of several hundreds of plants at a time. Compared to small scale plant cultivations, HT systems have much higher demands, from a conceptual and a logistic point of view, on experimental design, as well as the actual plant cultivation conditions, and the image analysis and statistical methods for data evaluation. Furthermore, cultivation conditions need to be designed that elicit plant performance characteristics corresponding to those under natural conditions. This manuscript describes critical steps in the optimization of procedures for HT plant phenotyping systems. Starting with the model plant Arabidopsis, HT-compatible methods were tested, and optimized with regard to growth substrate, soil coverage, watering regime, experimental design (considering environmental inhomogeneities) in automated plant cultivation and imaging systems. As revealed by metabolite profiling, plant movement did not affect the plants' physiological status. Based on these results, procedures for maize HT cultivation and monitoring were established. Variation of maize vegetative growth in the HT phenotyping system did match well with that observed in the field. The presented results outline important issues to be considered in the design of HT phenotyping experiments for model and crop plants. It thereby provides guidelines for the setup of HT experimental procedures, which are required for the generation of reliable and reproducible data of phenotypic variation for a broad range of applications. PMID:25653655

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

NASA Technical Reports Server (NTRS)

Hanson, John M.; Beard, Bernard B.

2010-01-01

This paper is focused on applying Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically the verification must show that requirement "x" is met for at least "y" % of cases, with, say, 10% consumer risk or 90% confidence. Two particular aspects of making these runs for requirements verification will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase but that will be known for each assembled vehicle (can be used to determine the payload capability and overall behavior of that vehicle), other items that become known before or on flight day (can be used for flight day trajectory design and go/no go decision), and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met or not and enables the user to determine how many Monte Carlo samples are required. Order statistics is not new, but may not be known in general to the GN&C community. The methods also apply to determining the design values of parameters of interest in driving the vehicle design. The paper briefly discusses when it is desirable to fit a distribution to the experimental Monte Carlo results rather than using order statistics.

Empirical Tryout of a New Statistic for Detecting Temporally Inconsistent Responders.

PubMed

Kerry, Matthew J

2018-01-01

Statistical screening of self-report data is often advised to support the quality of analyzed responses - For example, reduction of insufficient effort responding (IER). One recently introduced index based on Mahalanobis's D for detecting outliers in cross-sectional designs replaces centered scores with difference scores between repeated-measure items: Termed person temporal consistency ( D 2 ptc ). Although the adapted D 2 ptc index demonstrated usefulness in simulation datasets, it has not been applied to empirical data. The current study addresses D 2 ptc 's low uptake by critically appraising its performance across three empirical applications. Independent samples were selected to represent a range of scenarios commonly encountered by organizational researchers. First, in Sample 1, a repeat-measure of future time perspective (FTP) inexperienced working adults (age >40-years; n = 620) indicated that temporal inconsistency was significantly related to respondent age and item reverse-scoring. Second, in repeat-measure of team efficacy aggregations, D 2 ptc successfully detected team-level inconsistency across repeat-performance cycles. Thirdly, the usefulness of the D 2 ptc was examined in an experimental study dataset of subjective life expectancy indicated significantly more stable responding in experimental conditions compared to controls. The empirical findings support D 2 ptc 's flexible and useful application to distinct study designs. Discussion centers on current limitations and further extensions that may be of value to psychologists screening self-report data for strengthening response quality and meaningfulness of inferences from repeated-measures self-reports. Taken together, the findings support the usefulness of the newly devised statistic for detecting IER and other extreme response patterns.

An experimental evaluation of the Sternberg task as a workload metric for helicopter Flight Handling Qualities (FHQ) research

NASA Technical Reports Server (NTRS)

Hemingway, J. C.

1984-01-01

The objective was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopters engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny.

PubMed

Urrutia, Eugene; Chen, Hao; Zhou, Zilu; Zhang, Nancy R; Jiang, Yuchao

2018-06-15

Copy number variation is an important and abundant source of variation in the human genome, which has been associated with a number of diseases, especially cancer. Massively parallel next-generation sequencing allows copy number profiling with fine resolution. Such efforts, however, have met with mixed successes, with setbacks arising partly from the lack of reliable analytical methods to meet the diverse and unique challenges arising from the myriad experimental designs and study goals in genetic studies. In cancer genomics, detection of somatic copy number changes and profiling of allele-specific copy number (ASCN) are complicated by experimental biases and artifacts as well as normal cell contamination and cancer subclone admixture. Furthermore, careful statistical modeling is warranted to reconstruct tumor phylogeny by both somatic ASCN changes and single nucleotide variants. Here we describe a flexible computational pipeline, MARATHON, which integrates multiple related statistical software for copy number profiling and downstream analyses in disease genetic studies. MARATHON is publicly available at https://github.com/yuchaojiang/MARATHON. Supplementary data are available at Bioinformatics online.

Gender differences in learning physical science concepts: Does computer animation help equalize them?

NASA Astrophysics Data System (ADS)

Jacek, Laura Lee

This dissertation details an experiment designed to identify gender differences in learning using three experimental treatments: animation, static graphics, and verbal instruction alone. Three learning presentations were used in testing of 332 university students. Statistical analysis was performed using ANOVA, binomial tests for differences of proportion, and descriptive statistics. Results showed that animation significantly improved women's long-term learning over static graphics (p = 0.067), but didn't significantly improve men's long-term learning over static graphics. In all cases, women's scores improved with animation over both other forms of instruction for long-term testing, indicating that future research should not abandon the study of animation as a tool that may promote gender equity in science. Short-term test differences were smaller, and not statistically significant. Variation present in short-term scores was related more to presentation topic than treatment. This research also details characteristics of each of the three presentations, to identify variables (e.g. level of abstraction in presentation) affecting score differences within treatments. Differences between men's and women's scores were non-standard between presentations, but these differences were not statistically significant (long-term p = 0.2961, short-term p = 0.2893). In future research, experiments might be better designed to test these presentational variables in isolation, possibly yielding more distinctive differences between presentational scores. Differences in confidence interval overlaps between presentations suggested that treatment superiority may be somewhat dependent on the design or topic of the learning presentation. Confidence intervals greatly overlap in all situations. This undercut, to some degree, the surety of conclusions indicating superiority of one treatment type over the others. However, confidence intervals for animation were smaller, overlapped nearly completely for men and women (there was less overlap between the genders for the other two treatments), and centered around slightly higher means, lending further support to the conclusion that animation helped equalize men's and women's learning. The most important conclusion identified in this research is that gender is an important variable experimental populations testing animation as a learning device. Averages indicated that both men and women prefer to work with animation over either static graphics or verbal instruction alone.

Novelty or knowledge? A study of using a student response system in non-major biology courses at a community college

NASA Astrophysics Data System (ADS)

Thames, Tasha Herrington

The advancement in technology integration is laying the groundwork of a paradigm shift in the higher education system (Noonoo, 2011). The National Dropout Prevention Center (n.d.) claims that technology offers some of the best opportunities for presenting instruction to engage students in meaningful education, addressing multiple intelligences, and adjusting to students' various learning styles. The purpose of this study was to investigate if implementing clicker technology would have a statistically significant difference on student retention and student achievement, while controlling for learning styles, for students in non-major biology courses who were and were not subjected to the technology. This study also sought to identify if students perceived the use of clickers as beneficial to their learning. A quantitative quasi-experimental research design was utilized to determine the significance of differences in pre/posttest achievement scores between students who participated during the fall semester in 2014. Overall, 118 students (n = 118) voluntarily enrolled in the researcher's fall non-major Biology course at a southern community college. A total of 71 students were assigned to the experimental group who participated in instruction incorporating the ConcepTest Process with clicker technology along with traditional lecture. The remaining 51 students were assigned to the control group who participated in a traditional lecture format with peer instruction embedded. Statistical analysis revealed the experimental clicker courses did have higher posttest scores than the non-clicker control courses, but this was not significant (p >.05). Results also implied that clickers did not statistically help retain students to complete the course. Lastly, the results indicated that there were no significant statistical difference in student's clicker perception scores between the different learning style preferences.

Fade durations in satellite-path mobile radio propagation

NASA Technical Reports Server (NTRS)

Schmier, Robert G.; Bostian, Charles W.

1986-01-01

Fades on satellite to land mobile radio links are caused by several factors, the most important of which are multipath propagation and vegetative shadowing. Designers of vehicular satellite communications systems require information about the statistics of fade durations in order to overcome or compensate for the fades. Except for a few limiting cases, only the mean fade duration can be determined analytically, and all other statistics must be obtained experimentally or via simulation. This report describes and presents results from a computer program developed at Virginia Tech to simulate satellite path propagation of a mobile station in a rural area. It generates rapidly-fading and slowly-fading signals by separate processes that yield correct cumulative signal distributions and then combines these to simulate the overall signal. This is then analyzed to yield the statistics of fade duration.

The principles of effective case management of mental health services.

PubMed

Rapp, Charles A; Goscha, Richard J

2004-01-01

This paper identifies ten principles or active ingredients of case management that are common to interventions that produced statistically significant positive outcomes for people with serious psychiatric disabilities. Twenty-two studies employing experimental or quasi-experimental designs were selected for inclusion in this review. The use of the principles for systems design is briefly discussed. The term case management is used throughout this article because it is the term that is used in the studies reviewed. We acknowledge that this term is considered pejorative to many people with psychiatric disabilities. People with psychiatric disabilities are not "cases" and they do not need to be "managed." A more accurate reflection of what this service entails is that it is the services or resources that are managed in order to help people reach their goals. Until a more appropriate title becomes globally recognized, the term should be used with sensitivity to the negative connotations it carries.

The effects of survey question wording on rape estimates: evidence from a quasi-experimental design.

PubMed

Fisher, Bonnie S

2009-02-01

The measurement of rape is among the leading methodological issues in the violence against women field. Methodological discussion continues to focus on decreasing measurement errors and improving the accuracy of rape estimates. The current study used a quasi-experimental design to examine the effect of survey question wording on estimates of completed and attempted rape and verbal threats of rape. Specifically, the study statistically compares self-reported rape estimates from two nationally representative studies of college women's sexual victimization experiences, the National College Women Sexual Victimization study and the National Violence Against College Women study. Results show significant differences between the two sets of rape estimates, with National Violence Against College Women study rape estimates ranging from 4.4% to 10.4% lower than the National College Women Sexual Victimization study rape estimates. Implications for future methodological research are discussed.

Transmission over EHF mobile satellite channels

NASA Technical Reports Server (NTRS)

Zhuang, W.; Chouinard, J.-Y.; Yongacoglu, A.

1993-01-01

Land mobile satellite communications at Ka-band (30/20 GHz) are attracting an increasing interest among researchers because of the frequency band availability and the possibility of small earth station designs. However, communications at the Ka-band pose significant challenges in the system designs due to severe channel impairments. Because only very limited experimental data for mobile applications at Ka-band is available, this paper studies the channel characteristics based on experimental data at L-band (1.6/1.5 GHz) and the use of frequency scaling. The land mobile satellite communication channel at Ka-band is modelled as log-normal Rayleigh fading channel. The first and second-order statistics of the fading channel are studied. The performance of a coherent BPSK system over the fading channel at L-band and K-band is evaluated theoretically and validated by computer simulations. Conclusions on the communication channel characteristics and system performance at L-band and Ka-band are presented.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Use of experimental design in the investigation of stir bar sorptive extraction followed by ultra-high-performance liquid chromatography-tandem mass spectrometry for the analysis of explosives in water samples.

PubMed

Schramm, Sébastien; Vailhen, Dominique; Bridoux, Maxime Cyril

2016-02-12

A method for the sensitive quantification of trace amounts of organic explosives in water samples was developed by using stir bar sorptive extraction (SBSE) followed by liquid desorption and ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The proposed method was developed and optimized using a statistical design of experiment approach. Use of experimental designs allowed a complete study of 10 factors and 8 analytes including nitro-aromatics, amino-nitro-aromatics and nitric esters. The liquid desorption study was performed using a full factorial experimental design followed by a kinetic study. Four different variables were tested here: the liquid desorption mode (stirring or sonication), the chemical nature of the stir bar (PDMS or PDMS-PEG), the composition of the liquid desorption phase and finally, the volume of solvent used for the liquid desorption. On the other hand, the SBSE extraction study was performed using a Doehlert design. SBSE extraction conditions such as extraction time profiles, sample volume, modifier addition, and acetic acid addition were examined. After optimization of the experimental parameters, sensitivity was improved by a factor 5-30, depending on the compound studied, due to the enrichment factors reached using the SBSE method. Limits of detection were in the ng/L level for all analytes studied. Reproducibility of the extraction with different stir bars was close to the reproducibility of the analytical method (RSD between 4 and 16%). Extractions in various water sample matrices (spring, mineral and underground water) have shown similar enrichment compared to ultrapure water, revealing very low matrix effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Biofilm development in fixed bed biofilm reactors: experiments and simple models for engineering design purposes.

PubMed

Szilágyi, N; Kovács, R; Kenyeres, I; Csikor, Zs

2013-01-01

Biofilm development in a fixed bed biofilm reactor system performing municipal wastewater treatment was monitored aiming at accumulating colonization and maximum biofilm mass data usable in engineering practice for process design purposes. Initially a 6 month experimental period was selected for investigations where the biofilm formation and the performance of the reactors were monitored. The results were analyzed by two methods: for simple, steady-state process design purposes the maximum biofilm mass on carriers versus influent load and a time constant of the biofilm growth were determined, whereas for design approaches using dynamic models a simple biofilm mass prediction model including attachment and detachment mechanisms was selected and fitted to the experimental data. According to a detailed statistical analysis, the collected data have not allowed us to determine both the time constant of biofilm growth and the maximum biofilm mass on carriers at the same time. The observed maximum biofilm mass could be determined with a reasonable error and ranged between 438 gTS/m(2) carrier surface and 843 gTS/m(2), depending on influent load, and hydrodynamic conditions. The parallel analysis of the attachment-detachment model showed that the experimental data set allowed us to determine the attachment rate coefficient which was in the range of 0.05-0.4 m d(-1) depending on influent load and hydrodynamic conditions.

Sample size considerations for paired experimental design with incomplete observations of continuous outcomes.

PubMed

Zhu, Hong; Xu, Xiaohan; Ahn, Chul

2017-01-01

Paired experimental design is widely used in clinical and health behavioral studies, where each study unit contributes a pair of observations. Investigators often encounter incomplete observations of paired outcomes in the data collected. Some study units contribute complete pairs of observations, while the others contribute either pre- or post-intervention observations. Statistical inference for paired experimental design with incomplete observations of continuous outcomes has been extensively studied in literature. However, sample size method for such study design is sparsely available. We derive a closed-form sample size formula based on the generalized estimating equation approach by treating the incomplete observations as missing data in a linear model. The proposed method properly accounts for the impact of mixed structure of observed data: a combination of paired and unpaired outcomes. The sample size formula is flexible to accommodate different missing patterns, magnitude of missingness, and correlation parameter values. We demonstrate that under complete observations, the proposed generalized estimating equation sample size estimate is the same as that based on the paired t-test. In the presence of missing data, the proposed method would lead to a more accurate sample size estimate comparing with the crude adjustment. Simulation studies are conducted to evaluate the finite-sample performance of the generalized estimating equation sample size formula. A real application example is presented for illustration.

Robust matching for voice recognition

NASA Astrophysics Data System (ADS)

Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.

1994-10-01

This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.

DNA curtains for high-throughput single-molecule optical imaging.

PubMed

Greene, Eric C; Wind, Shalom; Fazio, Teresa; Gorman, Jason; Visnapuu, Mari-Liis

2010-01-01

Single-molecule approaches provide a valuable tool in the arsenal of the modern biologist, and new discoveries continue to be made possible through the use of these state-of-the-art technologies. However, it can be inherently difficult to obtain statistically relevant data from experimental approaches specifically designed to probe individual reactions. This problem is compounded with more complex biochemical reactions, heterogeneous systems, and/or reactions requiring the use of long DNA substrates. Here we give an overview of a technology developed in our laboratory, which relies upon simple micro- or nanofabricated structures in combination with "bio-friendly" lipid bilayers, to align thousands of long DNA molecules into defined patterns on the surface of a microfluidic sample chamber. We call these "DNA curtains," and we have developed several different versions varying in complexity and DNA substrate configuration, which are designed to meet different experimental needs. This novel approach to single-molecule imaging provides a powerful experimental platform that offers the potential for concurrent observation of hundreds or even thousands of protein-DNA interactions in real time. Copyright 2010 Elsevier Inc. All rights reserved.

Development of Computer Models for the Assessment of Foreign Body Impact Events on Composite Structures

NASA Technical Reports Server (NTRS)

Bucinell, Ronald B.

1997-01-01

The objective of this project was to model the 5-3/4 inch pressure vessels used on the NASA RTOP program in an attempt to learn more about how impact damage forms and what are the residual effects of the resulting damage. A global-local finite element model was developed for the bottle and the states of stress in the bottles were determined down to the constituent level. The experimental data that was generated on the NASA RTOP program was not in a form that enabled the model developed under this grant to be correlated with the experimental data. As a result of this exercise it is recommended that an experimental program be designed using statistical design of experiment techniques to generate data that can be used to isolate the phenomenon that control the formation of impact damage. This data should include residual property determinations so that models for post impact structural integrity can be developed. It is also recommended that the global-local methodology be integrated directly into the finite element code. This will require considerable code development.

The secret lives of experiments: methods reporting in the fMRI literature.

PubMed

Carp, Joshua

2012-10-15

Replication of research findings is critical to the progress of scientific understanding. Accordingly, most scientific journals require authors to report experimental procedures in sufficient detail for independent researchers to replicate their work. To what extent do research reports in the functional neuroimaging literature live up to this standard? The present study evaluated methods reporting and methodological choices across 241 recent fMRI articles. Many studies did not report critical methodological details with regard to experimental design, data acquisition, and analysis. Further, many studies were underpowered to detect any but the largest statistical effects. Finally, data collection and analysis methods were highly flexible across studies, with nearly as many unique analysis pipelines as there were studies in the sample. Because the rate of false positive results is thought to increase with the flexibility of experimental designs, the field of functional neuroimaging may be particularly vulnerable to false positives. In sum, the present study documented significant gaps in methods reporting among fMRI studies. Improved methodological descriptions in research reports would yield significant benefits for the field. Copyright © 2012 Elsevier Inc. All rights reserved.

Experimental design approach to the process parameter optimization for laser welding of martensitic stainless steels in a constrained overlap configuration

NASA Astrophysics Data System (ADS)

Khan, M. M. A.; Romoli, L.; Fiaschi, M.; Dini, G.; Sarri, F.

2011-02-01

This paper presents an experimental design approach to process parameter optimization for the laser welding of martensitic AISI 416 and AISI 440FSe stainless steels in a constrained overlap configuration in which outer shell was 0.55 mm thick. To determine the optimal laser-welding parameters, a set of mathematical models were developed relating welding parameters to each of the weld characteristics. These were validated both statistically and experimentally. The quality criteria set for the weld to determine optimal parameters were the minimization of weld width and the maximization of weld penetration depth, resistance length and shearing force. Laser power and welding speed in the range 855-930 W and 4.50-4.65 m/min, respectively, with a fiber diameter of 300 μm were identified as the optimal set of process parameters. However, the laser power and welding speed can be reduced to 800-840 W and increased to 4.75-5.37 m/min, respectively, to obtain stronger and better welds.

Study on the Optimization and Process Modeling of the Rotary Ultrasonic Machining of Zerodur Glass-Ceramic

NASA Astrophysics Data System (ADS)

Pitts, James Daniel

Rotary ultrasonic machining (RUM), a hybrid process combining ultrasonic machining and diamond grinding, was created to increase material removal rates for the fabrication of hard and brittle workpieces. The objective of this research was to experimentally derive empirical equations for the prediction of multiple machined surface roughness parameters for helically pocketed rotary ultrasonic machined Zerodur glass-ceramic workpieces by means of a systematic statistical experimental approach. A Taguchi parametric screening design of experiments was employed to systematically determine the RUM process parameters with the largest effect on mean surface roughness. Next empirically determined equations for the seven common surface quality metrics were developed via Box-Behnken surface response experimental trials. Validation trials were conducted resulting in predicted and experimental surface roughness in varying levels of agreement. The reductions in cutting force and tool wear associated with RUM, reported by previous researchers, was experimentally verified to also extended to helical pocketing of Zerodur glass-ceramic.

Improving the governance of patient safety in emergency care: a systematic review of interventions

PubMed Central

Hesselink, Gijs; Berben, Sivera; Beune, Thimpe

2016-01-01

Objectives To systematically review interventions that aim to improve the governance of patient safety within emergency care on effectiveness, reliability, validity and feasibility. Design A systematic review of the literature. Methods PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews and PsychInfo were searched for studies published between January 1990 and July 2014. We included studies evaluating interventions relevant for higher management to oversee and manage patient safety, in prehospital emergency medical service (EMS) organisations and hospital-based emergency departments (EDs). Two reviewers independently selected candidate studies, extracted data and assessed study quality. Studies were categorised according to study quality, setting, sample, intervention characteristics and findings. Results Of the 18 included studies, 13 (72%) were non-experimental. Nine studies (50%) reported data on the reliability and/or validity of the intervention. Eight studies (44%) reported on the feasibility of the intervention. Only 4 studies (22%) reported statistically significant effects. The use of a simulation-based training programme and well-designed incident reporting systems led to a statistically significant improvement of safety knowledge and attitudes by ED staff and an increase of incident reports within EDs, respectively. Conclusions Characteristics of the interventions included in this review (eg, anonymous incident reporting and validation of incident reports by an independent party) could provide useful input for the design of an effective tool to govern patient safety in EMS organisations and EDs. However, executives cannot rely on a robust set of evidence-based and feasible tools to govern patient safety within their emergency care organisation and in the chain of emergency care. Established strategies from other high-risk sectors need to be evaluated in emergency care settings, using an experimental design with valid outcome measures to strengthen the evidence base. PMID:26826151

Increasing the relevance of GCM simulations for Climate Services

NASA Astrophysics Data System (ADS)

Smith, L. A.; Suckling, E.

2012-12-01

The design and interpretation of model simulations for climate services differ significantly from experimental design for the advancement of the fundamental research on predictability that underpins it. Climate services consider the sources of best information available today; this calls for a frank evaluation of model skill in the face of statistical benchmarks defined by empirical models. The fact that Physical simulation models are thought to provide the only reliable method for extrapolating into conditions not previously observed has no bearing on whether or not today's simulation models outperform empirical models. Evidence on the length scales on which today's simulation models fail to outperform empirical benchmarks is presented; it is illustrated that this occurs even on global scales in decadal prediction. At all timescales considered thus far (as of July 2012), predictions based on simulation models are improved by blending with the output of statistical models. Blending is shown to be more interesting in the climate context than it is in the weather context, where blending with a history-based climatology is straightforward. As GCMs improve and as the Earth's climate moves further from that of the last century, the skill from simulation models and their relevance to climate services is expected to increase. Examples from both seasonal and decadal forecasting will be used to discuss a third approach that may increase the role of current GCMs more quickly. Specifically, aspects of the experimental design in previous hind cast experiments are shown to hinder the use of GCM simulations for climate services. Alternative designs are proposed. The value in revisiting Thompson's classic approach to improving weather forecasting in the fifties in the context of climate services is discussed.

Photon Strength Function at Low Energies in 95Mo

DOE PAGES

Wiedeking, M.; Bernstein, L. A.; Allmond, J. M.; ...

2014-05-01

A new and model-independent experimental method has been developed to determine the energy dependence of the photon strength function. It is designed to study statistical feeding from the quasi continuum to individual low-lying discrete levels. This new technique is presented and results for 95Mo are compared to data from the University of Oslo. In particular, questions regarding the existence of the low-energy enhancement in the photon strength function are addressed.

High Mobility Driver Performance Analysis

DTIC Science & Technology

1981-06-01

Adjusted Residuals 25 Table 13. Trials kAll Trials Including Civilian Drivers) During which Critical Incidents Occurred (Or Did Not Occur) 26 Table 14...0.05 (Winer, 1971 )3. At, the close of training an error score had been selected from amons alternative formulations as reasonably representative of...USNPA, Aug 1968. Winer, B. J. Statistical Principles in Experimental Design. Second (2d) edition. McGraw-Hill, New York, 1971 . 35 IN hi a. I i d A-14

Evaluation of Upland Disposal of Oakland Harbor, California, Sediment; Volume I: Turning Basin Sediments

DTIC Science & Technology

1992-10-01

infiltration studies ( Westerdahl and Skogerboe 1982). Extensive field 53 verification studies have been conducted with the WES Rainfall Simulator...Lysimeter System on a wide range of Corps project sites ( Westerdahl and Skogerboe 1982, Lee and Skogerboe 1984, Skogerboe et al. 1987). The WES Rain- fall...Vicksburg, MS. Winer, B. J. 1971. Statistical Principles in Experimental Design, McGraw- Hill Book Company, New York. Westerdahl , H. E., and Skogerboe, J

FY 1999 Laboratory Directed Research and Development annual report

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

PJ Hughes

2000-06-13

A short synopsis of each project is given covering the following main areas of research and development: Atmospheric sciences; Biotechnology; Chemical and instrumentation analysis; Computer and information science; Design and manufacture engineering; Ecological science; Electronics and sensors; Experimental technology; Health protection and dosimetry; Hydrologic and geologic science; Marine sciences; Materials science; Nuclear science and engineering; Process science and engineering; Sociotechnical systems analysis; Statistics and applied mathematics; and Thermal and energy systems.

Design of experiments (DoE) in pharmaceutical development.

PubMed

N Politis, Stavros; Colombo, Paolo; Colombo, Gaia; M Rekkas, Dimitrios

2017-06-01

At the beginning of the twentieth century, Sir Ronald Fisher introduced the concept of applying statistical analysis during the planning stages of research rather than at the end of experimentation. When statistical thinking is applied from the design phase, it enables to build quality into the product, by adopting Deming's profound knowledge approach, comprising system thinking, variation understanding, theory of knowledge, and psychology. The pharmaceutical industry was late in adopting these paradigms, compared to other sectors. It heavily focused on blockbuster drugs, while formulation development was mainly performed by One Factor At a Time (OFAT) studies, rather than implementing Quality by Design (QbD) and modern engineering-based manufacturing methodologies. Among various mathematical modeling approaches, Design of Experiments (DoE) is extensively used for the implementation of QbD in both research and industrial settings. In QbD, product and process understanding is the key enabler of assuring quality in the final product. Knowledge is achieved by establishing models correlating the inputs with the outputs of the process. The mathematical relationships of the Critical Process Parameters (CPPs) and Material Attributes (CMAs) with the Critical Quality Attributes (CQAs) define the design space. Consequently, process understanding is well assured and rationally leads to a final product meeting the Quality Target Product Profile (QTPP). This review illustrates the principles of quality theory through the work of major contributors, the evolution of the QbD approach and the statistical toolset for its implementation. As such, DoE is presented in detail since it represents the first choice for rational pharmaceutical development.

ICS-II USA research design and methodology.

PubMed

Rana, H; Andersen, R M; Nakazono, T T; Davidson, P L

1997-05-01

The purpose of the WHO-sponsored International Collaborative Study of Oral Health Outcomes (ICS-II) was to provide policy-markers and researchers with detailed, reliable, and valid data on the oral health situation in their countries or regions, together with comparative data from other dental care delivery systems. ICS-II used a cross-sectional design with no explicit control groups or experimental interventions. A standardized methodology was developed and tested for collecting and analyzing epidemiological, sociocultural, economic, and delivery system data. Respondent information was obtained by household interviews, and clinical examinations were conducted by calibrated oral epidemiologists. Discussed are the sampling design characteristics for the USA research locations, response rates, samples size for interview and oral examination data, weighting procedures, and statistical methods. SUDAAN was used to adjust variance calculations, since complex sampling designs were used.

Invited review: study design considerations for clinical research in veterinary radiology and radiation oncology.

PubMed

Scrivani, Peter V; Erb, Hollis N

2013-01-01

High quality clinical research is essential for advancing knowledge in the areas of veterinary radiology and radiation oncology. Types of clinical research studies may include experimental studies, method-comparison studies, and patient-based studies. Experimental studies explore issues relative to pathophysiology, patient safety, and treatment efficacy. Method-comparison studies evaluate agreement between techniques or between observers. Patient-based studies investigate naturally acquired disease and focus on questions asked in clinical practice that relate to individuals or populations (e.g., risk, accuracy, or prognosis). Careful preplanning and study design are essential in order to achieve valid results. A key point to planning studies is ensuring that the design is tailored to the study objectives. Good design includes a comprehensive literature review, asking suitable questions, selecting the proper sample population, collecting the appropriate data, performing the correct statistical analyses, and drawing conclusions supported by the available evidence. Most study designs are classified by whether they are experimental or observational, longitudinal or cross-sectional, and prospective or retrospective. Additional features (e.g., controlled, randomized, or blinded) may be described that address bias. Two related challenging aspects of study design are defining an important research question and selecting an appropriate sample population. The sample population should represent the target population as much as possible. Furthermore, when comparing groups, it is important that the groups are as alike to each other as possible except for the variables of interest. Medical images are well suited for clinical research because imaging signs are categorical or numerical variables that might be predictors or outcomes of diseases or treatments. © 2013 Veterinary Radiology & Ultrasound.

Peripheral myopization and visual performance with experimental rigid gas permeable and soft contact lens design.

PubMed

Pauné, J; Queiros, A; Quevedo, L; Neves, H; Lopes-Ferreira, D; González-Méijome, J M

2014-12-01

To evaluate the performance of two experimental contact lenses (CL) designed to induce relative peripheral myopic defocus in myopic eyes. Ten right eyes of 10 subjects were fitted with three different CL: a soft experimental lens (ExpSCL), a rigid gas permeable experimental lens (ExpRGP) and a standard RGP lens made of the same material (StdRGP). Central and peripheral refraction was measured using a Grand Seiko open-field autorefractometer across the central 60° of the horizontal visual field. Ocular aberrations were measured with a Hartman-Shack aberrometer, and monocular contrast sensitivity function (CSF) was measured with a VCTS6500 without and with the three contact lenses. Both experimental lenses were able to increase significantly the relative peripheral myopic defocus up to -0.50 D in the nasal field and -1.00 D in the temporal field (p<0.05). The ExpRGP induced a significantly higher myopic defocus in the temporal field compared to the ExpSCL. ExpSCL induced significantly lower levels of Spherical-like HOA than ExpRGP for the 5mm pupil size (p<0.05). Both experimental lenses kept CSF within normal limits without any statistically significant change from baseline (p>0.05). RGP lens design seems to be more effective to induce a significant myopic change in the relative peripheral refractive error. Both lenses preserve a good visual performance. The worsened optical quality observed in ExpRGP was due to an increased coma-like and spherical-like HOA. However, no impact on the visual quality as measured by CSF was observed. Copyright © 2014 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

Fracture resistance of retreated roots using different retreatment systems.

PubMed

Er, Kursat; Tasdemir, Tamer; Siso, Seyda Herguner; Celik, Davut; Cora, Sabri

2011-08-01

This study was designed to evaluate the fracture resistance of retreated roots using different rotary retreatment systems. Forty eight freshly extracted human canine teeth with single straight root canals were instrumented sequentially increasing from size 30 to a size 55 using K-files whit a stepback technique. The teeth were randomly divided into three experimental and one control groups of 12 specimens each. The root canals were filled using cold lateral compaction of gutta-percha and AH Plus (Dentsply Detrey, Konstanz, Germany) sealer in experimental groups. Removal of gutta-percha was performed with the following devices and techniques: ProTaper Universal (Dentsply Maillefer, Ballaigues, Switzerland), R-Endo (Micro-Mega, Besançon, France), and Mtwo (Sweden & Martina, Padova, Italy) rotary retreatment systems. Control group specimens were only instrumented, not filled or retreated. The specimens were then mounted in copper rings, were filled with a self-curing polymethylmethacrylate resin, and the force required to cause vertical root fracture was measured using a universal testing device. The force of fracture of the roots was recorded and the results in the various groups were compared. Statistical analysis was accomplished by one-way ANOVA and a post hoc Tukey tests. There were statistically significant differences between the control and experimental groups (P<.05). However, there were no significant differences among the experimental groups. Based on the results, all rotary retreatment techniques used in this in vitro study produced similar root weakness.

Statistical optimization of the growth factors for Chaetoceros neogracile using fractional factorial design and central composite design.

PubMed

Jeong, Sung-Eun; Park, Jae-Kweon; Kim, Jeong-Dong; Chang, In-Jeong; Hong, Seong-Joo; Kang, Sung-Ho; Lee, Choul-Gyun

2008-12-01

Statistical experimental designs; involving (i) a fractional factorial design (FFD) and (ii) a central composite design (CCD) were applied to optimize the culture medium constituents for production of a unique antifreeze protein by the Antartic microalgae Chaetoceros neogracile. The results of the FFD suggested that NaCl, KCl, MgCl2, and Na2SiO3 were significant variables that highly influenced the growth rate and biomass production. The optimum culture medium for the production of an antifreeze protein from C. neogracile was found to be Kalleampersandrsquor;s artificial seawater, pH of 7.0ampersandplusmn;0.5, consisting of 28.566 g/l of NaCl, 3.887 g/l of MgCl2, 1.787 g/l of MgSO4, 1.308 g/l of CaSO4, 0.832 g/l of K2SO4, 0.124 g/l of CaCO3, 0.103 g/l of KBr, 0.0288 g/l of SrSO4, and 0.0282 g/l of H3BO3. The antifreeze activity significantly increased after cells were treated with cold shock (at -5oC) for 14 h. To the best of our knowledge, this is the first report demonstrating an antifreeze-like protein of C. neogracile.

The Love of Large Numbers: A Popularity Bias in Consumer Choice.

PubMed

Powell, Derek; Yu, Jingqi; DeWolf, Melissa; Holyoak, Keith J

2017-10-01

Social learning-the ability to learn from observing the decisions of other people and the outcomes of those decisions-is fundamental to human evolutionary and cultural success. The Internet now provides social evidence on an unprecedented scale. However, properly utilizing this evidence requires a capacity for statistical inference. We examined how people's interpretation of online review scores is influenced by the numbers of reviews-a potential indicator both of an item's popularity and of the precision of the average review score. Our task was designed to pit statistical information against social information. We modeled the behavior of an "intuitive statistician" using empirical prior information from millions of reviews posted on Amazon.com and then compared the model's predictions with the behavior of experimental participants. Under certain conditions, people preferred a product with more reviews to one with fewer reviews even though the statistical model indicated that the latter was likely to be of higher quality than the former. Overall, participants' judgments suggested that they failed to make meaningful statistical inferences.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

The effectiveness of social marketing in global health: a systematic review.

PubMed

Firestone, Rebecca; Rowe, Cassandra J; Modi, Shilpa N; Sievers, Dana

2017-02-01

Social marketing is a commonly used strategy in global health. Social marketing programmes may sell subsidized products through commercial sector outlets, distribute appropriately priced products, deliver health services through social franchises and promote behaviours not dependent upon a product or service. We aimed to review evidence of the effectiveness of social marketing in low- and middle-income countries, focusing on major areas of investment in global health: HIV, reproductive health, child survival, malaria and tuberculosis. We searched PubMed, PsycInfo and ProQuest, using search terms linking social marketing and health outcomes for studies published from 1995 to 2013. Eligible studies used experimental or quasi-experimental designs to measure outcomes of behavioural factors, health behaviours and/or health outcomes in each health area. Studies were analysed by effect estimates and for application of social marketing benchmark criteria. After reviewing 18 974 records, 125 studies met inclusion criteria. Across health areas, 81 studies reported on changes in behavioural factors, 97 studies reported on changes in behaviour and 42 studies reported on health outcomes. The greatest number of studies focused on HIV outcomes (n = 45) and took place in sub-Saharan Africa (n = 67). Most studies used quasi-experimental designs and reported mixed results. Child survival had proportionately the greatest number of studies using experimental designs, reporting health outcomes, and reporting positive, statistically significant results. Most programmes used a range of methods to promote behaviour change. Programmes with positive, statistically significant findings were more likely to apply audience insights and cost-benefit analyses to motivate behaviour change. Key evidence gaps were found in voluntary medical male circumcision and childhood pneumonia. Social marketing can influence health behaviours and health outcomes in global health; however evaluations assessing health outcomes remain comparatively limited. Global health investments are needed to (i) fill evidence gaps, (ii) strengthen evaluation rigour and (iii) expand effective social marketing approaches. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging.

PubMed

Kim, Won Hwa; Hwang, Seong Jae; Adluru, Nagesh; Johnson, Sterling C; Singh, Vikas

2016-10-01

Consider an experimental design of a neuroimaging study, where we need to obtain p measurements for each participant in a setting where p ' (< p ) are cheaper and easier to acquire while the remaining ( p - p ') are expensive. For example, the p ' measurements may include demographics, cognitive scores or routinely offered imaging scans while the ( p - p ') measurements may correspond to more expensive types of brain image scans with a higher participant burden. In this scenario, it seems reasonable to seek an "adaptive" design for data acquisition so as to minimize the cost of the study without compromising statistical power. We show how this problem can be solved via harmonic analysis of a band-limited graph whose vertices correspond to participants and our goal is to fully recover a multi-variate signal on the nodes, given the full set of cheaper features and a partial set of more expensive measurements. This is accomplished using an adaptive query strategy derived from probing the properties of the graph in the frequency space. To demonstrate the benefits that this framework can provide, we present experimental evaluations on two independent neuroimaging studies and show that our proposed method can reliably recover the true signal with only partial observations directly yielding substantial financial savings.

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

Ceramic processing: Experimental design and optimization

NASA Technical Reports Server (NTRS)

Weiser, Martin W.; Lauben, David N.; Madrid, Philip

1992-01-01

The objectives of this paper are to: (1) gain insight into the processing of ceramics and how green processing can affect the properties of ceramics; (2) investigate the technique of slip casting; (3) learn how heat treatment and temperature contribute to density, strength, and effects of under and over firing to ceramic properties; (4) experience some of the problems inherent in testing brittle materials and learn about the statistical nature of the strength of ceramics; (5) investigate orthogonal arrays as tools to examine the effect of many experimental parameters using a minimum number of experiments; (6) recognize appropriate uses for clay based ceramics; and (7) measure several different properties important to ceramic use and optimize them for a given application.

Multivariate analysis techniques

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

Bendavid, Josh; Fisher, Wade C.; Junk, Thomas R.

2016-01-01

The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually bothmore » be improved by separating signal events from background events with higher efficiency and purity.« less

SCOUT: A Fast Monte-Carlo Modeling Tool of Scintillation Camera Output

PubMed Central

Hunter, William C. J.; Barrett, Harrison H.; Lewellen, Thomas K.; Miyaoka, Robert S.; Muzi, John P.; Li, Xiaoli; McDougald, Wendy; MacDonald, Lawrence R.

2011-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:22072297

SCOUT: a fast Monte-Carlo modeling tool of scintillation camera output†

PubMed Central

Hunter, William C J; Barrett, Harrison H.; Muzi, John P.; McDougald, Wendy; MacDonald, Lawrence R.; Miyaoka, Robert S.; Lewellen, Thomas K.

2013-01-01

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout of a scintillation camera. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools. PMID:23640136

In pursuit of a science of agriculture: the role of statistics in field experiments.

PubMed

Parolini, Giuditta

2015-09-01

Since the beginning of the twentieth century statistics has reshaped the experimental cultures of agricultural research taking part in the subtle dialectic between the epistemic and the material that is proper to experimental systems. This transformation has become especially relevant in field trials and the paper will examine the British agricultural institution, Rothamsted Experimental Station, where statistical methods nowadays popular in the planning and analysis of field experiments were developed in the 1920s. At Rothamsted statistics promoted randomisation over systematic arrangements, factorisation over one-question trials, and emphasised the importance of the experimental error in assessing field trials. These changes in methodology transformed also the material culture of agricultural science, and a new body, the Field Plots Committee, was created to manage the field research of the agricultural institution. Although successful, the vision of field experimentation proposed by the Rothamsted statisticians was not unproblematic. Experimental scientists closely linked to the farming community questioned it in favour of a field research that could be more easily understood by farmers. The clash between the two agendas reveals how the role attributed to statistics in field experimentation defined different pursuits of agricultural research, alternately conceived of as a scientists' science or as a farmers' science.

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.

Parabens abatement from surface waters by electrochemical advanced oxidation with boron doped diamond anodes.

PubMed

Domínguez, Joaquín R; Muñoz-Peña, Maria J; González, Teresa; Palo, Patricia; Cuerda-Correa, Eduardo M

2016-10-01

The removal efficiency of four commonly-used parabens by electrochemical advanced oxidation with boron-doped diamond anodes in two different aqueous matrices, namely ultrapure water and surface water from the Guadiana River, has been analyzed. Response surface methodology and a factorial, composite, central, orthogonal, and rotatable (FCCOR) statistical design of experiments have been used to optimize the process. The experimental results clearly show that the initial concentration of pollutants is the factor that influences the removal efficiency in a more remarkable manner in both aqueous matrices. As a rule, as the initial concentration of parabens increases, the removal efficiency decreases. The current density also affects the removal efficiency in a statistically significant manner in both aqueous matrices. In the water river aqueous matrix, a noticeable synergistic effect on the removal efficiency has been observed, probably due to the presence of chloride ions that increase the conductivity of the solution and contribute to the generation of strong secondary oxidant species such as chlorine or HClO/ClO - . The use of a statistical design of experiments made it possible to determine the optimal conditions necessary to achieve total removal of the four parabens in ultrapure and river water aqueous matrices.

Improvement on sugar cane bagasse hydrolysis using enzymatic mixture designed cocktail.

PubMed

Bussamra, Bianca Consorti; Freitas, Sindelia; Costa, Aline Carvalho da

2015-01-01

The aim of this work was to study cocktail supplementation for sugar cane bagasse hydrolysis, where the enzymes were provided from both commercial source and microorganism cultivation (Trichoderma reesei and genetically modified Escherichia coli), followed by purification. Experimental simplex lattice mixture design was performed to optimize the enzymatic proportion. The response was evaluated through hydrolysis microassays validated here. The optimized enzyme mixture, comprised of T. reesei fraction (80%), endoglucanase (10%) and β-glucosidase (10%), converted, theoretically, 72% of cellulose present in hydrothermally pretreated bagasse, whereas commercial Celluclast 1.5L converts 49.11%±0.49. Thus, a rational enzyme mixture designed by using synergism concept and statistical analysis was capable of improving biomass saccharification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exploring the interaction of patient activation and message design variables: message frame and presentation mode influence on the walking behavior of patients with type 2 diabetes.

PubMed

Ledford, Christy J W

2012-10-01

Examining interpersonal (physician-patient) communication strategies for promoting walking exercise to patients with type 2 diabetes assigned to primary care clinics, the study evaluated two message design variables--frame and presentation mode--as influencers of communication and adoption success. The single-site, four-week, prospective intervention study followed a 2×3 factorial, non-equivalent comparison group quasi-experimental design. Results showed frame was significantly related to steps walked; however, when including patient activation as an interaction, frame was non-significant. The model including patient activation interactions, however, detected significant mode effects on behavior. Results provide evidence that statistics are most effectively used with activated patients.

Designing and Interpreting Limiting Dilution Assays: General Principles and Applications to the Latent Reservoir for Human Immunodeficiency Virus-1.

PubMed

Rosenbloom, Daniel I S; Elliott, Oliver; Hill, Alison L; Henrich, Timothy J; Siliciano, Janet M; Siliciano, Robert F

2015-12-01

Limiting dilution assays are widely used in infectious disease research. These assays are crucial for current human immunodeficiency virus (HIV)-1 cure research in particular. In this study, we offer new tools to help investigators design and analyze dilution assays based on their specific research needs. Limiting dilution assays are commonly used to measure the extent of infection, and in the context of HIV they represent an essential tool for studying latency and potential curative strategies. Yet standard assay designs may not discern whether an intervention reduces an already miniscule latent infection. This review addresses challenges arising in this setting and in the general use of dilution assays. We illustrate the major statistical method for estimating frequency of infectious units from assay results, and we offer an online tool for computing this estimate. We recommend a procedure for customizing assay design to achieve desired sensitivity and precision goals, subject to experimental constraints. We consider experiments in which no viral outgrowth is observed and explain how using alternatives to viral outgrowth may make measurement of HIV latency more efficient. Finally, we discuss how biological complications, such as probabilistic growth of small infections, alter interpretations of experimental results.

Design, development, testing and validation of a Photonics Virtual Laboratory for the study of LEDs

NASA Astrophysics Data System (ADS)

Naranjo, Francisco L.; Martínez, Guadalupe; Pérez, Ángel L.; Pardo, Pedro J.

2014-07-01

This work presents the design, development, testing and validation of a Photonic Virtual Laboratory, highlighting the study of LEDs. The study was conducted from a conceptual, experimental and didactic standpoint, using e-learning and m-learning platforms. Specifically, teaching tools that help ensure that our students perform significant learning have been developed. It has been brought together the scientific aspect, such as the study of LEDs, with techniques of generation and transfer of knowledge through the selection, hierarchization and structuring of information using concept maps. For the validation of the didactic materials developed, it has been used procedures with various assessment tools for the collection and processing of data, applied in the context of an experimental design. Additionally, it was performed a statistical analysis to determine the validity of the materials developed. The assessment has been designed to validate the contributions of the new materials developed over the traditional method of teaching, and to quantify the learning achieved by students, in order to draw conclusions that serve as a reference for its application in the teaching and learning processes, and comprehensively validate the work carried out.

Optimizing the vacuum plasma spray deposition of metal, ceramic, and cermet coatings using designed experiments

NASA Astrophysics Data System (ADS)

Kingswell, R.; Scott, K. T.; Wassell, L. L.

1993-06-01

The vacuum plasma spray (VPS) deposition of metal, ceramic, and cermet coatings has been investigated using designed statistical experiments. Processing conditions that were considered likely to have a significant influence on the melting characteristics of the precursor powders and hence deposition efficiency were incorporated into full and fractional factorial experimental designs. The processing of an alumina powder was very sensitive to variations in the deposition conditions, particularly the injection velocity of the powder into the plasma flame, the plasma gas composition, and the power supplied to the gun. Using a combination of full and fractional factorial experimental designs, it was possible to rapidly identify the important spraying variables and adjust these to produce a deposition efficiency approaching 80 percent. The deposition of a nickel-base alloy metal powder was less sensitive to processing conditions. Generally, however, a high degree of particle melting was achieved for a wide range of spray conditions. Preliminary experiments performed using a tungsten carbide/cobalt cermet powder indicated that spray efficiency was not sensitive to deposition conditions. However, microstructural analysis revealed considerable variations in the degree of tungsten carbide dissolution. The structure and properties of the optimized coatings produced in the factorial experiments are also discussed.

Optimization and evaluation of clarithromycin floating tablets using experimental mixture design.

PubMed

Uğurlu, Timucin; Karaçiçek, Uğur; Rayaman, Erkan

2014-01-01

The purpose of the study was to prepare and evaluate clarithromycin (CLA) floating tablets using experimental mixture design for treatment of Helicobacter pylori provided by prolonged gastric residence time and controlled plasma level. Ten different formulations were generated based on different molecular weight of hypromellose (HPMC K100, K4M, K15M) by using simplex lattice design (a sub-class of mixture design) with Minitab 16 software. Sodium bicarbonate and anhydrous citric acid were used as gas generating agents. Tablets were prepared by wet granulation technique. All of the process variables were fixed. Results of cumulative drug release at 8th h (CDR 8th) were statistically analyzed to get optimized formulation (OF). Optimized formulation, which gave floating lag time lower than 15 s and total floating time more than 10 h, was analyzed and compared with target for CDR 8th (80%). A good agreement was shown between predicted and actual values of CDR 8th with a variation lower than 1%. The activity of clarithromycin contained optimizedformula against H. pylori were quantified using well diffusion agar assay. Diameters of inhibition zones vs. log10 clarithromycin concentrations were plotted in order to obtain a standard curve and clarithromycin activity.

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

PubMed

Lujan, J Luis; Crago, Patrick E

2009-01-01

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Application of D-optimal experimental design method to optimize the formulation of O/W cosmetic emulsions.

PubMed

Djuris, J; Vasiljevic, D; Jokic, S; Ibric, S

2014-02-01

This study investigates the application of D-optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non-ionic emulsifier in the relatively low concentration (1%), and the mixture of co-emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations. To determine the optimal composition of co-emulsifiers mixture, D-optimal mixture experimental design was used. Prepared emulsions were characterized with rheological measurements, centrifugation test, specific conductivity and pH value measurements. All prepared samples appeared as white and homogenous creams, except for one homogenous and viscous lotion co-stabilized by stearic acid alone. Centrifugation testing revealed some phase separation only in the case of sample co-stabilized using glyceryl stearate alone. The obtained pH values indicated that all samples expressed mild acid value acceptable for cosmetic preparations. Specific conductivity values are attributed to the multiple phases O/W emulsions with high percentages of fixed water. Results of the rheological measurements have shown that the investigated samples exhibited non-Newtonian thixotropic behaviour. To determine the influence of each of the co-emulsifiers on emulsions properties, the obtained results were evaluated by the means of statistical analysis (ANOVA test). On the basis of comparison of statistical parameters for each of the studied responses, mixture reduced quadratic model was selected over the linear model implying that interactions between co-emulsifiers play the significant role in overall influence of co-emulsifiers on emulsions properties. Glyceryl stearate was found to be the dominant co-emulsifier affecting emulsions properties. Interactions between the glyceryl stearate and other co-emulsifiers were also found to significantly influence emulsions properties. These findings are especially important as they can be used for development of the product that meets users' requirements, as represented in the study. © 2013 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Development and validation of ultrasound-assisted solid-liquid extraction of phenolic compounds from waste spent coffee grounds.

PubMed

Al-Dhabi, Naif Abdullah; Ponmurugan, Karuppiah; Maran Jeganathan, Prakash

2017-01-01

In this current work, Box-Behnken statistical experimental design (BBD) was adopted to evaluate and optimize USLE (ultrasound-assisted solid-liquid extraction) of phytochemicals from spent coffee grounds. Factors employed in this study are ultrasonic power, temperature, time and solid-liquid (SL) ratio. Individual and interactive effect of independent variables over the extraction yield was depicted through mathematical models, which are generated from the experimental data. Determined optimum process conditions are 244W of ultrasonic power, 40°C of temperature, 34min of time and 1:17g/ml of SL ratio. The predicted values were in correlation with experimental values with 95% confidence level, under the determined optimal conditions. This indicates the significance of selected method for USLE of phytochemicals from SCG. Copyright © 2016 Elsevier B.V. All rights reserved.

The effects of guided inquiry instruction on student achievement in high school biology

NASA Astrophysics Data System (ADS)

Vass, Laszlo

The purpose of this quantitative, quasi-experimental study was to measure the effect of a student-centered instructional method called guided inquiry on the achievement of students in a unit of study in high school biology. The study used a non-random sample of 109 students, the control group of 55 students enrolled in high school one, received teacher centered instruction while the experimental group of 54 students enrolled at high school two received student-centered, guided inquiry instruction. The pretest-posttest design of the study analyzed scores using an independent t-test, a dependent t-test (p = <.001), an ANCOVA (p = .007), mixed method ANOVA (p = .024) and hierarchical linear regression (p = <.001). The experimental group that received guided inquiry instruction had statistically significantly higher achievement than the control group.

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.

PSYCHOLOGY. Estimating the reproducibility of psychological science.

PubMed

2015-08-28

Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams. Copyright © 2015, American Association for the Advancement of Science.

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

PubMed

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

2018-07-15

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

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

USGS Publications Warehouse

Patton, Charles J.; Gilroy, Edward J.

1999-01-01

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

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.

Designing monitoring for conservation impact assessment in water funds in Latin America: an approach to address water-data scarcity (Invited)

NASA Astrophysics Data System (ADS)

Nelson, J. L.; Chaplin-Kramer, R.; Ziv, G.; Wolny, S.; Vogl, A. L.; Tallis, H.; Bremer, L.

2013-12-01

The risk of water scarcity is a rising threat in a rapidly changing world. Communities and investors are using the new institution of water funds to enact conservation practices in watersheds to bolster a clean, predictable water supply for multiple stakeholders. Water funds finance conservation activities to support water-related ecosystem services, and here we relate our work to develop innovative approaches to experimental design of monitoring programs to track the effectiveness of water funds throughout Latin America. We highlight two examples: the Fund for the Protection of Water (FONAG), in Quito, Ecuador, and Water for Life, Agua por la Vida, in Cali, Colombia. Our approach is meant to test whether a) water funds' restoration and protection actions result in changes in water quality and/or quantity at the site scale and the subwatershed scale, and b) the suite of investments for the whole water fund reach established goals for improving water quality and/or quantity at the basin scale or point of use. Our goal is to create monitoring standards for ecosystem-service assessment and clearly demonstrate translating those standards to field implementation in a statistically robust and cost-effective way. In the gap between data-intensive methods requiring historic, long-term water sampling and more subjective, ad hoc assessments, we have created a quantitative, land-cover-based approach to pairing conservation activity with appropriate controls in order to determine the impact of water-fund actions. To do so, we use a statistical approach in combination with open-source tools developed by the Natural Capital Project to optimize water funds' investments in nature and assess ecosystem-service provision (Resource Investment Optimization System, RIOS, and InVEST). We report on the process of identifying micro-, subwatershed or watershed matches to serve as controls for conservation 'impact' sites, based on globally-available land cover, precipitation, and soil data, without available water data. In two watersheds within the 'Water for Life' fund in Colombia, we used maps of nine biophysical inputs to RIOS to rank sites for their similarity to impact sediment retention, and then identified the top Impact/Control microwatershed pairs based on averaged, two-sample Kolmogorov-Smirnov statistics for each input. In FONAG, Ecuador, we used the approach to identify appropriate control sites for designated restoration sites. Our approach can be used at multiple scales, and can be used whether the conservation 'treatments' are assigned (a quasi-experimental approach) or both impact and control sites are identified in a fully experimental design. Our results highlight the need for innovative analytic methods to improve monitoring design in data-scarce regions.

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.

Prolonged release matrix tablet of pyridostigmine bromide: formulation and optimization using statistical methods.

PubMed

Bolourchian, Noushin; Rangchian, Maryam; Foroutan, Seyed Mohsen

2012-07-01

The aim of this study was to design and optimize a prolonged release matrix formulation of pyridostigmine bromide, an effective drug in myasthenia gravis and poisoning with nerve gas, using hydrophilic - hydrophobic polymers via D-optimal experimental design. HPMC and carnauba wax as retarding agents as well as tricalcium phosphate were used in matrix formulation and considered as independent variables. Tablets were prepared by wet granulation technique and the percentage of drug released at 1 (Y(1)), 4 (Y(2)) and 8 (Y(3)) hours were considered as dependent variables (responses) in this investigation. These experimental responses were best fitted for the cubic, cubic and linear models, respectively. The optimal formulation obtained in this study, consisted of 12.8 % HPMC, 24.4 % carnauba wax and 26.7 % tricalcium phosphate, had a suitable prolonged release behavior followed by Higuchi model in which observed and predicted values were very close. The study revealed that D-optimal design could facilitate the optimization of prolonged release matrix tablet containing pyridostigmine bromide. Accelerated stability studies confirmed that the optimized formulation remains unchanged after exposing in stability conditions for six months.